Search Results (208)

The earth-abundant, ecologically friendly structure of kesterite Cu₂ZnSn(S,Se)₄ (CZTSe) solar cells, with their advantageous optoelectronic characteristics, including a direct bandgap (1.0–1.5 eV) and a high optical absorption coefficient (>10⁴ cm⁻¹), have made them a very promising member of thin-film photovoltaics. However, the path toward commercialization has been slowed down by restraint such as high open-circuit voltage deficits, deep-level defect states, and compositional inhomogeneities that lead to charge recombination and efficiency loss. Despite these obstacles, very recent advances in material processing and device engineering have revitalized this technology. Incorporating elements like Ge, Ag, and Li; optimizing interface properties; and introducing methods like hydrogen-assisted selenization have all contributed to raising device efficiencies by around 15%. This review discusses recent progress and evaluates how far CZTSSe has come and what remains to be done to realize its commercial promise. Full article

Polyoxometalates (POMs) are nanoscale anionic clusters constructed from transition-metal oxide units with well-defined architectures and tunable electronic structures, offering abundant reversible redox sites and adjustable energy levels. Their diverse valence states and compositional flexibility of molecular architectures render them promising candidates for electrochemical energy storage. Rational molecular design and nano-structural engineering can significantly enhance the electrical conductivity, structural stability, and ion transport kinetics of POM-based materials, thus improving device performance. In solar cells, the tunable energy levels and light-harvesting capabilities contribute to enhanced photoconversion efficiency. In secondary batteries, the dense redox centers provide additional capacity. For supercapacitors, the rapid electron transfer supports high power density storage. This review systematically summarizes recent advances in POM-based functional nanomaterials, with an emphasis on material design strategies, energy storage mechanisms, performance optimization approaches, and structure–property relationships. Fundamental structures and properties of POMs are outlined, followed by synthesis and functionalization approaches. Key challenges such as dissolution, poor conductivity, and interfacial instability are discussed, together with progress in batteries and hybrid capacitors. Finally, future challenges and development directions are outlined to inspire further advancement in POM-based energy storage materials. Full article

Due to its unique electrical and optical properties, as well as the tunable band structure based on thickness, 2D phosphorene recently emerged as a research hotspot and holds significant potential for applications across various fields. In this study, due to the special band structure and excellent electron transport performance of phosphorene, it formed a series structure with SnO₂ as the electron transport layer of perovskite solar cells. Consequently, the photocurrent density was enhanced by approximately 20%, and the energy conversion efficiency was effectively elevated from 16.38% for pure SnO₂ to 18.03% for the SnO₂/phosphorene composite. Electrochemical measurements and spectral analyses revealed that the incorporation of phosphorene augmented electron mobility within the absorption layer, reduced the electron–hole recombination rate, and decreased the cell’s series resistance, thereby leading to improved efficiency of the perovskite solar cell. This research not only introduces a novel approach to enhancing solar cell efficiency but also paves a new pathway for the application of phosphorene. Full article

Copper nitride (Cu₃N) is gaining attention as an eco-friendly thin-film semiconductor in a myriad of applications, including storage devices, microelectronic components, photodetectors, and photovoltaic cells. This work presents a detailed optoelectronic study of Cu₃N thin films grown by reactive RF-magnetron sputtering under pure N₂. An overview of the state-of-the-art literature on this material and its potential applications is also provided. The studied films consist of Cu₃N polycrystals with a cubic anti-ReO₃ type structure exhibiting a preferential (100) orientation. Their optical properties across the UV-Vis-NIR spectral range were investigated using a combination of multi-angle spectroscopic ellipsometry, broadband transmission, and reflection measurements. Our model employs a stratified geometrical approach, primarily to capture the depth-dependent compositional variations of the Cu₃N film while also accounting for surface roughness and the underlying glass substrate. The complex dielectric function of the film material is precisely determined through an advanced dispersion model that combines multiple oscillators. By integrating the Tauc–Lorentz, Gaussian, and Drude models, this approach captures the distinct electronic transitions of this polycrystal. This customized optical model allowed us to accurate extract both the indirect (1.83–1.85 eV) and direct (2.38–2.39 eV) bandgaps. Our multifaceted characterization provides one of the most extensive studies of Cu₃N thin films to date, paving the way for optimized device applications and broader utilization of this promising binary semiconductor, and showing its particular potential for photovoltaic given its adequate bandgap energies for solar applications. Full article

Thermoelectric (TE) materials represent a critical frontier in sustainable energy conversion technologies, providing direct thermal-to-electrical energy conversion with solid-state reliability. The optimizations of TE performance demand a nuanced comprehension of structure–property relationships across diverse length scales. This review summarizes established and emerging spectroscopic and microscopic techniques used to characterize inorganic and polymer TE materials, specifically poly(3,4-ethylenedioxythiophene): poly(styrenesulfonate) (PEDOT:PSS). For inorganic TE, ultraviolet–visible (UV–Vis) spectroscopy, energy-dispersive X-ray (EDX) spectroscopy, and X-ray photoelectron spectroscopy (XPS) are widely applied for electronic structure characterization. For phase analysis of inorganic TE materials, Raman spectroscopy (RS), electron energy loss spectroscopy (EELS), and nuclear magnetic resonance (NMR) spectroscopy are utilized. For analyzing the surface morphology and crystalline structure, chemical scanning electron microscopy (SEM), transmission electron microscopy (TEM), and X-ray diffraction (XRD) are commonly used. For polymer TE materials, ultraviolet−visible–near-infrared (UV−Vis−NIR) spectroscopy and ultraviolet photoelectron spectroscopy (UPS) are generally employed for determining electronic structure. For functional group analysis of polymer TE, attenuated total reflectance–Fourier-transform infrared (ATR−FTIR) spectroscopy and RS are broadly utilized. XPS is used for elemental composition analysis of polymer TE. For the surface morphology of polymer TE, atomic force microscopic (AFM) and SEM are applied. Grazing incidence wide-angle X-ray scattering (GIWAXS) and XRD are employed for analyzing the crystalline structures of polymer TE materials. These techniques elucidate electronic, structural, morphological, and chemical properties, aiding in optimizing TE properties like conductivity, thermal stability, and mechanical strength. This review also suggests future research directions, including in situ methods and machine learning-assisted multi-dimensional spectroscopy to enhance TE performance for applications in electronic devices, energy storage, and solar cells. Full article

This study explores the use of mid-infrared (MIR) free-electron laser (FEL) irradiation as a tool for tailoring the surface properties of electrochemically synthesized TiO₂—graphene quantum dots (QDs). The QDs, prepared in colloidal form via a cost-effective electrochemical method in a KCl—citric acid medium, were exposed to MIR wavelengths (5.76, 8.02, and 9.10 µm) at the Kyoto University FEL facility. Post-irradiation measurements revealed a pronounced inversion of zeta potential by 40–50 mV and approximately 10% reduction in hydrodynamic size, indicating double-layer contraction and ionic redistribution at the QD—solvent interface. Photoluminescence spectra showed enhanced emission for GQDs and TiO₂/GQD composites, while Tauc analysis revealed modest bandgap blue shifts (0.04–0.08 eV), both consistent with trap-state passivation and sharper band edges. TEM confirmed intact crystalline structures, verifying that FEL-induced modifications were confined to surface chemistry rather than bulk lattice damage. Taken together, these results demonstrate that MIR FEL irradiation provides a resonance-driven, non-contact method to reorganize ions, suppress defect states, and improve the optoelectronic quality of QDs. This approach offers a scalable post-synthetic pathway for enhancing electron transport layers in perovskite solar cells and highlights the broader potential of photonic infrastructure for advanced nanomaterial processing and interface engineering in optoelectronic and energy applications. Full article

Perovskites (ABX₃) exhibit remarkable potential in optoelectronic conversion, catalysis, and diverse energy-related fields. However, the tunability of A, B, and X-site compositions renders conventional screening methods labor-intensive and inefficient. This review systematically synthesizes the roles of physical simulations and machine learning (ML) in accelerating perovskite discovery. By harnessing existing experimental datasets and high-throughput computational results, ML models elucidate structure-property relationships and predict performance metrics for solar cells, (photo)electrocatalysts, oxygen carriers, and energy-storage materials, with experimental validation confirming their predictive reliability. While data scarcity and heterogeneity inherently limit ML-based prediction of material property, integrating high-throughput computational methods as external mechanistic constraints—supplementing standardized, large-scale training data and imposing loss penalties—can improve accuracy and efficiency in bandgap prediction and defect engineering. Moreover, although embedding high-throughput simulations into ML architectures remains nascent, physics-embedded approaches (e.g., symmetry-aware networks) show increasing promise for enhancing physical consistency. This dual-driven paradigm, integrating data and physics, provides a versatile framework for perovskite design, achieving both high predictive accuracy and interpretability—key milestones toward a rational design strategy for functional materials discovery. Full article

Perovskite solar cells (PSCs) have emerged as promising photovoltaic technologies owing to their high power conversion efficiency (PCE) and material versatility. Conventional optimization of PSC architectures largely depends on iterative experimental approaches, which are often labor-intensive and time-consuming. In this study, a data-driven modeling strategy is introduced to accelerate the design of efficient and mechanically robust PSCs. Seven supervised regression models were evaluated for predicting key photovoltaic parameters, including PCE, short-circuit current density (Jsc), open-circuit voltage (Voc), and fill factor (FF). Among these, a stacking ensemble framework exhibited superior predictive accuracy, achieving an R² of 0.8577 and a root mean square error of 2.084 for PCE prediction. Model interpretability was ensured through Shapley Additive exPlanations(SHAP) analysis, which identified precursor solvent composition, A-site cation ratio, and hole-transport-layer additives as the most influential parameters. Guided by these insights, ten device configurations were fabricated, achieving a maximum PCE of 24.9%, in close agreement with model forecasts. Furthermore, multiscale mechanical assessments, including bending, compression, impact resistance, peeling adhesion, and nanoindentation tests, were conducted to evaluate structural reliability. The optimized device demonstrated enhanced interfacial stability and fracture resistance, validating the proposed predictive–experimental framework. This work establishes a comprehensive approach for performance-oriented and reliability-driven PSC design, providing a foundation for scalable and durable photovoltaic technologies. Full article

This study employed a sol–gel route to fabricate mesoporous silica (MS) carriers capable of simultaneously encapsulating two widely utilized UV absorbers—benzophenone-3 (BP-3) and octyl methoxycinnamate (OMC)—resulting in the composite sunscreen agent S4M1B1. Comprehensive characterization using FTIR, TGA, UV–vis spectroscopy, DSC, SEM, and standard photoprotective indices (SPF and UVA-PF) confirmed the successful immobilization of both active ingredients within the MS porous structure, achieving a notably high loading of up to 72 wt%. Sunscreen formulations incorporating the encapsulated composite demonstrated superior photoprotective performance, exhibiting SPF and UVA-PF values approximately 40% higher than equivalent physical mixtures of the same actives. Additionally, the MS encapsulation significantly enhanced the photostability of BP-3 and OMC, effectively maintaining their UV-protective efficacy after prolonged simulated solar exposure. Franz glass diffusion cell assays further revealed that encapsulation markedly reduced the in vitro skin permeation of both BP-3 and OMC by over 55%, substantially diminishing transdermal absorption risks. The dual benefits of enhanced UV-protection efficiency and reduced dermal penetration underscore the composite’s potential as a safer and more effective active ingredient in cosmetic sunscreen products, with promising applications in advanced skincare and cosmeceutical formulations. Full article

This study investigates the influence of temperature on the linear and nonlinear optical properties of ternary organic thin films for solar cell applications. Three-component organic thin films (poly({4,8-bis[(2-ethylhexyl)oxy]benzo [1,2-b:4,5-b′]dithiophene-2,6-diyl}{3-fluoro-2-[(2-ethylhexyl)carbonyl] thieno[3,4-b]thiophenediyl}) and (poly([2,6′-4,8-di(5-ethylhexylthienyl)benzo[1,2-b;3,3-b]dithiophene]{3-fluoro-2[(2-ethylhexyl)carbonyl]thieno[3,4-b]thiophenediyl}), marked PTB7 and PTB7th- donors, PCBM, phenyl-C61-butyric acid methyl ester acceptor, and Y5: 2,2′-((2Z,2′Z)-((12,13-bis(2-ethylhexyl)-3,9-diundecyl-12,13-dihydro[1,2,5]thiadiazolo[3,4e]thieno[2′,3′:4′,5′] thieno[2′,3′:4,5]pyrrolo[3,2-g] thieno[2′,3′:4,5]thieno[3,2-b]indole-2,10-diyl)bis(methanylylidene))bis(3-oxo-2,3-dihydro1H-indene-2,1-diylidene))dimalononitrile) and Y6 non-fullerene acceptors: (2,2′-((2Z,2′Z)-((12,13-bis(2-ethylhexyl)-3,9-diundecyl-12,13- dihydro-[1,2,5]thiadiazolo[3,4- e] thieno [2,″3″:4′,5′]thieno [2′,3′:4,5]), non-fullerene acceptors, were analyzed using spectroscopic ellipsometry and third-harmonic generation techniques across a temperature range of 30 °C to 120 °C. The absorption spectra of the ternary layers remained largely stable with temperature, but ellipsometry revealed temperature-dependent changes in layer thickness (a few percent increase during heating) and variations in refractive index and extinction coefficients, suggesting modest structural alterations. Analysis using a gradient model indicated that film composition varies with thickness. Third-harmonic generation measurements showed a decrease in χ⁽³⁾ after annealing, with the most significant change observed in the PTB7th:Y5:PCBM layer. Full article

This work presents a novel approach to investigating epitaxial GaAsN layers and GaAsN-based p-i-n solar cell structures using light-assisted scanning capacitance microscopy (SCM) and spectroscopy. Due to the technological challenges in growing high-quality GaAsN with controlled nitrogen incorporation, the epitaxial layers often exhibit inhomogeneity in their opto-electrical properties. By combining localized cross-section SCM measurements with wavelength-tunable optical excitation (800–1600 nm), we resolved carrier concentration profiles, internal electric fields, and deep-level transitions across the device structure at a nanoscale resolution. A comparative analysis between electrochemical capacitance–voltage (EC-V) profiling and photoluminescence spectroscopy confirmed multiple localized transitions, attributed to compositional fluctuations and nitrogen-induced defects within GaAsN. The SCM method revealed spatial variations in energy states, including discrete nitrogen-rich regions and gradual variations in the nitrogen content throughout the layer depth, which are not recognizable using standard characterization methods. Our results demonstrate the unique capability of the photo-scanning capacitance microscopy and spectroscopy technique to provide spatially resolved insights into complex dilute nitride structures, offering a universal and accessible tool for semiconductor structures and optoelectronic devices evaluation. Full article

This study provides an in-depth numerical simulation to optimize the structure of InGaN-based p-i-n single homojunction solar cells using SCAPS-1D software. The cell comprised a p-type ${\mathrm{I}\mathrm{n}}_{0.6}{\mathrm{G}\mathrm{a}}_{0.4}\mathrm{N}$ layer, an intrinsic i-type ${\mathrm{I}\mathrm{n}}_{0.52}{\mathrm{G}\mathrm{a}}_{0.48}\mathrm{N}$ layer, and an n-type ${\mathrm{I}\mathrm{n}}_{0.48}{\mathrm{G}\mathrm{a}}_{0.52}\mathrm{N}$ layer. A systematic parametric optimization methodology was employed, involving a sequential investigation of doping concentrations, layer thicknesses, and indium composition to identify the optimal device configuration. Initial optimization of doping levels established optimal concentrations of ${\mathrm{N}}_{\mathrm{d}}=1\times {10}^{16} {\mathrm{c}\mathrm{m}}^{-3}$ for the p-layer and ${\mathrm{N}}_{\mathrm{a}}=8\times {10}^{17} {\mathrm{c}\mathrm{m}}^{-3}$ for the n-layer. Subsequently, structural parameters were optimized through systematic variation of layer thicknesses while maintaining optimal doping concentrations. The comprehensive optimization culminated in the identification of an optimal device architecture featuring a p-type layer thickness of 0.2 μm, an intrinsic layer thickness of 0.4 μm, an n-type layer thickness of 0.06 μm, and an indium composition of x = 0.59 in the intrinsic layer. This fully optimized configuration achieved a maximum conversion efficiency (η) of 21.40%, a short-circuit current density (${\mathrm{J}}_{\mathrm{s}\mathrm{c}}$) of 28.2 mA/cm², and an open-circuit voltage ($V_{oc}$) of 0.874 V. The systematic optimization approach demonstrates the critical importance of simultaneous parameter optimization in achieving superior photovoltaic performance, with the final device configuration representing a 30.01% efficiency improvement compared to the baseline structure. These findings provide critical insights for improving the design and performance of InGaN-based solar cells, serving as a valuable reference for future experimental research. Full article

Highly scattering media have garnered significant interest in recent years, ranging from potential applications in solar cells, photocatalysis, and other novel photonic devices to research on fundamental topics such as topological photonics, enhanced light–matter coupling and light confinement. Here, we report measurements of spectrally and time-resolved delayed luminescence (DL) in highly scattering rutile TiO₂ films. The complex emission kinetics manifests in the non-exponential decay of photon density and the temporal evolution of the spectral composition. We found that while the energy levels of TiO₂ nanoparticles broadly set the spectral regions of excitation and emission, our results demonstrate that the DL intensity and duration are strongly influenced by the inherent multiple elastic and inelastic processes determined by the mesoscale inhomogeneous structure of random media. We show that the lifetime of DL increases up to 6 s for the largest redshift detected, which is associated with multiple reabsorption processes. We outline a simple model for spectrally resolved DL emission from dense scattering media that can guide the design and characterization of composite materials with specific spectral and temporal properties. Full article

Materials with perovskite phases are widely used in solar cells and ferroelectric, piezoelectric, dielectric and superconducting devices due to their various notable functions. However, structural instability limits some compositions in forming robust perovskite phases for device applications. The analytical approach using the tolerance factor (t) can only guarantee prediction accuracy within a limited range, ascribed to its nature of overlooking the atomic interaction. Hence, here we establish a prediction model using formation energy as the target parameter for its reflection of the reaction of atoms and apply machine learning as the analysis method since it has been successfully employed in plenty of material property prediction studies. Machine learning employs statistical methodologies to identify correlative patterns within large-scale datasets, enabling accurate predictions with robust generalization. In this work, we built a model to predict the formation energy of ABX₃ perovskite using machine learning and achieved a model with an R-squared value of 0.928 and a root mean square error of 0.301 eV/atom, validated by first-principles computations. In total, 75% of the values were correctly predicted within an error lower than 0.06. This work could contribute to accelerating the study of solving perovskites’ instability. Full article

The rising demand for sustainable energy solutions has spurred the development of advanced materials for photovoltaic devices. Among these, transparent conductive oxides (TCOs) play a pivotal role in enhancing device efficiency, particularly in silicon-based solar cells. However, the reliance on indium-based TCOs like ITO raises concerns over cost and material scarcity, prompting the search for more abundant and scalable alternatives. This study focuses on the fabrication and characterization of aluminum-doped zinc oxide (ZnO:Al, AZO) thin films deposited via Atomic Layer Deposition (ALD), targeting their application as transparent conductive oxides in silicon solar cells. The ZnO:Al thin films were synthesized by alternating supercycles of ZnO and Al₂O₃ depositions at 225 °C, allowing precise control of composition and thickness. Structural, optical, and electrical properties were assessed using Scanning Electron Microscopy (SEM), Energy-Dispersive X-ray Spectroscopy (EDS), Transmission Electron Microscopy (TEM), Raman spectroscopy, spectroscopic ellipsometry, and four-point probe measurements. The results confirmed the formation of uniform, crack-free ZnO:Al thin films with a spinel-type ZnAl₂O₄ crystalline structure. Optical analyses revealed high transparency (more than 80%) and tunable refractive indices (1.64 ÷ 1.74); the energy band gap was 2.6 ÷ 3.07 eV, while electrical measurements demonstrated low sheet resistance values, reaching 85 Ω/□ for thicker films. This combination of optical and electrical properties underscores the potential of ALD-grown AZO thin films to meet the stringent demands of next-generation photovoltaics. Integration of Zn:Al thin films into silicon solar cells led to an optimized photovoltaic performance, with the best cell achieving a short-circuit current density of 36.0 mA/cm² and a power conversion efficiency of 15.3%. Overall, this work highlights the technological relevance of ZnO:Al thin films as a sustainable and cost-effective alternative to conventional TCOs, offering pathways toward more accessible and efficient solar energy solutions. Full article