D5.2 – Life Cycle Model

D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 1 <Project Acronym: NOVETROL Grant Agreement number: 101192615 (HORIZON-CL5-2024-D2-01) Project Full Title: Novel current control for climate neutral energy infrastructure DELIVERABLE D5.2 – Life Cycle Model Dissemination level: PU -Public Type of deliverable: R -Report Contractual date of delivery: 30 November 2025 Deliverable leader: SPL Status - version, date: Final – v1.0, 2025-12-08 Keywords: Life cycle assessment; social life cycle assessment; sustainability; environmental impact; social impact; social risks; emerging technologies D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 2 EXECUTIVE SUMMARY The purpose of this document is to create two life cycle models, on which develop and test the future design of the current limiter device. The first model is created to evaluate the social risks arising from the value chain of producing the InSb-Printed Circuit Board (PCB) that will be part of the final Current Limiter device, whilst the second model is an LCA (Life Cycle Assessment) one focusing on the environmental impacts arising from the production of the Novetrol PCB. D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 3 Deliverable leader: SPL Contributors: Martina Pucciarelli (SPL) Reviewers: Mihaela Albu (UPB), Mina Gheamalinga (ACT) Approved by: UPB Document History Version Date Contributor(s) Description 0.1 25/11/2025 Martina Pucciarelli First draft 0.2 28/11/2025 Martina Pucciarelli Updated content 1.0 08/12/2025 Martina Pucciarelli Final version for submission D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 4 TABLE OF CONTENTS Executive Summary _________________________________________________ 2 Table of Contents ___________________________________________________ 4 Definitions, Acronyms and Abbreviations _________________________________ 5 Introduction ________________________________________________________ 6 Deliverable Overview and Objectives ____________________________________________ 6 Document Framework _______________________________________________________ 6 OVERALL METHOD: PROSPECTIVE LIFE CYCLE THINKING _______________ 6 CASE STUDY DEFINITION – GOAL AND SCOPE _________________________ 8 Goal of the study ____________________________________________________________ 8 Brief description of the manufacturing process and material and energy inventory _______ 8 Social-Life Cycle Assessment (S-LCA) – Case Study ______________________ 13 Modelling and Results _______________________________________________________ 16 RESULTS ______________________________________________________________ 17 Life Cycle Assessment (LCA) – Case study ______________________________ 21 RESULTS ______________________________________________________________ 22 BIBLIOGRAPHY ___________________________________________________ 29 D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 5 DEFINITIONS, ACRONYMS AND ABBREVIATIONS Acronym/ Abbreviation Title DMSO Dimethyl sulfoxide CTU Comparative Toxic Unit DALY Disability Adjusted Life Year LCA Life Cycle Assessment S-LCA Social-Life Cycle Assessment LCI Life cycle inventory LCIA Life cycle impact assessment S-LCI Social-Life cycle inventory S-LCIA Social -Life cycle impact assessment EC European Commission EU European Union JRC Joint Research Center ISO International Standardization Organization DC Direct-Current CL Current Limiter FU Functional unit GWP Global Warming Potential PCB Printed Circuit Board PSILCA Product Social Impact Life Cycle Assessment MRIO Multi-regional Input Output PV Photovoltaic EF Environmental Footprint LCT Life Cycle Thinking D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 6 INTRODUCTION DELIVERABLE OVERVIEW AND OBJECTIVES The deliverable 5.2 “Standard [Sustainability] Life Cycle Model Development” focuses on the application of Life Cycle Assessment (LCA) and Social Life Cycle Assessment (S-LCA) methodologies and their integration to estimate both the environmental performance and social risks associated with the current limiter device. The objectives are to identify a first-pilot study, identify and define an approach to carry out both LCA and S-LCA; start the first round of data collection (representative of the state of the project at the current date); creation of a first LCA model and of a first S-LCA model to be employed within the NOVETROL project, and improved going ahead with the project. DOCUMENT FRAMEWORK The document presents a first case study concerning the application of the S-LCA methodology to the current limiter manufacturing phase, as well as its environmental impacts evaluated throughout the LCA methodology. OVERALL METHOD: PROSPECTIVE LIFE CYCLE THINKING NOVETROL project has the main objective of creating a new technology and to increase its technology readiness level (TRL). Therefore, when applying both the Life Cycle Assessment (LCA) and Social Life Cycle Assessment (S-LCA) methodologies, the data collection would provide data representative for laboratory productions, and not for pilot or industrial scales. Results representative of lab-scale production are useful to identify hot-spots and understand issues that are linked to that specific production scale. A prospective approach is defined as a systematic way to explore the potential development of a production system at a certain time in the future. Therefore, it is an explorative approach that tries to define the development of a foreground and background system (production system) to go from a lab-scale production of a low TRL technology/product to an industrial-scale production of a high TRL product. This entails an upscale of the production system and an upgrade in terms of production technologies. Employment of a prospective approach would be useful to understand the environmental impacts associated with a pilot or industrial scale when the technology reaches a higher TRL. Based on this definition and the objective of this deliverable, which is the development of a life cycle model to assess the environmental and social performances of NOVETROL D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 7 technology, it has been decided to attempt to employ a prospective approach for both the LCA and S-LCA studies. Application of the prospective approach to both studies will also provide methodological consistency, which is fundamental for the integration of results required in D5.3 “Decision making model development and first pilot test”. Figure 1 Graphical illustration of prospective LCA across TRL and time (Hasnaningrum H., 2025). Moreover, in this case study we propose the application of the prospective approach to both LCA and S-LCA studies; this will have an impact, especially on the data collection and inventory phase. The data employed in both studies needs to be the same, aligned. The consistency needs to be at both quality levels, i.e. geographically and temporally. Knowing the geographical location of both background and foreground systems is a sine-qua-non condition for carrying S-LCA studies, whilst for LCA studies the lack of this information can be overcome. Starting from this constraint, it has been decided to start the sustainability assessment from the S-LCA study that entails the identification of possible suppliers, in terms of the most probable suppliers and their locations. This piece of information, together with others, is then used in the subsequent LCA study, as proposed in (Pucciarelli, 2023). D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 8 CASE STUDY DEFINITION – GOAL AND SCOPE This deliverable focuses on defining and trying out the proposed prospective life cycle thinking approach, starting from an S-LCA study and then moving to an LCA one, aiming at defining a standard sustainability life cycle model for the NOVETROL project. In this specific case, the model and results represent the status quo of the project at the moment when data were collected and the study was carried out, which means evaluation of the Printed Circuit Board (PCB) representing the core technology of the current limiter (CL) device. Once the data will be available, the study will be extended to integrate what is missing at the moment and to include if possible the use phase. GOAL OF THE STUDY The overall goal is the assessment throughout the application of the Life Cycle Assessment (LCA) and Social Life Cycle Assessment (S-LCA) of the environmental and social risks associated with the production of 1 (one) Printed Circuit Board (PCB) containing an indium antimonide (InSb) chip, as part of the final Current Limiter (CL) device to be developed within the Novetrol project. The focus is on the production process, which is reflected in the functional unit and its reference flow: “manufacturing and production of printed circuit board containing InSb chip with the technical specifications required to be integrated within the current limiter device (CL) developed within the NOVETROL project”. The reference flow in this case is equal to 1 item. Furthermore, the study explores a lab-scale production in 2025, in Europe, a sensitivity analysis concerning the geographical location of suppliers, and a scenario evaluation at 2030. The system boundaries reflect the FU, including all the “cradle-to-gate” processes, and excluding what comes after the production of the PCB, as it would need to be integrated within the CL, its use phase and end-of-life. The study excludes the production of capital goods and pieces of equipment required during the production/manufacturing of the PCB, as well as the waste management. BRIEF DESCRIPTION OF THE MANUFACTURING PROCESS AND MATERIAL AND ENERGY INVENTORY Within the Novetrol project, the Silicon Austria Labs (SAL) is in charge of designing, manufacturing and testing the PCB with the InSb chip. Data were collected from SAL throughout a Life Cycle data collection sheet, reviewed with the team and then employed in the modelling of both S-LCA and LCA models. The following process flow reports the main steps of the laboratory production, together with the inputs required and outputs. D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 9 Figure 2 Process flow diagram concerning the PCB manufacturing at lab-scale. Source of data SAL. [Hasnaningrum H., 2025]. Qualitative information concerning the materials and energy consumption, as well as the supplier location, were collected. It was assumed that all the electricity required was supplied from the national grid mix (Austria) and the waste was assumed to be managed by Austrias’s waste management system. Table 1 and Table 2 report materials and energy inputs, and wastes produced during the manufacturing process in 2025. Table 1 Materials and energy required at the laboratory scale in 2025. Data provided by SAL. Name of Process Inputs Quantity Unit Location Photoresist coating Photoresist nLoF 2020 0.002 l Germany InSb wafer 0.007 kg USA Electricity 1.07 kWh Austria Photolithography exposure Electricity 1.53 kWh Austria Photoresist development AZ 726 MIF developer 0.1 l Germany Deionized water 0.1 l Austria Metal layer deposition Ti pellets 0.0001 kg France D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 16 Photoresist coating Photoresist nLoF 2020 692.0 USD/l MicroChemicals (2025) InSb wafer 324,000.0 USD/kg MTI Corporation (2025) Photoresist development AZ 726 MIF developer 84.5 USD/l ConRo (2025) Deionized water 32.8 USD/l Fisher Scientific (2025b) Metal layer deposition Ti pellets 8287.8 USD/kg MaTeck GmbH (2025) Au pellets 107,419.3 USD/lg World Bank (2025) Photoresist removal DMSO 146.7 USD/l Fisher Scientific (2025a) Rinse, dry and dice Deionized water 32.8 USD/l Fisher Scientific (2025b) Integration in PCB PCB 1291.7 USD/kg Best Technology (2025) Technology (2025) Solder paste 283.9 USD/kg Farnell (2025) Electricity 0.31 USD/kWh Statistic Austria (2025) Waste 0.035 USD/kg Ettlinger & Bapasola (2016) MODELLING AND RESULTS The S-LCIA was carried out to evaluate the potential social risks linked to the supply chain of the CL device. The modelling and results estimation was done using OpenLCA (v. 2.3.0) together with PSILCA database, which enables to quantify social risks across selected stakeholder groups, including local communities, value chain actors, society, and workers. A cut-off criterion of 1E-5 mid risk working shours was applied to exclude negligible values from the assessment. The type of assessment applied was the social risk-based approach, implemented through the PSILCA Social Impacts Weighting Method, which translates sector and country-specific social risks into quantitative risk hours (Loubert et al., 2023). D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 17 Figure 3 Screenshot of the baseline system model created in OpenLCA (version 2.3). RESULTS Overall results are presented in Table 9. For the baseline case, most of the material inputs are sourced from Europe. Meanwhile, in the sensitivity analysis, the supply chain was modelled based on the biggest key players of the supplied materials, which are mainly located in China and East Asia. The highest social risk is generated by the process of photoresist coating, followed by metal layer deposition and integration in PCB processes respectively. Regarding the overall social risk, sensitivity analysis resulted in a higher risk than the baseline. Material sources that mostly come from Asia have a social risk equals to 177,150 medium risk hours, whilst the baseline, where the inputs generally come from Europe, has an overall social risk equals to 71,351 medium risk hours. This result indicates that the higher social risk in sensitivity analysis is likely caused by differences in labor conditions and economic development. Materials from Asia, specifically from China and Japan, have higher social risks because of longer working hours, lower wages, and less strong labor rights compared to Europe (Eurofound, 2019; You Xiaoying, 2025). Also, in some social categories such as health and safety, contribution to economic development, and social benefits, legal issues use percentage of GDP as a proxy to estimate the potential social risk (Loubert et al., 2023). In fact, GDP in East Asia, where China and Japan are located, has lower GDP than Europe. In April 2025, GDP in East Asia was reported to be 26.46 thousand USD, while GDP in Europe was reported 27.87 thousand USD (International Monetary Fund, D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 18 2025). Hence, the higher social risks in the sensitivity analysis for materials from Asia are caused by the combination of less favorable labor conditions and lower economic development. This shows that even if the processes are similar, the origin of materials has a big impact on the total social risk in the supply chain. Table 9 Overall social risk of each process corresponding to the Baseline (laboratory scale 2025); sensitivity analysis based on the location of supplier, and finally the optimised process with a different FU (EU level). Stakeholders Photoresist coating Photolithography exposure Photoresist development Metal layer deposition Photoresist removal Rinse, dry, and dice Integration in PCB BASELINE: Laboratory scale in 2025 UNIT Mid Risk Hours Local Community 5.46E+03 1.73E+00 4.86E+01 6.31E+02 6.49E+01 1.15E+01 1.94E+02 Society 8.22E+03 1.02E+00 4.37E+01 9.34E+02 5.87E+01 1.01E+01 1.14E+02 Value Chain Actor 1.40E+04 2.18E+00 3.87E+01 9.31E+02 4.97E+01 1.04E+01 1.31E+02 Worker 3.77E+04 3.80E+00 8.89E+01 2.05E+03 1.14E+02 2.35E+01 4.16E+02 TOTAL 6.54E+04 8.74E+00 2.20E+02 4.55E+03 2.88E+02 5.55E+01 8.55E+02 SENSITIVITY ANALYSIS OF SUPPLY CHAIN UNIT Mid Risk Hours Local Community 3.40E+04 1.67E+00 1.41E+02 6.12E+02 2.29E+02 1.06E+01 5.84E+02 Society 1.58E+04 9.49E-01 7.01E+01 8.86E+02 1.07E+02 8.91E+00 2.73E+02 Value Chain Actor 1.40E+04 2.14E+00 8.93E+01 1.22E+03 1.39E+02 9.74E+00 2.40E+02 Worker 1.39E+05 3.68E+00 5.48E+02 1.49E+03 9.22E+02 2.17E+01 2.38E+03 TOTAL 2.03E+05 8.44E+00 8.49E+02 4.21E+03 1.40E+03 5.09E+01 3.47E+03 2030 SCENARIO UNIT Mid Risk Hours Local Community 2.67E+09 7.49E+05 2.45E+07 3.21E+08 3.27E+07 5.77E+06 4.56E+07 Society 4.04E+09 4.37E+05 2.15E+07 4.77E+08 2.89E+07 4.99E+06 2.56E+07 Value Chain Actor 7.09E+09 9.54E+05 1.96E+07 4.82E+08 2.52E+07 5.26E+06 3.11E+07 Worker 1.89E+10 1.65E+06 4.43E+07 1.05E+09 5.70E+07 1.17E+07 9.67E+07 TOTAL 3.27E+10 3.79E+06 1.10E+08 2.33E+09 1.44E+08 2.78E+07 1.99E+08 Figure 4 showcases the percentage contribution of each process to the social risks associated with each stakeholders category. The most affected stakeholder groups are workers, followed by the value chain actor, local community, and society respectively. For example, in the photoresist coating process, workers contribute with 58% of medium risk hours, while value chain actor, local community, and society contribute with 21%, 8%, 13% respectively. It can be noted that across all processes, worker is constantly representing the largest share of social risk. It is indicated that labor-related issues are the most critical impact along the supply chain. Other than that, value chain actor is the second most affected stakeholder with the highest social risk generated by photoresist coating process (25%). Local community and society have D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 19 lower contributions in most processes. However, they still cannot be neglected as they have some contributions to the overall social risk. Figure 4 BASELINE: Social risks analysis concerning the stakeholder groups. Figure 5 Sensitivity analysis: Social risks analysis concerning the stakeholder groups. Figure 5 represents the result of different supply chains against the stakeholder groups. Similar with the baseline, the workers category is still becoming the most affected stakeholder, holding the largest share across all processes. However, differently from the baseline, the second most impacted stakeholder is local community. This difference is mainly because, in the sensitivity analysis, the materials such as InSb wafer, PCB, and some chemical products are coming from China, where social risks related to the local community stakeholder are higher. Value chain actors and society have lower contributions compared to workers and local community, but still represent important components of the overall social risk. It is Local Community Society Value Chain Actor Worker medium risk hours (%) Case 1: 2025 Baseline Photoresist coating Photolithography exposure Photoresist development Metal layer deposition Photoresist removal Rinse, dry, and dice Integration in PCB Local Community Society Value Chain Actor Worker medium risk hours (%) Sensitivity Analysis of Supply Chain Photoresist coating Photolithography exposure Photoresist development Metal layer deposition Photoresist removal Rinse, dry, and dice Integration in PCB D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 20 noteworthy to say that material sources from different regions can change the distribution of social impact across stakeholder groups. Figure 6 Social risks estimated in 2030. Lastly, the results on stakeholder groups of the prospective scenario can be seen in Figure 6. Like the other cases, worker remains to be the most affected stakeholder across all processes, with contributions ranging from 40% to 58%. In this case, photoresist coating contributes to the largest share in the worker stakeholder, followed by integration in PCB and metal layer deposition. These results are expected because the main materials, such as InSb wafers used in the photoresist coating process and PCB used in the integration in PCB process, dominate the social risk contribution. The system optimization in this case mainly targeted photoresist utilization efficiency and energy consumption efficiency, without changing the use of key materials such as PCB and InSb wafers. These results indicate that social risks are largely driven by the main material inputs and their supply chains, while improvements in material or energy efficiency have a limited effect on the distribution of social risks, based on the assumptions made in this case study. Local Community Society Value Chain Actor Worker medium risk hours (%) Case at 2030 Photoresist coating Photolithography exposure Photoresist development Metal layer deposition Photoresist removal Rinse, dry, and dice Integration in PCB D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 21 LIFE CYCLE ASSESSMENT (LCA) – CASE STUDY The Life Cycle Assessment is an internationally recognized methodology that enables the estimation of potential environmental impacts along the life cycle of products and/or services. It can be employed for different purposes, such as to understand the environmental impact of products already in the market, comparative studies, and to explore what would be the impact of emerging products with a low TRL. In this last case, LCA is useful to highlight possible issues and trade-off that may not be evident till the product is on the market. In this case, we employ LCA to explore the potential environmental impact that arise when producing the PCB to be integrated within the CL when the production is at laboratory scale, then based on the S-LCA, a sensitivity analysis based on the geography is carried out, together with an estimation of the potential environmental impact due to the estimated EU market demand in 2030. As explained in the section “CASE STUDY DEFINITION – GOAL AND SCOPE”, the functional unit for the baseline is equal to 1 item, the system boundaries are defined “cradleto-gate”, in the future they will be expanded to include the use phase as well. To align the S-LCA and LCA results, it was decided to leave out the study, at this point of the project development, some activities and or processes, these are: • Transportation from the supplier to the production site (in Austria); • Production and disposal of the packaging. The modelling was carried out in SimaPro software using the database ecoinvent (vv. 3.10) (Wernet et al., 2016). The impact categories investigated are listed in Table 10 and the calculation method selected is the Environmental Footprint ( vv.3.1) (Andreasi Bassi et al., 2023; EC-JRC, 2012; Zampori & Pant, 2019) . Table 10 List of the impact categories investigated in this LCA study. Impact category Unit Acidification mol H+ eq Climate change kg CO2 eq Ecotoxicity, freshwater CTUe Particulate matter disease inc. D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 22 Eutrophication, marine kg N eq Eutrophication, freshwater kg P eq Eutrophication, terrestrial mol N eq Human toxicity, cancer CTUh Human toxicity, non-cancer CTUh Ionising radiation kBq U-235 eq Land use Pt Ozone depletion kg CFC11 eq Photochemical ozone formation kg NMVOC eq Resource use, fossils MJ Resource use, minerals and metals kg Sb eq Water use m3 depriv. RESULTS Results are presented for the production at laboratory scale for one InSb PCB device to be integrated within the Novetrol Current Limiter device. Table 11 presents the results in absolute values for each impact category and for each lab manufacturing steps. Wastes from lab are considered as hazardous wastes undergoing incineration. The assembly process, which is the last one, includes only electricity. For a quicker understanding of the results, Figure 7 presents a contribution analysis, that help to understand how much (in %) each process contributes to a specific environmental impact category. D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 23 Table 11 Absolute results from the LCIA for the laboratory production of 1 InSb PCB to be integrated within the Novetrol Current Limiter device Impact category Unit Total Assembly Photoresist coating Photolithography Exposure Photoresist Development Metal layer deposition Photoresist Removal Rinse, dry and dice Acidification mol H+ eq 1,00E+00 2,04E-03 8,25E-03 6,50E-03 3,33E-05 9,06E-01 1,77E-03 8,43E-07 Climate change kg CO2 eq 1,14E+02 4,45E-01 1,31E+00 1,42E+00 9,07E-03 1,01E+02 1,91E-01 7,88E-05 Ecotoxicity, freshwater CTUe 9,34E+03 1,04E+00 4,01E+01 3,33E+00 1,70E-01 8,76E+03 2,30E+02 1,00E-02 Particulate matter disease inc. 7,54E-06 3,30E-09 3,39E-08 1,05E-08 3,10E-10 6,93E-06 1,11E-08 6,71E-12 Eutrophication, marine kg N eq 2,50E-01 4,80E-04 1,98E-03 1,53E-03 1,61E-05 2,32E-01 1,08E-04 6,73E-08 Eutrophication, freshwater kg P eq 3,81E-01 7,27E-04 1,96E-03 2,32E-03 2,41E-06 3,61E-01 3,81E-05 3,42E-08 Eutrophication, terrestrial mol N eq 2,91E+00 3,75E-03 1,98E-02 1,19E-02 8,20E-05 2,72E+00 1,10E-03 6,60E-07 Human toxicity, cancer CTUh 9,45E-08 4,86E-11 1,27E-09 1,55E-10 4,32E-12 8,58E-08 4,94E-11 1,71E-13 Human toxicity, non-cancer CTUh 6,86E-06 3,14E-09 5,07E-08 1,00E-08 7,16E-11 6,46E-06 1,37E-09 1,14E-12 Ionising radiation kBq U-235 eq 1,20E+01 6,91E-04 5,77E-02 2,20E-03 1,13E-03 1,09E+01 1,75E-02 9,89E-06 Land use Pt 9,79E+02 3,53E-01 2,97E+00 1,13E+00 3,20E-02 9,30E+02 3,55E-01 3,31E-04 Ozone depletion kg CFC11 eq 1,41E-06 2,81E-09 1,00E-08 8,97E-09 6,11E-10 8,43E-07 1,34E-08 3,02E-11 Photochemical ozone formation kg NMVOC eq 7,14E-01 1,00E-03 5,19E-03 3,19E-03 3,44E-05 6,62E-01 7,23E-04 2,56E-07 Resource use, fossils MJ 1,48E+03 4,70E+00 1,49E+01 1,50E+01 2,33E-01 1,32E+03 5,38E+00 1,04E-03 Resource use, minerals and metals kg Sb eq 1,38E-01 3,03E-07 4,71E-03 9,66E-07 7,27E-08 1,29E-01 1,56E-06 1,03E-09 Water use m3 depriv. 2,52E+01 2,96E-02 3,38E-01 9,44E-02 2,44E-03 2,27E+01 6,47E-02 8,79E-03 D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 24 From the graph, it is easy to understand that the main contributor to most of the environmental impacts is represented by the metal layer deposition, which consists in the deposition of gold and titanium layers. It is interesting to notice that this process is the main contributor to all the impact categories. When the process is analyzed in more detail (Figure 8), one can observe that gold production is the main contributor. The second element that contributes the most is the production of PCB. The third main contributor is represented by the photoresist coating, whilst almost all the others do not contribute significantly (less then 1%) to the environmental impacts. Figure 7 Contribution analysis of each laboratory-scale manufacturing process. Figure 8 Screenshot of the Sankey diagram representing the energy and material flows and their contribution percentage to the Climate Change impact category. Table 12 and D5.2 – Life Cycle Model Final – v1.0, 2025-12-08 Dissemination level: PU -Public Page 25 Table 13 showcase results concerning an envisaged production at European level of around 524,504 InSb PCB to be integrated in the Current Limiter devices in 2030. Therefore, these results try to give an idea of the order of magnitude of the impact that could arise from mass production of these items. From the results, the contribution of gold remains the same; indeed, the energy efficiency factor and the reduction of some chemicals are not relevant due to the significance of gold. It will be interesting to understand if gold will remain the main contributor to the environmental impact when the assessment will be extended to the Current Limiter device and to an use case-study. The key message from this assessment is the relevance that some materials, even if used in very small quantities, have on the environment. It should be investigated if the gold used in the device can be recycled gold and whether the supplier of gold pellets for the electronic industry do use recycled gold.