Advanced characterization techniques for organic and inorganic materials: Emerging trends, innovations, and multidisciplinary applications

 Corresponding author: Oresegun Olakunle Ibrahim. Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0. Advanced characterization techniques for organic and inorganic materials: Emerging trends, innovations, and multidisciplinary applications Oresegun Olakunle Ibrahim 1, *, Reuben Zakari Kabantiyok 2, Egbuzie Daniel Chinemerem 3, Emmanuel Favour Oluwadarasimi 4, Md Samin Yeasar Zahan Sparsha 5, Usoshi Mohsin 6, Abraham Chibuikem Ikeji 7, Mohammed Issa Abdulrahman 8, Modupe Elizabeth Ojewumi 9 and Sekete Maseala Camilla 10 1 Department of Mechanical Engineering, Zhejiang University, Hangzhou, China. 2 Department of Research and Innovation, Schrödinger Technologies Ltd, Kano State, Nigeria. 3 Department of Materials Science and Engineering, The Ohio State University, Columbus, USA. 4 Department of Chemical Engineering, Lagos State University, Ojo, Nigeria. 5 Department of Physics and Astronomy, East Texas A&M University, Commerce, USA. 6 Department of Chemistry, East Texas A&M University, Commerce, USA. 7 Department of Laboratory and Medical Pathology Mayo Clinic, Rochester, Minnesota, USA. 8 Department of Chemical Engineering, Faculty of Engineering, Carnegie Mellon University, USA. 9 Department of Civil and Environmental Engineering, FAMU-FSU College of Engineering, Tallahassee, 2525 Pottsdamer Street, Tallahassee, FL 32310, USA. 10 Department of Industrial Design Engineering, Zhejiang University, Hangzhou, China. World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 Publication history: Received on 30 April 2025; revised on 31 May 2025; accepted on 03 June 2025 Article DOI: https://doi.org/10.30574/wjarr.2025.26.3.2188 Abstract Advanced material characterization is credited with unraveling the complex structures and properties of organic and inorganic materials, thereby supporting innovations in energy, electronics, catalysis, and the environment. This review comprehensively analyzes modern characterization techniques, classifying them into spectroscopic, microscopic, chromatographic, thermal, optical, and specialized advanced methods. Specific emphasis is given to how the techniques respond to the unique demands of organic and inorganic systems. The review also discusses emerging trends such as in-situ and operando analysis, multimodal approaches, high-throughput procedures, and the integration of machine learning for data interpretation. Applications in organic electronics, nanomaterials, catalysis, energy storage, environmental monitoring, and quantum technologies are discussed. Challenges and future outlook are critically discussed to guide the creation of more efficient and automated platforms for next-generation materials research. Keywords: Advanced Characterization; Organic Materials; Inorganic Materials; In-Situ Techniques; Multimodal Analysis; Machine Learning. 1. Introduction The subject of materials science has seen a remarkable transformation due to the development of characterization techniques [1]. These techniques have progressed from simple mechanical testing to highly complex approaches that investigate materials on an atomic and molecular level. In materials research, characterization methods are pivotal in elucidating organic and inorganic materials’ structure, content, and characteristics [2]. These methods are essential for research and real-world applications because they show how organic and inorganic materials behave under various situations. Thermal analysis, microscopy, spectroscopy, and other characterization tools allow scientists to study organic and inorganic materials thermal, mechanical, chemical, and physical characteristics. The intrinsic structure of World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 280 materials, including crystal phases, grain boundaries, and microstructural characteristics, maybe revealed using advanced techniques like SEM and XRD. As a result, organic and inorganic materials designers can better connect a material’s structure and its mechanical and electrical characteristics [3-5]. Characterization is crucial to confirm organic and inorganic materials’ chemical structure, composition, thermal, optical, electrical, magnetic, mechanical properties, etc [6]. The industrial sector relies on heat analysis, tensile strength measures, and hardness testing to verify that materials are up to par. Characterization methods aid in the quest for novel materials with targetable characteristics in research and development (R&D). Materials failure in applications can be better understood using characterization techniques. Fatigue, corrosion, or incorrect processing are reasons why materials degrade; techniques like thermal analysis, fractography, and energy-dispersive X-ray spectroscopy (EDX) help pinpoint these issues [7]. Therefore, this review aims to provide an updated, structured, and comparative insight into the advanced characterization methods tailored for organic and inorganic materials. It not only categorizes the tools but also contextualizes them within current technological demands, emerging innovations, and multidisciplinary applications. Over the past decade, several reviews have addressed material characterization techniques. However, this review differentiates itself by integrating a comprehensive, side-by-side exploration of organic and inorganic materials, emerging technologies, and cross-disciplinary applications, while also addressing AI and automation integration, which many previous reviews overlook. The review begins by differentiating organic and inorganic materials, followed by a critical assessment of traditional and modern characterization methods. It explores both established and emerging techniques, highlighting novel instrumentation and data-driven approaches. Finally, it presents current and potential applications across diverse scientific domains, discusses present challenges, and outlines future perspectives. 1.1. Fundamentals of Organic and Inorganic Materials and the Role of Characterization Understanding the nature of materials—whether organic or inorganic is essential for the selection of appropriate characterization techniques. The structure, bonding, and properties of these materials define their performance in diverse applications, and precise characterization is central to optimizing material development. 1.1.1. Comparison of Organic and Inorganic Materials Organic materials are primarily carbon-based compounds that include polymers, biomolecules, and organic semiconductors. These materials exhibit covalent bonding and often feature complex molecular architectures with varying degrees of flexibility and functionality. Common organic materials include polyethylene, polystyrene, polythiophene, and small-molecule dyes [8].Organic materials are typically lightweight, flexible, and chemically tunable, making them ideal for applications in soft electronics, packaging, drug delivery, and photovoltaics. For example, organic light-emitting diodes (OLEDs) and organic solar cells (OSCs) are key technologies relying on the unique optoelectronic properties of organic compounds [9]. Inorganic materials on the other hand are composed of metals, ceramics, oxides, and salts, generally characterized by ionic or metallic bonding [10]. These materials tend to exhibit high thermal and chemical stability, hardness, and electrical conductivity. Common inorganic materials include silicon, titanium dioxide, copper oxides, and various metal alloys. Their robust mechanical and thermal properties make inorganic materials indispensable in structural applications, catalysis, energy storage, and semiconductors. For instance, silicon is the backbone of the microelectronics industry, while metal oxides serve as catalysts in industrial chemical processes [11]. The key distinctions between organic and inorganic materials lie in their bonding types, structural flexibility, and functional applications. Organic materials offer design flexibility and biocompatibility, while inorganic materials provide thermal stability and durability. These differences necessitate tailored characterization strategies. For example, while UV–Vis and FTIR spectroscopy are highly effective for probing organic systems, X-ray diffraction (XRD) and electron microscopy are more suited to inorganic crystals [12]. 1.1.2. Need for Advanced Characterization Approaches Characterization is a critical component of materials research, offering insights into the structure–property relationships that govern performance [1]. It provides the data needed to validate material synthesis, understand degradation mechanisms, and inform processing decisions. Effective characterization allows researchers to correlate World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 281 microscopic features with macroscopic behavior, enabling rational design and optimization of materials. Techniques like scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and thermal analysis provide detailed insights into morphology, composition, and stability. Such information is vital for quality control, failure analysis, and innovation in materials science [13]. Conventional techniques include optical microscopy, classical spectroscopy, and thermal gravimetric analysis. These methods have been foundational in material research, offering accessible tools to measure particle size, functional groups, thermal transitions, and optical properties. XRD has long served as the benchmark for crystallinity and phase identification in inorganic compounds. Despite their usefulness, traditional methods often lack the resolution, sensitivity, or specificity required for advanced materials. Optical microscopy, for instance, cannot resolve features below the diffraction limit (~200 nm), and bulk thermal techniques do not capture nanoscale heterogeneity. Furthermore, many conventional techniques are ex situ, failing to reveal dynamic behavior during real-world operation [14]. However, the emergence of complex materials systems such as nanostructured composites, hybrid interfaces, and quantum materials demands advanced techniques capable of high spatial, temporal, and spectral resolution. In situ and operando analyses, super-resolution microscopy, and AI-assisted data interpretation represent transformative innovations. These approaches not only overcome the limitations of classical techniques but also provide multidimensional data that drive materials-by-design initiatives [15]. 2. Advanced Characterization Techniques for Organic and Inorganic Materials Additional in-depth examination of the minute details of organic and inorganic materials, chemicals, or biological beings can be accomplished using advanced characterization techniques. These methods go beyond simple analysis by providing a more complex knowledge of characteristics and behaviors. For enhanced characterization, tools like GCMS, Auger electron spectroscopy, inductively coupled plasma, and electron spin resonance are used in organic and inorganic materials research. These techniques provide exact access to crystallography, elemental composition, and atomic and molecular structures of organic and inorganic materials for scientific investigation [16]. Table 1 is an overview of advanced characterization techniques for organic and inorganic materials 2.1. Spectroscopic Techniques NMR, FTIR, Raman spectroscopy, and UV/Vis are spectroscopic techniques vital to material science because they reveal intricate information about materials’ physical, chemical, and structural characteristics. 2.1.1. Nuclear Magnetic Resonance (NMR) Spectroscopy Nuclear magnetic resonance (NMR) spectroscopy is very useful to utilize radio wave range (wavelengths). Wave range is one of the most quantitative analytical methods for determining the structural information of organic and inorganic materials. The magnetic field involves the interaction of radio waves with nuclei that contain odd quantities of neutrons or protons that show evidence of the intrinsic magnetic moment, which can be able to possess resonant condition or flipping condition of spin state. Moreover, the resonant condition mainly depends upon the nuclei, chemical bonds, and functional groups. In addition, organic and inorganic compounds in both forms such as solid and liquid can be determined and also used for the synthesis of novel compounds and determination of chemical structures of biomolecules and polymers [17]. NMR spectroscopy aims to study and understand the physical process by which atomic nuclei with nonzero spin absorb and re-emit electromagnetic radiation in reaction to a magnetic field. By monitoring the resonance frequencies of specific nuclei (such as 1H and 13C), NMR spectroscopy reveals essential information on molecules’ dynamics, bonding, and structural makeup. This method can learn a lot about the molecular surroundings of different compounds and applies to a wide range of elements and isotopes [18]. Atomic nuclei with nonzero spin interacting with an externally applied magnetic field are the basis of the working principle of NMR spectroscopy (Figure 1). Nuclei composed of an uneven number of protons and neutrons can align with or against the magnetic field, resulting in different energy states due to their magnetic moment and angular momentum. The nuclei absorb the energy difference between these states and transition between them when radiofrequency radiation is supplied at a frequency corresponding to it. The nuclei release radiofrequency signals as they relax, and these signals are picked up and stored. Each nucleus’s electrical environment affects its resonance frequency, revealing information about the molecule’s chemical makeup, bonding, and atomic arrangement. World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 282 Figure 1 Instrumentation of NMR spectroscopy [19] 2.1.2. Infrared (IR) Spectroscopy Infrared spectroscopy (IR) is a non-destructive technique; it provides electronics and structural information of organic and inorganic materials with high spatial resolution and high spectra (vibrational and rotational). IR spectroscopy directly involving in vibrational and rotational transitions ranges between 4000 and 400cm-1; this range facilitates the permanent change of dipole moment. Subsequently, IR and Raman gave correlative molecular data, as regularly IRinactive modes are Raman-active modes and VV [20]. With regard to inorganic materials characterization, Fourier transform infrared (FT-IR) spectroscopy is basically used to examine the surface modification such as “ligand attachment” of nanomaterials. Specifically, organic molecules involved in characteristic adsorption of IR spectra due to the “fingerprint region” range from 10 to 25mm. This technique provides bands of different chemical bonds present in ligands and complex molecules. This also provides a clue to the coordination mode of ligands and coordination bands at a near-low wave number (400–500 cm-1). Henceforth, these types of organic nanomaterials are involved in the drug delivery system, e.g. nanoliposomes, and also used to the modification of nanoparticles with proteins [21]. This technique is also helpful in determining surface modifications in nanoparticles. Functional groups on the surface of zinc nanoparticles are identified by FT-IR spectroscopy [22]. Moreover, IR spectra involve in situ measurement for matrix molecules like water. Water is a highly strong IR absorber. In this strategy, these types of interfaces possess to minimize the usage of specific probing methods such as infrared attenuated total reflection infrared spectroscopy (IR-ATR) provided sur face sensitivity and a signal limited to the diffusion depth of the transitory field [23]. One of materials science’s most important analytical tools, FTIR spectroscopy, may reveal a material’s molecular makeup and structure. FTIR creates a distinct chemical fingerprint for each substance by measuring the absorption and transmission of infrared energy as the radiation passes through the sample. For qualitative investigation, FTIR works wonders, enabling exact material identification, as no two substances produce identical IR spectra. Furthermore, FTIR is useful for quantitative analysis since the magnitude of the peaks in the spectrum produced is proportional to the concentration of different components. This method improves over previous dispersive approaches; it uses state-ofthe-art software algorithms to give rapid, accurate analysis over a broad frequency spectrum. Materials’ chemical makeup, structural characteristics, and molecular interactions may be better understood using FTIR, which has important scientific and practical implications [24]. Using an interferometer to detect all infrared frequencies concurrently, FTIR considerably speeds up the process compared to standard dispersive IR instruments, which scan each frequency separately. The interferometer collects infrared light from a source and reflects it from two mirrors, one of which is stationary and the other of which is mobile. When the two beams’ different route lengths cause an interference pattern, an interferogram containing all the encoded infrared frequencies is produced. On the other hand, this interferogram defies direct interpretation. The individual frequencies are decoded using a mathematical procedure called Fourier transformation (Figure 2) to get a spectrum out of an interferogram. Spectra like this show how a material absorbs infrared light at different frequencies related to the vibrations of its chemical bonds [25]. World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 283 Figure 2 Instrumentation of FTIR spectroscopy [26] 2.1.3. Ultraviolet-visible (UV-Vis) Spectroscopy Ultraviolet-visible (UV-Vis) spectroscopy involves the spectroscopy of photons in the UV-Vis region to study the optical properties. Absorption of energies in the range 104–105 cm-1 by a molecule leads to the change in the electronic energy of the molecule due to the transition of valence electrons from occupied molecular orbitals. UV-Vis spectrum is basically a graph of light absorbance versus wavelength in a range of UV or visible regions [27]. Such a spectrum can often be produced directly by using a UV-Vis spectrophotometer. It is based on Beer–Lambert law stating that the absorbance (A) of a solution is directly proportional to the concentration (c) of the absorbing species present in the solution of the path length (l). According to Beer–Lambert’s law: 𝐴=−𝑙𝑜𝑔10(𝐼𝑡 𝐼𝑂)=𝜖𝑐𝑙 where I0 and It are the intensity of the incident light and the transmitted light, respectively, and ε is a constant of proportionality, called the absorptivity. Therefore, following Beer–Lambert equation, concentration of the absorber present in the solution can be determined for a fixed path length. The perceived color of the absorbing species directly depends on the absorption wavelength in the visible range. UV spectrum is normally recorded with sample dissolved in solvents like water, ethanol, or hexane which are transparent within the wavelength range used in the study of organic compounds [28]. In organic materials, the absorption maximum of complexes can be determined using UV/Vis spectroscopy, and complete spectra provide information on electronic transitions in complexes, ligand field effects, and metal oxidation states. In the case of metal nanoparticles (MNPs), the UV–visible spectrum is useful in determining the concentration and size of nanoparticles. The optical properties and surface plasmon resonance (SPR) of copper nanoparticles are determined by UV–visible spectroscopy [29]. 2.1.4. Raman Spectroscopy Raman spectroscopy is a fast, nondestructive technique used to study vibrational, rotational, and other low-frequency modes in a system. Raman scattering is the inelastic scattering of a photon at the electron mist of the particle requiring an adjustment in polarizability, which brings about a Raman shift and vibrational/rotational excitation. It was discovered by Sir C.V. Raman and later by Grigory Landsberg and Leonid Mandelstam. It is an analytical tool that gives the structural information producing a precise spectral fingerprint, unique to a molecule or indeed and individual molecular structure. The spectrum is plotted as intensity vs Raman shift in wavenumbers (cm-1), shifted from the absolute frequency (in cm-1) of the excitation laser. This technique can provide structural, physical, and chemical information (crystalline phase, polymorphic forms, intrinsic stress, etc.) [30]. Integrally, Raman spectroscopy depends on scattering processes with the small fraction of the occurrence of photons prompting vibrational modes through inelastic processes able to make stoke lines (e.g. less energy of emitted photons compared with incident photons) and anti-stoke (e.g. high energy of emitted photons compared with incident photons). Furthermore, Raman spectra having only one primary photon range from 106 to 107, the remaining signal scales are an incident photon, and lasers are required to the light source [31]. World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 284 Raman spectroscopy deduces information about a molecule’s electronic environment, composition, and symmetry from its inelastic light scattering. Because of this, it is an excellent tool for quantitative and qualitative investigation, allowing scientists to learn about phase transitions, identify chemicals, and comprehend molecular interactions in different materials. It finds extensive application in the characterization of semiconductors, polymers, nanomaterials, and many more [32]. Figure 3 displays the instrumentation of Raman spectroscopy. Figure 3 Instrumentation of Raman spectroscopy [19] 2.2. Microscopic Techniques Materials science extensively uses optical microscopy for microscale material imaging and characterization. One way to learn about a material’s makeup, structure, and characteristics is by examining its surface under a microscope. Features like surface morphology, defects, grain structure, and phase boundaries are frequently studied using this method. Optical microscopy’s use for investigating micron and submicron scales in several fields has grown exponentially during the past decade [33]. Digital video enables optical microscopy to capture images of fragile optical sections, and confocal optical systems are already operational at most prominent research institutes. When an electron beam is used to illumine the specimen to generate a magnified image, it is known as electron microscopy (EM) [34]. Various types of EM techniques are discussed here 2.2.1. Scanning Electron Microscopy (SEM) The scanning electron microscope (SEM) can acquire surface morphological, topographical, and compositional data of the constituent metal ions present in the materials [35]. SEM technique provides highly resolute three-dimensional images of conducting as well as non-conducting materials. The features of organic and inorganic materials which can be investigated through SEM are surface crack and other qualitative measures including contaminations [36]. The working principle of SEM is similar to the reflecting light microscope and is based on the reflection of the secondary electron from the surface of the material. The electrons coming out after the interaction of incident electron with the surface of the sample are known as backscattered electrons and maps the surface of the scanned sample by detecting the contrast area between different chemical compositions. The higher contrast region or brighter image in the backscattered electron images is observed due to the higher atomic number of atoms. The observed backscattered electron in the detector determines the relative intensity in the obtained scanned image. This also gives information about the quantitative part of the sample from the X-rays obtained by the interaction of electron beam with sample results from the electron transition from higher energy level to the lower energy levels [37]. SEM is especially constructive to visualize nanomaterials. Most of the conventional microscopy is used in glass lenses for magnifying image but EM is used in the electrons. SEM produces highly magnified, three-dimensional (3D) image. Also, this is impossible for light microscopy. When an electron ray with an increase of velocity of (3–30keV) is engaged in the sample, the actuated auxiliary and backscattered electrons are utilized for imaging. Because of inelastic scattering, secondary electrons (SEs) with low-level energy were generated. Also, SE produces signal to escape depth from the World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 285 surface. Moreover, SEM is generally manufactured with advanced electron optics and field emission (FE). In this strategy, which make to avoid the chromatic and spherical aberration nature of nanomaterials in the resolution of the nanometer (nm). Utilizing low-voltage SEM improves the surface affectability, decreases harm of the imaged nanomaterials, and essentially decreases the depth level of electron penetration in spatial resolution ranging from 0.4 to 1.6nm. Furthermore, low-voltage high-resolution SEM is used for the determination of morphology, size, and structure of 2D nanomaterials such as metallic, semi-metallic, and inorganic compounds. Besides, non-conductive materials such as C or Pt are also applied (Figure 4) [38]. Figure 4 Schematic diagram of the core components of an SEM microscope [39] 2.2.2. Transmission Electron Microscopy (TEM) TEM is one of the microscopy methods for the characterization of inorganic materials. TEM can be capable of providing direct high-resolution images and in-depth quantitative and quantitative chemical details for materials along with the spatial resolution downward to atomic dimensions range (<1nm) [40]. This technique is particularly important for nanoparticle characterization and provides information about morphological and structural aspect of materials science and inorganic chemistry. It assists in understanding the microstructural examination through high-resolution imaging of resolution 0.1–0.2 nm to identify ultrastructure. It provides results for understanding shapes, sizes, and uniformity in size/shapes of prepared materials. The use of suitable microscopic lenses combination along with replacing objective lens aperture by diffraction aperture, TEM can be utilized as an electron diffraction camera. In this, the electron is used for determining the orientation and shape of the crystal. It is also used to calculate the size of the crystallite by examining the pattern obtained from the TEM images [39]. High-resolution transmission electron microscopy (HR-TEM) mode is mainly involved in the determination of the crystallographic structure of the nanomaterials in “atomic level.” HR-TEM is an authoritative device to study the properties of materials on the atomic scale and the revelation of crystal structures. Also, it is used to analyze the nanoparticles crystals, arrangements, nanocrystalline texture in amorphous-based films, nanofibers, and their arrangement and absorbent materials [41, 42]. Figure 5 shows a schematic representation of TEM World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 286 Figure 5 Schematic diagram of the Components of TEM technique [39] 2.2.3. Scanning Transmission Electron Microscopy (STEM) STEM has proved very effective in measuring compositional changes at buried interfaces and the electronic structure and bonding relevant to a device’s mechanical and transport properties [43]. Detection of single dopant atoms with STEM, both on free surfaces and buried inside devices, has proved helpful in studies ranging from characterizing catalysts to understanding the material limits for transistor scaling. It is also possible to detect and image the spatial distribution of single vacancies either directly, by their strain fields, or spectroscopically from their electronic fingerprints on the local densities of states [44]. Similar in principle to SEM, STEM is involved in the determination of sample by using high-energy electron beam, the electron beam range around 100–300KeV. Although the thin layer of the specimen was captured as an image, the remaining part of the scattered electron was collected by “transmission mode”. The SEM is regularly operated as STEM, due to the presence of a transmission detector. As well as, the acceleration of voltage was in a limited range, around 30KeV [45]. The basic idea behind STEM characterization is to create a 2D map of a thin sample by directing a high-energy electron beam onto it and then scanning it over it. By detecting scattered electrons and signals from ionized atoms when the beam interacts with the sample, precise information on the sample’s structure and composition may be derived. At the atomic level, information about bonds and chemicals may be derived from measurements of the energy lost by transmitted electrons due to core and valence excitations. The capacity to concentrate the electron beam into a tiny area World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 287 while keeping enough beam current dictates the resolution and efficiency of STEM. Recent developments in correcting lens aberrations have greatly enhanced spatial resolution, paving the way for atomic-resolution imaging and subangstrom beam sizes. TEM also has a good capability for using STEM mode, because of the existence of scanning coils. The resolution into STEM mode mainly depended on the electron probe in dimension. In addition, high electrons are collected by the “bright field detector.” These electrons relation between low angle vs. axis. As well as transmitted electrons are collected by “dark field detector,” these electrons relatively high angle vs. optical axis, while inner angle of dark field detector is set as the large value, for this purpose collecting only scattered electrons. It is called as “Z-Contrast”/high-angle angular dark field (HAADR) imaging because of the enhanced atomic number (Z), which primarily depends on the contrast of the image [46]. 2.2.4. Atomic Force Microscopy (AFM) AFM is an advanced technique for studying the properties of materials at an atomic scale. The method has significantly influenced material science, molecular biology, and solid-state physics. AFM was invented in 1986 by G. Binning, C. F. Quate, and Ch. Gerber [47]. AFM operates based on nanoscale surface interaction employing a sharp, probing tip connected to a spring-like cantilever. Attractive or repulsive forces develop between the tip and the sample as it gets closer. The cantilever is pushed away from the sample by repulsive forces and drawn toward it by attractive forces; the Pauli exclusion principal accounts for this behavior. A very sensitive position-sensitive detector records the changes in the direction of the laser beam as it reflects off the surface of the cantilever; even small deflections may be detected in this way. Scanner cantilever deflection is controlled thanks to a feedback loop that keeps a preset set point. A piezoelectric XYZ-scanner accurately controls the tip and sample’s x, y, and z movements, enabling high-resolution 3D imaging of the sample’s topography [48]. The probe depends on the flexible cantilever, which makes able to produce force by using “Hook’s law” and can be expressed as: 𝐹=𝐾𝑋 Where F is force; K is constant of the cantilever (probe mounted) and x is the deflection of the cantilever Generally, AFM uses various types of the probe, cantilever length, and weight due to the different types of materials. However, the force was prohibited by the “feedback mechanism.” As well as, the short distance between the sample surface and probe was determined by “van der Waal’s force”. In addition, various modes of AFM operations are possible using AFM due to van der Waal’s force. In addition, AFM has a good capability of generating force curves, which make it useful for the determination of mechanical and electrical properties of materials [49]. Figure 6 shows the schematic diagram and mechanism of AFM technique Figure 6 Schematic diagram of AFM technique [17] 2.3. Chromatographic Techniques Chromatographic methods are used in materials science to efficiently isolate and measure the different elements present in complicated mixes of materials. These methods rely on chemical composition analysis, impurity detection, molecular structure, and interaction comprehension. By isolating individual molecules using chromatography, scientists may learn more about the chemical behavior and features of many materials, such as polymers, ceramics, and metals. Optimal material performance, new material development, and quality control rely on chromatographic World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 294 2.6.7. Electron Spin Resonance Spectroscopy Analyzing chemical species or materials with one or more unpaired electrons can be effectively accomplished through electron para magnetic resonance or ESR [82]. An ESR spectrum is often generated by altering the magnetic field intensity at a constant microwave frequency, as shown in Figure 11(b). This technique is used to detect unpaired electrons in metal complexes as well as evaluate the magnetic properties of complexes. ESR is a powerful tool for characterizing metal nanoparticles, especially those containing paramagnetic metal centers. It provides detailed information on the electronic structure, local environments, dynamic behavior, and interactions of metal nanoparticles [83]. Figure 11 (a) Inductively coupled plasma, (b)Electron spin resonance, (c) Gas chromatographyMass spectrometry, (d) Auger electron spectroscopy [16] 2.6.8. Synchrotron Radiation X-ray Diffraction For more precise and quick investigation of even thick or complicated materials, synchrotron radiation is utilized in advanced applications. Synchrotron radiation sources are characterized by great coherence, high brightness, and efficient collimation throughout a wide range of wavelengths. Characterization methods based on synchrotron radiation have lately had a big impact in solving important scientific problems in the energy conversion area. Importantly, they have shed light on the ways in which atomic and electronic structures evolve at solid− liquid interfaces, offering vital experimental proof for comprehending processes of energy conversion. Furthermore, the identification of actual active phases and active sites is made possible by in situ and operando technologies, which capture the kinetic progression of catalytic processes. SRXRD provides better capabilities for studying long-range ordered structures and crystal phase measurements compared to traditional XRD, which is useful for examining bulk crystal phase structures. The superior signal quality achieved by SRXRD makes it a more potent instrument when contrasted with traditional XRD [84]. SRXRD is an advanced diffraction technique that utilizes highly intense and tunable X-rays generated by a synchrotron source. In this process, electrons are accelerated to near-light speeds in a storage ring and guided along a curved path by magnetic fields, emitting high-brightness, collimated X-ray beams as they change direction. These X-rays are then monochromatized using silicon crystal optics to select specific wavelengths, while mirrors or zone plates focus the beam onto the sample. When the monochromatic X-ray beam interacts with the sample, diffraction occurs according to Bragg’s law, and the resulting diffraction pattern is recorded using high resolution detectors. This allows for precise structural analysis, including phase identification, strain mapping, and defect characterization. The superior properties of synchrotron X rays, such as higher intensity, better collimation, and energy tunability, enable SRXRD to achieve World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 295 significantly higher resolution than conventional XRD. Additionally, its ability to perform in situ and operando studies makes it a powerful tool for real-time monitoring of structural changes under varying environmental conditions, such as temperature, pressure, and chemical reactions. Figure 12 displays a general schematic representation of SRXRD. Figure 12 Schematic of SRXRD [19] With the growth in synchrotron radiation (SR) facilities, synchrotron-based analytical techniques have become outstanding tools that are used in many areas of research, including physics, chemistry, biology, materials, environment, and the nanoscience. For instance, synchrotron radiation X-ray fluorescence (XRF) analysis is particularly well suited to investigating the micro-distributions of trace elements in biological samples, because it has high spatial resolution, the capacity to analyze several elements simultaneously, quantitatively and nondestructively, and its detection limit can reach down to the 50–100 ng/g range for many elements [85]. Synchrotron radiation X-ray absorption spectroscopy (XAS) is very sensitive to the local chemical environment of the element of interest, and can be used to acquire information on its oxidation state, coordination number, the identities of its nearest neighbors, and bond lengths, which are crucial for understanding the interaction of nanoparticles with biomolecules and the mechanisms of the toxicological effects of nanoparticles in living systems [86]. Synchrotron radiation circular dichroism (SRCD) is useful for performing conformational analyses of biomolecules based on the higher energy transitions of chromophores such as n→π* transitions, π→π*, n→σ*, etc. [9]. Additionally, the enhanced brilliance of modern synchrotron facilities and advances in focusing optics allow for high spatial resolution in the 0.5 1 µm range for hard X-rays (>3 keV) and of around 30 nm for soft X-rays (-1KeV). All of these properties—high chemical sensitivity, high spatial resolution and low detection limits—of synchrotron-based X ray microprobe techniques are of particular interest in nanotoxicological studies. In addition, synchrotron-based techniques such as X-ray diffraction, X-ray small angle scattering, and X-ray photo electron spectroscopy have become important nano-characterization tools [87]. 2.6.9. X-ray Tomography X-ray tomography is a non-destructive material testing in which reconstruction of the 2D and 3D images is done. The production and use of X-ray was well known before and now more and more advancements are taking place for increasing its field of utilization [88]. Ultrasonic testing being the most reliable and established method for material characterization is unable to extract the 3D data for the calculation of internal voids/ porosity. With the repeatability of measurements, it has been found that x-ray computed tomography emerged as a very useful technique in determining the porosity in a given material with good accuracy in case of large voids and calculation of shape, size and distribution of internal voids with little less accuracy. The high resolution in X-ray computed tomography (XCT) is needed for the accurate and precise measurement of small pores [89]. To get the good surface characteristics and for deeply understanding of image noise, the modulation transfer functions can be used. Accuracy and repeatability of measurement, results are significantly influenced by the methods used in determining the starting threshold. When default settings will be used in commercial CT evaluation software, the errors in the measurement are genuine [90]. World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 296 Table 1 Overview of Advanced Characterization Techniques for Organic and Inorganic Materials S/N Technique Applicable Material Type Application 1 UV–Vis Spectroscopy organic Electronic transitions, conjugation, and bandgap analysis 2 FT-IR Spectroscopy Organic & Inorganic Molecular vibrations, functional group identification 3 Raman Spectroscopy Organic & Inorganic Molecular structure, crystallinity, and stress analysis 4 NMR Spectroscopy Organic Molecular structure, dynamics, and functional groups 5 X-ray Photoelectron Spectroscopy (XPS) Inorganic & Surfacemodified Organic Surface elemental composition and oxidation states 6 X-ray Diffraction (XRD) Inorganic Crystalline structure, phase identification, and lattice parameters 7 Scanning Electron Microscopy (SEM) Organic/Inorganic Morphology, surface structure, and particle size 8 Transmission Electron Microscopy (TEM) Organic/Inorganic Nanoscale imaging, crystallography, and defects 9 Atomic Force Microscopy (AFM) Organic/Inorganic Topography, surface roughness, and mechanical properties 10 Differential Scanning Calorimetry (DSC) Organic Thermal transitions (Tg, Tm), crystallinity, and purity 11 Thermogravimetric Analysis (TGA) Organic/Inorganic Thermal stability, decomposition patterns 12 Inductively Coupled Plasma Mass Spectrometry (ICP-MS) Inorganic Trace elemental analysis 14 Scanning Tunneling Microscopy (STM) Inorganic & Conductive Organic Electronic states, atomic resolution surface mapping 17 Nano-Computed Tomography (Nano-CT) Inorganic & Composite 3D internal structure, porosity, and defect analysis 18 Kelvin Probe Force Microscopy (KPFM) Organic/Inorganic Surface potential mapping and electronic properties 20. In Situ/Operando Techniques (multi-modal) Organic/Inorganic Real-time structural, thermal, or chemical changes under operational conditions 3. Emerging Trends and Innovation in Material Characterization Material characterization has undergone a paradigm shift in recent years, driven by the urgent need to develop highperformance materials for applications ranging from energy storage and catalysis to biomedical devices and environmental remediation. Traditional characterization techniques, while foundational, often provide limited insight into the real-time behavior of materials under operational conditions. This has catalyzed a wave of innovation, giving rise to a suite of advanced methodologies that enable deeper, more holistic understanding of material structure, dynamics, and functionality. Among these, in-situ and operando methods, multimodal characterization strategies, and high-throughput automated techniques are at the forefront of emerging trends reshaping the landscape of materials science [91]. World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 297 3.1. Advances in In-situ and Operando Techniques In-situ and operando characterization techniques have revolutionized the way materials are studied by allowing scientists to observe changes in real-time under realistic working environments. Unlike ex-situ methods which examine materials after processing or reaction has occurred in-situ techniques capture the dynamic evolution of material properties as a function of stimuli such as temperature, pressure, electric field, or chemical environment. Operando techniques take this further by combining structural characterization with simultaneous performance evaluation, providing direct correlation between material structure and functional behavior during actual operation [92]. These techniques are particularly transformative in fields like catalysis, battery research, and phase-change materials, where structural or compositional changes dictate performance. For instance, in battery materials, operando X-ray diffraction (XRD) and X-ray absorption spectroscopy (XAS) have been used to monitor phase transitions and oxidation state changes during charge-discharge cycles, thereby revealing degradation mechanisms that affect long-term stability and efficiency. Similarly, in catalytic systems, operando infrared (IR) and Raman spectroscopy have enabled real-time monitoring of surface intermediates and active site evolution under reaction conditions [93]. The implementation of synchrotron-based in-situ methods has further enhanced spatial and temporal resolution, allowing the study of transient phenomena and reaction kinetics on the sub-second timescale. Such advances are instrumental in designing materials with tailored properties and in accelerating the development of next-generation technologies [94]. 3.2. Multimodal Characterization Approaches The complexity of modern materials especially hybrid systems that integrate organic and inorganic components necessitates characterization techniques that can probe multiple aspects of structure and function simultaneously. Multimodal characterization involves the integrated use of two or more complementary techniques to provide a comprehensive picture of material behavior across different length and time scales [95]. By combining microscopy, spectroscopy, and diffraction methods, multimodal approaches capture both surface and bulk information, as well as chemical and physical attributes. For example, correlative imaging that combines scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDS) enables spatial mapping of elemental composition alongside morphological analysis. Similarly, coupling atomic force microscopy (AFM) with infrared spectroscopy (AFM-IR) allows for high-resolution chemical imaging of nanostructured materials and biological specimens [96]. Recent developments in data fusion and artificial intelligence (AI) have further enhanced the power of multimodal characterization. Machine learning algorithms can now integrate data from disparate sources—such as X-ray tomography, electron microscopy, and Raman maps—to uncover hidden patterns and correlations that are not evident from any single technique alone. These integrative approaches are proving invaluable in fields such as biomaterials, photovoltaics, and nanocomposites, where understanding structure-property-function relationships is essential for performance optimization [97]. 3.3. High-throughput and Automated Techniques High-throughput and automated techniques have emerged as powerful solutions to this challenge, enabling rapid screening and analysis of large material libraries with minimal human intervention. It integrates robotics, microfabrication, and real-time data acquisition to evaluate numerous samples in parallel. Techniques such as automated X-ray diffraction (HT-XRD), combinatorial sputtering, and high-speed spectroscopy are commonly employed in materials discovery platforms to screen for optimal compositions and processing conditions. For example, in the development of perovskite solar cells, high-throughput photoluminescence and absorption measurements have accelerated the identification of stable and efficient materials by orders of magnitude compared to conventional trialand-error methods [98]. Automation is further facilitated by advances in software and machine learning, which enable intelligent data analysis, anomaly detection, and decision-making in real-time. Tools such as autonomous scanning probe microscopy can adaptively choose regions of interest based on prior measurements, thereby increasing efficiency and reducing operator bias. The integration of high-throughput screening with cloud computing and digital twins is pushing the frontier even further, enabling virtual experiments and predictive modeling that complement physical characterization. These developments are expected to play a central role in accelerating the design and deployment of advanced materials in a sustainable and cost-effective manner [99]. World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 298 3.4. Integration of Machine Learning and AI in Characterization AI is a transformative technology that enables machines to emulate human cognition and behavior, facilitating intelligent decision-making, task execution, and problem-solving. By leveraging data-driven AI techniques, these systems can surpass human capabilities in speed, efficiency, and scalability, making them invaluable tools across various fields, including materials science. The integration of AI and ML into the processing of characterization data such as spectroscopy and microscopy has revolutionized the way complex data sets are interpreted in materials science. AI algorithms, particularly deep learning models, are increasingly employed to automate baseline correction, denoising, peak identification, and feature extraction in spectroscopic techniques like FTIR, NMR, and Raman spectroscopy [100]. Similarly, in microscopy (e.g., SEM, TEM, AFM), convolutional neural networks and other vision-based algorithms enable rapid phase classification, defect detection, and morphological analysis with high accuracy and reproducibility. These approaches not only reduce manual effort and bias but also enhance the speed and depth of data interpretation, allowing researchers to uncover hidden patterns and correlations that are otherwise difficult to detect using traditional methods. Moreover, AI is being leveraged in autonomous or “self-driving” laboratories to guide experimental design based on real-time feedback from characterization data. As AI continues to evolve, its role in processing and interpreting spectroscopy and microscopy data will be central to accelerating materials discovery and development. Among the most impactful branches of AI is ML, which utilizes data-driven algorithms to extract patterns, make predictions, and optimize decision-making without explicit programming. In the realm of materials science, ML plays a pivotal role in accelerating the discovery, design, and optimization of advanced materials. Traditional methods of material development, which rely heavily on empirical experimentation and computational simulations, are often timeconsuming, resource-intensive, and limited in scope. ML circumvents these challenges by analyzing vast data sets, identifying intricate relationships between structural and functional properties, and generating predictive models that guide material synthesis and characterization. Through descriptor generation, model construction, material property prediction, and experimental validation, ML enhances the efficiency of materials research, enabling the rapid screening of candidates with desirable characteristics. Moreover, by integrating AI with established computational methods such as first-principles calculations and MD, researchers can significantly reduce computational costs while expanding the predictive accuracy and applicability of simulations. This synergy between AI and ML has revolutionized materials science, paving the way for data-driven approaches that not only expedite the innovation cycle but also unlock new possibilities for designing next-generation materials with tailored properties [101]. 4. Multidisciplinary Applications of Advanced Characterization Techniques Advanced material characterization techniques are the backbone of interdisciplinary innovation, empowering researchers to tailor materials for applications spanning electronics, energy, environment, healthcare, and quantum computing. The convergence of novel characterization tools with machine learning, in situ analytics, and high-resolution imaging has significantly accelerated the pace of discovery, especially in areas where structural, compositional, and functional precision are paramount. This section dives into the multidisciplinary applications of advanced characterization techniques 4.1. Organic Electronics and Photovoltaics The field of electronics and photonics has rapidly grown and evolved over the last few decades, driven by the demand for smaller, faster, and more efficient devices. The miniaturization of electronic components and the development of new materials have led to significant advancements in information technology, telecommunications, energy generation, and sensing applications. Since the discovery of the semiconducting nature of poly-thiophene, organic electronics have experienced tremendous development [102]. In particular, organic field-effect transistors (OFETs), light-emitting diodes (OLEDs), and photovoltaic cells (OPVs) are key candidates for next generation of electronics and optoelectronics, thus revolutionizing the information, photonics, and energy sciences [103]. Recently, the electrical and optoelectrical performance of OFETs, OLEDs, and OPVs have improved impressively, due to new molecular design strategies, improved process engineering, effective interface optimization, and advanced device architecture. However, despite these remarkable advances, as a new research topic, organic devices still face some key challenges, as follows: (i) the important aspects of packing motifs and growth strategies of organic semiconducting films for high-performance applications are still difficult; (ii) the relationship between charge transport physics and the molecular structure properties is not fully understood; and (iii) an in-depth understanding of electrode, dielectric, and interface properties under various device structures and operating circumstances is still lacking. To solve these issues, it is important to utilize more advanced characterization techniques [104]. In-situ/operando techniques for studying organic semiconductors have been developed as powerful tools to achieve unprecedented insights into complex film growth, electronic states, and structure-property relationships under World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 299 conditions relevant to device operation or device manipulation, which cannot be revealed by common ex-situ measurements. Hence, in situ/operando techniques can contribute to our understanding of the nature of molecular assembly mechanisms and intrinsic electronic properties, which can further improve molecular design and device performance [105]. Recently, Lee et al. [106] used in-situ optical microscopy to ob serve the crystallization process of TIPS-pentacene thin films using a continuous-flow microfluidic-channel-based meniscus-guided coating (CoMiC), which could precisely manipulate the flow behavior via microfluidic channels (Figures 13(a) and 13(b)). Based on the in-situ characterization and numerical simulation, the relationship between flow pattern, thin-film crystallization, and electrical performance of OFETs is comprehensively analyzed and reveals that chaotic advection leads to device-to-device uniformity. This work provides effective strategies to tune solution-based crystallization properties for performance optimization of OFETs, solar cells, and displays. Furthermore, top-view and side-view in-situ high-speed optical microscopies were used to obtain three-dimensional (3D) meniscus geometry under multiple experimental conditions during solution shearing (Figures 13(c)) [107]. The top-, side-, and 3D view microscopies for the visualization of the contact line/crystallization process and cross-sectional meniscus shape are shown in Figure 13 (d), contributing to the mathematical model for mass and momentum transport within the meniscus geometry. Therefore, in-situ high-speed optical microscopy enables the analysis and prediction of the crystallization process of organic films under multiple experimental parameters. Figure 13 In-situ optical microscopy of organic films using CoMiC: (a) Flow path and meniscus shape during coating. (b) Crystallization and film boundary evolution of doped TIPS-pentacene via FM-CoMiC and SHM-CoMiC [106] c) Top and side-view in-situ microscopy showing how 3D meniscus geometry relates to crystallization during solution shearing. (d) Multi-angle microscopy visualizing contact line dynamics, crystallization, and meniscus cross-section [107] World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 300 4.2. Nanomaterials, Nanocomposites and Hybrid Materials The emergent significance of two-dimensional (2D) nanomaterials are determined by the continuous innovation of new properties such as optical, electrical, and mechanical, which further strengthen their utility toward electronic, energy storage, and biomedical domain [108]. The graphene is one of the most 2D nanomaterials due to their physicochemical properties and high energetic capability, and also, transition metal dichalcogenides (TMDCs) having good fundamental properties involve practical applications. The specific determination of the properties of the nanomaterials is the most important section in nanotechnology and which can be executed by advanced techniques that are responsive to nanoscale dimensions (nm). In recent years, nanomaterials’ advanced characterization techniques involve determination of character of nanosized materials [109]. Raman spectroscopy is one of the most standard characterization methods of carbon-based nanomaterials such as graphene and graphite; the characteristic bands are located at the 1580cm-1 and the 2D band at 2700cm-1. A third attribute, the D band, around 1350cm-1 is not Raman spectra, its defects of the pristine graphene band value. The D band also called as “defect induced band.” The G band at 1586cm-1 results from in-plane vibration sp2 carbon atoms and is the majority significant feature of graphite materials. The 2D band involved in double resonance (e.g. second-order overtone) process indicates scattering of two photons with the opposite moment with K point of symmetry (stacking order) due to the “Brillouin zone of graphene.” Raman spectroscopy is also used in the investigation of CNTs, metal oxides, nano-belts, quantum dots, and nanorods [110]. However, in certain metal nanoparticles, they may additionally improve the Raman signals known as surface-enhanced Raman spectroscopy (SERS), which is used in the determination of plasmonic and chemical enhancement effects signal ranging from 108 to 1011, which is able to characterize such nanomaterials in innovative details [111]. Nilchi et al [112] chemically synthesized and evaluated a hydrous manganese dioxide–polyacrylonitrile (MnO2–PAN) as an organic–inorganic composite material. The physico-chemical characterization was carried out by Fourier transform infrared spectroscopy (FT-IR), X-ray powder diffraction (XRD), CHN elemental analysis, scanning electron microscopy (SEM), nitrogen adsorption–desorption studies and thermogravimetry-differential scanning calorimetry (TGA-DSC). Figure 14 (a) depicts XRD patterns of the synthesized materials and polyacrylonitrile. The analysis of X-ray patterns revealed that the XRD data corresponding to synthetic manganese dioxide agreed well with the Powder Diffraction Files Search Manual (card no.12 716, 1986). It was also observed that the 2y values at the peak points of MnO2–PAN are the same as those in MnO2, and hence their crystalline structure is very similar. Furthermore, comparing the XRD patterns indicates that manganese dioxide has been loaded on polyacrylonitrile. The IR spectrum of MnO2 – PAN composite is recorded in Figure 14 (b). The broad band in the region of 3200–3650cm-1 is due to interstitial water and hydroxyl groups and the sharp peak at 1620 cm-1 corresponds to the bending vibration of water molecules. Strong absorption peak at 2140 cm-1 can be assigned to cyanide stretching vibration. The spectrum of the sample shows the characteristic band for–CH2 at 1453 cm-1. The band at 1080–1100 cm-1 is assigned to the C–O stretching vibration. The bands in the 400–550 cm-1 region are due to the Mn–O stretching. Investigation of infrared spectra of ion exchange material prior to and after irradiation (Figure 14 (b)) showed that there is no significant difference. Therefore, these ion exchangers were resistant to gamma irradiation of up to 200 kGy. The nitrogen adsorption–desorption studies showed that the BET surface area of manganese dioxide–polyacrylonitrile composite is 53.03 m2/g. Scanning electron microscopic photograph of the prepared MnO2–PAN composite bead is shown in Figure 14 (c). The results revealed that the particles were not homogeneous. The pore size of the inner part of the particles was larger than that near the surface. The kinetic of sorption on these adsorber beads must be very fast, since the MnO2 powder, which is the active material, is found to be dispersed throughout the binding matrix. The TGADSC thermal analysis of MnO2–PAN composite is shown in Figure 14(d), which shows decomposition steps. Batch experiments were carried out as a function of contact time, interference of the coexisting ions and initial pH of adsorptive solution applying a radiotracer technique. The effect of temperature on the distribution coefficient of cesium has been utilized in order to evaluate the changes in the standard thermodynamic parameters. The results indicated that Csþ ions could be efficiently removed using MnO2–PAN composite in the pH range of 4–9 from aqueous solutions and the uptake of cesium is affected to varying degrees by the presence of some diverse co-ions. The equilibrium isotherms have been determined and the sorption data were successfully modeled using Freundlich model. Organic-inorganic hybrid materials are a class of advanced materials that combine the advantageous properties of both organic and inorganic components. These materials are designed to leverage the flexibility and functional diversity of organic compounds with the robustness and thermal stability of inorganic materials. This synergy opens new avenues for applications across various fields such as electronics, photonics, catalysis and biomedicine. Organic-inorganic hybrid World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 301 materials are at the forefront of materials science due to their ability to combine the best properties of both organic and inorganic components [113]. Organic/inorganic material hybrids are not simply physical mixtures. They can be defined as nanocomposites at the molecular scale, having at least one component, either the organic (or biological) component or the inorganic component, with a characteristic length scale on the nanometer size (a few Å to several tens of nanometers). The properties of hybrid materials do not simply result from the sum of the individual contributions of their com ponents, but also from the strong synergy created by an extensive hybrid interface. Indeed, the mineral/organic interface, including the types of interactions present, the surface energy, and the existence of labile bonds, plays a strong role in modulating of a number of properties (optical, mechanical, separation capacity, catalysis, and chemical and thermal stability) [114]. Today, the potential of hybrid materials is reflected by the fact that many of them are entering a variety of markets. New materials and systems produced by man in the future must aim toward higher levels of sophistication and miniaturization, be recyclable and respect the environment, be reliable and consume less energy or help save energy [115]. Figure 14 (a) XRD of PAN, MnO₂, and MnO₂–PAN composite; (b) IR spectrum of MnO₂–PAN; (c) SEM cross-section of composite bead; (d) TGA/DSC curves of the composite [112] 4.3. Catalysis Catalysis represents one of the most characterization-intensive domains due to their reliance on surface phenomena and dynamic chemical processes. XPS, Auger electron spectroscopy (AES), and Fourier-transform infrared spectroscopy (FTIR) provide surface composition, oxidation states, and functional group information. Chemisorption techniques and temperature-programmed desorption (TPD) further quantify surface area and active site density. In situ Raman and infrared (IR) spectroscopy, coupled with mass spectrometry or X-ray absorption spectroscopy (XAS), enable real-time observation of catalytic mechanisms under working conditions. These tools are pivotal for revealing transient intermediates and reaction kinetics. According to Joshi et al., MoS2 catalysts were created and placed on carbon fiber (CF) materials to generate solar hydrogen via membrane-less electrochemical water splitting. Three separate peaks at around 33°, 44°, and 65° were identified in the XRD patterns of the CF−MoS2 sample. These peaks were corresponding to the (100), (104), and (200) hexagonal MoS2 (2H-MoS2) reflections, respectively. This confirms what has been reported before. As a result of less stacking, the MoS2 nanosheets grown on CF exhibited a weak and broad (200) diffraction peak. Diffraction peaks for the (002), (100), (104), and (200) reflections were used to describe the nanostructured 2H-MoS2 CF−MoS2. In the XRD pattern of the (100), (104), and (200) planes of the hexagonal MoS2 phase were identified by four distinct diffraction peaks at 33.1°, 44°, and 68.7°, respectively. The XRD pattern showed a notable peak at 25.6°, which is the diffraction pattern often seen in CF-generated amorphous carbon (JCPDS Card no. 37−1492) [116]. World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 302 In situ DRIFTS could be a promising technique to clarify the reaction mechanism of catalyst since spectroscopy could continuously and directly observe the change in the specimen. For example, in situ DRIFTS was carried out on Au/SiO2 containing functional SiO2 -X (X =–Schiff, –NH2) catalysts -X support and Au-NPs active center [117]. As shown in Figure 15 (a), Au/SiO2 -NH2 exhibited distinct CO adsorption and the formation of ionic carbamate species. In contrast, a new adsorption peak was observed in Au/SiO2 -Schiff besides the peaks of Au/SiO indicating a new adsorption pattern for CO2 -NH2, (i.e., the surface-bonded carbamate zwitterion intermediates). Interestingly, after the CO evacuation, the quick disappearance of this new band suggested its instability, and the vulnerability to be easier removed than ionic carbamate species (Figure 15 (b)). Following this, the further in situ DRIFTS carried under the H2 atmosphere showed that the formate product could only be found with the presence of surface-bonded carbamate zwitterion instead of the ionic carbamate (Figure 15 c & d)). These results indicated that the microenvironment building by support could influence or even decide the reaction process. However, the advantage of the FTIR technique could also be the shortage, i.e., organic impurities also induce the interference signal due to the high sensitivity of FTIR [118]. Figure 15 (a) FTIR of Au/SiO₂ and Au/SiO₂–Schiff under humid CO₂; (b) Time-resolved DRIFTS post wet-CO₂-NH₂ evacuation; (c,d) In situ DRIFTS of CO₂ hydrogenation on Au/SiO₂–Schiff without (c) and with (d) carbamate zwitterion [117] 4.4. Energy Storage Systems Inorganic multifunctional nanomaterials play vital part in energy storage, energy generation, energy saving, energy conversion as well as in energy transmission applications owing to their distinctive properties, like chemical stability, higher surface area, outstanding thermal and electrical conductivity. Lower toxicity, lower cost, more functions and higher performance are the path being developed for future energy related applications using inorganic multifunctional nanomaterials. Despite they have terrific potential possibility, the scientific research community yet wants to make huge efforts to address their execution as well as achievement in extensive implementations. Inorganic multi-functional nanomaterials, mechanism of working is currently remains fuzzy. Therefore, to get more knowledge of the propertiesstructure relations of inorganic multifunctional nanomaterials, in depth and comprehensive characterization employing cutting-edge tools and techniques coupled with scientific research interpretation models ought to be altered. The features of materials have a direct impact on how devices work [119]. Excitingly, in the last several years, the rapid development of various material characterization and electrochemical analysis techniques makes it possible and easy to obtain an in-depth mechanism understanding of Li–S battery systems. Generally, the former was used to probe the structure or components of the electrode/electrolyte under in situ or ex situ conditions, while the latter mainly focuses on the overall electrochemical reaction and device performance. Usually, material characterization techniques work together with electrochemical analysis methods, and provide the World Journal of Advanced Research and Reviews, 2025, 26(03), 279–314 303 complementary information to each other, especially for the in situ and in operando characterization experiments. Usually, in situ means in position, while in operando means a special case of in situ, where the battery is in operation [120]. X-ray absorption spectroscopy (XAS), as a typical example of advanced characterization techniques, has played a critical role in promoting the mechanism understanding of Li–S battery systems [121]. Specifically, ex situ/in situ XAS experiments not only accelerate the understanding of chemical/electrochemical reaction mechanism in Li–S batteries, but also contribute to the identification of Li poly sulfides and radical anions upon cycling. In addition, other advanced characterization techniques, such as X-ray diffraction (XRD), UV–visible spectroscopy, Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR), electron paramagnetic resonance (EPR), X-ray photoelectron spectroscopy (XPS), transmission electron micros copy (TEM), transmission X-ray microscopy (TXM), etc., combined with ex situ or in situ experimental methods also provided complementary information to each other in understanding the structure changes, morphology evolutions, as well as the behavior of sulfur and polysulfides in Li–S batteries [122]. Trocoli et al. [123] created rechargeable micro batteries that use LiMn4 (LMO) and zinc, which have high specific power. Figure 16a-d shows surface and cross-sectional SEM images of the films. Grain structures in the samples are stickshaped and randomly orientated; the thicker the LMO1000 layer, the greater the grain dimensions. Faceted crystals seem associated with grain elongation, suggesting a preferred development direction. The samples LMO400 and LMO1000, which range from 400 to 1000 nm, respectively, have similar thicknesses as evaluated by ellipsometry. An LMO/Li2SO4 /Zn complete battery was built using these electrodes, with the help of an aqueous electrolyte and a zinc metallic foil that was 1 μm thick. Schwieters et al. [124] used ICP techniques to study graphite electrodes from old lithium-ion batteries to determine how much lithium was lost in the SEI. The methods used were laser ablation, inductively coupled plasma mass spectrometry (LA ICP-MS), and inductively coupled plasma optical emission spectroscopy (ICP-OES). The main goal was to determine how much lithium was used up during the formation of SEIs, so aged graphite electrodes were analyzed objectively for lithium concentration. It was found that a large amount of lithium was lost during the initial stages of lithiation before graphite intercalation compounds like LiC30 were formed. X-ray tomography is dealing in a unique field for characterization and that is the characterization of electrochemical devices. Lithium ion-batteries, solid oxide fuel cells and polymer electrolyte fuel cell are some of the main leaders in this category [88]. Due to the volumetric nature of the XCT, it emerges as one of the most effective and efficient technique in determining the complex internal features especially in case of parts manufactured by the additive manufacturing process. Large research is going on to firmly established the X-ray tomography as a measurement tool compared to other methods of dimensional metrology and making it industrial pertinent technology [125]. Figure 16 Top and cross-sectional SEM micrographs of the LMO electrode. (a) LMO 400 top. (d) LMO 1000 top. (b) LMO 400 cross section. 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