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DOE OSTI2025

Mobility assessment of the BCC and carbide phases in the C-Nb, C-U and Nb-U systems

Uranium carbides with refractory metal additions are considered for Gen IV nuclear reactors and nuclear thermal propulsion as fuels for their high-temperature and corrosion resistant properties. Understanding kinetic effects that dictate microstructural evolution during fabrication and operating conditions is essential to advance technological development of these fuels. This work presents the development of an atomic mobility database for C-Nb-U systems based off available experimental data supported with ab-initio methods. The mobility assessments and uncertainty quantification (using Markov chain Monte Carlo) were conducted in the Kawin software. Carbon diffusion is considered dominant, as metal diffusion is much slower, with niobium diffusion being even slower and rate limiting than uranium metal. We provide a comprehensive and self-consistent thermo-kinetic database that is validated by diffusion couple simulations through Kawin. In conclusion, this enables prediction of microstructural and phase evolution critical for the development and lifetime assessment of next generation nuclear fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Studying electroweak few-body observables in chiral effective field theory

The use of nuclei to study electroweak probes is becoming increasingly relevant experimentally. The success of dark matter and neutrino experiments strongly depends on the ability to control nuclear effects in order to extract the fundamental parameters associated with external probes. Therefore, reliable theoretical calculations of nuclear structure and reactions, with well-controlled errors, are crucial for the success of experimental efforts. Currently, chiral effective field theory ($\chi$EFT) coupled with {\it ab-initio} methods represents one of the best approaches that fulfills these requirements. To use this approach as a tool for studying fundamental physics, it is essential to validate it against experimental data for which the calculations are well under control, such as the elastic scattering of electrons on nuclei. In this proceeding, I will present recent developments in the fitting of electromagnetic currents derived using $\chi$EFT and the calculation of electromagnetic form factors of light nuclei. The results of these calculations demonstrate the strength of the theory in describing the interaction of nuclei with electromagnetic probes over a broad range of momentum transfers and highlight the robustness of $\chi$EFT for analyzing future experimental data aimed at extracting fundamental parameters.

Gnech, Alex [Old Dominion Univ., Norfolk, VA (Unit↗

DOE OSTI2026

Computing neutrino cross sections from Euclidian responses

Energy integrated neutrino cross sections are integrals of nuclear responses weighted with kinematic prefactors. We decompose the prefactors into a limited set of functions of energy transfer and show the relevant integrals are the moments of the responses, and integrals weighted with $1/(a+ω)^n$ with $n\leq 2$. These can be directly obtained from the Euclidean response, avoiding the need for inversion of the Laplace transform. As a proof of concept we study the procedure with toy-model responses for the quasielastic peak. We show that the different contributions can be straightforwardly organized in terms of relative importance, and how flux-averaged cross sections can be obtained. Using a realistic model for the response and numerical uncertainty we show that it is feasible to obtain the required integrals from the Euclidean response, with large uncertainties only for the third moment. Due to kinematic restrictions, the integrals contain contributions from the unphysical region for neutrino scattering, coming from high-momentum nucleons. We show that (in the absence of two-body currents) robust corrections for this contamination are obtained from the single-nucleon momentum distribution. These results present an opportunity to compute certain neutrino cross sections with ab-initio methods with controlled uncertainties.

Nikolakopoulos, A. [Washington U., Seattle]↗

DOE OSTI2026

Computing neutrino cross sections from Euclidian responses

Nikolakopoulos, A. [Washington U., Seattle]↗

DOE OSTI2024

A modular and extensible CHARMM-compatible model for all-atom simulation of polypeptoids

Peptoids (N-substituted glycines) are a class of sequence-defined synthetic peptidomimetic polymers with applications including drug delivery, catalysis, and biomimicry. Classical molecular simulations have been used to predict and understand the conformational dynamics of single chains and their self-assembly into morphologies including sheets, tubes, spheres, and fibrils. The CGenFF-NTOID model based on the CHARMM General Force Field has demonstrated success in accurate all-atom molecular modeling of peptoid structure and thermodynamics. Extension of this force field to new peptoid side chains has historically required reparameterization of side chain bonded interactions against ab initio data. This fitting protocol improves the accuracy of the force field but is also burdensome and precludes modular extensibility of the model to arbitrary peptoid sequences. In this work, we develop and demonstrate a Modular Side Chain CGenFF-NTOID (MoSiC-CGenFF-NTOID) as an extension of CGenFF-NTOID employing a modular decomposition of the peptoid backbone and side chain parameterizations, wherein arbitrary side chains within the large family of substituted methyl groups (i.e., –CH 3 , –CH 2 R, –CHRR', and –CRR'R") are directly ported from CGenFF. We validate this approach against ab initio calculations and experimental data to develop a MoSiC-CGenFF-NTOID model for all 20 natural amino acid side chains along with 13 commonly used synthetic side chains and present an extensible paradigm to efficiently determine whether a novel side chain can be directly incorporated into the model or whether refitting of the CGenFF parameters is warranted. We make the model freely available to the community along with a tool to perform automated initial structure generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Model-free Rayleigh weight from x-ray Thomson scattering measurements

X-ray Thomson scattering (XRTS) has emerged as a powerful tool for the diagnostics of matter under extreme conditions. In principle, it gives one access to important system parameters such as the temperature, density, and ionization state, but the interpretation of the measured XRTS intensity usually relies on theoretical models and approximations. In this context, a key property is given by the Rayleigh weight that describes the electronic localization around the ions. Here, we show that it is possible to extract the Rayleigh weight directly from the experimental data without the need for any model calculations or simulations. As a practical application, we consider an experimental measurement of strongly compressed Be at the National Ignition Facility [Döppner et al., Nature 618, 270–275 (2023)]. We demonstrate that experimental results for the Rayleigh weight open up new avenues for the interpretation of XRTS experiments by matching the measurement with ab initio simulations such as density functional theory or path integral Monte Carlo. Interestingly, this new procedure leads to significantly lower density compared to previously used chemical models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Excited electronic states of Na 2 and K 2 : The potential for long-lived “reservoir” states leading to collision induced population inversions

Potential energy curves (PECs) for the spin-free (ΛS) and spin–orbit (Ω) states associated with the four lowest-lying dissociation channels of Na 2 and K 2 were calculated at the SA-CASSCF/SO-CASPT2/aug-cc-pwCVQZ-DK level. The PECs of Na 2 were consistent with the experimental data and with the FS-CCSD (2,0) calculations, reproducing the double-well and the “shelf” character for some of the potentials of the excited states. For K 2 , the PECs behaved in a similar way and the spectroscopic parameters for the ground and the excited states are in good agreement with the available experimental values. The dissociation energy of K 2 was predicted to be D e = 4454 cm −1 , within an agreement of 5 cm −1 with the experiments. For Na 2 , D e = 5789 cm −1 compared to the experimental value of 6022 cm −1 . The inclusion of spin–orbit coupling effects resulted in avoided crossings, which affect the PECs. Spin–orbit changes the predicted curves for some excited Ω states arising from ΛS states that overlap each other, affecting their associated vibrational frequencies and bond distances. Here, the current studies of the low-lying states in K 2 reveal a similar structure to those of Na 2 , which suggests the accessibility of long-lived energy storing reservoir states and possible population inversions in K 2 following prior experimental work on the reaction of halogen atoms with Na 3 to produce excited states of Na 2 .

Ab-initio methods↗

DOE OSTI2024

Machine learning the electric field response of condensed phase systems using perturbed neural network potentials

Abstract The interaction of condensed phase systems with external electric fields is of major importance in a myriad of processes in nature and technology, ranging from the field-directed motion of cells (galvanotaxis), to geochemistry and the formation of ice phases on planets, to field-directed chemical catalysis and energy storage and conversion systems including supercapacitors, batteries and solar cells. Molecular simulation in the presence of electric fields would give important atomistic insight into these processes but applications of the most accurate methods such as ab-initio molecular dynamics (AIMD) are limited in scope by their computational expense. Here we introduce Perturbed Neural Network Potential Molecular Dynamics (PNNP MD) to push back the accessible time and length scales of such simulations. We demonstrate that important dielectric properties of liquid water including the field-induced relaxation dynamics, the dielectric constant and the field-dependent IR spectrum can be machine learned up to surprisingly high field strengths of about 0.2 V Å −1 without loss in accuracy when compared to ab-initio molecular dynamics. This is remarkable because, in contrast to most previous approaches, the two neural networks on which PNNP MD is based are exclusively trained on molecular configurations sampled from zero-field MD simulations, demonstrating that the networks not only interpolate but also reliably extrapolate the field response. PNNP MD is based on rigorous theory yet it is simple, general, modular, and systematically improvable allowing us to obtain atomistic insight into the interaction of a wide range of condensed phase systems with external electric fields.

Science & Technology - Other Topics↗

DOE OSTI2025

Experimental and modeling study of the autoignition behavior of a saturated heterocycle: Pyrrolidine

Experiments are conducted in both rapid compression machine (RCM) and shock tube (ST) to better quantify autoignition behavior (e.g., ignition delay, heat release) and understand heteroatomic effects in heterocyclic compounds, which are important reference components for the combustion of biomass-derived liquid fuels. These tests focus on the nitrogen-containing, five-membered saturated ring, pyrrolidine, at diluted conditions covering pressures of 20 and 50 bar, temperatures of 720–1450 K and a range of stoichiometries (ϕ = 0.5–2). A chemical kinetic model is developed and coupled to an existing combustion kinetics framework describing key nitrogen containing intermediates (e.g. pyrrole, ammonia and NOx). H-abstraction reactions by OH, H, CH 3 and HO 2 , are determined using ab-initio transition state theory methods, while analogies to cyclopentane are adopted for many other reactions, such as ring-opening. Here, the autoignition measurements reveal the lack of negative temperature coefficient (NTC) behavior and low-temperature chemistry for pyrrolidine, as opposed to its saturated hydrocarbon analogue, cyclopentane. Interestingly, at the lowest temperatures (T < 750 K), the reactivity of cyclopentane is greater than pyrrolidine, while at higher temperatures, pyrrolidine becomes more reactive. Agreement between the experimental measurements and the model is good, and it is found that H-abstraction reactions by HO 2 and ensuing chemistry play key roles in controlling the reactivity of this cyclic amine. Most of the fluxes, i.e., >70 %, are predicted to move through 1- or 2-pyrroline (C 4 H 7 N) and then the cyclic C 4 H 6 N radical, at both lower and higher temperatures, to form either CH 2 CHCHCHNH via ring-opening or pyrrole via β-scission. It appears that the ring opens more easily at lower temperature whereas the C–H β-scission dominates at higher temperature and lower pressure, such that the reaction of the fuel radical intermediate carrying an unpaired electron on the nitrogen atom with HO 2 is the next most notable in promoting oxidation. When comparing pyrrolidine and cyclopentane, which exhibits distinct pathways in different temperature regimes, the pyrrolidine pathways and sensitivity analysis align more closely to the high temperature case of cyclopentane where the important role of HO 2 radicals is seen to provide chain branching through HO 2 reaction with the fuel, accompanied by H 2 O 2 formation and decomposition to OH. The formation of 5-membered diene rings and ring opening reactions are also found to be highly relevant. Of particular note, it is found that there is little influence of small molecule nitrogen-chemistry, e.g., NH 2 , HCN, NO/NO 2 on the reactivity of the pyrrolidine mixtures investigated here where no recirculated combustion gases are included.

Autoignition↗

DOE OSTI2026

Planar Systems for Quantum Information

This project aims to develop two‐dimensional (2D) moiré materials as a quantum simulator to implement model Hamiltonians and their phase diagrams. Progress in quantum information science (QIS) requires the development of advanced quantum materials systems. The rich family of layered van der Waals materials and their heterostructures present opportunities to create previously unrealized types of applications for QIS. Specifically, when two layers of van der Waals materials are overlaid with a small twist angle or/and lattice mismatch, a moiré superlattice with a period of about ten nanometers is formed. This provides a periodic trapping potential for electrons. Electrons can tunnel between the traps and repel each other by their mutual Coulomb interactions. The platform of 2D moiré materials provides many attractive features, including tunability of length and energy scales, charge density, and even lattice symmetry. It presents new possibilities for realizing quantum simulation of the many-body physics in a solid-state platform. This integrated team of six investigators seeks to develop relevant theoretical treatments to link ab-initio studies of 2D moiré materials to model Hamiltonians and to evaluate correlated phases predicted by these model Hamiltonians in the relevant regimes. On the experimental side, the team aims to develop methods to realize a homogeneous and highly controlled potential landscape for the electrons and to initiate, protect, and measure their quantum many-body states.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Machine Learning an Ab-Initio Based Bond-Order Potential for Bismuthene

Bismuthene is a heavy 2D material whose strong spin–orbit coupling and recently observed single-element ferroelectricity have intensified interest in its structural, vibrational, and transport properties. Accurate modeling of these behaviors requires a short-range interatomic potential that can reproduce the underlying bonding physics at a fraction of the computational cost of first-principles methods. However, such a potential is currently unavailable. Here, in this work, we construct a Tersoff bond-order potential for β-bismuthene using a reinforcement-learning framework that integrates a continuous Monte Carlo Tree Search with a simplex-based local optimizer. The optimized parameter sets reproduce first-principles lattice constants, cohesive energy, the equation of state, elastic constants, and phonon dispersion. We validate the models by performing thermal-conductivity calculations and uniaxial fracture simulations our findings confirm the reliability of the resulting models across multiple thermomechanical regimes. Comparison of the three best solutions reveals how differences in pairwise interactions, angular terms, and bond-order behavior govern phonon features and mechanical responses. We demonstrate an interpretable and computationally efficient potential for bismuthene and demonstrate a general reinforcement-learning strategy for developing bond-order models in emerging 2D materials.

deformation↗

DOE OSTI2025

Development and transferability of neural-network models for plasma-surface interactions

Plasma-surface interactions are increasingly critical to modern technologies; yet, accurate molecular dynamics simulations remain limited by the capabilities of interatomic potentials. Deep Potentials (DPs) promise to revolutionize the field by providing a systematic method for producing accurate interatomic potentials. The primary challenge of DP development is selecting a dataset, which efficiently spans the set of atomic environments one expects to encounter in the subsequent molecular dynamics simulations. The computational cost of density functional theory calculations, which are the typical basis for DP development, makes it impossible to directly verify the quality of a given DP. To address this challenge, we explore the development of a deep-learned interatomic potential, “DeepREBO,” trained to reproduce the behavior of the REBO2 empirical potential, enabling direct validation of training methodology and transferability. Using an active learning framework, we begin with a minimal dataset and iteratively expand it to train a Deep Potential-Smooth Edition model that faithfully reproduces REBO2 results for 25 eV hydrogen bombardment of diamond (001), a particularly challenging case. We show that small, carefully curated datasets can outperform large, unguided ones, with effective models requiring fewer than 15 000 snapshots. Subsequent transferability tests demonstrate that while DeepREBO generalizes well to diamond (111) surfaces, performance degrades for amorphous carbon or higher-energy impacts, highlighting the need for use-case-specific training data. We also evaluate methods to improve short-range repulsion. This study outlines best practices for training robust deep potentials and underscores the importance of dataset design for predictive plasma simulations.

Ab-initio molecular dynamics↗

DOE OSTI2025

How the choice of exchange–correlation functional affects DFT-based simulations of the hydrated electron

Hydrated electrons are anionic species that are formed when an excess electron is introduced into liquid water. Building an understanding of how hydrated electrons behave in solution has been a long-standing effort of simulation methods, of which density functional theory (DFT) has come to the fore in recent years. The ability of DFT to model the reactive chemistry of hydrated electrons is an attractive advantage over semi-classical methodologies; however, relatively few density functional approximations (DFAs) have been used for the hydrated electron simulations presented in the literature. Here, we simulate hydrated electron systems using a series of exchange–correlation (XC) functionals spanning Jacob’s ladder. We calculate a variety of experimental and other observables of the hydrated electron and compare the XC functional dependence for each quantity. We find that the formation of a stable localized hydrated electron is not necessarily limited to hybrid XC functionals and that some hybrid functionals produce delocalized hydrated electrons or electrons that react with the surrounding water at an unphysically fast rate. Here, we further characterize how different DFAs impact the solvent structure and predicted spectroscopy of the hydrated electron, considering several methods for calculating the hydrated electron’s absorption spectrum for the best comparison between structures generated using different density functionals. None of the dozen or so DFAs that we investigated are able to correctly predict the hydrated electron’s spectroscopy, vertical detachment energy, or molar solvation volume.

Ab-initio molecular dynamics↗

DOE OSTI2026

New correlated numerical methods for attosecond molecular single and double ionization

This project resulted in the development of ASTRA, a new molecular ionization code capable of describing single and double ionization processes in polyatomic molecules with correlated electrons and time-dependent fields. Key achievements include: (i) the development of the PRISM hybrid-integral library enabling core-ionization and high-angular-momentum convergence; (ii) implementation of time-dependent Schrödinger equation solvers for pump–probe spectroscopies; (iii) validation against experimental and theoretical benchmarks for atoms and molecules; and (iv) extension to two-photon double ionization using the finite-pulse virtual-sequential model. These developments establish ASTRA as a versatile platform for attosecond molecular dynamics.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2025

Static Subspace Approximation for Random Phase Approximation Correlation Energies: Applications to Materials for Catalysis and Electrochemistry

Modeling complex materials using high-fidelity, ab initio methods at low cost is a fundamental goal for quantum chemical software packages. The GW approximation and random phase approximation (RPA) provide a unified description of both electronic structure and total energies using the same physics in a many-body perturbative approach that can be more accurate than generalized-gradient density functional theory (DFT) methods. However, GW/RPA implementations have historically been limited to either specific materials classes or application toward small chemical systems. Here, the static subspace approximation allows for reduced cost full-frequency GW/RPA calculations and has previously been benchmarked thoroughly for GW calculations. Here, we describe our approach to including partial occupations of electronic orbitals in full-frequency GW and RPA calculations for the study of electrocatalysts. We benchmarked RPA total energy calculations using the subspace approximation across a diverse test suite of materials for a variety of computational parameters. The benchmarking quantifies the impact of different extrapolation procedures for representing the static polarizability at infinite screened cutoff, and shows that using screened cutoffs above 20-25 Ryd result in diminishing accuracy returns for predicting RPA total energies. Additionally, for moderately sized electrocatalytic models, 2-3 times fewer computational resources are used to compute RPA total energies by representing the static polarizability with 20-30% of the static subspace basis, with an error of approximately 0.01 eV or better in RPA adsorption energy calculations. Finally, we show that for these electrochemical models RPA can shift DFT adsorption energy shifts by up to 0.5 eV and that GW can frequently shift DFT eigenvalues of surface and adsorbate states by approximately 0.5-1 eV.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Charge order driven multiferroic behavior in Sr 4 Fe 6 O 12 : An ab-initio study

Here, in this paper, we report the structural, electronic, and ferroelectric properties of the layered mixed-valent transition-metal compound Sr 4 ⁢ Fe 6 ⁢O 12 (SFO). We demonstrate how SFO undergoes a phase transition from a high-temperature (𝑇) centrosymmetric tetragonal phase (𝑃⁢4 2 /𝑚⁢𝑛⁢𝑚) to a low-𝑇 polar orthorhombic phase (𝑃⁢𝑚⁢𝑛⁢2 1 ). The transition is primarily driven by charge ordering at tetrahedral Fe-layer creating Fe 3+ and Fe 2+ cations between two edge-sharing tetrahedra. This charge ordering induces electronic polarization, which is remarkably larger (3.5 times) in magnitude than ionic polarization and oppositely directed, giving a net polarization of 0.05 C/m 2 which is comparable to the state-of-the-art rare-earth nickelets and manganite perovskites. The direction of structural distortion, governed by the polar mode irrep $Γ^−_5$, depends sensitively on the type of magnetic ordering in the Fe-octahedral layer. Consequently, both the ionic and electronic polarization directions are influenced by magnetic ordering, suggesting the potential for multiferroic behavior with strong magnetoelectric coupling in this material.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗