Organoarsenic ligands have long been far less extensively explored than their phosphorus analogs, mainly because of safety concerns associated with volatile and toxic arsenic precursors. However, recent progress in practical synthetic methods has enabled access to a wide variety of arsine, arsine oxide, and multidentate organoarsenic ligands, opening new opportunities in coordination chemistry and functional materials. In this review, we summarize recent advances in metal complexes bearing organoarsenic ligands, with a particular emphasis on their structures and photophysical properties. We first outline synthetic strategies for organoarsenic ligands, including conventional and recently developed safer routes. The resulting ligand library covers monodentate, bidentate, mixed-donor, and multidentate systems. We then discuss luminescent metal complexes based on Cu(I), Au(I), Pt(II), Re(I), Os(II), and Eu(III), highlighting how arsenic affects coordination geometry, spin–orbit coupling, metallophilic interactions, charge-transfer excited states, and non-radiative deactivation pathways. Finally, we describe advanced functional materials, including porous materials, stimuli-responsive luminophores, vapor-triggered structural transitions, and processable/recyclable luminescent coordination polymers. These examples demonstrate that organoarsenic ligands are not merely heavier analogs of phosphines but rather provide unique design elements for controlling structure, dynamics, and excited-state behavior in functional metal complexes.
Chirality is the property of an object that cannot be superimposed with its mirror image by any translation or rotation. This property plays a crucial role in the biological activities of molecules and in the optical and magnetic properties of materials. This review will show recent advances in the study of ultrafast chiral processes occurring in molecular systems and materials investigated by high-order harmonic generation (HHG) spectroscopy, both from a theoretical and experimental point of view. HHG is a highly nonlinear optical process providing coherent XUV radiation with attosecond duration. The chemical physics community, in its broadest sense, has developed an interest in HHG spectroscopy, given the increasing number of studies of complex molecules, including those of biological relevance, chemical reactions, and characterization of the structure of solids by means of an ultrafast probe. Indeed, HHG is a powerful tool to capture the photoinduced electron dynamics in their natural timescale, also enabling the investigation of transient chirality, which is so far mostly unexplored. The study of chirality on the ultrafast timescale represents an opportunity to bridge the gap between atomic physics, chemical physics, and materials science in their traditional definitions and gain insight into fundamental chiral processes at the electron level.
Electrocatalytic energy conversion processes demand precise control of the electronic properties of active sites to overcome slow reaction kinetics and achieve high energy conversion efficiency. This review systematically examines recent developments in active-site engineering from four complementary dimensions. Composition regulation customizes electronic structures via metal doping, defect engineering, and dual-atom site construction. Structural design optimizes stepped surfaces and porous structure to improve mass transport and expose more accessible active sites. Interface modulation utilizes heterogeneous junctions and refined coordination environments to generate synergistic catalytic effects, while operating-environment tuning emphasizes how electrolytes and applied potentials dynamically reshape active-site states. By integrating advanced in situ/operando characterization with theoretical modeling, these strategies provide deeper mechanistic understanding and more principle-driven design guidelines. Coupling these insights with atomic-precision synthesis and artificial intelligence is expected to accelerate the development of next-generation, high-performance electrocatalysts for sustainable energy technologies.
Two-dimensional electron gases (2DEGs) at epitaxial oxide interfaces, such as LaAlO3/SrTiO3 heterostructures, have long served as model platforms for exploring emergent interfacial phenomena, including superconductivity, magnetism, and tunable metal–insulator transitions. While such systems were initially investigated primarily within the context of condensed matter physics, their relevance is being redefined by recent advances in non-epitaxial oxide 2DEGs, which offer new opportunities for practical applications. In contrast to polarity-driven epitaxial interfaces, non-epitaxial oxide 2DEGs are often governed by chemically driven carrier generation mechanisms, most notably oxygen vacancy (VO) formation induced by interfacial redox reactions. These mechanisms enable systematic tuning of interfacial electronic properties using amorphous or polycrystalline oxides and industry-compatible processes. This review provides a unified perspective linking the fundamental formation mechanisms of oxide 2DEG to their emerging applications. We first survey the principal physical origins of oxide 2DEGs, followed by an in-depth discussion of VO generation pathways in non-epitaxial oxide systems, including ionic bombardment, metal-induced redox reactions, and surface chemical effects. Building on this mechanistic foundation, we connect interfacial chemistry to application-level performance metrics, with particular emphasis on memory and neuromorphic technologies motivated by rapidly expanding computational demands in the AI era. In memory architectures, oxide 2DEGs are evaluated as enablers of both selector devices and storage elements, while in neuromorphic hardware, sensor platforms exploiting 2DEG transport are highlighted for their capability to emulate biological sensory functions and dynamics. Key challenges for practical deployment of oxide 2DEGs, including compatibility with three-dimensional integration, thermal stability during processing, and limitations in material selection, are critically examined. Potential strategies for overcoming these constraints, such as interfacial chemistry control, defect engineering, and process–structure–property correlations, are discussed. By bridging the fundamental physics and chemistry of oxide 2DEGs with emerging device-level applications, this review underscores their potential as a cornerstone material platform for next-generation, energy-efficient computing architectures.
The need for sustainable renewable energy is urgent, and harnessing solar energy to produce green hydrogen is promising. Hydrogen is a versatile energy carrier that can be stored and converted into various forms of energy. The FreeHydroCells project aims to create a novel, wireless tandem, monolithic photoelectrochemical (PEC) cell for water splitting, offering a cheap, efficient, and modular hydrogen-generating solution. However, scaling up PEC technology presents significant challenges, with performance losses occurring as systems reach industrial dimensions. Optimizing light energy capture and reducing parasitic light absorption are key to maximizing performance. This study investigates light attenuation in a monolithic PEC water-splitting system, providing guidance on material selection regarding optical properties, scalability, and cost. The assembled device was characterized using both laboratory-grade and portable spectrophotometers, showing a total transmitted flux of roughly 63%. A simple optical model underestimated the transmitted flux by 11%. The global optical efficiency of the device is estimated to be about 14%, but limited to 9% without a reflector. The study highlights substantial optical losses, approximately 33%, from the windows and electrolyte alone. These findings emphasize the importance of holistic optical design and rigorous experimental validation in developing scalable PEC systems.
High-throughput virtual screening (HTVS) is now routinely used for the discovery and rationalization of molecular materials with interesting excited-state properties for optoelectronics. While robust methods exist for the computation of energy levels for large datasets, it is more challenging to tackle more advanced properties related to the photophysics of the compounds. The challenge is related to both the complexity of the models and the difficulties in validating them against sufficiently large and homogeneous experiments. This work provides an overview of the challenges encountered when virtual screening approaches are used in organic electronics to study properties that are more advanced than just the energy levels of the system. We discuss how more advanced photophysical properties have begun to be incorporated into HTVS protocols, including excitation–vibration coupling and non-radiative rates. We examine how it is often necessary to go beyond the commonly used time-dependent density functional theory (TDDFT). We also provide examples of physical insights that can emerge from HTVS campaigns, highlighting the contribution that these screening approaches can give to fundamental understanding.
Electrochemical metallization (ECM) memristors, with their advantages of high ON/OFF ratio, fast switching speeds, and low power consumption, have shown broad prospects in emerging applications such as neuromorphic computing, low-power logic computing, and artificial intelligence hardware. To fully realize the potential of ECM memristors, it is necessary to gain a deep understanding of the complexity of ion migration and redox reactions associated with resistive switching at the nanoscale. This review first systematically elucidates the resistive switching mechanism of ECM memristors, then focuses on discussing various novel physical effects emerging at the nanoscale, including the nanobattery effect, quantized conductance effect, diffusion effect, photo-induced resistive switching effect, and bio-voltage effect. A further review of the latest application advancements of these effects in cutting-edge fields such as artificial synapses, bioelectronic interfaces, in-memory computing, and neuromorphic perception. Finally, we explored the key challenges and potential opportunities facing ECM memristors in their future development, aiming to lay the groundwork for future neuromorphic computing research.
The electronic and optical properties of organic semiconductors are strongly determined by their structural properties. Combining two or more semiconductor compounds in multicomponent blends is commonly exploited to tune the properties and meet the requirements for high-performance applications such as organic solar cells, light-emitting diodes, and transistors. Here, we discuss the structural and optical properties characteristic of binary systems containing the archetypal organic semiconductor pentacene. Typical examples are shown for the formation of a solid solution, a co-crystal, and phase separation. They not only allow the elucidation of the mixing behavior in more complicated binary systems but also broaden the understanding of binary blends in general. We highlight the importance of the local occupation configuration geometry and environment beyond the global thermodynamic mean-field considerations of mixing vs demixing. A thorough understanding of mixing in small organic molecule binary blends on the nanoscale is highly beneficial for capitalizing on the full power of organic semiconductors.
Transition dipole coupling between localized molecular vibrations represents a fundamental mechanism of energy delocalization in molecular solids. These collective states, referred to as vibrational excitons, give rise to distinct vibrational frequency shifts and mode splitting encoding information about molecular orientation, packing, conformation, and structural disorder. Originally developed to describe ideal crystalline materials, vibrational exciton spectroscopy and modeling have since evolved into a versatile tool applicable to a broad range of chemical systems, including molecular crystals, self-assembled monolayers (SAMs), molecular liquids, and biomolecular assemblies. However, diffraction-limited vibrational Raman and IR spectroscopy spatially averages over macroscopic ensembles of molecules, making it challenging to resolve inhomogeneities on nanometer length scales, which dictate the overall response of many molecular solids. Recently extended to the nanoscale, vibrational coupling nano-crystallography (VCNC) combines IR scattering-type scanning near-field optical microscopy (IR s-SNOM) with vibrational exciton theory to spatially resolve local molecular order and domain structure with nanometer resolution. In this review, we describe recent advances in near-field spectroscopy of vibrational excitons to image local molecular order in crystals, SAMs, and biological systems. Finally, we conclude with a perspective for VCNC to study excited-state dynamics, energy transport, collective quantum phenomena, and nanoscale structural evolution in complex molecular systems.
Extrinsic energy filtering (EEF) selectively allows high-energy charge carriers to pass through an energy barrier, blocking lower-energy (cold) carriers. This mechanism enhances thermoelectric performance by increasing the Seebeck coefficient S, since only high-energy carriers contribute, while maintaining electrical conductivity σ due to their higher mobility despite lower carrier density. The combined effect significantly boosts the power factor (PF) σS2. The concept of EEF dates back nearly 50 years, initially demonstrated by embedding metallic nanoparticles in telluride materials. Since then, theoretical models have advanced, and practical implementations have expanded to include elemental semiconductors, chalcogenides, and recently polymers. Nanostructured systems have played a key role by enabling close comparisons between theory, computational simulations, and experiments, deepening the understanding of EEF physics. This review offers a critical overview of both theoretical foundations and experimental progress in EEF over five decades. It highlights criteria for identifying genuine energy filtering effects in real materials and stresses the importance of distinguishing this phenomenon from other mechanisms that also improve the thermoelectric PF.
The diffusion behavior of macromolecules in dynamic cross-linked networks (DCNs) represents a core scientific issue linking the intrinsic physical properties of the network to mass transport processes. The inherent dynamism and heterogeneity of DCNs challenge classical diffusion theories and call for new theoretical frameworks. This review summarizes recent advances in understanding how reversible bonds mediate network topology reconstruction and thereby regulate diffusion. Particular emphasis is placed on the quantitative relationships between key physical parameters—such as mesh size, topology, bond exchange rate, and characteristic relaxation time—and the resulting diffusion dynamics, as well as on the coupling among different timescales, including bond lifetime, network relaxation, and diffusion. By integrating insights from theoretical modeling, simulations, and experimental studies, we highlight emerging principles that underpin the regulation of diffusion in DCNs. Finally, we identify the remaining open problems and key challenges for advancing the predictive understanding and control of diffusion in DCNs.
Machine learning is increasingly used to predict reaction properties such as barrier heights, reaction energies, rates, or yields, as well as the underlying molecular geometries, including transition state structures. While such predictions have the potential to provide mechanistic insight for high-impact applications such as synthesis planning and reaction optimization, the field remains at an early stage of development. This perspective discusses and critically assesses the current state of the art in (organic) reaction property prediction, highlighting the key limitations related to data availability and quality, molecular and transformation representations, and machine learning (ML) architectures used in both predictive and generative models. A special focus is given on current challenges and on possible paths forward toward efficient and accurate ML models for on-the-fly prediction of reaction energetics.
Microbial rhodopsins are widely used in optogenetics as light-driven actuators and genetically encoded voltage indicators. However, most rhodopsins exhibit extremely weak fluorescence due to rapid nonradiative relaxation of the retinal chromophore on the first excited-state potential-energy surface. Understanding the molecular origin of this behavior is therefore essential for the rational design of the brighter rhodopsin-based fluorophores. This review summarizes recent experimental and computational studies that establish electrostatic control of excited-state pathways as the central mechanism governing fluorescence in microbial rhodopsins. Following photoexcitation, the retinal chromophore relaxes from the Franck–Condon region toward a fluorescent state (FS) and subsequently toward a twisted intramolecular diradical intermediate (TIDIR) configuration located near the S1/S0 conical intersection. Fluorescence efficiency is therefore governed by the S1 isomerization barrier separating the FS from the TIDIR decay region. We discuss how this barrier can be modulated through three physically well-defined parameters: protonation of Schiff-base counterions, retinal isomeric composition, and mutation-induced redistribution of electric fields within the chromophore cavity. The unusual photophysical behavior of Neorhodopsin provides direct experimental validation of this electrostatic framework, while automated quantum mechanics/molecular mechanics strategies such as the automated rhodopsin modeling protocol demonstrate how these principles can guide the discovery of new fluorescent variants. Taken together, these results identify electrostatic control of the S1 isomerization barrier as a general design principle for engineering bright near-infrared rhodopsin fluorophores for optogenetic imaging.
Colloidal quantum-dots (QDs) are garnering significant attention as a promising material for next-generation optoelectronic devices due to their tunable emission wavelengths, high photoluminescence quantum yield, and solution-process compatibility and scalability. While QD-based technologies have seen widespread adoption in display applications, expanding their use into broader optoelectronic fields requires a precise understanding of their optical and electrical properties. Accurate modeling and prediction of device behaviors are critical for performance optimization, necessitating a comprehensive approach that integrates advanced computational techniques. This review explores state-of-the-art simulation methods and machine learning (ML)-based predictive models for QD devices. Key processes, including charge transport, exciton dynamics, and light outcoupling, are introduced to provide insights into efficiency and stability improvements. Modified electrical simulations are discussed alongside advanced optical simulations to assess the role of material properties and device architectures in determining performance. Additionally, the integration of ML algorithms has emerged as a powerful tool for accelerating device design, leveraging large datasets to efficiently predict and optimize QD structures, material compositions, and processing conditions. By combining computational simulations with ML-driven approaches, this review aims to establish a comprehensive framework for QD optoelectronic device research. The synergy between theoretical modeling and data-driven optimization is expected to enhance the development of high-performance QD-based technologies, paving the way for applications beyond conventional display systems.
While multi-walled carbon nanotubes (CNTs) have entered early mass production for battery applications, graphene oxide (GO) and single-walled CNTs are facing technical challenges in scaling production. Among various processing approaches, fluid-phase processing is the most promising method for achieving the desired nanocarbon structures at scale. Rheomechanics refers to the study of equilibrium and nonequilibrium thermodynamic states, including static and dynamic stability, and the evolution of microstructure in fluid phase and within solid phase during flow, with short and long-range time scales. Notably, significant advancements have been made in both theoretical and experimental methods to overcome strong van der Waals (vdW) interactions among nanocarbons for stable dispersions and control the microstructures during the fluid processing, drying, and heat treatment—such as electrode coating with GO pastes and wet spinning of CNT dopes. This review summarizes recent advances in the colloidal rheomechanics of highly concentrated dispersions of GO and CNT, whose individual particles exhibit micrometer-scale lateral sizes and lengths, with a focus on colloidal and thermodynamic stability, microstructural evolution, and rheological behavior. In particular, we highlight the role of excluded volume effects in governing these phenomena. The discussion begins with an analysis of attractive and repulsive potentials in GO and CNT dispersions, including modifications and evaluations of vdW, electrostatic, depletion, and excluded volume potentials for achieving colloidal stability in ultra-high-concentration dispersions. In the perspective presented in this review, the extending studies modifying Derjaguin–Landau–Verwey–Overbeek theory to explain the stable state of large-sized nanocarbons are essential for evaluating colloidal stability. In addition, extended studies based on Onsager theory serve as starting point elucidating thermodynamic stability and microstructures at equilibrium, with or without tactoids, as the free energy of 1D and 2D nanocarbon dispersions is primarily influenced by orientational entropy and excluded volume interactions. The perspective also points to the crucial role of excluded volume in the dynamic state, as well as in stability at equilibrium. The review then explores microstructure and orientation evolution during flow, particularly in shear and extensional rheology relevant to processes such as coating and wet spinning. Finally, microstructural evolution is addressed in the context of coagulation, heat treatment, and drying processes, with an emphasis on elasto-capillary effects. By providing an in-depth analysis of these key aspects, this review aims to advance the understanding of colloidal rheomechanics in GO and CNT dispersions, paving the way for improved processing techniques and material performance.
The development of highly efficient, stable, and scalable photoelectrode materials is paramount for developing photoelectrochemical (PEC) water splitting as a sustainable and practical approach for hydrogen production. The rapid progress in two-dimensional (2D) and layered materials, combined with innovative synthesis methodologies and sophisticated interface engineering strategies, is projected to drive substantial breakthroughs in solar-driven hydrogen generation, contributing to the global transition toward sustainable energy solutions. A diverse range of 2D and layered materials, including transition metal dichalcogenides, transition metal oxides, MXenes, graphene, nitrides, carbides, and their hybrid architectures, have demonstrated outstanding potential in enhancing PEC performance. These materials exhibit exceptional optical absorption properties, efficient charge carrier transport, and remarkable catalytic activity, making them highly attractive for next-generation PEC systems. Similarly, layered transition metal chalcogenides and metal-based layered double hydroxides have emerged as promising candidates for photoelectrode applications due to their high surface area, tunable electronic structures, and superior charge separation efficiency. Furthermore, heterostructured photosystems, intentionally engineered through precise interface modulation, have shown notable efficiency in accelerating charge transfer kinetics and mitigating charge recombination losses. In this regard, these layered materials have proven to be a versatile and robust platform for the fabrication of spatially controlled multilayered nanoarchitectures. Such an approach enables precise regulation of material composition, interfacial properties, and thickness, thereby optimizing light harvesting and charge carrier dynamics to achieve enhanced photocatalytic efficiency. This review provides an in-depth evaluation of emerging 2D and layered materials for PEC hydrogen evolution, emphasizing their structural advantages, intrinsic charge transport mechanisms, and synergistic interactions within heterostructured architectures. Additionally, critical challenges related to long-term stability, large-scale fabrication, and integration into existing PEC systems are thoroughly examined to offer insights into future research directions and practical implementation strategies.
For a wide range of photocatalytic uses, graphitic carbon nitride's (g-C3N4) exceptional physicochemical, optical, and structural characteristics have made it an attractive metal-free semiconductor candidate. Highlighting tactics such as heterojunction construction, morphology control, heteroatom doping, and defect engineering to improve photocatalytic efficiency, this review offers a thorough synopsis of current developments in the synthesis, modification, and functionalization of g-C3N4-based materials. We assess their efficacy in a variety of contexts, including water splitting, carbon dioxide reduction, degradation of pollutants, antibiotic activity, and sensing. We go over the correlations between structural features, photocatalytic performance, and synthesis factors in detail, as well as the present constraints, such as charge-carrier recombination, limited visible-light absorption, and stability issues. Emphasizing the potential of g-C3N4 in sustainable energy production and environmental remediation, we conclude by outlining new opportunities and research directions to close the gap between laboratory-scale demonstrations and real-world implementation.
The gemstone ruby, corundum (α-Al2O3) with Al3+ ions partially substituted by Cr3+ ions (Al2O3:Cr3+) possesses exceptional photophysical properties with an extremely long-lived (4270 μs) spin-flip phosphorescence at 694 nm with a very high photoluminescence (PL) quantum yield (90%). The phosphorescent soluble molecular congener [Cr(ddpd)2]3+ called “Molecular Ruby,” emitting at 738 and 775 nm, also shows record values in the field of chromium(III) complexes in PL lifetime (1122 μs) and quantum yield (13.7%). The comparably lower photophysical parameters stress the huge challenge of designing high-performance photoluminescent molecular systems. This tutorial review discusses general design concepts of Molecular Rubies, which are transferable to other photoactive molecular complexes. An introductory theoretical frame is given, including crystal field, ligand field, and molecular orbital theory of transition metal complexes, also highlighting photophysical processes in vertical (absorption and emission) and horizontal (internal conversion, intersystem crossing, and inductive-resonant energy transfer to high-energy oscillators) transitions. These challenges or disadvantages at first sight also include possibilities or levers to significantly tune specifically the photophysical properties and reactivity, such as emission energy, and to enable applications in photocatalysis and sensing.
Photoelectronic effects in nanostructures, such as the photovoltaic effect in solar cells and the photogating effect in photodetectors, represent both fundamental issues in solid state physics and promising application prospects. This review focuses on the progress and challenges of the lateral photovoltaic effect (LPE) in nanostructures. As a characteristic attribute in semiconductor-based materials, LPE originates from the lateral diffusion of photon-generated carriers under non-uniform illumination. A carrier concentration gradient between two lateral electrodes on the same side generates the lateral photovoltage (LPV) that varies linearly with light spot position. This linear relationship enables the LPE's primary application in position-sensitive detectors (PSDs) for high-precision displacement measurements and real-time trajectory tracking of light sources. The key parameter of LPE is position sensitivity, defined as the rate of LPV change per unit displacement. Pursuing a high LPE sensitivity under specific operational requirements has attracted substantial research attention. Herein, we systematically summarize the mechanisms of LPE and enhancement strategies of sensitivity including local surface plasmonic engineering and external field modulation techniques. We review some recent advancements across diverse nanostructures, such as nanofilms, quantum dots, nanowires, graphene, transition-metal chalcogenides, and so on. This review provides a comprehensive overview of LPE in semiconductor-based nanostructures while offering the future outlook on the development of PSDs.
Delafossite ABO2 materials, characterized by their layered superlattice structure of alternating O–A–O dumbbell layers and BO6 octahedra, exhibit exceptional light-harvesting capabilities and tunable electronic bandgaps (0–5.0 eV), establishing a unique platform for photocatalytic applications. This review systematically examines recent progress in the fundamental research and engineering applications of these materials. Mechanistic insights focus on how electronic structure features govern redox reaction kinetics, while material design strategies—including mechanochemical synthesis and elemental doping—are analyzed for their role in modulating microstructure and performance. Applications in environmental remediation (e.g., pollutant degradation) and energy conversion (e.g., photocatalytic water splitting, CO2 reduction) are critically evaluated in terms of efficacy, limitations, and preliminary techno-economic potential. Current bottlenecks—such as rapid charge recombination, limited stability under operational conditions, and scalability challenges in synthesis—are discussed in the context of practical deployment. To overcome these barriers, multiscale innovations involving heterostructure engineering, atomic-scale doping, and in situ protective layers are highlighted. Looking forward, this review emphasizes emerging pathways for advancing delafossite-based systems, including AI-aided material discovery, hybrid photoelectrochemical design, and—critically—comprehensive techno-economic assessment to evaluate economic viability, manufacturing costs, and environmental impact. Such holistic analysis will be essential to guide the transition of delafossite photocatalysts from laboratory research toward scalable, economically feasible sustainable energy and environmental solutions.
