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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Cellular Automaton Simulation for Predicting Phase Evolution in Solid-State Reactions

New computational tools for solid-state synthesis recipe design are needed in order to accelerate the experimental realization of novel functional materials proposed by high-throughput materials discovery workflows. This work contributes a cellular automaton simulation framework for predicting the time-dependent evolution of intermediate and product phases during solid-state reactions as a function of precursor choice and amount, reaction atmosphere, and heating profile. The simulation captures the effects of reactant particle spatial distribution, particle melting, and reaction atmosphere. Reaction rates based on rudimentary kinetics are estimated using density functional theory data from the Materials Project and machine learning estimators for the melting point and the vibrational entropy component of the Gibbs free energy. The resulting simulation framework allows for the prediction of the likely outcome of a reaction recipe before any experiments are performed. We analyze five experimental solid-state recipes for BaTiO 3 , CaZrN 2 , and YMnO 3 found in the literature to illustrate the performance of the model in capturing reaction selectivity and reaction pathways as a function of temperature and precursor choice. This simulation framework offers an easier way to optimize existing recipes, aid in the identification of intermediates, and design effective recipes for yet unrealized inorganic solids in silico .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

In situ electric-field control of ferromagnetic resonance in the low-loss organic-based ferrimagnet V[TCNE] x ∼2

We demonstrate indirect electric-field control of ferromagnetic resonance (FMR) in devices that integrate the low-loss, molecule-based, room-temperature ferrimagnet vanadium tetracyanoethylene (V[TCNE]x∼2) mechanically coupled to PMN-PT piezoelectric transducers. Upon straining the V[TCNE]x films, the FMR frequency is tuned by more than 6 times the resonant linewidth with no change in Gilbert damping for samples with α = 6.5 × 10−5. We show this tuning effect is due to a strain-dependent magnetic anisotropy in the films and find the magnetoelastic coefficient |λs| ∼ (1–4.4) ppm, backed by theoretical predictions from density-functional theory calculations and magnetoelastic theory. Noting the rapidly expanding application space for strain-tuned FMR, we define a new metric for magnetostrictive materials, magnetostrictive agility, given by the ratio of the magnetoelastic coefficient to the FMR linewidth. This agility allows for a direct comparison between magnetostrictive materials in terms of their comparative efficacy for magnetoelectric applications requiring ultra-low loss magnetic resonance modulated by strain. With this metric, we show V[TCNE]x is competitive with other magnetostrictive materials, including YIG and Terfenol-D. This combination of ultra-narrow linewidth and magnetostriction, in a system that can be directly integrated into functional devices without requiring heterogeneous integration in a thin film geometry, promises unprecedented functionality for electric-field tuned microwave devices ranging from low-power, compact filters and circulators to emerging applications in quantum information science and technology.

Materials Science↗
DOE OSTI2025

Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials: Part II Resveratrol Exemplar

This SAND report summarizes work supported by an Engineering Sciences Research Foundation (ESRF) Lab Directed Research and Development (LDRD) project entitled “Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials.” This SAND report is written in two parts with Part 1 discusses recrystallization of our explosive exemplar and Part 2 summarizing our work with recrystallization of resveratrol. We have studied resveratrol recrystallization with a multiscale approach combining experiments, modeling and simulation. At the single crystal scale, microscopy experiments illuminate crystal time-dependent growth rates using advanced image analysis. Bench scale experiments were carried out to look at growth of multiple particles in a small reactor creating thousands of particles and analyzing the results with microscopy and μCT. For the modeling we combine kinetic Monte Carlo (kMC) models with subscale information from density functional theory (DFT) or molecular dynamics. This work is discussed in Part 1 and can also be found in a paper from the project discussing a coarse-grained kMC model specifically developed for resveratrol. For well-mixed systems, we have population balance equations (PBE) linked with species mass conservation forming a set of ordinary differential equations that can be solved quickly. For more complicated geometries, such as the vat crystallization used throughout the complex, a coupled computational fluid dynamic (CFD)/PBE method was developed to account for gradients in temperature and concentration and differences in crystallization rates throughout the domain. These simulations are more complex and require high performance computing. We present results for two cases: 5% seed fast cool with parameters fit to the well-mixed case and 5% seed slow cool using the same parameters. We show reasonable agreement with experiments though are particles are significantly larger than the experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multi-modal characterization of the B2 phase in the Ta-Re binary system

The energy and transportation industries demand materials that retain their mechanical property at high temperatures. Refractory complex concentrated alloys (RCCAs) with a BCC + B2 microstructure offer a potential solution, where maintaining the high temperature mechanical properties can be achieved by precipitation strengthening. This depends on the B2 phase in RCCAs being thermodynamically stable with a high solvus temperature. Recently, we predicted the high temperature stability of the B2 structure in the Ta-Re binary system, using density functional theory. Here, in this study, we provide experimental evidence for the existence of this phase for the first time, using a Ta 65 Re 35 alloy. Despite Ta-Re binary phase diagrams predicting a single-phase BCC microstructure for Ta 65 Re 35 , we show that a high Z nanoscale secondary phase appears after heat treatment at 1550 °C and 1100 °C. Scanning transmission electron microscopy (STEM) revealed that this phase has a cubic structure and is equiatomic TaRe though B2 superlattice reflections were absent in fast Fourier transforms (FFT) and diffraction patterns (DPs). DP simulations indicate that the B2 TaRe superlattice reflections are up to two orders of magnitude weaker than their fundamental reflections, making their detection challenging via electron microscopy. Neutron diffraction confirmed the second phase had a B2 structure. This study identified a previously unobserved high temperature stable B2 phase in the Ta-Re system, enabling the development of new high temperature BCC + B2 RCCAs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Machine learning approach for vibronically renormalized electronic band structures

Here, we present a machine learning (ML) method for efficient computation of vibrational thermal expectation values of physical properties from first principles. Our approach is based on the nonperturbative frozen phonon formulation in which stochastic Monte Carlo algorithm is employed to sample configurations of nuclei in a supercell at finite temperatures based on a first-principles phonon model. A deep-learning neural network is trained to accurately predict physical properties associated with sampled phonon configurations, thus bypassing the time-consuming ab initio calculations. To incorporate the point-group symmetry of the electronic system into the ML model, group-theoretical methods are used to develop a symmetry-invariant descriptor for phonon configurations in the supercell. We apply our ML approach to compute the temperature dependent electronic energy gap of silicon based on density functional theory (DFT). We show that, with less than a hundred DFT calculations for training the neural network model, an order of magnitude larger number of sampling can be achieved for the computation of the vibrational thermal expectation values. Our work highlights the promising potential of ML techniques for finite temperature first-principles electronic structure methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Defect-Limited Mobility and Defect Thermochemistry in Mixed A-Cation Tin Perovskites: (CH3NH3)1-xCsxSnBr3

Hybrid organic-inorganic semiconductors crystallizing in the perovskite structure present a significant opportunity for realizing defect-tolerant semiconductors. In this work, we examine the solid solution, (CH3NH3)1-xCsxSnBr3, and identify the thermochemistry dictating the intrinsic carrier concentrations and how local structural distortions influences this electronic behavior. This family of compounds exhibits the expected systematic trend in decreasing optical gap with the cesium to methylammonium A-site mixing ratio, x, in the visible region. However, the carrier mobility, as determined from time-resolved microwave conductivity measurements, trends opposite to that expected from first-principles calculations combined with Boltzmann scattering theory calculations of the carrier mobility. We propose that this is a result of increasing carrier scattering with x in (CH3NH3)1-xCsxSnBr3 due to a significant increase in the carrier density with x. By examining the dependence of the carrier density as a function of x, we infer the compositional-dependence of the average enthalpy and nonconfigurational entropy per defect. While diffraction reveals a cubic aristotypic perovskite structure as a function of x at room temperature, the pair distribution functions obtained from synchrotron X-ray total scattering from these materials are better described by symmetry-adapted displacement modes of the Pm3m crystal structure, which we attribute to a large degree of anharmonic dynamics of the atom positions. This analysis shows that CH3NH3+-rich compositions retain mostly linear Sn-Br-Sn bonding environments through the displacements, while Cs+-rich compositions lead to more significantly bent Sn-Br-Sn environments. We propose that these bent bonding arrangements in Cs-rich compositions yield a higher propensity for defect formation. This also provides a rationale for carrier trapping that gives rise to anomalous microwave transients. Together, these results provide insight into the structure-dynamics-properties relationships in this highly anharmonic system with high amplitude atomic motions and low defect formation energies.

defect thermochemistry↗
DOE OSTI2024

Mixed Valence {Ni 2+ Ni 1+ } Clusters as Models of Acetyl Coenzyme A Synthase Intermediates

Acetyl coenzyme A synthase (ACS) catalyzes the formation and deconstruction of the key biological metabolite, acetyl coenzyme A (acetyl-CoA). The active site of ACS features a {NiNi} cluster bridged to a [Fe4S4] n+ cubane known as the A-cluster. The mechanism by which the A-cluster functions is debated, with few model complexes able to replicate the oxidation states, coordination features, or reactivity proposed in the catalytic cycle. In this work, we isolate the first bimetallic models of two hypothesized intermediates on the paramagnetic pathway of the ACS function. The heteroligated {Ni 2+ Ni 1+ } cluster, [K(12-crown-4) 2 ][1], effectively replicates the coordination number and oxidation state of the proposed “A red ” state of the A-cluster. Addition of carbon monoxide to [1] - allows for isolation of a dinuclear {Ni 2+ Ni 1+ (CO)} complex, [K(12-crown-2) n ][2] (n = 1–2), which bears similarity to the “A NiFeC ” enzyme intermediate. Structural and electronic properties of each cluster are elucidated by X-ray diffraction, nuclear magnetic resonance, cyclic voltammetry, and UV/vis and electron paramagnetic resonance spectroscopies, which are supplemented by density functional theory (DFT) calculations. Calculations indicate that the pseudo-T-shaped geometry of the three-coordinate nickel in [1] – is more stable than the Y-conformation by 22 kcal mol –1 , and that binding of CO to Ni 1+ is barrierless and exergonic by 6 kcal mol –1 . UV/vis absorption spectroscopy on [2] - in conjunction with time-dependent DFT calculations indicates that the square-planar nickel site is involved in electron transfer to the CO π*-orbital. Further, we demonstrate that [2] - promotes thioester synthesis in a reaction analogous to the production of acetyl coenzyme A by ACS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Vacancy-Dependent Diffusion Mechanism in Oxygen-Defective SrFeO 3 Perovskite Materials: First-Principles Density Functional Theory and Experimental Approach

Understanding oxygen diffusion at the atomic scale in SrFeO 3−δ perovskites is crucial for developing oxygen storage materials with optimal performance. Such materials are required to have high stability, corrosion resistance, and acceptable oxygen storage capacity at moderate operating temperatures and pressures. Here, in this study, we used first-principles density functional theory and thermogravimetric analysis to study the vacancy-dependent oxygen diffusion in oxygen-deficient SrFeO 3−δ (δ = 0, 0.065, 0.125, 0.25, 0.5) perovskites. The electronic structures, including the partial- and spin-resolved density of states, for different SrFeO 3−δ phases were calculated and compared with available experimental and theoretical results. By mapping the migration pathways, we investigated diffusion mechanisms and calculated the energy barriers for oxygen diffusion in cubic, orthorhombic, and brownmillerite phases of SrFeO 3−δ perovskites. Using the calculated energy barriers, we deduced the diffusion time scales and diffusion coefficients within SrFeO 3−δ . A diffusion coefficient on the order of 10 –8 m 2 /s was obtained for SrFeO 2.875 . We experimentally investigated the roles of temperature and oxygen partial pressures on the redox kinetics and deduced the kinetics rate and diffusion density, which agreed well with the calculated values for the density of diffusing oxygen vacancy in the lattice. Our results showed that the energy barrier tends to reduce at higher oxygen concentrations. Our results serve as an important guideline for designing oxygen storage materials with optimal redox kinetics.

chemical looping with oxygen uncoupling (CLOU)↗
DOE OSTI2024

Realization of Organocerium-Based Fullerene Molecular Materials Showing Mott Insulator-Type Behavior

Abstract Electron-rich organocerium complexes (C 5 Me 4 H) 3 Ce and [(C 5 Me 5 ) 2 Ce(ortho-oxa)], with redox potentials E 1/2 = –0.82 V and E 1/2 = –0.86 V versus Fc/Fc + respectively, were reacted with fullerene (C 60 ) in different stoichiometries to obtain molecular materials. Structurally characterized co-crystals: [(C 5 Me 4 H) 3 Ce] 2 •C 60 (1) and [(C 5 Me 5 ) 2 Ce(ortho-oxa)] 3 •C 60 (2) of C 60 with cerium-based rare earth molecular precursors are reported for the first time. The extent of charge transfer in 1 and 2 was evaluated using a series of physical measurements: FT-IR, Raman, solidstate UV-vis-NIR spectroscopy, X-ray absorption near edge structure (XANES) spectroscopy, and magnetic susceptibility measurements. The physical measurements indicate that 1 and 2 comprise the cerium(III) oxidation state with formally neutral C 60 as a co-crystal in both cases. Pressure-dependent periodic density functional theory calculations were performed to study the electronic structure of 1. Inclusion of a Hubbard-U parameter removes Ce f states from the Fermi level, opens up a band gap, and stabilizes FM/AFM magnetic solutions that are isoenergetic because of the large distances between the Ce(III) cations. Furthermore, the electronic structure of this strongly correlated Mott insulator-type system is reminiscent of the well-studied Ce 2 O 3 .

36 MATERIALS SCIENCE↗
DOE OSTI2024

Coexistence of Interacting Charge Density Waves in a Layered Semiconductor

Coexisting orders are key features of strongly correlated materials and underlie many intriguing phenomena from unconventional superconductivity to topological orders. Here, we report the coexistence of two interacting charge-density-wave (CDW) orders in EuTe 4 , a layered crystal that has drawn considerable attention owing to its anomalous thermal hysteresis and a semiconducting CDW state despite the absence of perfect FS nesting. By accessing unoccupied conduction bands with time- and angle-resolved photoemission measurements, we find that mono- and bi-layers of Te in the unit cell host different CDWs that are associated with distinct energy gaps. The two gaps display dichotomous evolutions following photoexcitation, where the larger bilayer CDW gap exhibits less renormalization and faster recovery. Surprisingly, the CDW in the Te monolayer displays an additional momentum-dependent gap renormalization that cannot be captured by density-functional theory calculations. This phenomenon is attributed to interlayer interactions between the two CDW orders, which account for the semiconducting nature of the equilibrium state. Finally, our findings not only offer microscopic insights into the correlated ground state of EuTe 4 but also provide a general non-equilibrium approach to understand coexisting, layer-dependent orders in a complex system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Ripening of Rh Nanoparticle Catalysts in Reverse Water–Gas Shift via a Data-Driven Model Combining Physics, Theory, and Experiment

Degradation via sintering is an ongoing challenge that impedes the broad commercial success of supported metallic nanoparticle catalysts. To mitigate degradation via informed catalyst design and process operations, here we aim to disambiguate the underlying mechanisms of sintering by combining theory and experiment in a quantitative framework. While mechanistic sintering models exist, they only model a single sintering pathway, even though multiple sintering mechanisms can occur simultaneously or dominate at different stages of the process. Data-driven machine learning models have emerged as a means to represent complex processes through data regression. However, machine learning models have very large data needs and lack mechanistic insights due to their black-box encoding. To develop an interpretive model of catalyst degradation via sintering, we constructed a hybrid model combining mechanistic “physics-based” models and data-driven methods to obtain both reliable predictions and mechanistic insights regarding experimentally observed sintering phenomena. Focusing on nanoparticle sintering in the Rh–TiO 2 catalyst for the reverse water–gas shift (RWGS) reaction, the hybrid model couples a mechanistic term for Ostwald ripening with energy values calculated via density functional theory (DFT) with a parametric, data-driven discrepancy function term for unmodeled mechanisms. The hybrid model is trained using Bayesian inference with data collected from small-angle X-ray scattering (SAXS) in situ experiments wherein average nanoparticle diameter versus time was measured at three relevant operating temperatures. The calibrated hybrid model results show that an Ostwald ripening-only model parameterized with fixed DFT energies does not fully capture the time and temperature dependence of the SAXS-observed sintering kinetics, and that an additional functional contribution, or DFT energy calibration, is required to reconcile simulation and experiment. Analysis of the hybrid-model error confirms that the hybrid model outperforms both the purely mechanistic and purely data-driven alternatives in terms of expected predictive accuracy for time-evolving average particle sizes. Furthermore, the results support the hypothesis that the Ostwald ripening mechanism is less important for explaining the sintering phenomena as operating temperature increases under an assumed fixed DFT parameterization. This could be explained in one of two ways: either latent, unmodeled sintering mechanisms dominate at higher temperatures, or the DFT uncertainty increases with temperature. The proposed modeling approach directly links theory to experiments and simulations via a statistical hybrid modeling framework and can be extended to other catalytic systems to improve predictive models and mechanistic understanding.

Bayesian hybrid modeling↗
DOE OSTI2025

Speciation and diffusive dynamics in hydrated grain boundaries of complex oxide Gd2Ti2O7

Abstract Grain boundaries in polycrystalline materials significantly affect their properties, such as ionic transport, corrosion, and chemical durability. The pyrochlore compound (Gd 2 Ti 2 O 7 ) is employed as a model for complex oxides and is known for its diverse applications, including nuclear waste immobilization. Density functional theory-based first-principles molecular dynamics simulations were performed at different temperatures on the hydrated grain boundary system. The results show extensive transformations within the grain boundaries among hydrous water species (OH − , H 2 O, and H 3 O + ). The temperature dependence of self-diffusion coefficients follows Arrhenius behavior, with an activation energy of 35.9 kJ/mol for hydrogen and 46.3 kJ/mol for oxygen. The lifetime of OH − is about three to four times longer than that of H 2 O at temperatures from 800 to 2100 K, suggesting the greater stability of OH − over H 2 O, a unique characteristic of the grain boundaries. The estimated lifetime of the hydrous species decreases as the temperature increases, with an activation energy of 9.9 kJ/mol for OH − and 13.4 kJ/mol for H 2 O. While Gd 3 + is more mobile than Ti 4+ , both the Gd 3 + and Ti 4+ cations are orders of magnitude less mobile than the water species. The results suggest that water species are much more mobile within grain boundaries than in the bulk crystal and have the potential to penetrate deep into polycrystalline materials through grain boundaries, leading to grain boundary degradation and dissolution. The different mobilities of cations in complex oxides can lead to leaching of certain cations and incongruent dissolution during the chemical weathering of Earth and industrial materials.

B. Ghosh, Dipta↗
DOE OSTI2024

Ligand Controls Excited Charge Carrier Dynamics in Metal-Rich CdSe Quantum Dots: Computational Insights

Small metal-rich semiconducting quantum dots (QDs) are promising for solid-state lighting and single-photon emission due to their highly tunable yet narrow emission line widths. Nonetheless, the anionic ligands commonly employed to passivate these QDs exert a substantial influence on the optoelectronic characteristics, primarily owing to strong electron–phonon interactions. In this work, we combine time-domain density functional theory and nonadiabatic molecular dynamics to investigate the excited charge carrier dynamics of Cd 28 Se 17 X 22 QDs (X = HCOO – , OH – , Cl – , and SH – ) at ambient conditions. These chemically distinct but regularly used molecular groups influence the dynamic surface-ligand interfacial interactions in Cd-rich QDs, drastically modifying their vibrational characteristics. The strong electron–phonon coupling leads to substantial transient variations at the band edge states. The strength of these interactions closely depends on the physicochemical characteristics of passivating ligands. Consequently, the ligands largely control the nonradiative recombination rates and emission characteristics in these QDs. Our simulations indicate that Cd 28 Se 17 (OH) 22 has the fastest nonradiative recombination rate due to the strongest electron–phonon interactions. Conversely, QDs passivated with thiolate or chloride exhibit considerably longer carrier lifetimes and suppressed nonradiative processes. The ligand-controlled electron–phonon interactions further give rise to the broadest and narrowest intrinsic optical line widths for OH and Cl-passivated single QDs, respectively. Finally, obtained computational insights lay the groundwork for designing appropriate passivating ligands on metal-rich QDs, making them suitable for a wide range of applications, from blue LEDs to quantum emitters.

36 MATERIALS SCIENCE↗
DOE OSTI2024

GPAW: An open Python package for electronic structure calculations

We review the GPAW open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent density functional theory (DFT) equations using three different wave-function representations, namely real-space grids, plane waves, and numerical atomic orbitals. The three representations are complementary and mutually independent and can be connected by transformations via the real-space grid. This multi-basis feature renders GPAW highly versatile and unique among similar codes. By virtue of its modular structure, the GPAW code constitutes an ideal platform for the implementation of new features and methodologies. Moreover, it is well integrated with the Atomic Simulation Environment (ASE), providing a flexible and dynamic user interface. In addition to ground-state DFT calculations, GPAW supports many-body GW band structures, optical excitations from the Bethe–Salpeter Equation, variational calculations of excited states in molecules and solids via direct optimization, and real-time propagation of the Kohn–Sham equations within time-dependent DFT. A range of more advanced methods to describe magnetic excitations and non-collinear magnetism in solids are also now available. In addition, GPAW can calculate non-linear optical tensors of solids, charged crystal point defects, and much more. Recently, support for graphics processing unit (GPU) acceleration has been achieved with minor modifications to the GPAW code thanks to the CuPy library. We end the review with an outlook, describing some future plans for GPAW.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

The total neutron cross section of liquid and solid ammonia

Ammonia is a material of interest for future neutron moderators at high-power sources due to its high hydrogen density, low melting point, and resistance to polymerization in an intense radiation field. Its performance in such applications cannot currently be calculated due to the absence of suitable computer models for the interaction of neutrons with ammonia under relevant conditions. In an effort to develop suitable scattering kernels for computer simulations of moderator performance, we have conducted a series of Density Functional Theory and Molecular Dynamics calculations of the molecular-level thermal properties of ammonia at various temperatures within both the solid and liquid phases. In this paper, we compare computer calculations for the energy-dependent total neutron cross section of ammonia, based on these models, to experimental measurements of those cross sections at temperatures of 221 K, 180 K, and 35 K. The experimental data were collected over an energy range from 0.1 meV to 10 eV using time-of-flight techniques at the Low Energy Neutron Source (LENS) facility at Indiana University. This comparison provides a first validation in the development of thermal scattering libraries for Monte Carlo source design simulations based on liquid and solid ammonia. In conclusion, we also provide some insights into where additional development of tools for creating such models may be needed.

Ammonia↗
DOE OSTI2025

Fe‐Triazolate Metal–Organic Frameworks as Water Oxidation Catalysts with Dual Photoanode Functionality

Artificial photosynthesis is an emerging technology that achieves renewable fuels, such as hydrogen, from sunlight. Its realization depends on finding highly active and stable catalysts of water splitting and photoactive materials for light absorption. To be scalable, these should contain only abundant elements. Here, for the first time, Fe-triazolate (Fe(ta) 2 ) and its metal substituted derivatives (Fe-Metal(ta) 2 ) Metal-organic frameworks (MOFs) are characterized as new dual-function materials for photo-absorption and water oxidation catalysis in acidic media. The materials were studied by a range of structural, spectroscopic, and computational density functional theory (DFT) techniques. Fe(ta) 2 and Fe-Mn(ta) 2 were found to be highly active and stable in chemical and photochemical water oxidation, and in addition function as photoanodes, with photo-electrocatalytic currents (∼2.00 x 10 −3 Acm −2 at + 1.4 V vs. Ag/AgCl) at pH = 1. The possibility of a unique catalytic mechanism where O─O bond formation is possible from the coupling of two adjacent Fe IV = O fragments was demonstrated by DFT analysis. Thus, Fe-triazolate MOF has been established as a new, stable, scalable, versatile, and efficient platform for sustainable energy conversion in the realm of artificial photosynthesis.

Artificial photosynthesis↗
DOE OSTI2025

Nature of molybdenum carbide surfaces for catalytic hydrogen dissociation using machine-learned potentials: an ensemble-averaged perspective

Molybdenum carbides with an electronic structure similar to noble metals have gained attention as a promising low-cost catalyst for biomass valorization and the hydrogen evolution reaction. However, our fundamental understanding of the catalyst surface and how different phases of these catalysts behave at varying reaction conditions is limited to ground state density functional theory calculations as ab initio molecular dynamics (AIMD) is computationally prohibitive at relevant length and time scales. Here, in this work, we train a multi-atomic cluster expansion (MACE) machine-learned interatomic potentials (MLIP) to study hydrogen dissociation and dynamics over Mo, δ-MoC, α-Mo 2 C, and β-Mo 2 C surfaces at varying temperatures and hydrogen partial pressures. Our simulations identify unique and different molecular and atomic hydrogen adsorption sites on different surfaces that do not depend on the temperature. At low hydrogen pressures, the surface coverage is monolayer, which transitions to two-layer adsorption at higher pressures. We find that atomic hydrogen diffusion and recombinations are preferred over molybdenum atom hollow sites, while the diffusion over carbon-terminated facets was negligible, signifying particularly strong C–H interactions. In contrast, molecular hydrogen adsorption occurs mostly atop Mo or the bridging sites. At a comparable hydrogen loading, β-Mo 2 C (001) is the most active surface for hydrogen dissociation reaction. This work provides insights into the dynamic nature of the hydrogen dissociation chemistry and the diversity of hydrogen adsorption sites on molybdenum carbides.

08 HYDROGEN↗
DOE OSTI2026

Influence of Markovianity and self-consistency on time-resolved spectral functions of driven quantum systems

We present a systematic comparison of the real-time Dyson expansion (RTDE) with established nonequilibrium Green's function (GF) approaches for simulating driven, interacting quantum systems. Focusing on density matrix dynamics, time-off-diagonal GFs, and time-resolved photoemission spectra, we benchmark RTDE against fully self-consistent Kadanoff-Baym equation (KBE) calculations, the generalized Kadanoff-Baym ansatz, and exact diagonalization for small systems using second-order many-body perturbation theory. Using a driven two-band Hubbard model, we show that mean-field single-particle density matrix trajectories provide a reliable baseline for RTDE across a broad range of interaction strengths and excited-carrier populations. Further, RTDE accurately captures correlation effects in the GFs, including long-lived oscillations and revivals that are strongly suppressed by the overdamping inherent to self-consistent KBE schemes. As a consequence, RTDE resolves rich nonequilibrium spectral structure in time-resolved photoemission, such as interaction- and population-dependent quasiparticle splittings and band gap renormalization, which are largely washed out in self-consistent approaches yet are present in exact solutions. Furthermore, our results demonstrate that RTDE bridges the gap between mean-field propagation and full two-time KBE simulations, retaining favorable linear scaling while capturing essential dynamical correlations relevant for ultrafast spectroscopy.

Electronic structure↗