Optical sensor system for monitoring the pH of cellular media: application to an organ-on-a-chip platform

Universidade do Minho Escola de Engenharia Fernando Luís Bior Mendes Optical sensor system for monitoring the pH of cellular media: application to an Organ-on-a-chip platform Dissertação de Mestrado Mestrado Integrado em Engenharia Física Trabalho efetuado sob a orientação de Professora Doutora Raquel O. Rodrigues Professor Doutor Stefan Gassmann setembro de 2020 ii DECLARAÇÃO Nome: Fernando Luís Bior Mendes Endereço eletrónico: [email protected] Telefone: +351930423091 Bilhete de Identidade/Cartão do Cidadão: 15345740 Título da dissertação: Optical sensor system for monitoring the pH of celular media: application to an Organ-on-a-chip platform Orientadores: Professora Doutora Raquel O. Rodrigues Professor Doutor Stefan Gassmann Ano de conclusão: 2020 Mestrado em Engenharia Física É AUTORIZADA A REPRODUÇÃO INTEGRAL DESTA DISSERTAÇAO APENAS PARA EFEITOS DE INVESTIGAÇÃO, MEDIANTE DECLARAÇÃO ESCRITA DO INTERESSADO, QUE A TAL SE COMPROMETE. Universidade do Minho, ____/____/________ Assinatura: iii DIREITOS DE AUTOR E CONDIÇÕES DE UTILIZAÇÃO DO TRABALHO POR TERCEIROS Este é um trabalho académico que pode ser utilizado por terceiros desde que respeitadas as regras e boas práticas internacionalmente aceites, no que concerne aos direitos de autor e direitos conexos. Assim, o presente trabalho pode ser utilizado nos termos previstos na licença abaixo indicada. Caso o utilizador necessite de permissão para poder fazer um uso do trabalho em condições não previstas no licenciamento indicado, deverá contactar o autor, através do RepositóriUM da Universidade do Minho. Licença concedida aos utilizadores deste trabalho Atribuição-NãoComercial-SemDerivações CC BY-NC-ND https://creativecommons.org/licenses/by-nc-nd/4.0/ [Esta é a mais restritiva das nossas seis licenças principais, só permitindo que outros façam download dos seus trabalhos e os compartilhem desde que lhe sejam atribuídos a si os devidos créditos, mas sem que possam alterá-los de nenhuma forma ou utilizá-los para fins comerciais.] iv STATEMENT OF INTEGRITY I hereby declare having conducted this academic work with integrity. I confirm that I have not used plagiarism or any form of undue use of information or falsification of results along the process leading to its elaboration. I further declare that I have fully acknowledged the Code of Ethical Conduct of the University of Minho. v This work results partially of the project NORTE-01-0145-FEDER-029394, RTChip4Theranostics, supported by Programa Operacional Regional do Norte - Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF) and by Fundação para a Ciência e Tecnologia (FCT), IP, project reference PTDC/EMD-EMD/29394/2017. vi “I seem to have been only like a boy playing on the seashore, and diverting myself in now and then finding a smoother pebble or a prettier shell than ordinary, whilst the great ocean of truth lay all undiscovered before me.” Isaac Newton “It is strange that only extraordinary men make the discoveries, which later appear so easy and simple.” Georg C. Lichtenberg vii Acknowledgments The author acknowledges the support given by the Erasmus Placement mobility programme and the University of Minho, especially to the International Relations Office for the concern during the mobility program and for allowing the scholarship for the elaboration of the Master's thesis in cooperation with Jade Hochschule - Wilhelmshaven, Germany. To my advisor and co-advisor Professor Doctor Raquel O. Rodrigues and Professor Doctor Stefan Gassmann, and lab technicians Dipl.-Ing. Helmut Schütte and Dipl.-Ing. Robert Buse, all the support and knowledge that they shared with me, and all the help they gave me during my experience in Germany. A special thanks to Professor Doctor Graça Minas and Professor Doctor Thomas for being two very important pillars and guides in the Portuguese and German universities, respectively, that helped me know in which direction to proceed with my work and study. For the engineers Raquel Lopes and Miguel Madureira who have been two great supports in professional and personal terms in my research course abroad. They helped me to believe and to be resilient and patient. To all the Jade Hochschule, especially to Mechanical & Optics laboratory for the availability of its facilities, with great work conditions. To everyone who was present and marked me during my academic journey, especially to all professors who shared their knowledge with me. To Inês Carvalho my great gratitude for teaching me to be better and good to everyone. More than a colleague, she was an incredible friend who marked my academic journey more than anyone, who was present in everything. Finally and with love, to all my family and friends for always believing in me and all the patient. viii Abstract pH is a physiological parameter that changes its value according to cellular state of a human organ. When a tumour is being developed, it is known that they have a more acid interstitial pH than normal tissues. This is mainly due to the high metabolic activity of the abnormal cells with increase of acidic sub-products and the absence of organised vasculature of tumours, that leads to poor tissue oxygenation. Indeed, in in vitro animal systems, such as static cell culture experiments or advanced microfluidic devices, the cell’s metabolic activity during incubation causes the alteration of the cell culture pH, which drops the pH from close to the physiological (7.4) to acidic ones (lower than 7.0). Because low environmental pH inhibits cell survival, proliferation and activity, cell culture media has to be consecutively replaced for fresh one. For the pH monitoring, cell culture media is, in general, complemented with a pH colorimetric indicator (e.g. phenol red). However, the colour change of the cell culture media does not quantify the pH value. For this reason, the monitoring and quantification of cell culture medium pH, especially in advanced cell culture devices, such as organ-on-a-chip (OoC), which contain healthy and/or tumour organ models, is still a challenge and a parameter of utmost importance for the maintenance of homeostasis (auto-regulation). The pH of tissues can be measured by a variety of techniques, being pH electrodes the most used. Nevertheless, other methods can be used for pH measurement, such as optical sensors. In general, this technique eliminates the tissue injury effects, but results in an integrated measurement over a long period and demanding a relatively large volume of sample. Particularly, in OoC platforms, the small size of each OoC constituent part, has triggered the development of micro(bio)sensors to be integrated in the microchambers that feed the perfusion chambers containing the organ models, which are used for monitoring the pH of the cell culture media in circulation. In this study, a literature review of pH sensors that can be miniaturised and integrated in OoC was investigated. Based on this previews literature research, and the presence of a colorimetric pH indicator (phenol red) that is commercially added to cell culture media, a miniaturization of an optical pH sensor, for real-time sensing of the cell culture medium feeding advanced microfluidic devices was investigated. This strategy can have several advantages, such as low-cost implementation and improvement of the pH reading based on the beam-splitter phenomenon. For ix this purpose, a microchamber, processed by micromilling in PMMA, was developed and optimised to support the pH optical sensing system, creating a prototype device that can be directly incorporated into an OoC platform. For the pH sensing experiments, buffered solutions with stablished pH and phenol red were used to test and optimize the optical sensor, by analysing their transmittance signal. In this study, the colorimetric pH indicator (phenol red) was added in the same concentration than the one used in commercial cell culture media. The results shown that the pH reading was successful achieved in intervals of 0.2 pH units, in a range between 6.0 to 8.0. Keywords: Optical sensor, Beam-splitter, Organ-on-a-chip, Cell culture medium, Buffer solutions, Phenol red, pH, Microchamber, Micromilling. xvi Figure 49 - Acquisition setup for the buffer transmittance response. PC, on the left, camera for placing the buffer, in the middle, and light source and spectrometer, on the right, connected to the camera by optical fiber............................................................................................................... 65 Figure 50 - Radiation flux in microchannel. ............................................................................. 67 Figure 51 - Graphical representation of the intensity on the 6 channels of Adafruit AS7262 using a white optic fiber light source. .................................................................................................. 70 Figure 52 - Setup to measure pH values. A pH meter from inoLab in measuring the pH and temperature conditions of buffer solution in a test tube with a stirrer, placed in an IKA RCT basic magnetic stirrer. ......................................................................................................................... 71 Figure 53 - Transmittance Spectra of complete buffer solutions at different pH levels, obtained with the software OceanView. ..................................................................................................... 72 Figure 54 - AutoCAD design of the 1 mm chamber to study the transmittance level for different buffer solutions. ......................................................................................................................... 74 Figure 55 - (a) Method of inserting the glue with a small needle to fix the optical fibers on the chip; (b) fixed optical fiber so that the waveguides are directed to the microchamber; (c) the 1 mm microchamber PMMA microchip with the optical fibers. ............................................................. 74 Figure 56 - Setup for the transmittance measurements on the microchamber. The buffer solutions go to the microchip in continuous flow during the whole measurement through a micropump with a frequency near to 100 Hz. The waste liquid is discarded into a beaker. .................................. 75 Figure 57 - Intensity of Adafruit AS7262 6-channels for experiment performed for buffer solutions with pH 5.8, 6.4, 7.0, 7.4, 8.0, respectively over time. The experiment is done by alternating the reference sample, pure water, and buffer solutions, in the 1 mm chamber. Each step corresponds to the response of the buffer solution in relation to the water response (maximum observable value). .................................................................................................................................................. 75 Figure 58 - Transmittance of channels violet and green of Adafruit AS7262 for experiment performed for buffer solutions pH 5.8, 6.4, 7.0, 7.4, 8.0, respectively over time. The experiment is done by alternating the reference sample, pure water and buffer solutions, in the 1 mm chamber. Each step corresponds to the response of the buffer solution in relation to the pure water response (maximum observable value). .................................................................................................... 76 Figure 59 - Transmittance response of channels violet and green of Adafruit AS7262 for pH 5.8 - 8.0 range. The experiment is performed for buffer solutions pH 5.8, 6.4, 7.0, 7.4, 8.0, in the 1 mm chamber, which is done by alternating the reference sample, pure water and buffer solutions. .................................................................................................................................................. 77 Figure 60 - Expected theoretical response (T) and experimental transmittance response (TP) of green channel of Adafruit AS7262 for pH 5.8 - 8.0 range. A polynomial approach is made to study the error between what is obtained and what is expected, through polynomial equations. The experiment was performed for buffer solutions pH 5.8, 6.4, 7.0, 7.4, 8.0, in the 1 mm chamber, which is done by alternating the reference sample, pure water and buffer solutions. ................. 78 Figure 61 - AutoCAD design of the 2 mm chamber to study the transmittance level for different buffer solutions. ......................................................................................................................... 79 Figure 62 - Intensity of Adafruit AS7262 6-channels for the experiment performed with buffer solutions of pH 5.8, 6.4, 7.0, 7.4, 8.0, respectively, and over time. The experiment is done by alternating the reference sample, pure water and buffer solutions, in the 2 mm chamber. Each xvii step corresponds to the response of the buffer solution in relation to the pure water response (maximum observable value). .................................................................................................... 79 Figure 63 - Transmittance of channels violet, blue, green and yellow of Adafruit AS7262 for experiment performed with buffer solutions pH 5.8, 6.4, 7.0, 7.4, 8.0, respectively, over time. The experiment is done by alternating the reference sample, pure water and buffer solutions, in the 2 mm chamber. Each step corresponds to the response of the buffer solution in relation to the pure water response (maximum observable value). ........................................................................... 80 Figure 64 - Transmittance response of channels violet, blue, green and yellow of Adafruit AS7262 for pH 5.8 - 8.0 range. The experiment is performed for buffer solutions pH 5.8, 6.4, 7.0, 7.4, 8.0, in the 2 mm chamber, which is done by alternating the reference sample, pure water and buffer solutions. ................................................................................................................................... 81 Figure 65 - Expected theoretical response (T) and experimental transmittance response (TP) of green channel of Adafruit AS7262 for pH 5.8 - 8.0 range. A polynomial approach is made to study the error between what is obtained and what is expected, through polynomial equations. The experiment is performed for buffer solutions pH 5.8, 6.4, 7.0, 7.4, 8.0, in the 2 mm chamber, which is done by alternating the reference sample, pure water and buffer solutions. ................. 82 Figure 66 - Noise signal of the channels of photodetector of Adafruit AS7262. ....................... 83 Figure 67 - Solutions 1, 2 and 3 prepared with red food coloring ink and pure water, 4:1, 8:1, 12:1, respectively....................................................................................................................... 84 Figure 68 - Transmittance Spectra of red food colouring ink solutions 1, 2 and 3, obtained with the software OceanView. ............................................................................................................ 84 Figure 69 - Transmittance obtained with the sensor for experiment performed with red food coloured ink solution, first, second and third solution, respectively over time. The experiment is done by alternating the reference sample, pure water, and red food coloured ink solution, pumping the fluids using neMESYS syringe pump at a flowrate of 20 µL/min. Each step corresponds to the response of the solutions in relation to the pure water response (maximum observable value). . 85 Figure 70 - Transmittance Spectra of black food colouring ink solution, obtained with the software OceanView. ................................................................................................................................ 86 Figure 71 - Transmittance obtained with the sensor for experiment performed with black food coloured ink solution (black food colouring ink and pure water in the proportion of 1:10), over time. The experiment was done by alternating the reference sample, pure water, and black food coloured ink solution, pumping the fluids using neMESYS syringe pump at a flowrate of 20 µL/min.. Each step corresponds to the response of the same solution in relation to the pure water response (maximum observable value). .................................................................................................... 86 Figure 72 - Transmittance obtained with the sensor without mirror for experiment performed with black food coloured ink solution (black food colouring ink and pure water in the proportion of 1:10), over time. The experiment was done by alternating the reference sample, pure water, and black food coloured ink solution, pumping the fluids using neMESYS syringe pump at a flowrate of 20 µL/min. The step corresponds to the response of the same solution in relation to the pure water response (maximum observable value). ..................................................................................... 87 Figure 73 - Transmittance obtained with the sensor for experiment performed with buffer solutions pH 5.8, 6.0, 6.2, 6.4, 6.6, 6.8, 7.0, 7.2, 7.4, 7.6, 7.8 and 8.0, respectively, over time. The experiment was done by alternating the reference sample, pure water and buffer solutions, in the 1 mm chamber, pumping the fluids using neMESYS syringe pump at a flowrate of 20 µL/min. xviii Each step corresponds to the response of the buffer solution in relation to the pure water response (maximum observable value). .................................................................................................... 88 Figure 74 - Sensor transmittance response over the range pH 6.0 - 8.0, with a sensitivity of 1.7%/0.2 pH and a linear regression that shows an accuracy around 94% . .............................. 89 Figure 75 - Interface aspect for (a) solution with pH outside the pH 6.0-8.0 range, and for (b) the zero level (pH=6.0). ................................................................................................................... 90 xix List of tables Table 1 - Main physicochemical PMMA characteristics (Altuglas International, 2006). ............. 35 Table 2 - Properties of the used Zecha tools to mill. ................................................................. 39 Table 3 - Optical characteristics AS7262 (Pass Band). (ams AG, 2016) .................................. 47 Table 4 - Tech Specifications Of Micro Arduino board. (AG, 2014) ........................................... 49 Table 5 - Phosphate buffer for different pH values (Works, 2018) ............................................ 63 Table 6 - Optical features of DH-MINI Ocean Optics UV-VIS-NIR Fiver Optic Light Source (Ave, n.d.). .......................................................................................................................................... 65 Table 7 - Measured transmittance for buffer solutions with different pH in a 1 cm cuvette and forecast for 1 mm and 2 mm microchamber. ............................................................................ 69 Table 8 - Measures of pH with prepared buffer solutions with error associated and temperature conditions. ................................................................................................................................. 71 Table 9 - Transmittance in two peaks of transmittance spectra for the buffer solutions. ........... 73 Table 10 - Transmittance and absorption values for the buffer solutions in the pH range 6.0 - 8.0, with a step of pH 0.2 obtained with the sensor. ......................................................................... 89 xx List of abbreviations 3D Three-Dimensional AU Absorbance Units CAD Computer-Aided-Design CAE Calcein Acetoxymethyl Ester CAM Computer-Aided Manufacturing CDA Clean Dry Air CNC Computer Numerical Control CTAB Hexadecyltrimethylammonium Bromide EGFET Extended-Gate Field Effect Transistor FET Field-Effect Transistor FWHM Full Width at Half Maximum GPTMS–ETEOS 3-glycidoxypropyltrimethoxysilane – rthyltriethoxysilane HPTS 8-hydroxypyrene-1,3,6-trisulfonic acid HPTS-IP 8-hydroxypyrene-1,3,6-trisulfonic acid – Ion Pared IC Integrated Circuit IDE Interdigitated Electrode IR Infra-Red ISFET Ion-Sensitive Field-Effect Transistor LED Light-Emitting Diode LWL Light-Waveguide MEMS Micro-Electro-Mechanical Systems MLCT Metal to Ligand Charge Transfer MOSFET Metal Oxide Field Effect Semiconductor Transistor NC Numerical Control NEMS Nanoelectromechanical Systems NIR Near-Infrared OoC Organ-on-a-chip pHe Extracellular pH pHi Intracellular pH PCB Printed Circuit Board xxi PDMS Polydimethylsiloxane PI Propidium Iodide PMMA poly(methyl methacrylate) POC Point-of-Care PSP Phenolsulfonphthalein RE Reference Electrode RPMI Roswell Park Memorial Institute medium SE Sensitive Electrode SMT Surface Mount Technology USB Universal Serial Bus UV Ultraviolet VIS Visible 1 Chapter I – Introduction 2 1.1. Objectives and Motivation Interest in tumour pH started when the pioneering work of Otto Warburg implied that aerobic glycolysis was a characteristic property of malignant cells (Warburg, Posener, 1924). Warburg conjectured that the oxygenation supply of tumour cells was harmed, so that they preferentially metabolised via anaerobic pathways, generating large quantities of lactic acid. This metabolic pathway makes malignant tissue more acidic than healthy ones, which led to several experimental tests to measure tissue pH (Freeman et al., 1980). As a result, it is now established that at least some tumours have a more acid interstitial pH than normal tissues. Organ-on-a-chip (OoC) systems are miniaturised microfluidic devices with 3D human organ or tissue replicas, designed to repeat the essential biological and physiological parameters observed in vivo (Ahadian et al., 2018) . The OoC arisen as a practical platform for differentiated medicine and drug screening tests. The in vitro models with biomimetic compositions and functions are projected to take over the traditional static cell cultures. An entire system of interconnected organoid models with microfluidics, mimicking in vivo conditions, contribute to analyse multiple interactions between several organs. Although an extensive multiplicity of OoC models have been created so far, there are still challenges in the incorporation of micro(bio)sensor systems for their continuous monitoring. Therefore, the in situ and continual measuring of the microenvironment parameters and the dynamic activities of the organs is still a critical technological issue. Additionally, automated and noninvasive proceeds are clearly favorite for the long-term monitoring. Generally, the in vitro systems for biology and drug development involve low volume microdevices for the chemical signalling, microfabricated pumps, valves, electrochemical sensors for rapid metabolic assessment, advanced bioinformatics, integrated electronic control and many other components. The development of portable and integrated biosensing devices for real‐time analysis, can offer significant advantages over current analytical methods. Integrated optics‐based biosensors have become the most appropriate technology for OoC integration, due to their ability for miniaturization, high sensitivity, reliability, and their potential for mass production at low cost. The main goal of this dissertation project, performed through a partnership between University of Minho (Portugal) and Jade Hochschule – Wilhelmshaven, (Germany), is to develop and optimize reliable and miniaturised optical pH sensors for cell culture media monitoring, has response to the 3 biological organoid activity, both tumoral and healthy tissues. Overall, the designed pH micro(bio)sensor has the potential to be integrated with OoC platforms for continuous monitoring of organ models during several days. 4 1.2. Structure The present dissertation is divided into five main chapters, namely: Chapter I where the objectives and motivation have been set out. Chapter II refers to the survey of all literature considered important for the idealization of the optical sensor, from the type of sensors already existing for measuring pH, the cell culture medium used in cell culture practices and the study of the optical compost for transmittance measurements in 1 cm cuvettes and 1 and 2 mm microchambers. Chapter III describes the entire sensor manufacturing process. It refers to the micro-camera, light source and photodetector technologies used, codes used in both signal acquisition and sensor user interface, materials and structure used. Chapter IV leads through the procedures and experiments and the optical response measurements on 1 and 2 mm microchambers and the sensor. The work presented in these two last chapters (III and IV), represents the experimental work developed in Germany. Finally, Chapter V presents the main conclusions, as well as the suggestions for future work. 11 2.3.1. Organ-on-chip sensing and control Conventional sensing devices to control the cellular microenvironment are still difficult to integrate with microfluidic OoC systems, due to the low-volume bioreactors for continual monitoring (Shaegh et al., 2016). However, the micrometric structures have a huge surface-volume ratio, allowing the control of physical parameters at a higher level. Therefore, the attention that is being given to the development of these platforms is increasing. The OoC systems impart the integration of sensors to scrutinize the physicochemical properties of cultured organoids growing in the platform, maintaining a good microenvironment. Meantime, human OoC models have been produced, as the four-organ Homo chippiens (i.e., mimic human body using a network of simulated organs, cf. Figure 3). However, studies on the inclusion of sensors are not yet sufficient for continuous real-time measurement, either to read microenvironmental parameters or to acquire the dynamic behaviour that organoids demonstrate in response to pharmaceutical compounds over the time. Besides, these platforms must have automated sensoring potential for long-term monitoring (Y. S. Zhang, 2017). Figure 3 - A concept drawing of a four-organ µHu (Homo chippiens). (A) An on-chip peristaltic ventricular assist, (B) Right heart, (C) Lung, (D) Left heart, (E) Liver, (F) Peripheral circulation, (G) Microchemical analyser of metabolic activity. The system would work on a single microfluidic chip, with on-chip pneumatic valves controlling system functions and connections (Wikswo et al., 2013). The interactions between organs place a severe restriction on the total and carrier circulating fluid. For this reason, it is crucial to develop the pump systems, valves, and analytical instruments in the microdevices design to study and maintain the physiological contributions within the normal parameter’ values found in the human body (Ayuso et al., 2019). 12 One of the most important features to achieve a device with similar physiological parameters of the human body, is the volume of cell culture (mimicking blood supply) in proportion to the mass of cells. In other words, the total volume of fluid in OoC devices must be proportional to the total platform size, in the same proportion as between the volume of blood in the human body and its mass. (Wikswo et al., 2013). Advanced cell culture platforms, such as OoC, must update various cell types while optimising physiological processes. Therefore, the monitoring of parameters related to the medium for cell culture can be seen as a focal point for the optimization of OoC. To maintain the good working conditions of an OoC, the pH of cell culture media is a key parameter to be conditioned and observed. The pH must be kept within relatively narrow limits (pH 6.5 - 7.5)(Met, 1987), for the maintenance and growth of most cells. 13 2.4. Medium for cell culture 2.4.1. pH in cell culture medium The chemical and physical conditions in the environment of cells may immediately determine or alter the cellular activities. Therefore, a major effort is made to study how to handle the appropriate conditions to maintain cells in active proliferation and growth. In previous observations (Absolonova et al., 2018) was observed that the changes in hydrogen ion (H+) concentrations are related to the response of animal cells in the environments. Broadly speaking, where a metabolic reaction involves H+ as a reactant, there is a pH-dependence of the apparent equilibrium constant and related parameters, such as the free energy change and the 𝑝𝐾𝑎 value or the redox potential (Ullmann & Bombarda, 2013), cf. Figure 4. In short, the pH scale is between 0 and 14. A solution is acid when the pH value is below 7 (neutral pH), while a solution is basic when the pH value is above 7 (Mohan, 2003). pH measurement is one of the most important parameters in biochemistry as almost all biological processes depend on the pH. In general, there are metabolic complications if a small change in the pH value occurs. Figure 4 - Graph showing the relationship between pH and 𝑝𝐶02 in three media. Solution A, bicarbonate enriched medium. Solution B, standard medium. Solution C, bicarbonate-deficient medium (TAYLOR, 1962). The acidification of the extracellular medium (low pHe) and the simultaneous intracellular alkalification of the cytoplasm (high pHi) are important carcinogenic characteristics that cause the formation of an inverse pH gradient, manifesting themselves through the increase of activity of several plasmatic membrane carriers and acid efflux proteins that control the pH homeostasis (Aoi & Marunaka, 2014). This inverse pH gradient is connected to tumour proliferation (Gillies et al., 14 2012). The cancer cells present pHi>7.4 and pHe~6.7−7.1 whereas normal cells show a pHi~7.2 and a pHe~7.4 (Webb et al., 2011, Persi et al., 2018). As mentioned before, these changes in the pH can be used to monitor cellular activity and identify abnormal cancer cells. A range of cellular processes are correlated with pHi changes, which occur during cell proliferation and secretion (Press, 1991). Since intracellular pH plays an important part in the transport of nutrients and enzymatic reactions in the cells, the regulation of intracellular pH is a fundamental physiological process of great significance to the growth and metabolism of cells, which in turn apply a lot of energy to the regulation of cytoplasmic pH. Most animal cells in culture are grown close to a neutral pH (Ham & McKeehan, 1979), isogenic with the cytoplasmic pH, which has to be maintained within a narrow range for optimum growth of cells. Therefore, pH control is achieved through either the incorporation of buffers in the medium and/or replacement of the medium (Met, 1987). 2.4.2. RPMI 1640 For the in vitro cell culture, certain environmental conditions are necessary for cell growth and maintenance. Cell culture media are artificial gel or liquids that create an artificial environment for the cell activity and homeostasis. The selection of cell culture medium depends on the cell type and metabolic requirements. Among cell culture media, RPMI (Roswell Park Memorial Institute) is a medium commonly used in cell culture. The complex media RPMI 1640, Figure 5, uses a bicarbonate buffer system (Ozturk & Palsson, 1990) and it is a medium that works for most types of mammalian cells (Shimizu et al., 2001), as in the growth of cells, when used with primary cells such as hematopoietic cells (Del Pup et al., 2003). It works with different cell lines if accurately complemented with serum, later serum replacements, or proper growth factor supplementation. 15 Figure 5 - RPMI 1640 from ThermoFisher (A) without phenol red and (B) with phenol red. Moreover, the medium offers an advantage to pH monitoring by incorporating the colorimetric pH indicator, phenol red, phenolsulfonphthalein (PSP), often used in cell biology laboratories, typically in a concentration of 1.1 mg/L. 2.4.3. Phenol red As mentioned above, phenol red is a water-soluble molecule, used as pH indicator in medium for in vitro cell culture. Its colour gradually changes from yellow (λmax = 443 nm), corresponding to a pH 6.8, to red (λmax = 570 nm), a pH of 8.2 (Mittal et al., 2009), and above 8.2 pH units becomes a bright pink colour. Phenol red is a steady red crystal in air (Mittal et al., 2009) and behaves like a weak acid at 20 °C. It has a solubility of 0.77 grams per liter (g/L), when dissolved in water, and 2.9 g/L if dissolved in ethanol. In crystalline form or solution under extremely acidic conditions, the compound is established as a zwitterion (Belattar et al., 2018), cf. Figure 6. This zwitterion form is written as H+2PS− and has an orange-red colour. If the pH is above 1.2 pKa, the ketone group loses one proton, resulting in the ion HPS−, with a yellow tone. Higher than a pKa of 7.7, the hydroxy group of phenol red loses its proton, creating the red ion, PS2−. (Kazushige Sogawa, 1970) 16 Figure 6 - Structure of phenol red (Berthois et al., 1986). 2.4.3.1. Phenol red as an indicator for cell culture Most living tissues thrive at a near-neutral pH. For instance, the pH of blood has values between 7.35 and 7.45 pH units. Therefore, to grow cells in tissue culture is necessary to have a medium with the pH corresponding to its normal physiological value. To control the pH of the medium, a small amount of phenol red is added, giving a pink-red colour under normal conditions (cf. Figure 7, at pH 7.4) (Ian Freshney, 2015). The colour change of the indicator, to yellow, is due to the acidification of the medium, which occurs in case of problems in the cells such as accumulation of metabolic sub-products produced by them. In the case of cancer cells, they present excessive amounts of glycolysis that produce high lactate (Granja et al., 2017), or when they are dying or have an excessive growth of contaminants. The colour change, which can be identified with the naked eye, is an accessible way to rapidly verify the health of the tissue cultures. Even without cancer cells in the medium, the change of colour from pink-red to orange or yellow indicates that the medium must be replaced, so cells are maintained in optimal conditions (Phelan & May, 2017). This colorimetric indicator is promising in the application of cancer detection, being used as an assistant in identification the interface between the cancer and normal tissue. Figure 7 - Phosphate buffers (100 mL) with phenol red (concentration of 1.1 mg/L) for different pH values. 17 2.5. pH sensors The boom in biotechnology has helped the rise of several industrial processes based on cell and microbial culture, translated in an enormous number of bioprocesses at the laboratory scale and enhancing the development and optimization of the final process. To develop the processes of cell growth in medium, it is crucial the acquisition of data once it allows the monitoring of operating and performing of the experiments. As mentioned before, one of the key parameters of biotechnological processes is the pH value during cell culture, since cell behaviour is extremely sensitive to the surrounding microenvironment. Even in small changes of extracellular, pH can influence considerably the production of matrix macromolecules (Seifan et al., 2017, Kakkar et al., 2017). Mainly, pH sensing can be realised by electrochemical or optical-based detection devices. In the past decades, a substantial effort was been done to develop electrochemical and nonelectrochemical pH sensors for various applications. In electrochemical methodology, electrodes prevent their use from being non-invasive, but the manufacturing process is relatively complicated. A matter of cross-chemistry between adjacent sensors (Suzuki & Akaguma, 2000) since the working and reference electrodes are always required. The phenomenon of signal drift dependent on the flow rate is a huge obstacle, due to interferences resulting from the compositions of the tested liquid (Kurita et al., 2002, Zhang & Chen, 2019). Due to these challenges, electrochemical sensors are not suitable for pH monitoring in a cell culture, in which its flow rate can be dynamic and molecules can interfere in the reading (Morris et al., 2009). For this reason, many studies and projects are directed on the development of an optical-based pH sensor. Among the advantages, the optical pH sensors are low cost, resistant to electrical interference, viable for miniaturization and, most important, are a non-invasive sensing technique. In short, optical pH sensors are based on alterations in the spectroscopic properties of solutions, known roughly as absorption (Islam et al., 2016, Wu et al., 2007) or fluorescence (Gotor et al., 2017, Yadavalli & Pishko, 2004), due to pH variation. The following sub-chapters will describe pH, electrochemical and optical sensors. It will be discussed and clarified why non-invasive optical sensors, are a more promising type of sensors to be incorporated in an OoC, in comparison to electrochemical sensors. 18 2.5.1. Electrochemical pH sensors In the area of electrochemical sensors, there is a vast literature on non-glass membrane pH sensor electrodes, which imply low cation interference with good measurement results at high temperatures. Unfortunately, this kind of electrode often shows a considerable redox sensitivity, causing them to deteriorate more rapidly. Nevertheless, the pH-response of these electrodes can rarely be explained with simple ion-exchange processes, which often includes pH-dependent redox equilibria (Gerischer, 1963). An ideal electrochemical pH sensor of the ion-exchange type, must have certain common properties in their interfaces with external electrolytes, offering almost uniform composition surfaces, which permit rapid exchange of protons in the film or bulk phase, being an ionic semiconductor without electronic conductivity (Madou & Morrison, 1989) Overall, a good working pH sensor must provide a stable phase over a wide temperature range, with uniform ion exchange capacity over the pH range and be independent of material oxidizing and reducing due to the reagents in the ambient media (Manjakkal et al., 2020). The types of materials that are most used in the manufacturing of electrochemical pH sensors are glass (Pradela-Filho et al., 2020, Manjakkal et al., 2018), metal oxides (Ghadi et al., 2020, Jović et al., 2018), polymer or carbon (Alam et al., 2018, Joshi et al., 2017), Metal/Metal oxide (Manjakkal et al., 2020, Sadig & Cheng, 2020) and mixed-conduction oxides (W. D. Huang et al., 2011). The sensors based on metal oxide are the most advantageous. Similarly to the glass electrodebased pH sensors, the metal oxide-based pH sensors, have a sensitivity close to Nernstian response, long lifetime and high accuracy. These also present fast response, low interferences to other ions, very low hysteresis, drift, and optical effects, easy maintenance and miniaturised size, as Metal/Metal oxide-based pH sensors. These sensors can be applied in flexible/wearable systems, as polymer or carbon-based ones, and are compatible with online monitoring applications. Nevertheless, this type of sensors demonstrates a slow response in basic solutions, causing large drift, hysteresis and optical effect (on ISFET based sensors). Another barrier or these sensors is that some materials show low accuracy and resolution, and others show a super-Nernstian or subNernstian response (Kurzweil, 2009). Within the electrochemical pH sensors based on metal oxides, it is important to highlight the 19 potentiometric pH sensor, the capacitive/conductimetric/inductive based pH sensor and the IonSensitive Field-Effect Transistor pH sensor. The potentiometric sensor comprises a combination of an sensitive electrode (SE), thick films in the form of nanostructures (nanowires, nanotubes or nanoflowers) (Manjakkal et al., 2020) and an reference electrode (RE), based on glass, immersed in a solution, deposited using screen printing on the same substrate, Figure 8(A), with its sensitivity determined by the difference in potential between the two electrodes. The conductivity method can be a simple two-electrode probe configuration in an electrochemical (Gill et al., 2008) cell configuration, i.e. an IDE on a substrate and screen printing deposition of a sensitive layer (Manjakkal et al., 2014), Figure 8(C). Unlike the potentiometric sensor, it does not use RE (Antohe et al., 2011) and the response to the electrochemical reaction that occurs at the solution-RE interface is measured by the change in electrical properties such as capacitance or impedance of the film deposited in the IDE. In the ISFET pH sensors, the ISFET is formed directly on the FET (Field-Effect Transistor) electrode (Y. Qin et al., 2015). The gate is coated with a layer of oxide, ceramic, organic, polymer or composed of catalytic metals (Bergveld, 2003, Y. Qin et al., 2015), ion-sensitive, deposited between the source and the drain, detecting the pH (Wei et al., 2020). Figure 8 - Schematic representation of (A) potentiometric pH sensor fabricated by screen-print method, (B) thick film Ag/AgCL RE, (C) IDE based conductimetric pH sensor and (D) chemi-resistor (Manjakkal et al., 2020). 20 Even the metal oxide, the more advantageous electrochemical pH sensors, are not the best option to pH measurement because of their several disadvantages, as the potential deterioration by extended operation in distinct conditions, limiting its application, device instability, low current sensitivity, direct contact with the solution to be measured and sensitivity to light. Although these disadvantages, electrochemical methods are still the most widely adopted techniques for pH sensing. However, mechanical fragility and the lack of flexibility/bendability hinder their implementation in emerging areas, such as wearable systems. Further, durability and performance instability at high temperatures and pressures, limit their use for pollution monitoring and other industrial applications. These drawbacks of the mentioned sensors have encouraged researchers to explore alternative ways to perform pH sensing. For small applications, where the space and liquid volume are limited and agitation is vigorous, such as in OoC, the conventional electrode-type sensors used for monitoring biomodels, are impractical to implement. Besides, in the electrochemical sensors, the probes are inherently invasive, and the stringent sterility requirements are difficult to achieve and maintain (Kermis et al., 2003). Additionally, the cost of instrumenting multiple small devices becomes unreasonable, since they are designed to be disposable. For these applications, there is a demand for sensing technology that is non-invasive, robust, compact and amenable to mass production. 2.5.2. Optical pH sensors Potentiometry is the standard technique for pH measurement, due to its simplicity, reversibility, speed, precision and inexpensiveness. However, in some applications, optical sensors offer more advantages, namely, insensitivity to electrical interferences, electrical safety, lack of the need for a reference element, low-cost (Wu et al., 2009), better characteristics to measuring extreme pH values in low ionic strength solutions, even in the presence of organic matter (Capel-Cuevas et al., 2010), such as in OoC platforms. In general, optical pH sensors are used for measurement and control of pH for applications in chemistry (Korostynska et al., 2007), biochemistry (Schäferling, 2016), clinical chemistry (Boysen et al., 2017) and environmental sciences (Alemohammad et al., 2018). New technological advances have made it possible to manufacture optical pH sensors with the most diverse 27 2.6. Spectrophotometry concepts 2.6.1. Quantitative analysis of light In 1870, Lambert observed that there was a relationship between the transmission of light and the thickness of the absorbent medium layer. When a monochromatic light feature (I0) pass through a homogeneous transparent medium, each layer of the medium absorbs a fraction of light that pass through, regardless of the intensity of the light, which can be expressed as Equation 1: where, I is the intensity of the light that is emitted I0 is the incident intensity k is the absorption coefficient and d is thickness of the medium. This concludes that the intensity of the light that is emitted (I) decreases exponentially as the thickness (d) of the absorbent medium increases. Previously, in 1853, Beer observed that a certain solution absorbs light in proportion to the molecular concentration of the solute found in it. That is, the intensity of a monochrome light beam decreases exponentially as the concentration of the absorbing substance increases (Hughes, 1963). The Beer-Lambert–Bouguer absorption law, or Beer’s law, when it comes to the absorption in an optical medium, is precise only at power densities lower than a few kW. This law, at higher power densities, neglects the processes of stimulated emission and spontaneous emission (Kocsis et al., 2006). This is because at high photon flux, the processes of stimulated emission and spontaneous emission cannot be ignored. Since, its start to affect the population of the energy levels of the atoms (Abitan et al., 2008). Thus, the general absorption law, reduces the Beer’s law for low power densities, Figure 13. The laws of Lambert-Beer are treated simultaneously, a process in which the amount of light I=I010−k.d (1) 28 absorbed or transmitted by a given solution depends on the concentration of the solute and the thickness of the solution. Lambert-Beer's law can be expressed mathematically by the relationship described as Equation 2 (Swinehart, 1962): T=e−a.d.C (2) where, T=Transmittance e = Euler's Natural Logarithm a = constant d = Thickness of the solution C = Solution concentration. Converting the equation to logarithmic form, Equation 3: −lnT=a.d.C (3) Using logarithm on base 10, the absorption coefficient is converted into the extinction coefficient k. From here follows Equation 4: −logT=k.d.C (4) where, k=a/2.303 This can be expressed as the absorptivity, as following: I I0=10−α.d.C (5) A=−log I I0 (6) α= 4πk λ (7) A= α.d.C (8) 29 where, α is the molar absorptivity of the substance and λ is the wavelength of the beam of light. Figure 13 - Schematic of the decrease in radiant power of a monochrome radiation after crossing a cuvette of width, l, containing a solution with a concentration, c, in the component understudy and a characteristic molar absorption coefficient, 𝜀 (Spencer Lima, 2013). If d and α are known, the concentration of the substance can be determined from the quantity of light transmitted. The units of C and α depend on how the concentration of the absorbing substance is expressed (Wypych, 2018), and if the substance is liquid it should be expressed as a molar fraction. The units of α are the inverse of the length. In short, the Lambert-Beer law explains that there is an exponential relationship between the transmission of light through a substance and the concentration of the substance, as well as between the transmission and the length of the body that the light passes through (Davies‐Colley & Vant, 1987). The correlation of the law between concentration and light absorption is the starting point for the use of spectroscopy to determine the concentration of substances in analytical chemistry (Axner et al., 2006). In the field of absorption spectroscopy, spectroscopists use absorption spectra as a technique to detect and characterize substances (Axner et al., 2006). Spectrophotometry is a method used to measure quantities of chemical absorption, reading intensity when a beam of light passes through the chemical solution. The measurement is also used to measure the amount of a known chemical, once each compound absorbs or transmits light in a certain wavelength range. 30 2.6.2. Spectrophotometry measurements The knowledge of light absorption by matter, is the most usual way to determine the concentration of compounds present in solution. All chemical compounds absorb, transmit or reflect light (electromagnetic radiation) at a certain wavelength range. Through spectrophotometry, the intensity of light is measured in wavelengths, and the components of a solution can be identified by their characteristic ultraviolet, visible or infrared spectra (Rojas et al., 1988). The technique uses the property of the solutions to absorb or transmit light to quantify reactions. In practice, the amount of light absorbed or transmitted is proportional to the concentration of the substance in solution. The more concentrated the solution, the greater the light absorption is (Vogelmann & Evans, 2002). On the other hand, the color of the solution is determined by the color of the transmitted light. The two most important concepts in spectrometry are transmittance and absorbance. Transmittance expresses the fraction of light energy that can pass through a certain thickness of a material without being absorbed (Woolley, 1971). In short, it expresses the capacity to transmit light. Absorbance expresses the fraction of light energy that is absorbed by a given thickness of a material, the capacity to absorb light (Gong & Krishnan, 2019). Therefore, the absorbance is the intrinsic capacity of materials to absorb radiation at a specific frequency. Usually, such property is employed in the analysis of solutions in analytical chemistry. In spectroscopy, absorbance is defined as Equation 9: Aλ=log10(I0 I) (9) The term absorption refers to the physical process of absorbing light, while absorbance refers to mathematical quantification. Absorbance only refers to the ray of light transmitted over incident light, not the mechanism by which the intensity of light decreases. This property is often treated as AU (Absorbance Units) (Srinivasan Damodaran, Kirk L. Parkin, 2010). The absorbance of a solution is related to the transmittance. When the absorbance of a solution increases, the transmittance decreases. Transmittance and absorbance tend to be complementary magnitudes. Thus, its sum (for the same energy and incident wavelength) is approximately equal to 1, or 100%. If 90% of the light is absorbed, then 10% is transmitted (De Los Ríos & Fernández, 2014). 31 The measurement of the absorbance of a substance is performed in a spectrophotometer, usually performed in a solution. Then, a monochromatic light of the desired wavelength passes through a cell containing the sample, and another identical beam of light passes through a white one, filled with the same solvent as the sample, but without the substance being analysed (i.e., blank). A detector measures the intensity of the transmitted beams. Some equipment requires the blank to be measured before the sample, while others measure both simultaneously. Comparison with the blank, ensures that only the absorbance relative to the solute of interest is evaluated, and the absorbance of the solvent and losses, due to reflections in the cell, are discounted (Donald Voet, Judith G. Voet, 2016). The longer the length crossed by the beam (optical path), the higher the absorbance, since the beam will interact with more particles of the attenuating substance. As the absorbance is a logarithmic measure of a ratio of luminous intensities, it has no dimensionality. The logarithm in base 10 generates the following relations, Equation 10 and 11: Absorbance: A=−log10(I I0) (10) Transmittance: T= I I0 (11) Therefore, in this study, by comparing the signal that is transmitted through the 1 mm chamber by the different samples and the reference sample, i.e., the blank, the transmittance fraction of each sample can be obtained. Thus, these different values of the transmittance fraction, corresponding to each sample, can be translated into the pH difference. Since the buffer samples will have a colorimetric indicator, phenol red, the pH differences of each buffer in test will be translated into a different spectrometry response. Consequently, each sample with a different pH will have a different transmittance or absorbance level. 32 Chapter III - Development and implementation of the optical pH sensor 33 3.1. Microfluidic Chamber At the macroscale, the milling process is very versatile and can create three-dimensional characteristics and structures. At the microscale, this process allows a fast and immediate fabrication of micro-molds and masks, enhancing the development of microcomponents (Friedrich & Vasile, 1996).The micromilling process ensures a high level of resolution and a small error of tolerance, at the microscale level (Geschke et al., 2004). The operation of micromachining is mostly restricted to precision machining of two-dimensional microparts, normally performed on micro-electrical discharge machining or microlaser computer numerical control (CNC) machine tools. To achieve complex three-dimensional micro-geometries, micromilling can entirely use computer-aided design/computer-aided manufacturing (CAM) software abilities. Hence, both the movement and position of the tools are controlled by the computer. Optimization methodologies and generic algorithms can be coupled with CAM software, after following totally defining the parameters and related constraints of this process, resulting in a small calculation cost. There is a direct correlation between the fragility and the size of the tools, since the smaller the tool is, the more fragile it will be, demanding more caution during the fabrication process. Therefore, due to the small size of the tool tip, it is quite difficult to detect wear on the cutting edges of the tool and its breakage. It results that it is more difficult to predict, since the technology of microscale sensors has limitations, as any technology. The geometrical accuracy of microtools, which varies between approx. 5 and 10 μm, is a significant technological constraint (Krimpenis et al., 2014). A lower surface quality is obtained when the cutting edge of a standard microtool has a small damage. Thermal processes should also be performed on microtools through their manufacturing, and thus improving the microtool cutting performance (Cuypers et al., 2010). Besides, different grain sizes can be used for microtools amelioration, helping in the stability of the manufacturing process (Fleischer & Kotschenreuther, 2007). 34 3.1.1. The material selection The success and growth of microfluidic technology applications depend directly on the material selection, which depends on the needs and conditions of those applications, samples, buffers and their polarities, design and budget. For the development of this work the only material that was used was Plexiglass, also known as PMMA, acrylic glass or Plexiglas XT 0A000 (Figure 14). Figure 14 - Molecular structure of PMMA (Altuglas International, 2006). PMMA is a typical substrate material used in microfluidics, due to its exceptional optical property, biocompatibility, appropriate strength and low cost (Hupert et al., 2007). Due to these advantages it was used as the target substrate in this work. This material is a clear rigid plastic acrylic, transparent and colorless, which can replace glass. For these properties, is commonly usage goes from hockey rinks, signs and lenses. It is a material produced by emulsion polymerization, solution polymerization or bulk polymerization. To produce 1 kg of PMMA, about 2 kg of petroleum is needed. PMMA was a temperature of ignition at 430 °C and burns. For this reason, PMMA is typically processed at 240 – 250 °C (Hupert et al., 2007). The moulding process applied to PMMA consists of injection, compression and extrusion moulding. In order to produce high quality PMMA sheets, cell casting is used, in which the polymerization and moulding stages take place simultaneously (X. Huang & Brittain, 2001). PMMA is a strong, tough and lightweight material. It has a density of 1.17 – 1.20 g/cm3 (Pawar, 2016), which is less than half of glass. In addition to a high density, it also has better resistance. In addition, PMMA is a very transparent material, transmitting up to 92% of visible light (for plates with 3 mm thickness), and gives a reflection of about 4% from each of its surfaces due to its refractive index (1.4905 at 589.3 nm) (Bernini et al., 1992). Regarding the different types of 35 light other than visible light, PMMA is capable of filtering ultraviolet (UV) light at wavelengths below 300 nm, similar to normal window glass, allows infrared light to pass up to 2800 nm and blocks IR from longer wavelengths up to 25000 nm. Table 1 summarizes the main physiochemical characteristics found in PMMA. PMMA has many good properties, however, it swells and dissolves in many organic solvents and also has poor resistance to many other chemicals, due to its easily hydrolysed ester groups. Even so, its environmental stability is superior to most other plastics, such as polystyrene and polyethylene (Barkoula et al., 2008). Table 1 - Main physicochemical PMMA characteristics (Altuglas International, 2006). 3.1.2. Microfabrication In this subsection, it will be presented the methodology used to make the microchannels by micromilling. The setup for the actual milling consists on a regular desktop with the software, the micromilling machine ( Minitech Mini-Mill/GX ) and a second monitor with the point-of-view of the microscope attached to the milling machine, cf. Figure 15. This process passes through three software, namely AutoCAD , Visual Mill and Mach3 . At first, the AutoCAD is used to draw the microchannel geometries. After the drawings, the files are exported for the Visual Mill software to program all the movements for the milling process, to post the code in “.nc”, making compatible with the final software, the Mach3 . This Mach3 tool is the one used to mill the microchannels. In this chapter it will be also presented every detailed step, as well as the specifications of the milling material, tools, the assemble and cleaning, as well as the most common errors that occurred during the process of fabrication. Density (𝛒) 1190 Kg/m3 Forming Temperature 150 - 160 ºC Ignition Temperature 430 ºC Production Extruded Colour Colourless and clear 36 Figure 15 - Setup for Micromilling in Fachbereich Ingenieurwissenschaften Labore Tchnische Optik&Mikrofertigung , at Jade Hoschule. 3.1.2.1. Software Support AutoCAD Intending to design the microchannels, using AutoCAD, Figure 16, there are several aspects and steps to have into consideration: ▪ The drawing must start at the position (0,0) ▪ The scale used is 1 unit, corresponding to 1 mm in the scale used at the milling machine ▪ As the milling is done by parts, each of which has its polygon, it is mandatory to close all the polygons. Since, it is possible to do different conjunctions of polygons for the same design, making the path selection for the tools easier, while programming and saving time, once using different tools in the same channel ▪ Every inlet and outlet circles must be created with 2.1 mm of diameter ▪ At the end of the process, the file is saved as a “.dxf” format. Figure 16 - Window of AutoCAD software. 43 Figure 24 - Microfluidic devices with microchannels and a 1 mm chamber fabricated in PMMA assembled with connecting tubes. 44 3.2. Design of the photodetection system 3.2.1. Light source A white LED from OSRAM, LW G6CP, was used as light source, an advanced power TOPLED, which features a compact package with a wide brightness range and high luminous efficiency. It has a white SMT package, colorless clear silicon resin, using the technology ThinGaN. The colour can be described as C x =0.33, C y = 0.33 (chromaticity coordinate). The schematic of the basic circuit of a LED, Figure 25, was made on Eagle software and the board was then designed, Figure 26, with the appropriate dimensions, and manufactured the respective PCB with the LPKF machine that manufactures high performance from eagle design to finished prototype circuit board. Figure 25 - Schematic of the source light on Eagle software. Figure 26 - Board design for the source light PCB on Eagle software. 45 The understanding of how the LED light beam affects the 1 mm chamber is achieved by viewing the image that is created by the beam when it reaches the chamber via a typical USB microscope camera, using the sploview program. This image, Figure 27(b), is followed by using optical filters, allowing the light to filter into its three components. Figure 27 - (a) Apparatus with camera with brightness connected to a computer via USB, monitored in the software sploview interface, micro-camera, two optical filters 1/10 and 1/5 and LED on to obtain (b) the incidence behaviour of the 3 components of white light emitted by the LED. The spectral response of the LED observed at Figure 28, was made using the spectrometer and the OceanView software. Two peaks are observed in the light intensity spectrum of the LED, for 456 nm and 565 nm, with more and less intensity, respectively. These observations are compatible with the LED datasheet. This LED is suitable for the study of solutions with phenol red, because compared to the spectral response of the transmittance to the different buffer solution, with different pH, the sharpest peak is at 560 nm. Therefore, the peak with less intensity of the LED, is superimposed with the peak transmittance response of the solutions. Figure 28 - Example of the spectra intensity of the LED obtained with spectrometry on OceanView software. 46 3.2.2. Photodetector The photodetector used in the sensor was incorporated in the AS7242, a 6-channel visible spectral_ID Device whit Electronic Shutter and Smart Interface. It is a code effective multi-spectral sensor-on-chip solution, sensing in the visible wavelengths from approximately 430 nm to 670 nm, a good range (2.88 eV – 1.85 eV) corresponding to the interval of transmittance response of the sample solutions in study (i.e, 560 nm). The AS7262 incorporates Gaussian filters into standard CMOS silicon via nano-optic added interference filter technology and is packaged in an LGA package that offers a built-in aperture to control the light entering the sensor array, cf. Figure 29. Figure 29 - (a) Adafruit AS7262 and (b) its photodiode array. The compact 6-channel spectrometry solution features in the 450, 500, 550, 570, 600 and 750 nm, each with 40 nm FWHM. It is a simple and easy device to operate, Figure 30, since no additional signal conditioning is required, using a 16-bit ADC with digital access. Also, it has low voltage operation, i.e., 2.7 V to 3.0 V. The control and spectral data access are implemented through 𝐼2𝐶 register set. Figure 30 - AS7262 Visible Spectral_ID System. (ams AG, 2016) The optical characteristics of AS7262, Table 3, are relative to calibration and measurements made using diffuse light, in each channel tested with GAIN=16x, Integration Time (INT_T)= 166 ms and 47 VDD=VDD1=VDD2= 3.3 V in an environment temperature of 25 ºC. The accuracy of the channel counts/(µW/𝑐𝑚2) is ± 12%. The source light used is a 5700 K white LED with an irradiance of ~600 𝜇𝑊/𝑐𝑚2 (300 – 1000 nm). The energy at each channel (V, B, G, Y, O, R) is calculated with a ± 40 nm bandwidth around the center wavelengths (450, 500, 550, 570, 600 and 650 nm). Table 3 - Optical characteristics AS7262 (Pass Band). (ams AG, 2016) Parameter Test Conditions Channel (nm) Min Typ Max Unit Channel V 5700K White LED 450 45 count/(µW/cm2) Channel B 5700K White LED 500 45 count/(µW/cm2) Channel G 5700K White LED 550 45 count/(µW/cm2) Channel Y 5700K White LED 570 45 count/(µW/cm2) Channel O 5700K White LED 600 45 count/(µW/cm2) Channel R 5700K White LED 650 45 count/(µW/cm2) FWHM 40 40 nm Wavelength Accuracy ±5 nm Dark Channel Counts 5 counts PFOV ±20.0 deg 3.2.3. Software for signal acquisition using Arduino The programming of Adafruit AS7262 is user-friendly in Arduino, as it has libraries associated with many predefined functions in the "Adafruit_AS726x.h" library. In this chapter is presented the explanation of the code of the acquisition chip for the photodetector signal (full code in Appendix II). Briefly, the first lines of code allow the inclusion of two libraries. The “<Wire.h>” library allows us to communicate with I2C devices. The wire library implementation used 32-byte buffer; therefore, any communication should be within this limit, exceeding bytes in a single transmission will just be dropped. The "Adafruit_AS726x.h" library is a class that stores state and functions for interacting with AS726z spectral sensors. 48 To create the object (“ams”) in the code it is used "Adafruit_AS726x ams", therefore it is necessary a buffer “sensorValues [AS726x_NUM_CHANNELS]” to hold vales. The main function of code is the "setup" function. In this code part the data acquisition baud rate is implemented in 9600 with the function "Serial.begin (9600)". The digital pin LED_BUILTIN is set as an output and if is not possible to connect with the sensor, an information will be processed to the user: "could not connect to the sensor! Please check your wiring". If there is a connection with the sensor, the code will run the function "loop" with an integration time of 0.28 s. The function "setIntegrationTime" on the sensor object, allows the signal acquisition with an integration time of 2.8 ms multiplied by the number in this function. To read the set, the LED with a current of approximately 10 mA, uses a cable connection with the LED of the chip, directly with the source light LED, so there is just the need to connect the USB cable if the MICRO Arduino is connected to the PC. Power implementation is just needed for the source light. The LED is turned on in the chip with the function "drvOn" with a 12.5 mA current, translated to the number 0 in the function "setDrvCurrent". In the function “loop”, the device temperature can be read, and the measurements are started with the function "startMeasurement". The values are read with the function "readRawValues" and at every 0.28 s is given an output of the intensity read in counts, on each of the 6 photodetector channels (violet, blue, green, yellow, orange, red), with the function "Serial.print(sensorValues[AS726x_VIOLET", in the case of the violet channel and printed with the function "Serial.print". 3.2.4. Acquisition hardware and reading In order to achieve the acquisition of the signal reading, it is necessary to connect the sensor to the computer and program it. This sensor has four mounting holes and two header breakout strips. The power pins are Vin (power pin 3-5VDC), 3Vo (3.3V output) and GND (common ground for power and logic). The logic pins are SCL, SDA and RST. SCL and SDA are the I2C clock pins, connected to microcontrollers I2C clock line with a 10K pullup, level shifted to use 3-5VDC. The RST is the reset pin, which when pulled to ground the sensor rests itself. In the same way as the two other pins, RST is level shifted 49 to use the 3-5VDC logic. The Micro board is based on the ATmeda23U4 developed with Adafruit. It has 20 digital input/output pins (Figure 31), a 16 MHz crystal oscillator, a micro USB connection, an ICSP header, and a reset button. Every important tech specification of the board is listed on the Table 4. It contains all the information needed to support the microcontroller. This board is simply connected to a computer with a micro USB cable. Table 4 - Tech Specifications Of Micro Arduino board. (AG, 2014) Operating Voltage 5 V Input Voltage (recommended) 7-12 V Input Voltage (limit) 6-20 V Digital I/O Pins 20 PWM Channels 7 Analog Input Channels 12 DC Current per I/O Pin 20 mA DC Current for 3.3V Pin 50 mA Flash Memory 32 KB (ATmega 32U4) of which 4 KB used by bootloader SRAM 2.5 KB (Atmega 32U4) EEPROM 1 KB (ATmega 32U4) Clock Speed 16 MHz LED_BUILTIN 13 Length 48 mm Width 18 mm Weight 13 g 50 Figure 31 - Pinout Diagram of MICRO ARDUINO board, available on Arduino Store. © 2020 Arduino For the acquisition of signal, there are four connections that need to be made between the sensor Adafruit AS7262 and the micro Arduino board. The Vin is connected to the power supply (pin +5 V), the same voltage that the microcontroller logic is based on. The GND is connected to common power/data ground (pin GND). The SCL is connected to the I2C clock SCL pin on Arduino (PD0), and the SDA pin to the I2C data SDA pin, on Arduino (PD1). The connections are made with welded wires in adapters for the Micro Arduino. 3.2.5. Holdering the acquisition chip board When the connection is made, it is necessary that the photodetector aligns directly with the light beam that comes through the optical fiber. The Adafruit AS7262 is placed in a PMMA holder designed in AutoCAD , cf. Figure 32, to be stable and the open photodetector be perfectly placed in the center of the holder. To manufacture the holder, it is necessary that the height removed from PMMA is compatible with the height of the AS7262 dipositive PCB components. In order to have a close contact with the PCB. For example, in this study 1.6 mm of PMMA had to be removed, as there are parts on the used device with a height of 1.5 mm. In micromilling, an air syringe is normally used to help remove PMMA residue from the surface 51 that was processed. In this case, the surface is needed with a very small roughness, to make sure it fits perfectly. Therefore, some oil is used on PMMA with the Zecha 1 x 2.5, 1000 µm tool. The 4 holes at the corners of the design shown in Figure 43 are a bit more open after the micromilling, using a 2.5 mm screw and oil, to make sure that the screws between Adafruit AS7262 and the holder are tightened without damaging the PMMA. Figure 32 - AutoCAD design of Holder for Adafruit AS7262 with a hole representative of the photodetector entrance. By using a microscope, Figure 33(a), the alignment is done through a pinhole placed above the photodetector, Figure 33(b). All these alignment components, microbank structures, are used in optical setups (black structures observed in the Figure 33). After the photodetector is in the center, it is possible to place an adapter for the optical fiber, Figure 33(c), that makes the light beam from the optical fiber and the photodetector be placed in the center. The setup is shown in Figure 33(d). Figure 33 - (a) Microscope and the part to align. (b) Pinhole to align. (c) Adaptor to connect optical fiber to Adafruit AS7262. (d) Setup to achieve the spectral responsivity od Adafruit AS7262. 52 3.3. Design of the Beam-splitter Sensor 3.3.1. Conceptual design With the goal that the optical path, in the 1 mm chamber to be integrated in the pH sensor, is the same as the optical path in a 2 mm chamber, a configuration has been thought of, so that the light goes through the 1 mm microchamber twice. In other words, the light falls on the micro camera and when it reaches its extremity, the light goes the opposite way, so that we have the optical path doubled and thus more intensity in the values that can be measured by spectroscopy. To achieve this goal, a beam-splitter setup was thought. In order to divide a beam of light into a multiplicity of parallel beams of equal intensity, the material used must have at least two blocks of light-transmitting isotropic material. These blocks must have one main face (incident input beam) coated to be partially transmissible and one silvery opposite face. These are arranged so that when the beam reaches the first block (input beam), it splits into a reflected part and a transmitted part. The transmitted part enters the block and after full internal reflection provides an output beam parallel to the reflected part of the first beam. Each subsequent block receives all parallel beams from the previous block, and so on (Partitioner, 1987). However, in some applications, the beam splitter is presented with a single parallel-sided slab with a given coating. The material used in the coating varies along the length, causing the coefficients of reflection and transmission to vary, causing successive internal reflections, emerging in parallel and with equal intensity. The technical drawing, Figure 34, shows apparatus for the sensor producing two parallel output beams of equal intensity from a single led beam. 59 3.3.5. PMMA microchip A new microchamber was manufactured using the same manufacturing method and material as presented before in chapter 3.1.2, so that it can be positioned on the base cube with 4 screws in the round openings, as shown in Figure 44 in the AutoCAD design. The inlet and outlet of the chip were positioned outside the area of the manufactured pinhole (which works as an optical path stop). Figure 44 - AutoCAD design of PMMA chip of 1 mm microchamber of the sensor. 3.3.6. Sensor and acquisition on PCB A PCB was designed in Eagle , Figure 45, and then manufactured to implement the connections between Arduino Micro and Adafruit AS7262. In this way, both Adafruit sensors are paired as a single device, Figure 46, ready to be functional and connected through the user with a USB cable. Figure 45 - Eagle design of sensor PCB board. 60 Figure 46 - Sensor viewed from (a) right side, (b) left side, (c) front and (d) back. 3.3.7. Interface algorithm and software In this chapter the explanation of the code used in the interface is given (full code in Appendix V). The interface was created in the Processing software, using Java language. The explanation is given using information that can be imported into the processing website database. The presented interface consists of a small window to be integrated in the monitoring of an OoC system, to observe the current pH within the 1 mm microchamber, being able to inform users and researchers of the OoC device, when it is necessary to renew the medium for cell culture. It is also possible to observe the transmittance variation over time. Briefly, “Control P5.*” is a necessary library with Controllers to build a graphical user interface on top of processing sketch, which includes sliders, checkboxes, amongst others, and can be easily added to a processing sketch. The “processing.serial.*” is the serial class for sending and receiving data using the serial communication protocol, good to be adapted to Arduino’s serial communication. After the communication object has been created and the data is communicated, the global variables are created. “Pfont” is the font class for Processing, which uses fonts with the .vlw font format (uses images for each letter). “setup” is the first function created from the interface that 61 opens the commutation port and set the baudrate (9600) of the communication. The "settings" function is created to define some of the graphical settings of the operative window to the user. This is a public void function. The ON and DISPLAY, "button" and "button2" buttons are also created, respectively. The ON button switches on the input values for the interface and the start of the pH reading, which is initially 0, as default. The DISPLAY button starts the transmittance response over time and the pH 6 value corresponds to the initial reference, when the transmittance is total. The "draw" function consists of two parts. The first part is programmed to draw the ON and DISPLAY buttons and their colours are defined with the "fill" function. If the data is being received, the program reads these values "myPort.readStringUnt" and they are saved in the variable "val" and the variable is printed in the console "println(val)". When the mouse passes the DISPLAY button the variable "val" is saved as integer in the variable "ref", to be used in the second part of the "draw" function. Data that are not stored under the variable "val" are stored under the variable "green", then standardised and stored under the variable "g". This normalization is done by dividing the values by their own value and then multiplied by 100, to obtain the transmittance in percent for easy readability and comparison, and pH value assignment in the code. The variable "r" is created for the pH value and is 0.000 by default and will present a certain value (pH) to the user, according to the transmission value, “g”, of the sample in the microchamber. Each interval corresponds to a certain pH value and will only be set after the sensor operation have been checked and finally measured. When the mouse hovers over the ON button, the data is available again. The graphical representation of the transmission has its color defined with the "stroke" function and is defined with the "line" function, which updates its "prev" value with each data that the software receives. The value of the "prev" variable is a 1 in 1 count and serves as the advance of the x coordinate value of the transmittance graph. The variable "f" creates the font with font Arial and size 16. The texts of the buttons are superimposed on the rectangle of the button with the function "text", positioned in a determinate GUI coordinate ( x , y ). The colours of the letters and the pH value box are defined with the function "fill". Finally, and if a reading is executed in which the data occupy the whole window, the transmittance profile (line) starts again at the beginning, in the coordinate x =0. 62 Chapter IV - Results and Discussion 63 4.1. Macroscopic measurements of pH solutions 4.1.1. Preparation of pH buffer solutions with phenol red The concentration of phenol red that commercial cell culture medium normally presents is 1.1 mg/L (Basel et al., 1982). To obtain stable pH solutions, without the need for cleanroom environments, several phosphate buffer solutions were prepared (Works, 2018), and mixed with phenol red at the defined concentration of 1.1 mg/L. Briefly, to prepare 100 mL of a 0.1 M phosphate buffer, is necessary to mix a volume of 0.2 M of sodium phosphate dibasic dodecahydrate (Na2HPO4∙12H2O,FW=358.14), solution A, with a volume of 0.2 M sodium phosphate monobasic monohydrate (NaH2PO4∙H2O,FW= 138.01) , solution B, and dilute 1:1 v/v with deionised water. The proportion of solution A and B, gives the pH value, as shown in Table 5. Table 5 - Phosphate buffer for different pH values (Works, 2018) pH at 25ºC Solution A (mL) Solution B (mL) 5.8 4.0 46.0 6.0 6.15 43.85 6.2 9.25 40.75 6.4 13.25 36.75 6.6 18.75 31.25 6.8 24.5 25.5 7.0 30.5 19.5 7.2 36 14 7.4 40.5 9.5 7.6 43.5 6.5 7.8 45.75 4.25 8.0 47.35 2.65 To make a reasonable amount of stock solutions, A and B, 500 mL of each stock solutions were prepared. Therefore, for solutions A and B, with a concentration of 0.2 mol/L, 35.816 g and 13.799 g were weighed, respectively. 64 The quantities for phenol red and sodium phosphate dibasic dihydrate and sodium phosphate monobasic monohydrate were made in the Sartorius professional weighing laboratory scale. The quantity of phenol red was weighed on this same scale for A and B solutions, 5.5 mg of phenol red powder was weighed and mixed until completely dissolved in the solutions, Figure 47. Figure 47 - Solutions A and B with phenol red in 500 mL volumetric balloon. Based on the fact that buffer solutions can change their pH as they are exposed to external conditions, such as humidity and temperature changes for a long time, and stock solutions A and B are more stable, it was decided to add the phenol red directly to these solutions and store them until needed. Stock solutions can be stored for a maximum of one month at a low temperature of 4 ºC. Figure 48 presents the final 12 buffer solutions, with pH ranging from 5.8 – 8.0, and their colour change due to the presence of the pH indicator, phenol red. Figure 48 - Buffer solutions and water (reference solution) in 1 cm cuvettes. 4.1.2. Transmittance response acquisition on 1 cm cuvettes – pre-study The setup for the acquisition of the response over the wavelength range, Figure 49, is easy to assemble and fast in obtaining the response. The light comes from DH Ocean Optics UV-VIS-NIR 65 Fiber Optic Light Source , with a high-power light source MINI Deuterium Tungsten Halogen Source with a 200 - 2000 nm shutter (Ave, n.d.), whose properties are shown in Table 6. This light is propagated to the dark chamber, through fiber optics, where the cuvettes of different buffer solutions are placed. This camera allows that there is no interference from other light sources, which act as noise in the obtained signal. The light then crosses the buffer solution inside the cuvette, an optical path of 1 cm, and is transmitted again to fiber optics. The light propagates within the optical fiber to the receiver, the spectrometer, which translates into a transmittance signal read and presented to the user at the OceanView interface. The operation of the OceanView software is shown in the Appendix III. A spectrometer allows the decomposition of light into different wavelengths. The transmission of light or radiation, in general, is measured on a fluid (liquid or gaseous pores) at different wavelengths. This produces the transmission spectrum that is characteristic of each substance. Figure 49 - Acquisition setup for the buffer transmittance response. PC, on the left, camera for placing the buffer, in the middle, and light source and spectrometer, on the right, connected to the camera by optical fiber. Table 6 - Optical features of DH-MINI Ocean Optics UV-VIS-NIR Fiver Optic Light Source (Ave, n.d.). Spectral output 200 - 2500 nm Stability <0.2% (standard deviation for k=1) Drift <0.1%/h Warm-up time 6 minutes, dependent on ambient conditions Bulb lifetime (average/guaranteed) 2000 – 1000 h Output connector SMA 905 Power consumption 12 W 66 Each substance has a so-called characteristic wavelength, during which radiation is absorbed. By measuring the transmittance (the ratio of the optical radiation power before and after the light pass through the sample), the substance itself can be determined, or in this case, the pH of the sample in study. The obtained results are presented in Table 7. 67 4.2. Microfluidic chamber measurements In order to have an expected transmittance response value in a 1 mm microchamber, through transmittance values already obtained for a 1 cm cuvette, a theoretical study was made based on the radiation behavior in microchannels, Figure 50. At the boundary surfaces of the optical waveguides and the microchannels radiation, losses occur due to the millimetre size apparatus. Figure 50 - Radiation flux in microchannel. Φin: incident radiant flux (W) Φex: continuous radiant flux (W) Φre: loss of reflection upon entry (W) τi: pure transmission (number) Φ´re: loss of reflection on exit (W) d: layer thickness of the fluid (mm) As mentioned, the (gross) transmission factor is measured by τ=I/I0. However, reflection, ρ= Φre/Φin, and scattering represents losses in the measuring apparatus. Together with the radiation losses (factors), the radiation flux Φ𝑒𝑥 at the output, Equation 12: Φex =Φin ∙(1−ρ)∙τi∙(1−ρ) (12) The transmittance describes the ratio of the outgoing to the incoming radiation flow in the medium itself. The "pure" transmission therefore only refers to the weakening by the medium (fluid) itself. The other attenuation factors are determined by the apparatus. The total factor of attenuation in this present setup is P with (1−𝜌)2=𝑃. This weakening factor P is determined by an empty 68 measurement without sample. For this purpose, the deionised solvent, i.e. pure water with τi= 1, is pumped through the microchannel. The pure transmission is: τi=τ/P (13) It follows the equation that calculates the radiation flux in vacuum: Φ𝑣=Φin ∙(1−ρ)∙τi∙(1−ρ) (14) From Φex and Φv: τi=Φex Φ𝑣 (15) The pure transmission is directly obtained from the optical power measurement with a sample solution concerning the empty measurement without any sample. The test solution, i.e. with pure water, measured according to the equation τi. The transmission drops exponentially with greater layer thickness d and higher concentration k , it filters out the general weakness law (Equation 16). The absorption coefficient alpha describes the weakening of light. Φex =Φ𝑣∙𝑒−𝛼.𝑑 (16) 𝛼: absorption coefficient in nm 𝑘: concentration in g (sample)/g(solution) d: layer thickness of the fluid in mm There is a constant for fluids, the so-called extinction coefficient 𝜀. This is the characteristic substance size. τi=1∙𝑒−𝜀∙𝑘∙𝑑 (17) From this equation and with the results of the complete transmission spectrum for buffer solutions we can predict the transmittance result for the designed microchambers: 𝑐𝑜𝑛𝑠𝑡=𝜀∙𝑘 =−lnτi 𝑑 (18) For instance, for an 8.0 pH sample the transmittance in a 1 cm cuvette is 24.7 %. It follows: 75 The results that are presented in this chapter, are achieved through the setup shown in Figure 56, where at every 10 minutes the flow of pure water and the different buffer solutions is alternated. Figure 56 - Setup for the transmittance measurements on the microchamber. The buffer solutions go to the microchip in continuous flow during the whole measurement through a micropump with a frequency near to 100 Hz. The waste liquid is discarded into a beaker. The different steps presented, as shown in Figure 57, are the intensity response, in counts, for the buffer solutions with pH 5.8, 6.4, 7.0, 7.4 and 8.0 (calibration points in this study). The maximum value read from each of the channels represents the reference intensity value, pure water. The photodetector channels with the highest variation, and with attention to the percentage variation between the reference level and the different levels for each buffer solution, are the green channel and the violet channel (Figure 57). It can be assumed that the read values are stable, and the abrupt variations observed can be due to the presence of bubbles. Figure 57 - Intensity of Adafruit AS7262 6-channels for experiment performed for buffer solutions with pH 5.8, 6.4, 7.0, 7.4, 8.0, respectively over time. The experiment is done by alternating the reference sample, 76 pure water, and buffer solutions, in the 1 mm chamber. Each step corresponds to the response of the buffer solution in relation to the water response (maximum observable value). The transmittance values are achieved by normalizing the intensity values. The values are divided by the reference value, in this case, the value of pure water. Analysing the transmittance value over the time of the experiment, Figure 58, the violet channel response, increases with the increase in pH. On the other hand, the transmittance read through the green channel, decreases with increasing pH. If we compare these with the transmittance results in % read, by the spectrometer for a 1 cm cuvette, the values agree. A variation of the transmittance response along the different pH values for these two photodetector channels, cf. Figure 59, shows that between 5.8, 6.0, 6.2 and 6.4 pH, the transmittance variation is too small to have a good accuracy in a sensor. Figure 58 - Transmittance of channels violet and green of Adafruit AS7262 for experiment performed for buffer solutions pH 5.8, 6.4, 7.0, 7.4, 8.0, respectively over time. The experiment is done by alternating the reference sample, pure water and buffer solutions, in the 1 mm chamber. Each step corresponds to the response of the buffer solution in relation to the pure water response (maximum observable value). 77 Figure 59 - Transmittance response of channels violet and green of Adafruit AS7262 for pH 5.8 - 8.0 range. The experiment is performed for buffer solutions pH 5.8, 6.4, 7.0, 7.4, 8.0, in the 1 mm chamber, which is done by alternating the reference sample, pure water and buffer solutions. The error between the theoretical and practical values is less than 3.97%, analysing in detail the Figure 60. These deviations can be explained due to the following factors: (1) The theoretical value comes from considering the transmittance value only in one wave compress, 560nm, in a 1 cm cuvette; and (2) The actual value of the green channel of the photodetector makes an integration in a range of wavelengths and presents only a digital value. Nevertheless, it can be observed from the trend lines, that the behaviour between the theoretical and experimental lines, which characterises the transmittance along the pH, are similar. 78 Figure 60 - Expected theoretical response (T) and experimental transmittance response (TP) of green channel of Adafruit AS7262 for pH 5.8 - 8.0 range. A polynomial approach is made to study the error between what is obtained and what is expected, through polynomial equations. The experiment was performed for buffer solutions pH 5.8, 6.4, 7.0, 7.4, 8.0, in the 1 mm chamber, which is done by alternating the reference sample, pure water and buffer solutions. Overall, it can be concluded that the accuracy for the 1 mm chamber is not enough to distinguish the pH values in a pH 0.2 range. Therefore, it is necessary to increase the optical path in the 1 mm chamber. 79 4.6. pH measurements using 2 mm chamber To prove that by doubling the optical path it is possible to have enough accuracy before proceeding with the development of the sensor, the same test as performed in the chapter 4.5, was performed for a 2 mm chamber, cf. Figure 61. Figure 61 - AutoCAD design of the 2 mm chamber to study the transmittance level for different buffer solutions. The photodetector channels with the highest sensitivity are the violet, blue, green and yellow channels, Figure 62, taking the same considerations into account when choosing photodetector channels for the 1 mm camera. Contrary to the response of the 1 mm camera, this can have a higher number of channels with a reasonable response. Figure 62 - Intensity of Adafruit AS7262 6-channels for the experiment performed with buffer solutions of pH 5.8, 6.4, 7.0, 7.4, 8.0, respectively, and over time. The experiment is done by alternating the reference 80 sample, pure water and buffer solutions, in the 2 mm chamber. Each step corresponds to the response of the buffer solution in relation to the pure water response (maximum observable value). The intensity is then normalised and translated into the transmittance that these four channels present for the five buffer solutions, Figure 63. Figure 63 - Transmittance of channels violet, blue, green and yellow of Adafruit AS7262 for experiment performed with buffer solutions pH 5.8, 6.4, 7.0, 7.4, 8.0, respectively, over time. The experiment is done by alternating the reference sample, pure water and buffer solutions, in the 2 mm chamber. Each step corresponds to the response of the buffer solution in relation to the pure water response (maximum observable value). From the transmittance response over the time of the experiment, it is presented the transmittance response corresponding to the different pH values, for the four chosen channels, Figure 64. 81 Figure 64 - Transmittance response of channels violet, blue, green and yellow of Adafruit AS7262 for pH 5.8 - 8.0 range. The experiment is performed for buffer solutions pH 5.8, 6.4, 7.0, 7.4, 8.0, in the 2 mm chamber, which is done by alternating the reference sample, pure water and buffer solutions. The transmittance range is increased by increasing the optical path. The green channel demonstrates once again to be the best channel for the sensor integration. It can be stated that an optical path of 2 mm allows the sensor to obtain sufficient precision to distinguish the different transmittance values, which correspond to the different pH values, ranging 0.2 pH between the different samples. The error between the predicted value for the 2 mm chamber and the experimental value obtained, is less than 6.91% (this error is obtained for the 8.0 pH buffer solution, analysing the Figure 65. Again, different factors lead to this deviation. 82 Figure 65 - Expected theoretical response (T) and experimental transmittance response (TP) of green channel of Adafruit AS7262 for pH 5.8 - 8.0 range. A polynomial approach is made to study the error between what is obtained and what is expected, through polynomial equations. The experiment is performed for buffer solutions pH 5.8, 6.4, 7.0, 7.4, 8.0, in the 2 mm chamber, which is done by alternating the reference sample, pure water and buffer solutions. 83 4.7. pH measurements using beam-splitter sensor 4.7.1. Stability and signal noise To analyse the stability of the sensor, the reference level of the 6 photodetector channels was measured. It consists of a measurement of the standard intensity response and transmittance level that the channels read for pure water, pumped into the microchip with the neMESYS syringe pump at 20 µL/min. The common range for the green, yellow, orange and red channels was 0.002 during the measurement, as it can be seen in the noise signal behaviour, Figure 66. This response demonstrates good sensor stability and accuracy. The violet and blue channels take longer to stabilize, but after reaching the final reference intensity level, are stable as the other four channels. 0,994 0,996 0,998 1 1,002 0200 400 600 Transmittance Time (s) Violet channel noise 0,954 0,966 0,978 0,99 1,002 0200 400 600 Transmittance Time (s) Blue channel noise 0,994 0,996 0,998 1 1,002 0200 400 600 Transmittance Time (s) Green channel noise 0,994 0,996 0,998 1 1,002 0200 400 600 Transmittance Time (s) Yellow channel noise 0,994 0,996 0,998 1 1,002 0200 400 600 Transmittance Time (s) Orange channel noise 0,994 0,996 0,998 1 1,002 0200 400 600 Transmittance Time (s) Red channel noise Figure 66 - Noise signal of the channels of photodetector of Adafruit AS7262. 84 4.7.2. Proof of operation Three solutions, as shown in Figure 67, were prepared from red food coloring ink to check if the sensor has a response that corresponds to that measured in a 1 cm cuvette on the spectrometer using the optical cover setup already described in sub-chapter 4.1.2. These three solutions were used instead of the solutions with different pH as they have quite different transmittance spectra, Figure 68, and can therefore be used with references for calibration and testing of the sensor. The first solution, solution 1, was prepared with red food coloring ink and pure water in a 4:1 ratio (v/v). The second solution, solution 2, was a dilution from the first solution with pure water in a 4:1 ratio (v/v). The third solution, solution 3, was a dilution from the second solution with pure water in the proportion of 4:1 (v/v). Figure 67 - Solutions 1, 2 and 3 prepared with red food coloring ink and pure water, 4:1, 8:1, 12:1, respectively. Figure 68 - Transmittance Spectra of red food colouring ink solutions 1, 2 and 3, obtained with the software OceanView . 1 2 3 91 Chapter V - Conclusion and Future applications 92 5.1. Final remarks The purpose of this project was to develop an optical sensor, with the potentiality to be further integrated in an Organ-on-a-Chip (OoC), capable to measure pH in a range between 6.0 - 8.0 with pH steps of 0.2, in a 1 mm microchamber, using spectrophotometry, especial optical absorption. The microchamber defines the volume where the medium for cell culture can flow to feed the tissues or organs being cultured. To achieve the objective of the work, buffer solutions with a colorimetric indicator, phenol red, were used. The concentration of phenol red in the solutions was selected to be the same as the one found in the commercial culture cell media. To study the optical absorption and transmittance behaviour for solutions with different pH, a 1 mm deep PMMA microchamber was fabricated using the micromilling process. Every fabrication process has challenges and limitations that need to be addressed. Over this milling process a few challenges and setbacks appeared as expected. During the procedure, there were problems with broken tools and irregular microchannels during the milling. The zero on z -axis sometimes was not defined with accuracy, the speed configuration during the NC coding and insufficient application of cooling agent, led to the most seen errors. One of the major problems in using PMMA microdevices, such as the microchambers used in this research, is the appearance of several bubbles, which make it difficult to read assays without disturbances and associated errors. After several experiments with the 1 mm microchamber, which led to the presentation of a stable transmittance reading in this study, it was understood that the optical path needed to be increased. Increasing the optical path leads to an increase in the intensity readings and a higher difference in transmittance between different solutions with different pH and, consequently, the accuracy that a sensor can measure is improved as well. Therefore, the same study was done for a 2 mm microchamber to prove the veracity of this idea. After it was proven that the optical path of the pH sensor, integrated in a 1 mm microchannel, was not sufficient to have a signal difference between the transmittance value read in the pH range of interest tested with different buffer solutions, it was necessary to think and study an innovative setup where we could increase the optical path in the microchamber without change the settled dimensions. From this need emerged a beam-splitter setup with incorporation of a mirror. Without changes in the 1 mm microchamber, we were able to acquire the same values that are read in a 2 mm microchamber. 93 In the elaboration of this sensor, were present many processes and studies. The choice of light source was crucial for the advance of the initial readings in the microchambers. When it was defined that a white light LED would be used as the light source, the optical fibers and the DH-MINI Ocean Optics UV-VIS-NIR Fiver Optic Light Source could be used, because the behaviour is identical, on the grounds that both are white light sources. The signal acquisition was made with a revolutionary photodetector already present in an Adafruit digital sensor. The implementation of this type of digital detection in the sensor makes this innovative and easy to project. There have been several Eagle PCB design and subsequent soldering of components, in laboratory work. The acquisition of signal to the computer to read was done between Adafruit AS7262 and an Arduino Micro board, which is easy to program with existing libraries. The choice of a NanoBank structure allowed us to reduce the sensor size to a few small units in centimetres that can be implemented in a future OoC device. An interface was later created in Processing so that each transmittance value was related to a pH level. It was possible to quantify, with the buffers used, pH below the commercial range (6.8 - 8.2), using only the green wavelength range of the Adafruit AS7262 photodetector chip with a sensitivity of 8.5%/pH in terms of transmittance response. 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Nano Energy . https://doi.org/10.1016/j.nanoen.2020.104760 109 Appendix I Here is presented the procedure, to a better understanding of the software possibilities, to use de neMESYS syringe pump used to test different types of flow and its behaviour on the mixing channel. After opening the user interface program, we should start to "Scan Devices", so the program can detect the syringes existing in the neMESYS. The syringes are assigned, having in consideration their brands and volumes, with a right-click on the name of each of syringe and then "Configure Syringe". If the opened window with numerous sample syringes with associated companies and sizes do not have the syringe that you need, it must be added with the necessary characteristics. When it's essential to change the names of the syringes so that no misunderstandings occur, you double-click on the source name, and that allows a window, where the name can be changed, to open. 110 The syringe pump can be operated manually or automatically. To work in automatic mode, you select "Flow Profile" and choose the option "Load Flow Profile", where you going to upload a preprepared ".nfp" file, previously prepared, with the times and flow rates, of the individual dosages that you want to work in. This process is repeated to all the of the syringes. To start the automatic flow profile right click with the mouse on the "Dosing Units" window, making sure that the name of the syringe is green, and a new window will appear. Then you chose the "Select Operation Mode" and then change it to "Flow Profile". As the desired mode of operation is automatic, click on "Sync Start" and a new window, "Start units synchronously" will appear. You must select the syringes that you want to operate, with a checkmark, and then click "OK". The synchronised start was confirmed, and it will start working. 111 Description of the execution automatic program: The first column has the time in µs of each step. The second column has the flow rate of the step. And then the third column has the number 1 or 0, indicating the behavior of the flow. We use both numbers when we want a smart step-up, with a valve. And then, if the 1 is activated the syringe will fill, if not, 0, the liquid will be flushed to the microchannel. In this case we just have the zero in all the columns, because we don´t have a valve and we just want that the liquids go inside of the microchannels to watch the behavior of the flow. 112 Appendix II The pinout of the supplier Arduino is shown, embedded in the company website, and the code used to program it. 113 #include <Wire.h> #include "Adafruit_AS726x.h" //create the object Adafruit_AS726x ams; //buffer to hold raw values uint16_t sensorValues[AS726x_NUM_CHANNELS]; //buffer to hold calibrated values (not used by default in this example) //float calibratedValues[AS726x_NUM_CHANNELS]; void setup() { Serial.begin(9600); while(!Serial); // initialize digital pin LED_BUILTIN as an output. pinMode(LED_BUILTIN, OUTPUT); //begin and make sure we can talk to the sensor if(!ams.begin()){ Serial.println("could not connect to sensor! Please check your wiring."); while(1); } ams.setIntegrationTime (100); //this time multiplied by 2.8ms will be the integration time that the sensor will acquire signal //ams.setGain(2);//0:1x 1:3.7x 2:16x 3:64x(power.on default;; just need to set the gain if it is needeed less signal) ams.drvOn(); //turn on the LED of the chip 12.5 on defaut 114 ams.setDrvCurrent(0);//0:12.5mA (12.6) 1:25mA (25.32) 2:50mA (too much) 3:100mA(too much). //ams.enableIndicator();//ams.disableIndicator(); //ams.setIndicatorCurrent(0)//0:1mA 1:2mA 2:4mA 3:8mA //ams.setMeasurementMode(2)//0:continuous reading of VBGY (Visible)/ SRUV (IR) 1:continuous reading of GYor (Visible)/ RTUX (IR) 2:continuous reading of all channels //3:one-shot reading of all channels (power-on default) } void loop() { //read the device temperature uint8_t temp = ams.readTemperature(); //ams.drvOn(); //uncomment this if you want to use the driver LED for readings ams.startMeasurement(); //begin a measurement //wait till data is available bool rdy = false; while(!rdy){ delay(5); rdy = ams.dataReady(); } //ams.drvOff(); //uncomment this if you want to use the driver LED for readings //read the values! ams.readRawValues(sensorValues); //ams.readCalibratedValues(calibratedValues); //Serial.print("Temp: "); Serial.print(temp); //Serial.print(" Violet: "); //Serial.print(sensorValues[AS726x_VIOLET]); //Serial.print(" "); //Serial.print(" Blue: "); //Serial.print(sensorValues[AS726x_BLUE]); //Serial.print(" "); //Serial.print(" Green: "); Serial.print(sensorValues[AS726x_GREEN]); Serial.print(" "); //Serial.print(" Yellow: "); //Serial.print(sensorValues[AS726x_YELLOW]); //Serial.print(" "); //Serial.print(" Orange: "); //Serial.print(sensorValues[AS726x_ORANGE]); //Serial.print(" "); //Serial.print(" Red: "); //Serial.print(sensorValues[AS726x_RED]); //Serial.print(" "); Serial.println(); delay(100); } 115 Appendix III The acquisition of response along the wavelength ranges through OceanView is fast and easy. This is the saturated signal that appears when the software is turned on and the light source ( DHMINI Ocean Optics UV-VIS-NIR Fiver Optic Light Source ) is on. Then in Acquisition Group Window the integration time is set to automatic and 20 scans to average were used. When the reference sample (in the cuvette) is placed in the setup (Figure 35) for the transmission signal reading, the reference is made to the readings of the other samples to be read. The first step is to click on the yellow lamp while the light source is on. 116 The second step is to turn off the light source and click on the grey lamp. When the light source is switched on again we already have the transmittance signal of the reference solution as 100%. 123 if(count>=width){ //if values fill the entire window it delete the line count=0; //and start again in the x=0 prev=0; background(200); } else { count++; //advance in the x coordinate } } } }