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DOE OSTI2025

Machine Learning for Predicting Multipactor Susceptibility in Planar RF Structures

Multipactor discharge is a persistent challenge in high-power microwave (HPM) and accelerator systems, where secondary electron avalanches can cause heating, vacuum degradation, and failure. This work presents the first supervised machine learning (ML) framework for multipactor prediction, trained on high-fidelity 3D Particle-in-Cell (PIC) simulation data in planar geometries. The model maps operational, geometric, and material-dependent secondary electron yield (SEY) parameters to the time-averaged electron growth rate, enabling rapid reconstruction of susceptibility charts. Among the models evaluated, tree-based ensemble methods such as Random Forest and Extra Trees demonstrate superior generalization to unseen materials compared to neural networks such as multilayer perceptron (MLP). Performance metrics, including Intersection over Union (IoU), Structural Similarity Index Measure (SSIM), and Pearson correlation, show close agreement with simulation benchmarks. Principal Component Analysis attributes generalization limits to material feature-space disjointedness.

43 PARTICLE ACCELERATORS↗

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

A First-Principles Study of the Structural and Thermo-Mechanical Properties of Tungsten-Based Plasma-Facing Materials

Tungsten (W) and tungsten alloys are being considered as leading candidates for structural and functional materials in future fusion energy devices. The most attractive properties of tungsten for the design of magnetic and inertial fusion energy reactors are its high melting point, high thermal conductivity, low sputtering yield, and low long-term disposal radioactive footprint. Despite these relevant features, there is a lack of understanding of how the structural and mechanical properties of W-based alloys are affected by the temperature in fusion power plants. In this work, we present a study on the thermo-mechanical properties of five W-based plasma-facing materials. First-principles density functional theory (DFT) calculations are combined with the quasi-harmonic approximation (QHA) theory to investigate the electronic, structural, mechanical, and thermal properties of these W-based alloys as a function of temperature. The coefficient of thermal expansion, temperature-dependent elastic constants, and several elastic parameters, including bulk and Young’s modulus, are calculated. Our work advances the understanding of the structural and thermo-mechanical behavior of W-based materials, thus providing insights into the design and selection of candidate plasma-facing materials in fusion energy devices.

42 ENGINEERING↗

DOE OSTI2026

Graphitization of banana peel – synergistic effect of Ca and other elements of the biomass on carbon structure transformation

Recently, growing interest has been observed in using calcium as an effective catalyst for graphitizing disordered carbon materials derived from biomass and bioprecursors, such as cellulose and lignin, at relatively low tem peratures (<2000 °C). Herein, it is demonstrated that in the presence of elements such as calcium, silicon, sulfur, and potassium, which are abundant in banana peel composed of cellulose and lignin base, graphitization occurs much more effectively. The addition of external calcium source, in the form of calcium carbonate, to the banana peel-derived carbon and heat-treatment of the mixture under protective atmosphere up to 1750 °C results in a significant increase in the degree of the graphitization order and local formation of graphite crystals, whereas the same preparation and heat-treatment procedure applied to carbon material derived from pristine cellulose does not lead to such effective graphitization. It is indicated that the graphitization of banana peel carbon occurs due to the synergistic effect of the external Ca-based catalyst and the internal elements present in the raw biomass, supporting the transformation of the disordered graphene-like layers into graphitic structures. These findings are important for the future production of green graphite from biomass

09 BIOMASS FUELS↗

DOE OSTI2025

Engineering 2D Square Lattice Hubbard Models in 90° Twisted GeX/SnX (X =S, Se) Moiré Superlattices

Because of the large-period superlattices emerging in moiré two-dimensional (2D) materials, electronic states in such systems exhibit low energy flat bands that can be used to simulate strongly correlated physics in a highly tunable setup. While many investigations have thus far focused on moiré flat bands and emergent correlated electron physics in triangular, honeycomb, and quasi-one-dimensional lattices, tunable moiré realizations of square lattices subject to strong correlations remain elusive. Here, in this work, we propose a feasible scheme to construct moiré square lattice systems by twisting two or more layers of 2D materials in a rectangular lattice by 90°. We demonstrate the concept with twisted GeX/SnX (X =S, Se) moiré superlattices and calculate their electronic structures from first principles. We show that the lowest conduction flat band in these systems can be described by a square lattice Hubbard model with parameters which can be controlled by varying the choice of host materials, number of layers, and external electric fields. In particular, twisted double bilayer GeSe realizes a square lattice Hubbard model with strong frustration due to the next-nearest-neighbor hopping that could host unconventional superconductivity, in close analogy to the Hubbard model for copper-oxygen planes of cuprate high-temperature superconductors. The presented scheme uses 90° twisted 2D materials with rectangular unit cells as a promising platform for realizing the physical phenomena of square lattice Hubbard models, establishing a new route for studying its rich phase diagram of magnetism, charge order, and unconventional superconductivity in a highly tunable setting.

2-dimensional systems↗

DOE OSTI2026

Effects of Composition and Oxidation States on the Structures of Chromium-Containing Sodium Silicate Glasses: Molecular Dynamics Simulations using Machine Learning Interatomic Potentials

Chromium represents a significant challenge for the vitrification of high-level nuclear waste into silicate and borosilicate glasses due to its low solubility and variable oxidation states, which can limit the waste loading due to promotion of crystallization or phase separation during processing. In this study, we modeled chromium containing silicate glasses using molecular dynamics simulations with three machine learning interatomic potentials (MLIPs), MACE, CHGNet, and PFP were employed, to gain insights on glass composition and oxidation states on the structures of these glasses. One of the goals is to evaluate their ability of these MLIPs to accurately represent the general structure of silicate glasses and chromium local environments as a function of chromium oxidation states. Density Functional Theory (DFT) based calculations and experimental data such as neutron structure factors were used to validate the structural models. It was found that the foundation models of all three MLIPs are able to reproduce general structural features of the sodium silicate glass structure consistent with experimental and DFT data, but only CHGNet and PFP can accurately capture the oxidation states and local environment of chromium: tetrahedral for Cr6+ and octahedral for Cr3+. Furthermore, we studied the effect of varying Cr3+/ Cr6+ (Cr3+/Crtotal) ratio and total chromium content using PFP. Our results show that Cr6+ enhances network polymerization by reducing non-bridging oxygens through Na? charge compensation required due to the formation of chromate (CrO42-) species, while Cr³? acts as a network modifier that disrupts connectivity. System size effects on the structural characteristics and chromium environments were also tested using the PFP potential. This work highlights the importance of careful validation on the precision, transferability, and potential of MLIPs for modeling glasses containing transition metal elements that can exist in multiple oxidation states. It is also encouraging to see the foundational models are all three MLFFs are able to reproduce the basic sodium silicate glass structures, while suggesting additional training or refining is needed to improve the description of more complex systems containing transition metals.

Puga, Christina L.↗

DOE OSTI2024

The occurrence rate of galaxies with polar structures may be significantly underestimated

Polar-ring galaxies are photometrically and kinematically decoupled systems that are highly inclined to the major axis of the host. These galaxies have been explored since the 1970s, but the rarity of these systems has made such systematic studies difficult. However, over 250 good candidates have been identified. In this work, we examine a sample of over 18 000 galaxies from the Sloan Digital Sky Survey (SDSS) Stripe 82 for the presence of galaxies with polar structures. Using deep SDSS Stripe 82, DESI Legacy Imaging Surveys, and Hyper Suprime-Cam Subaru Strategic Program, we selected 53 good candidate galaxies with photometrically decoupled polar rings, 9 galaxies with polar halos, 6 galaxies with polar bulges, and 34 possibly forming polar-ring galaxies, versus 13 polar-ring candidates previously selected in Stripe 82. Our results suggest that the occurrence rate of galaxies with polar structures may be significantly underestimated, as revealed by the deep observations, and may amount to 1–3% of non-dwarf galaxies.

Astronomy & Astrophysics↗

DOE OSTI2025

Influence of functional additives, fillers, and pigments on thermal and catalytic pyrolysis of polyethylene for waste plastic upcycling

Pyrolysis offers a relatively green and economical method to convert waste plastics into valuable chemicals and fuels without the need for harmful solvents, toxic chemicals, or costly high-pressure reactors. Despite its popularity among chemical upcycling technologies, industrial adoption suffers from feedstock heterogeneity, low-quality products, and catalyst deactivation. Most plastics in our daily lives are formulated with functional additives, fillers, and colorants. These additives remaining in end-of-life waste streams increase feedstock heterogeneity, creating a challenging issue in recycling plastics. Still, the potential impacts of additives on the chemical upcycling of plastics have been poorly understood. In this study, polyethylene compounded with a range of widely used additives (antioxidants, stabilizers, pigments, fillers, slip agents, and flame retardants) was subjected to both thermal pyrolysis and catalytic pyrolysis in different catalyst-to-feedstock contact modes. It showed that many inorganic additives, such as talc, kaolin, CaCO 3 , TiO 2 , carbon black, and zinc stearate, facilitated polymer decomposition during pyrolysis, increasing light hydrocarbons while also promoting aromatic and carbon residue formation. Conversely, antioxidants and stabilizers inhibited depolymerization, favoring heavier hydrocarbons. During catalytic pyrolysis with HZSM-5 zeolite, additives strongly enhanced aromatic and catalytic coke formation, especially when there was direct contact between plastics and catalysts. Although certain additives seem beneficial in the short term by promoting polymer cracking and improving the selectivity of aromatics, the transport of the additives and their degradation products and increased carbon coking can contaminate products, deactivate or modify catalysts, and foul reactors. These findings address a critical knowledge gap in effectively converting waste plastics via a greener route.

42 ENGINEERING↗

DOE OSTI2023

Polycarbonate‐Based Solid‐Polymer Electrolytes for Solid‐State Sodium Batteries

Solid-polymer electrolytes comprised of polypropylene carbonate (PPC) and varied sodium bis(fluorosulfonyl)imide (NaFSI) salt concentrations are investigated for implementation as a conductive solid polymer electrolyte into solid-state cathode composites utilizing a sodium-layered oxide active material. The ionic conductivity generally increases with NaFSI salt content, reaching ≈1 mS cm −1 at 80 °C at the highest salt concentration (PPC:NaFSI = 0.5:1). Through an all-in-one slurry casting method, Na 2/3 Ni 1/3 Mn 2/3 O 2 cathode composites are fabricated in which the dispersed PPC electrolyte acts as the primary binder. Enabled by a bilayer polymer electrolyte system, cycling performance with the PPC cathode electrolyte is optimized with respect to salt concentration and anode material. The best cyclability is achieved with a moderate salt concentration electrolyte (PPC:NaFSI = 5:1), showcasing an initial capacity of 83 mA h g −1 with a remarkable 80% capacity retention after 150 cycles at C/5 rate and 60 °C. The superior performance of the lower salt concentration electrolyte is attributed to better electrochemical stability, as confirmed by linear sweep voltammetry and online electrochemical mass spectrometry measurements. In conclusion, these results underscore the potential of carbonate-based polymer electrolytes and the importance of balancing electrolyte conductivity and stability in cell design.

25 ENERGY STORAGE↗

DOE OSTI2026

The impact of chemistry on anion migration in bixbyite-structured lanthanide oxides

This manuscript describes atomistic calculations of oxygen vacancy and interstitial migration in bixbyite structured lanthanide oxides. We examine two types of compounds, one in which only one type of lanthanide cation is present and a second class in which two lanthanides are present in a 3:1 ratio as dictated by the symmetry of the bixbyite crystal structure. Using temperature accelerated dynamics and the nudged elastic band method, we quantify the role of chemistry on the energy barriers for the most important pathways for both vacancy and interstitial migration. We then analyze the impact of these variations on the overall diffusivity of each defect, quantifying the contribution of each pathway using the theory of kinosons. We find that vacancy mobility can vary by as much as three orders of magnitude through changes in chemistry at 500 K. Changes in interstitial mobility are more modest but can still vary by an order of magnitude. This points to the ability to tune the mass transport characteristics of these compounds through appropriate choices in chemistry. We have also included supplementary information containing the atomic structures of the relevant pathways.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Comprehensive structural characterization of charged polymers involved in moisture-driven direct air capture

This study provides a comprehensive structural characterization of commercially available alkaline anion-exchange polymers (Fumasep FAA-3 and IRA 900) used in moisture-driven direct air capture (DAC) of carbon dioxide. Using X-ray diffraction, SAXS/WAXS, atomic force microscopy, FIB-SEM, and transmission electron microscopy, the authors identify nanoscale clustering, porosity, swelling behavior, and humidity-dependent structural changes that influence CO₂ adsorption and release. These findings establish structure–function relationships critical for designing more durable and energy-efficient DAC polymer materials.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Correlated Ion Transport Governed by Dynamic Local Structure in High Concentration and Localized High Concentration Electrolytes

Understanding the dynamics of cluster formation and network percolation provides the mechanistic link between microscopic solvation structure and transport in concentrated electrolytes, including localized high-concentration electrolytes (LHCEs). Although recent studies have shown LHCEs to form micelle-like aggregates at specific compositions, a quantitative understanding of how solvation structures and transport properties depend on salt–solvent–diluent ratios remains limited. Here, we integrate molecular dynamics with Onsager transport analyses to chart the evolution of solvation microstructure and associated ionic transport in LiFSI/DMC/TTE, achieving good agreement with experimental conductivities across composition. We show that micelle formation arises from a dynamic instability of the cation–anion network, and that network percolation is the primary determinant of conductivity. Two compositional thresholds emerge: A critical network concentration (CNC) and a critical micelle concentration (CMC) that delineate transitions from extended percolating networks to micelle-like clusters and then to fragments. These structural transitions rationalize the nonintuitive conductivity decrease at intermediate dilution despite monotonically decreasing viscosity and provide composition-level design rules for LHCEs.

Mohanakrishnan, Rohith Srinivaas [University of Ca↗

DOE OSTI2025

Development of a high fidelity CFD model for solvent evaporation and transport in porous structure during battery electrode drying

An efficient battery manufacturing process is the key to the mass production of Electric Vehicles (EV), in which drying is one of the most energy-intensive steps significantly influencing the battery cell performance. An accurate 3D CFD model for drying is essential for predicting the drying mechanism and optimizing its parameters. By optimizing the drying process, it is possible to reduce energy consumption and cost during battery manufacturing, minimize binder loading and maximize active material loading to achieve superior electrochemical performances and facilitate wider and faster public adoption of EV. This project aims to optimize the drying process during electrode manufacturing by leveraging high-fidelity, porous electrode simulations for solvent evaporation. By optimizing this process, we seek to reduce energy consumption during battery manufacturing, while minimizing binder loading and maximizing active material loading, with the overall goal of enhancing electrical vehicle performance.

Horner, Jeffrey Scott [Sandia National Laboratorie↗

DOE OSTI2026

Insulating ground state and 2−𝑘 magnetic structure of candidate Weyl hydrogen-atom K2⁢Mn3⁢(AsO4)3

The ideal Weyl "hydrogen-atom" semimetal exhibits only a single pair of Weyl nodes and no other trivial states at the Fermi energy. Such a material would be a panacea in the study of Weyl quasi-particles, allowing direct unambiguous observation of their topological properties. The alluaudite-like K2⁢Mn3⁢(AsO4)3 compound was recently proposed as such a material. Here, we use comprehensive experimental work and first-principle calculations to assess this prediction. We find K2⁢Mn3⁢(AsO4)3 crystallizes in the 𝐶⁢2/𝑐 symmetry with a quasi-one-dimensional Mn sublattice, growing as small needle-like crystals. Bulk property measurements reveal magnetic transitions at ≈8 and ≈4 K, which neutron scattering experiments show correspond to two distinct magnetic orders, first a partially ordered ferrimagnetic 𝐤𝟏=(0,0,0) structure at 8 K and a second transition of 𝐤𝟐=(1,0,0) at 4 K to a fully ordered state. Below the second transition, both ordering vectors are necessary to describe the complex magnetic structure with modulated spin magnitudes. Both of the best-fit magnetic structures in this work are found to break the symmetry necessary for the generation of Weyl nodes, though one of the magnetic structures allowed by 𝐤𝟏 does preserve this symmetry. However, the crystals are optically transparent and ellipsometry measurements reveal a large band gap, undermining expectations of semimetallic behavior. Density functional theory calculations predict an insulating antiferromagnetic ground state, in contrast to previous reports, and suggest potential frustration on the magnetic sublattice. Given the wide tunability of the alluaudite structure, we consider ways to push the system closer to a semimetallic state.

Taddei, Keith M [Argonne National Laboratory]↗

DOE OSTI2026

Transition from Vehicular to Structural Ionic Transport in Electrified Alkali Aqueous Solutions

A molecular understanding of the solvation and dynamics of ions under static electric fields is crucial for modelling a wide range of natural and technological processes. Yet, traditional simulation methods suffer from a trade-off that has to be made between accuracy and statistical convergence. To bridge this gap, herein we extend our recently introduced Perturbed Neural Network Potential Molecular Dynamics (PNNP MD) approach to investigate the solvation structures and ionic transport mechanisms of electrified alkali cationic solutions. We obtain ionic conductivities for Li+, Na+ and Cs+ from the field dependence of the ionic current density in good agreement with experiment. Surprisingly, the migration mechanism is found to be strikingly different for the three ions despite their similar ionic conductivities. While Li+ conducts predominantly through vehicular migration of a stable 4-fold coordinated ion at all field strengths, Cs+ conducts strictly through a structural diffusion mechanism, where 9-12 transient first shell water coordination bonds are broken and renewed. Notably, aqueous Na+ emerges as a “Goldilocks” ion: its ion-water interactions are strong enough to maintain distinct 5-6 fold coordination shells at zero field (unlike Cs+) yet labile enough to be strongly perturbed by electric fields (unlike Li+). As a consequence, we observe an electric field-induced transition from vehicular to structural ionic transport for Na+ that is accompanied by a marked increase in the ionic current density. Our results imply that the conductance mechanism of ions with moderate ion-solvent interactions can be effectively tuned by external electric fields.

Joll, Kit↗

DOE OSTI2026

Effect of Oxidizing Impurities on the Corrosion Behavior of Structural Alloys Exposed to MgCl 2 Molten Salt Vapor

The corrosion behavior of structural alloys SS304 and IN617 when exposed to vapors of MgCl 2 molten salt at 764 °C for 100 h in an argon atmosphere was investigated as a function of the level of oxidizing impurities (e.g., NaOH) present in the salt. Increasing the concentration of oxidizing impurities in the salt caused an increase in corrosion in both structural alloys, as measured by Cr depletion layers. A poorly adhered oxide scale layer containing Mg, Al, and Cr was observed on the surface of the metals, and local attack was observed as well. The Ni-based IN617 showed lower Cr depletion and less scale formation than the Fe-based SS304. These results demonstrate that oxidizing impurities in the molten salt will impact the vapor phase corrosion for structural members exposed to the molten salt headspace. This finding is highly relevant for understanding the effects of the vapor phase in molten salt applications, including molten salt thermal energy storage, molten salt nuclear reactors, and molten salt electrochemistry.

25 ENERGY STORAGE↗

DOE OSTI2025

Entanglement Structure of Non-Gaussian States and How to Measure It

Rapidly growing capabilities of quantum simulators to probe quantum many-body phenomena require new methods to characterize increasingly complex states. Here, we present a protocol that constrains quantum states using experimentally measured correlation functions. This method enables measurement of a quantum state’s entanglement structure, opening a new route to study entanglement-related phenomena. Our approach extends Gaussian state parameterizations by systematically incorporating higher-order correlations. We show the protocol’s usefulness in conjunction with current and forthcoming experimental capabilities, focusing on weakly interacting fermions as a proof of concept. Here, the lowest nontrivial expansion quantitatively predicts early time thermalization dynamics, including signaling the onset of quantum chaos indicated by the entanglement Hamiltonian.

Fermi gases↗

DOE OSTI2024

Elucidation of Design Criteria for V‐based Redox Mediators: Structure‐Function Relationships that Dictate Rates of Heterogeneous Electron Transfer

Redox mediators are attractive solutions for addressing the stringent kinetic stipulations required for efficient energy conversion processes. In this work, we compare the electrochemical properties of four vanadium complexes, namely [V(acac) 3 ], [V 6 O 7 (OMe) 12 ], [ n Bu 4 N] 3 [V 6 O 13 (TRIS NO2 ) 2 ], and [ n Bu 4 N] 5 [V 18 O 46 (NO 3 )] in non-aqueous solutions on glassy carbon electrodes. The goal of this study is to investigate the electron transfer kinetics and diffusivity of these compounds under identical experimental conditions to develop an understanding of structure-function relationships that dictate the physicochemical properties of vanadium oxide assemblies. Complex selection was dictated by two criteria – (1) nuclearity of the transition metal complexes (2) distribution of electron density in the native electronic configuration. In conclusion, our analyses establish that electronic communication between metal centers significantly impacts charge transfer kinetics of these vanadium-based compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗