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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10

Understanding failure in austenitic steels: Key considerations for molten salt storage in CSP applications

Owing to their excellent properties, austenitic stainless steels are extensively used in boilers, furnaces, molten salt tanks, and other applications that are subjected to extreme mechanical loads and high-temperature conditions. Their high corrosion and creep resistance make them suitable for high-temperature operating environments. Additionally, good fatigue resistance and favorable mechanical and visual properties are essential. However, the premature failure of several components at elevated temperatures has been previously reported. Although the failure analysis of components in service is complex, processes such as cold work and welding have been identified as contributing factors to the performance degradation of these steels. This study aims to analyze the various documented failure modes and mechanisms in austenitic steels, including creep, cracking, stress relaxation cracking, and fatigue, to better understand the multi-objective design requirements for these alloys as structural materials for high-temperature molten salt tanks in Concentrating Solar Power (CSP) plants. Stabilized austenitic grades, such as AISI 347H, demonstrate superior resistance to creep and corrosion-related degradation when compared to non-stabilized grades like AISI 316L at temperatures relevant to concentrated solar power (CSP) applications. In contrast, nickel-based alloys offer enhanced corrosion resistance, albeit at a higher cost. This review underscores that creep, stress relaxation cracking, and thermo-mechanical fatigue are the predominant long-term failure risks in CSP hot tanks.

14 SOLAR ENERGY↗

Multiscale characterization of phase change materials for building thermal energy storage applications

Phase change materials (PCMs) store and release large amounts of thermal energy because of their high latent energy storage capacity. However, long-term cyclic stability, supercooling and performance-scalability are some of the major challenges for their use in building thermal energy storage (TES) applications. Here, in this study, we present a comprehensive multiscale characterization of two commercially available organic PCMs, Puretemp 18 and Puretemp 23. At the microscale, differential scanning calorimetry (DSC) was used to characterize phase change temperature, specific heat, and latent heat. At the mesoscale, a heat flow meter apparatus (HFMA), following the ASTM C1784 standard, was employed to measure the phase change temperature, specific heat, and latent heat properties. A comparative analysis of latent heat as a function of temperature was conducted by integrating the DSC and HFMA results. At the macroscale, the thermal performance and cyclic stability of the TES system was evaluated using Puretemp 23. The TES system consisted of a finned tube heat exchanger with a storage volume of 0.0189 m 3 (5 gal), which represents a compact, real-world TES solution suitable for building energy storage. The results showed consistent thermal stability of the PCM over 200 cycles, and the supercooling temperature remained within 0.2 °C, which was not detected in smaller-scale characterization methods. Additionally, the macroscale testing methodology of the PCM revealed that the TES is able to charge and discharge stored latent energy within 2 h under a temperature differential of 16.67 °C measured between the inlet water temperature and the phase transition temperature of the PCM. The proposed multiscale PCM characterization method provides a systematic basis for comparing important thermal storage properties while also investigating the scalability, reliability and integration challenges in large scale TES applications.

Latent heat↗

MOOSE ProbML: Parallelized probabilistic machine learning and uncertainty quantification for computational energy applications

Here, this paper presents the development and demonstration of massively parallel probabilistic machine learning (ML) and uncertainty quantification (UQ) capabilities within the Multiphysics Object-Oriented Simulation Environment (MOOSE), an open-source computational platform for parallel finite element and finite volume analyses. In addressing the computational expense and uncertainties inherent in complex multiphysics simulations, this paper integrates Gaussian process (GP) variants, active learning, Bayesian inverse UQ, adaptive forward UQ, Bayesian optimization, evolutionary optimization, and Markov chain Monte Carlo (MCMC) within MOOSE. It also elaborates on the interaction among key MOOSE systems — Sampler, MultiApp, Reporter, and Surrogate — in enabling these capabilities. The modularity offered by these systems enables development of a multitude of probabilistic ML and UQ algorithms in MOOSE. Example code demonstrations include parallel active learning and parallel Bayesian inference via active learning. The impact of these developments is illustrated through five applications relevant to computational energy applications: UQ of nuclear fuel fission product release, using parallel active learning Bayesian inference; very rare events analysis in nuclear microreactors using active learning; advanced manufacturing process modeling using multi-output GPs (MOGPs) and dimensionality reduction; fluid flow using deep GPs (DGPs); and tritium transport model parameter optimization for fusion energy, using batch Bayesian optimization. These capabilities are part of the MOOSE framework.

97 - MATHEMATICS AND COMPUTING↗

Enriching OpenStreetMap network data for transportation applications: Insights into the impact of urban congestion on accessibility

OpenStreetMap (OSM) data is a valuable open-source resource for various transportation, traffic, and planning applications. However, OSM network data lack operating traffic speed information, which is critical for transport planning and operations. Addressing this shortcoming, this study leverages commercial vendor data (to serve as ground truth) with exogenous, open-source variables characterizing local transport infrastructure, land use, and demographic information to predict average congested traffic speeds on OSM networks. Three machine-learning models were tested and estimated for OSM links with and without speed limit information in the Denver metropolitan region. Among these, XGBoost performed best, with mean absolute errors of 3.27 and 3.62 mph for links with and without speed limits, respectively. The developed models accurately predicted traffic speeds for different hours and days of the week compared to ground truth data. Using these predicted speeds, drive accessibility scores were computed for the Denver region for different time periods using the Mobility Energy Productivity (MEP) metric to understand the impact of congestion on energy-efficient accessibility. Results show that congestion-adjusted drive accessibility can be significantly lower compared to accessibility calculated using free flow speeds. Specifically, weekday evening hours saw a 42 % drop in accessibility due to reduced speeds, particularly around downtown Denver. Across the Denver metro region, approximately half as many opportunities and jobs are accessible in under 20 min by car during the evening peak period relative to free flow conditions. These findings underscore the importance of using congestion-adjusted operating speeds rather than speed limits in accessibility calculations, as reliance on speed limits can substantially overestimate energy-efficient drive accessibility in large, car-centric cities susceptible to significant congestion. In conclusion, the methodology presented here could further enrich OSM network data, making them useful for an even broader range of transportation applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Substitutional doping of 2D transition metal dichalcogenides for device applications: Current status, challenges and prospects

Two-dimensional (2D) transition metal dichalcogenides (TMDs) have emerged as a class of materials with exceptional electronic, optical, and mechanical properties, making them highly tunable for diverse applications in nanoelectronics, optoelectronics, and catalysis. Here, this review focuses on substitutional doping of TMDs, a key strategy to tailor their properties and enhance device performance, with a focus on its applications over the past five years (2019–2024). We delve into both theoretical and experimental doping approaches, including established methods like chemical vapor transport (CVT) and chemical vapor deposition (CVD) alongside liquid phase exfoliation (LPE) and post-synthesis treatments. Advanced growth techniques are also explored. Challenges like dopant uniformity, concentration control, and stability are addressed. The influence of various dopants on the electronic band structure, carrier concentration, and defect engineering is analyzed in detail. We further explore recent advancements in utilizing doped TMDs for field-effect transistors (FETs), photodetectors, sensors, photovoltaics, optoelectronic devices, energy storage and conversion, and even quantum computers. By examining both the potential and limitations of substitutional doping, this review aims to propel future research and technological advancements in this exciting field.

36 MATERIALS SCIENCE↗

Direct writing of PVBVA/Ti 3 C 2 T x (MXene) triboelectric nanogenerators for energy harvesting and sensing applications

Triboelectric nanogenerators (TENGs) have gained recognition for their potential to convert mechanical energy into electrical energy, making them attractive for applications in healthcare, robotics, and human-device interfaces. However, many TENG devices rely on fluorinated polymers for high charge generation and involve complex fabrication processes, which limit their practicality and environmental sustainability. Here, we developed an eco-friendly composite of poly (vinyl butyral-co-vinyl alcohol-co-vinyl acetate) (PVBVA) and Ti 3 C 2 T x MXene for extrusion printing onto aluminum foil substrates, enabling the additive manufacturing of TENGs. Experimental results indicate that integrating 5.5 mg mL -1 of MXene (P-MX 5.5) into PVBVA resulted in a power density of 760 mW·m -2 , with simultaneous improvements in open-circuit voltage (129 %) and short-circuit current (250 %), demonstrating enhanced charge transfer efficiency. Beyond aluminum foil-based devices, we further explored the fully printed P-MX 5.5 TENG by utilizing silver ink electrodes, eliminating the need for aluminum foil. This fully printed, flexible TENG was successfully used for real-time human motion sensing, demonstrating its ability to detect activities such as walking, running, knee bending, and jumping. Collectively, our additively manufactured and sustainable PVBVA-MXene TENG composites, including both aluminum-based and fully printed versions, show promise for future energy harvesters, sensors, wearable electronics, healthcare, and robotic applications.

Additive manufacturing↗

ENDF/B-VIII.1: Updated Nuclear Reaction Data Library for Science and Applications

The ENDF/B-VIII.1 library is the newest recommended evaluated nuclear data file by the Cross Section Evaluation Working Group (CSEWG) for use in nuclear science and technology applications, and incorporates advances made in the six years since the release of ENDF/B-VIII.0. Among key advances made are that the 239 Pu file was reevaluated by a joint international effort and that updated 16,18 O, 19 F, 28–30 Si, 50–54 Cr, 55 Mn, 54,56,57 Fe, 63,65 Cu, 139 La, 233,235,238 U, and 240,241 Pu neutron nuclear data from the IAEA coordinated INDEN collaboration were adopted. Over 60 neutron dosimetry cross sections were adopted from the IAEA's IRDFF-II library. In addition, the new library includes significant changes for 3 He, 6 Li, 9 Be, 51 V, 88 Sr, 103 Rh, 140,142 Ce, Dy, 181 Ta, Pt, 206–208 Pb, and 234,236 U neutron data, and new nuclear data for the photonuclear, charged-particle and atomic sublibraries. Numerous thermal neutron scattering kernels were reevaluated or provided for the very first time. On the covariance side, work was undertaken to introduce better uncertainty quantification standards and testing for nuclear data covariances. The significant effort to reevaluate important nuclides has reduced bias in the simulations of many integral experiments with particular progress noted for fluorine, copper, and stainless steel containing benchmarks. Data issues hindered the successful deployment of the previous ENDF/B-VIII.0 for commercial nuclear power applications in high burnup situations. These issues were addressed by improving the 238 U and 239,240,241 Pu evaluated data in the resonance region. The new library performance as a function of burnup is similar to the reference ENDF/B-VII.1 library.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

High fidelity multiphysics tightly coupled model for a lead cooled fast reactor concept and application to statistical calculation of hot channel factors

A tightly coupled multiphysics code system is established using the MOOSE framework for hot channel factor (HCF) evaluation on a Lead Fast Reactor (LFR) concept. The coupled system is driven by the Griffin multiphysics coupling capability under which the MOOSE Heat Transfer module and NekRS computational fluid dynamics solver are coupled for conjugate heat transfer using the Cardinal application. The coupled capability is demonstrated on an LFR assembly model based on materials and geometry of a prototypical lead-cooled fast reactor design by Westinghouse Electric Company, LLC. Moreover, the work integrates the Multiphysics Object Oriented Simulation Environment (MOOSE) Stochastic Tools Module (STM) to perform calculations for statistical analysis of HCF. Furthermore, the coupling strategy and workflow demonstrated in this paper is not only useful for predicting accurate hot channel factors for different kinds of advanced reactors but also for other engineering applications such as control rod worth assessment, generation of high-fidelity database for Artificial intelligence (AI)/machine learning (ML) training, design optimization and multi-resolution modeling.

Cardinal↗

Design of novel refractory equiatomic multi-principal elemental alloys based on Mo-Nb-Ti system for Gen IV reactor applications

Excellent irradiation damage resistance demonstrated by multi-principal elemental alloys (MPEAs) has sparked significant interest among researchers, prompting exploration into their vast compositional space, to validate their suitability for nuclear applications. A combined approach of thermodynamic and empirical parameters calculations alongside CALPHAD (CALculation of PHAse Diagrams) for phase formation predictions enable high-throughput material selection for sophisticated applications like nuclear, overcoming laborious and time-consuming experiments. Key thermodynamic and empirical parameters for eight novel equiatomic MPEAs, based on seven low thermal neutron cross section refractory elements, for predicting phase formation were calculated, and equilibrium and non-equilibrium simulations in CALPHAD were employed to comprehensively model the systems. Pseudo binary phase diagram simulations showed that Zr, V or equiatomic CrV additions to the base MoNbTi alloy (MoNbTi-Zr, MoNbTi-V and MoNbTi-CrV alloys) favor the formation of isomorphous body-centered cubic (BCC) phase at high temperatures, while Cr, Al, equiatomic ZrV, or equiatomic CrAl additions (MoNbTi-Cr, MoNbTi-Al, MoNbTi-ZrV or MoNbTi-CrAl alloys) limit the solubility of them. Equilibrium CALPHAD simulations at 750 oC were consistent with XRD results on MoNbTi, MoNbTiZr and MoNbTiCr alloys, and partially for others. Notably, elemental segregation observed in the backscattered electron (BSE) scanning electron microscopy (SEM) images of the alloys was accurately simulated through non-equilibrium Scheil solidification calculations in CALPHAD, further verified by experiments. The precipitation of TiCr2 Laves phase in Cr containing MoNbTiCr and MoNbTiCrAl was accurately predicted while discrepancies were noted in MoNbTiCrV. The equilibrium simulations also provided insights into phase compositions at specific temperatures offering a pathway for tailoring the desired microstructure and properties of these systems. Empirical parameters calculations successfully predicted random solid solution in the base MoNbTi alloy, and with an exception in MoNbTiV and MoNbTiAl, predicted intermetallic precipitation in the rest, especially, Laves phase precipitation in Cr containing alloys.

36 - MATERIALS SCIENCE↗

Emergence of deep eutectic solvents (DES): chemistry, preparation, properties, and applications in biorefineries and critical materials

The emergence of renewable deep eutectic solvents (DES) as clean and efficient catalysts and solvents has created new opportunities for lignocellulosic biorefineries and critical material sectors, including chemical, energy, pharmaceutical, textile, and hydrometallurgical industries. This review provides an in-depth overview of DES, covering their chemistry, classifications, preparation methods, processing characteristics, and recyclability, while highlighting their unique attributes and industry relevant applications. Emphasis is placed on the integration of DES into advanced biorefinery systems, focusing on their tunable physicochemical and thermodynamic properties for biomass pretreatment and the production of value-added products. The review explores how DES can be tuned for selective dissolution of biomass components and evaluates production and valorization of DES-derived biochemicals, with attention to lignin extraction mechanisms and conversion of biomass into bioproducts and biofuels. Beyond biorefineries, the scope extends to DES applications in electrochemical energy devices, where they serve as electrolytes, synthesis media for electrode materials, and leaching agents in battery recycling. The multifunctional roles of DES in pharmaceutical, hydrometallurgical, and textile sectors are also explored for contributions to sustainable processing. Finally, the review identifies future research directions, outlining benefits, challenges, and knowledge gaps, for continued industrial development.

09 BIOMASS FUELS↗

Roadmap to an electron beam or X-ray center for industrial applications

Here, this paper introduces the topics that need consideration to allow an effective feasibility analysis of electron beams and/or X-rays technologies prior to potential investment and implementation of these technologies for industrial applications. It also highlights considerations for planning, developing and construction of an electron beam or X-ray facility The focus of this paper is on business topics and it provides details of where additional technical information can be found. The paper also describes current applications for electron beam and X-ray technologies to demonstrate their potential.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The influence of ambient light spectrum (LED, INC, CFL, Xenon…) on the efficiency of perovskite indoor photovoltaic solar cells for Internet of Things (IoT) applications

This record provides a numerical investigation of a MAGeI₃-based perovskite solar cell with the structure FTO/TiO₂/MAGeI₃/Spiro-OMeTAD, evaluated for both outdoor and indoor light-harvesting applications using the SCAPS-1D simulator. Device performance is analyzed under AM 1.5G sunlight and several artificial light sources, including LED, incandescent, compact fluorescent lamp (CFL), flashlight, and xenon illumination. The study reports initial and optimized power conversion efficiencies and examines the influence of absorber layer thickness and bandgap on device performance under different lighting conditions. The results highlight the potential of MAGeI₃-based perovskite solar cells for indoor energy harvesting and low-power Internet of Things (IoT) applications.

14 SOLAR ENERGY↗

Ecologically inspired metrics for transitioning to a sustainable and resilient circular economy with application to multilayer plastic films

Current Circular Economy (CE) frameworks applied to product chains exhibit notable shortcomings. These include neglecting the resilience and robustness of design, requiring detailed economic and environmental data for impact assessment, and relying on qualitative rather than quantitative metrics capturing certain CE design aspects. In the current contribution, we addressed these shortcomings by developing an Ecologically inspired (Eco-inspired) Framework using the mathematical foundations of Ecological Network Analysis (ENA). While ENA metrics have previously found application in designing circular economies, particularly in Industrial Symbiosis (IS) networks, our adaptation tailors these metrics for use in product-level CE, recognizing the inherent distinctions between product-level CE and IS. Our Eco-inspired Framework comprises three key categories to provide holistic and granular-level metrics for designing product-level CE. The first set of metrics assesses circularity and resource efficiency. The second set gauges network intensity and robustness as complementary indicators ensuring a CE is both sustainable and resilient. The third group of metrics evaluates enhancement potential of CE strategies through introducing quantitative metrics for measuring the degree of closed-loop strategies and average circularity level of a CE design. The three comprehensive set of indicators within the Eco-inspired Framework uniquely captures various facets of circular design, whether originating from technological innovations and recovery improvement at the end of life (EoL), shifts in human consumption patterns, alterations in product design, or changes in business models. The framework’s application is tested in designing a CE for multilayer Polyethylene-Polyamide (PE-PA) films. Using the Eco-inspired Framework, we identified the best strategy for designing a resilient and sustainable CE for PE-PA films. A diverse set of EoL strategies along with a reduction in product consumption can improve circularity and resilience by 650% and 255%, respectively, and mitigate greenhouse gas emissions by 90%. The framework minimizes trade-offs between sustainability and circularity goals and offers insights on how to enhance each strategy for achieving a resilient and sustainable CE for products.

54 ENVIRONMENTAL SCIENCES↗

Advances in high-pressure and high-temperature heat exchangers: Innovations via additive manufacturing and their applications

This paper provides a comprehensive overview of technological developments and applications for high-pressure and high-temperature (HPHT) heat exchangers produced through additive manufacturing (AM) techniques. As the demand for high-efficiency energy systems has been rising, the role of heat exchangers for thermal management and transport is becoming increasingly crucial. In this context, AM has emerged as a promising manufacturing solution to address the challenges posed by higher operating temperatures and/or pressures. This paper delves into three primary areas: the exploration of HPHT regimes supported by conventional heat exchangers, the impact of AM processes on thermal transport devices, and the discussion focused on HPHT heat exchangers produced via AM. The study examines the traditional manufacturing processes, materials, structures and geometries, and limitations of the commonly used heat exchangers for HPHT applications. Furthermore, it highlights the potential of AM in optimizing HPHT heat exchanger design, by reviewing studies that enable uniform flow distribution, minimization of fouling, and thermo-hydraulic performance augmentation without compromising structural stability. While addressing the limitations of cost, size, and other constraints, this study offers insights into the possibilities of AM in revolutionizing HPHT heat exchanger technology. The goal has been to fill the gap in literature by summarizing key studies, findings, and limitations, presenting a detailed examination, and proposing new areas for research. In conclusion, this review contributes to a deeper understanding of AM’s role in advancing HPHT heat exchangers for future energy systems.

36 MATERIALS SCIENCE↗

Recent Advances and Future Perspectives of Low-Concentration CO 2 Enrichment and Emerging Applications

Low-concentration carbon dioxide (LCCO 2 ) streams, ranging from ambient air to industrial flue gas, represent a significant yet underutilized carbon resource. This review examines recent advances in technologies for enriching LCCO 2 and enabling its integration into a wide range of applications. It covers emerging materials and processes for CO 2 capture, including immobilized amines, metal oxides, polymers, porous carbons, and zeolites, with a focus on performance metrics, regeneration strategies, and process intensification. Beyond capture, the review explores the direct utilization of LCCO 2 through reactive capture pathways enabled by novel catalysts and processes, as well as nonreactive applications, such as greenhouse cultivation, enhanced weathering, and sustainable agriculture. Additionally, this review highlights the role of LCCO 2 in enhancing critical metal recovery. Finally, the review outlines crucial future research directions necessary to fully realize LCCO 2 enrichment’s potential within circular carbon economies and critical material supply chains, paving the way toward a more energy-innovative and resource-resilient industrial sector. The findings are significant for researchers in academia, industry, and government, as well as the public interested in extending the value of LCCO 2 .

atmospheric chemistry↗

Classical Preoptimization Approach for ADAPT-VQE: Maximizing the Potential of High-Performance Computing Resources to Improve Quantum Simulation of Chemical Applications

The ADAPT-VQE algorithm is a promising method for generating a compact ansatz based on derivatives of the underlying cost function, and it yields accurate predictions of electronic energies for molecules. In this work, we report the implementation and performance of ADAPT-VQE with our recently developed sparse wave function circuit solver (SWCS) in terms of accuracy and efficiency for molecular systems with up to 52 spin orbitals. The SWCS can be tuned to balance computational cost and accuracy, which extends the application of ADAPT-VQE for molecular electronic structure calculations to larger basis sets and a larger number of qubits. Using this tunable feature of the SWCS, we propose an alternative optimization procedure for ADAPT-VQE to reduce the computational cost of the optimization. Furthermore, by preoptimizing a quantum simulation with a parametrized ansatz generated with ADAPT-VQE/SWCS, we aim to utilize the power of classical high-performance computing in order to minimize the work required on noisy intermediate-scale quantum hardware, which offers a promising path toward demonstrating quantum advantage for chemical applications.

ADAPT-VQE↗

Black Phosphorus for Mid-Infrared Optoelectronics: Photophysics, Scalable Processing, and Device Applications

High efficiency mid-infrared (λ = 3-8 μm) light emitters and photodetectors are pivotal for advancing next-generation optoelectronics. However, narrow-bandgap semiconductors face fundamental challenges such as pronounced nonradiative carrier recombination and thermally generated noise, which impede device performance. Recently, two-dimensional layered black phosphorus (BP) and its alloys have attracted substantial interest for mid-infrared device applications, demonstrating superior performance relative to conventional III-V and II-VI semiconductors with similar bandgaps. In this review, we discuss the optical properties of BP, contrasting these with those of covalent compounds. Owing to its inherently self-terminated surface structure and reduced nonradiative recombination, BP exhibits high performance in light emission and photodetection at room temperature. Furthermore, this review highlights recent advances in the large-area processing of BP thin films, paving the way for practical device applications and integration. Finally, we explore ongoing challenges and emerging opportunities in the utilization of BP for functional mid-infrared devices.

Higashitarumizu, Naoki↗

Atomic Structure, Dynamics, Changes in Chemical Bonding and Semiconductor-Metal Transition in Sb 2 Se 3 : A Remarkable Material for Quantum Networks and Energy Applications

Antimony sesquiselenide has become an outstanding functional material for photovoltaics, energy storage and transformation, memory and photonic applications. Sb 2 Se 3 is one of the most successful emerging solar light absorbers and has also been identified as a highly promising ultralow-loss phase-change material (PCM) for next-generation coherent nanophotonic processors, photonic tensor cores, quantum and neuromorphic networks. Unlike benchmark telluride PCMs, Sb 2 Se 3 features a quasi-one-dimensional (1D) crystalline structure consisting of (Sb 4 Se 6 ) ∞ ribbons, lacks the typical PCM chemical bonding, and undergoes an extended semiconductor-metal transition above the melting point. Consequently, the origin of high optical contrast between crystalline (SET) and amorphous (RESET) logic states remains elusive and presents a significant challenge. Using high-energy X-ray diffraction and Raman spectroscopy over a wide temperature range, supported by first-principles simulations and complemented by thermal, optical and electrical measurements, as well as by 121 Sb-Mossbauer spectroscopy, the quasi-1D network of orthorhombic antimony sesquiselenide was found to undergo significant evolution in amorphous and supercooled Sb 2 Se 3 , leading to lower coordination, shorter interatomic distances and a higher p-electron density on antimony, indicating changes in chemical bonding. The observed novel Sb 2 Se 3 nanocrystalline polymorph, characterized by trigonal antimony coordination and more isolated Sb-Se ribbons, could help reduce multiple trapping defect states in the bandgap, which are typical of orthorhombic Sb 2 Se 3 , thereby enhancing the power-conversion efficiency of photovoltaic devices. Semimetallic and metallic liquid Sb 2 Se 3 exhibit a gradual transformation into a denser 2D and/or 3D network with higher antimony coordination. Localized electron states in the pseudogap are becoming extended, leading to an increase in electronic conductivity σ following the relationship σ ∝ N(E F ) 2 . Liquid Sb 2 Se 3 also appears to be strongly fragile, with a nonmonotonic change in viscosity and higher atomic mobility in the metallic liquid. Furthermore, these results explain extraordinary functionalities of Sb 2 Se 3 for photonic and energy applications.

antimony↗