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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Mean-field dynamo as a quantum-like modulational instability

Presented here is a novel formulation of the mean-field dynamo as a modulational instability of magnetohydrodynamic (MHD) turbulence. This formulation, termed mean-field wave kinetics (MFWK), is based on the Weyl symbol calculus and allows describing the interaction between the mean fields (magnetic field and fluid velocity) and turbulence without requiring scale separation that is commonly assumed in the literature. The turbulence is described by the Wigner–Moyal equation for the spectrum of the two-point correlation matrix (Wigner matrix) of magnetic-field and velocity fluctuations and depicts the turbulence as an effective plasma of quantum-like particles that interact via the mean fields. Eddy–eddy interactions, which serve as ‘collisions’ in this effective plasma, are modelled within the standard minimal tau approximation to aid comparison with existing theories. Using MFWK, the non-local electromotive force is calculated for generic turbulence from first principles, modulo the limitations of MFWK. This result is then used to study, both analytically and numerically, the modulational modes of MHD turbulence, which appear as linear instabilities of the said effective quantum-like plasma of fluctuations. The standard α 2 -dynamo and other known results are reproduced as special cases. A new dynamo effect is predicted that is driven by correlations between the turbulent flow velocity and the turbulent current.

astrophysical plasmas↗
DOE OSTI2026

Analytic model for neutral penetration and plasma fueling

Neutral atoms recycled from wall interaction interact with confined plasma, thereby refuelling it, most strongly in the region closest to the wall. This occurs near the X-point in diverted configurations, or else near the wall itself in limited configurations. A progression of analytic models is developed for neutral density in the vicinity of a planar or linear source in an ionising domain. First-principles neutral transport simulations with DEGAS2 are used throughout to test the validity and limits of the model when using equivalent sources. The model is further generalised for strong plasma gradients or the inclusion of charge exchange. An important part of the problem of neutral fuelling from recycling is thereby isolated and solved with a closed-form analytic model. A key finding is that charge exchange with the confined plasma can be significantly simplified with a reasonable sacrifice of accuracy by treating it as a loss. The several assumptions inherent to the model (and the simulations with which it is compared) can be adapted according to the particular behaviour of neutrals in the divertor and the manner in which they cross the separatrix.

fusion plasma↗
DOE OSTI2026

Role of ion acoustic instability in magnetic reconnection

We report on a first-principles numerical study of magnetic reconnection in plasmas with different initial ion-to-electron temperature ratios. In cases where this ratio is significantly below unity, we observe intense wave activity in the diffusion region, driven by the ion-acoustic instability. Our analysis shows that the dominant macroscopic effect of this instability is to drive substantial ion heating. In contrast to earlier studies reporting significant anomalous resistivity, we find that anomalous contributions due to the ion-acoustic instability are minimal. These results shed light on the dynamical impact of this instability on reconnection processes, offering new insights into the fundamental physics governing collisionless reconnection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Fundamental Thermodynamic, Kinetic, and Mechanical Properties of Lithium and Its Alloys

Lithium alloying reactions are beneficial in promoting uniform plating and stripping of lithium metal in all-solid-state batteries. First-principles calculations are performed to predict thermodynamic, kinetic, and mechanical properties of lithium and several important Li–M alloys (M = Mg, Ag, Zn, Al, Ga, In, Sn, Sb, and Bi). While the Li–Mg binary system forms a solid solution, most other lithium–metal alloys prefer stoichiometric intermetallic compounds with common local motifs that enable fast Li diffusion. Lithium and Li-rich alloys exhibit an unusually flat energy landscape along paths that connect BCC to close-packed structures like FCC and HCP, with important implications for mechanical properties. Very low migration barriers for Li diffusion that rival those of superion conductors are predicted, both in pure Li and in Li–M intermetallics. However, vacancy concentration, which is crucial for substitutional diffusion, is predicted to be low in metallic Li and most Li–M intermetallics. Compounds such as B32 LiAl and LiGa as well as D0 3 Li 3 Sb and Li 3 Bi exhibit structural vacancies at higher ends of their voltage windows, which together with low migration barriers leads to exceptionally high Li mobilities. In the Li–Mg solid solution, the addition of Mg is found to decrease the vacancy tracer diffusion coefficient by an order of magnitude.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ligand Hole Driven Metal–Insulator Transition Exemplified in a Layered Transition Metal Oxide

The interplay of cooperative Jahn–Teller (JT) distortions and charge-disproportionation (CD) with a strong electronic correlation in transition metal oxides leads to structural symmetry breaking. Both JT and CD often manifest in the form of significant modifications in electronic and structural properties such as band splitting, metal–insulator transitions (MIT), and enhanced electron lattice interactions. Notably, the charge-disproportionation is a key electronic feature that drives the MIT. Here, we demonstrate and quantify it using first-principles calculations combining density-functional theory, dynamical mean-field theory, and spin–lattice Monte Carlo simulations. Taking Ca 2 FeMnO 6 as a prototypical example of a correlated oxide, our ab initio study shows that MIT in Ca 2 FeMnO 6 arises from the partial localization of oxygen ligand holes at alternate Fe sites that control both charge and magnetic ordering. Interestingly, the band gap was found to be fundamentally controlled by the strength of the charge-transfer energy and not by the Mott–Hubbard interactions. The novel physics and insights presented in this work reveal promising routes for tuning the electronic functionality in transition-metal oxides.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Leveraging Polymorphism in YbCuBi to Map Transport and Elastic Properties

AMX Zintl compounds with the hexagonal ZrBeSi structure have gained significant attention for their remarkable vacancy tolerance and low thermal conductivity. Their 2D honeycomb sublattice, composed of M–X covalent bonds, is believed to contribute to high anharmonicity and unusual thermal transport properties. In this study, we explore the temperature-dependent polymorphism of YbCuBi as a model system to investigate the relationship between the structure and elastic and thermal transport properties in AMX Zintls. YbCuBi undergoes a structural transition from the “flat” Cu–Bi layers in the ZrBeSi structure to corrugated layers in the LiGaGe structure below 410 K, resulting in a distortion of its centrosymmetric structure. To probe the effects of this crystallographic transition, we employ inelastic neutron scattering and temperature-dependent resonant ultrasound spectroscopy. These experimental findings, coupled with first-principles calculations and thermal conductivity measurements, allow us to elucidate a direct relationship between corrugation of the honeycomb lattice and the observed changes in elastic and thermal transport properties. These insights can be extended to other Zintl phases with similar structure types, providing a platform for the rational design of functional materials with tailored thermal properties.

Chemical structure↗
DOE OSTI2026

Cs X Si 15 P 21 ( X = Sn or Pb): Polar Noncentrosymmetric Si–P Frameworks Stabilized by Covalent X –P Bonding

Metal silicon phosphides composed of earth-abundant Si and P tend to exhibit semiconducting properties and adopt diverse crystal structures with relatively small additions of structure-directing elements. The potential of silicon phosphide materials in nonlinear optical applications has been hindered by the inability to systematically produce noncentrosymmetric structures with such a flexible framework. Here, in this work, two isostructural compounds with a novel noncentrosymmetric structure were made possible by the inclusion of elements with stereochemically active lone pairs (Sn 2+ and Pb 2+ ). The structures were determined through single-crystal and synchrotron powder X-ray diffraction. Analysis of chemical bonding in real space through the electron localization function revealed stereochemically active Pb 2+ and Sn 2+ species in a trigonal pyramidal coordination with {Pb/Sn}–P bonds. Such covalent bonding between Pb and P is quite uncommon in extended solids and has been reported in a few rare instances. Band structure calculations and linear optical measurements confirm the semiconducting nature of Cs X Si 15 P 21 ( X = Sn or Pb). The synthesis was optimized to yield high-purity polycrystalline samples. The nonlinear optical properties show promising second-harmonic generation (SHG) coefficients from the Kurtz–Perry method. First-principles calculations of the nonlinear optical properties support the experimentally determined SHG values and provide moderate values of birefringence, suggesting Cs X Si 15 P 21 could be phase-matchable and practical nonlinear optical materials in the mid-IR region.

crystal structure↗
DOE OSTI2026

Anisotropic Ferromagnetism in CrAu 3 Sb 6

The crystal structure and properties of CrAu 3 Sb 6 are presented, determined by measurements on single crystal and polycrystalline samples and first-principles calculations. The trigonal structure (space group P$\overline{3}$1m) comprises a CdI 2 -like sublattice of AuSb 2 with Cr occupying octahedral holes in a fully ordered triangular array. It can be viewed as a variation of the interesting and well-known families of partially intercalated transition metal dichalcogenides, but with stronger interactions along the stacking direction evidenced by short Cr–Au distances. The compound is metallic and ferromagnetic with a Curie temperature of 164 K. A strong anomalous contribution to the Hall effect is seen in the ferromagnetic state, and quantum oscillations are observed in magnetization at 2 K. Magnetization measurements show that the ordered moments of 1.5 μ B per Cr are oriented along the c-axis with relatively strong magnetocrystalline anisotropy. Electronic structure calculations confirm this uniaxial anisotropy and the important role of spin–orbit coupling in CrAu 3 Sb 6 and reveal strongly favored ferromagnetic ground state consistent with the measured Curie temperature. Through combined experiment and theory, this work provides a detailed picture of the basic properties and behaviors of this uniquely structured, Cr-based, anisotropic ferromagnet.

Crystal structure↗
DOE OSTI2024

Proton Conducting Neuromorphic Materials and Devices

Neuromorphic computing and artificial intelligence hardware generally aims to emulate features found in biological neural circuit components and to enable the development of energy-efficient machines. In the biological brain, ionic currents and temporal concentration gradients control information flow and storage. It is therefore of interest to examine materials and devices for neuromorphic computing wherein ionic and electronic currents can propagate. Protons being mobile under an external electric field offers a compelling avenue for facilitating biological functionalities in artificial synapses and neurons. In this review, we first highlight the interesting biological analog of protons as neurotransmitters in various animals. We then discuss the experimental approaches and mechanisms of proton doping in various classes of inorganic and organic proton-conducting materials for the advancement of neuromorphic architectures. Since hydrogen is among the lightest of elements, characterization in a solid matrix requires advanced techniques. We review powerful synchrotron-based spectroscopic techniques for characterizing hydrogen doping in various materials as well as complementary scattering techniques to detect hydrogen. First-principles calculations are then discussed as they help provide an understanding of proton migration and electronic structure modification. Outstanding scientific challenges to further our understanding of proton doping and its use in emerging neuromorphic electronics are pointed out.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Microwave-Assisted Reactive CO 2 Capture with the SrCO 3 -Graphite System

This study details the initial development of a microwave heat-driven reactive CO 2 capture (RCC) process using the SrO/SrCO 3 cycle and graphitic carbon to absorb ppm-levels of CO 2 from humidified room temperature air and selectively convert it into CO. By combining first-principles density functional theory (DFT) simulations with thermogravimetric analysis (TGA) and X-ray diffraction (XRD) verification, it is demonstrated that SrO spontaneously absorbs moisture to generate Sr(OH) 2 followed by Sr(OH) 2 *1H 2 O, which then can spontaneously react with atmospheric levels of CO 2 to form SrCO 3 . The resulting SrCO 3 can then react with solid carbon at elevated temperatures to selectively produce CO and regenerate SrO. Graphitic carbon is an excellent microwave absorber that can quickly generate temperatures approaching 1000 °C and then cool to room temperature within minutes, potentially allowing for integration with intermittent electricity. It is shown that using microwaves to selectively heat a mixture of graphitic carbon and SrCO 3 produced CO with 85 ± 3% selectivity and stable performance over ten cycles. The rapid heating for release and room temperature CO 2 uptake processes appeared to prevent performance loss from particle sintering typically observed with traditional thermal systems. In conclusion, these results demonstrate a new RCC approach that adds to the growing number of potential technologies available for converting CO 2 to useful chemicals.

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

Optimal Design and Operation of Intensified Absorbers with 3D-Printed Packing for Solvent-Based CO 2 Capture

Many potential solvent-based carbon capture processes suffer from a high heat of absorption of CO 2 that adversely affects the thermodynamic driving force. While interstage coolers are often used for removing a portion of the generated heat by removing the solvent or a portion of the solvent from a stage and cooling and returning it back to the absorber, they can be placed only at discrete locations in the tower. This work investigates intensified absorbers with 3D-printed packing that includes an internal cooler and therefore can be potentially used for maximizing the operational efficiency of the absorbers for CO 2 capture. The intensified absorber is modeled by using a generic, first-principles, equation-oriented absorber column model. Since the placement of these intensified packings would cause a loss of area/volume used for mass transfer, optimization of the proposed intensified absorber is performed by optimally selecting the locations at which to place these devices and designing them such that the trade-off due to the addition of the heat removal area and the resulting loss in the mass transfer area is accounted for. Results show that optimally placed and designed intensified packings can lead to a significant increase in the capture efficiency of the process in comparison to a similar column with no internal cooling. It is also observed that by optimally placing and designing intensified packings, the lean solvent flow rate to the absorber can be decreased, and the CO 2 lean loading can be increased while still maintaining the same capture efficiency. These process changes can lead to a substantial reduction in the cost of capture.

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

Net Present Value Optimization of a Natural Gas Combined Cycle Plant with CO 2 Capture using a Water-Lean Solvent Considering Transient Electricity Price for Multiple Regions

Global CO 2 emissions are increasing at about a 1.5% rate per year. Fossil fuel-based plants are one of the main contributors to this rise. In the power generation industry, fossil fuel plants are dominant, and many plants are under development. In this study, a natural gas combined cycle (NGCC) power plant with postcombustion capture using a leading water-lean solvent is considered. For optimal design and operating schedule, large-scale dynamic optimization is undertaken for net present value (NPV) optimization. The first principle dynamic model of NGCC is developed, including a model of the highly efficient H-class gas turbines. For computational tractability of the dynamic optimization problem, a reduced-order model is developed by using the Hankel singular value decomposition. A waterlean solvent, N-(2-ethoxyethyl)-3-morpholinopropan-1-amine, is used for carbon capture. A model of the capture system is developed in Aspen Plus, which is used to develop a reduced-order model by using ALAMO, a machine learning software. In addition, a reduced model of the CO 2 compression system with a dehydration unit is also considered. The integrated system is used for NPV optimization by using the Python-based PYOMO platform. The PCC process is analyzed for three configurations-conventional packed bed, rotating packed bed (RPB), and a combination of RPB and direct contact cooler. The NPV optimization is performed for 14 regional markets by considering year-long clustered and continuous locational marginal price data with a 1 h interval. Optimization results show that the PCC can achieve 90% CO 2 capture with a positive NPV for six regions. Sensitivity studies conducted by using the PCC configurations indicate that the process is economically feasible for 9 regions out of 14 regional electricity markets with NPV values in the range of 33−540 $MM.

cabon capture↗
DOE OSTI2025

Search for Stable and Low-Energy Ce–Co–Cu Ternary Compounds Using Machine Learning

Cerium-based intermetallics have garnered significant research attention as potential new permanent magnets. In this study, we explore the compositional and structural landscape of Ce−Co−Cu ternary compounds using a machine learning (ML)- guided framework integrated with first-principles calculations. We employ a crystal graph convolutional neural network (CGCNN), which enables efficient screening for promising candidates, significantly accelerating the material discovery process. With this approach, we predict five stable compounds, Ce 3 Co 3 Cu, CeCoCu 2 , Ce 12 Co 7 Cu, Ce 11 Co 9 Cu, and Ce 10 Co 11 Cu 4 , with formation energies below the convex hull, along with hundreds of low-energy (possibly metastable) Ce−Co−Cu ternary compounds. Firstprinciples calculations reveal that several structures are both energetically and dynamically stable. Notably, two Co-rich low-energy compounds, Ce 4 Co 33 Cu and Ce 4 Co 31 Cu 3 , are predicted to have high magnetizations.

Chemical structure↗
DOE OSTI2025

La 3 CuTe 5 : A Narrow-Gap Semiconductor with Indirect Gap and Dual-Regime Thermally Activated Transport

Metal-chalcogenide systems remain a long-standing research topic because of their structural diversity and potential to host emergent phenomena. Here, we report a new compound, La 3 CuTe 5 , synthesized from the halide-flux method. Single-crystal X-ray diffraction studies indicate the structure to be unique among reported ones. Here, the compound crystallizes in a novel structure type adopting the orthorhombic space group Pnma and a unit cell of a = 24.3947(14) Å, b = 4.4232(2) Å, and c = 10.2142(5) Å. The tetrahedral [CuTe 4 ] building blocks form chains along [010] by corner sharing and link [LaTe 7 ] and [LaTe 8 ] polyhedra via edge sharing, resulting in a three-dimensional bulk structure. Thermal analysis results indicate that the material remains stable with a temperature up to 950 °C and decomposable at 1400 °C. First-principles calculations reveal an indirect electronic band gap and flat valence bands dominated by Te p and Cu d states. Optical absorption measurements yield a band gap of ∼0.65 eV, consistent with semiconducting behavior observed in transport measurements. Fittings to the temperature-dependent resistivity reveal two thermally activated regimes associated with Arrhenius-type conduction and three-dimensional variable range hopping, respectively.

Chalcogenides↗
DOE OSTI2025

Cluster-Graph Fingerprinting: A Framework for Quantitative Analysis of Machine-Learned Interatomic Model Training and Simulation Data

Machine-learned interatomic models represent a significant advancement in simulation methods, extending the predictive ability of first-principles methods to previously inaccessible length and time scales. However, the data-driven nature of these models can lead to difficult-to-detect errors that can compromise prediction accuracy. To address this challenge, we introduce a novel fingerprinting approach based on the Chebyshev Interaction Model for Efficient Simulation (ChIMES) ML-IAM graph-based descriptor. Our strategy enables efficient and statistically rigorous analysis of system configurations used in ML-IAM training and those generated by their application, e.g., in molecular dynamics simulations. We demonstrate that these fingerprints can effectively assess novelty of a configuration relative to an existing data set and determine dissimilarity among individual configurations, which are two key tasks in workflows for active learning-based ML-IAM training, data set curation, and on-the-fly uncertainty quantification.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Perspective on Many-Body Methods for Molecular Polaritonic Systems

Recent advances in strong light–matter interactions have revealed a wealth of new physical phenomena in molecules embedded in optical cavities, including modified chemical reactivity, altered excitation spectra, and novel quantum correlations. To describe these effects from first-principles, the field of ab initio quantum electrodynamics (QED) has emerged as a compelling extension of quantum chemistry that treats electronic and photonic degrees of freedom on equal footing. In this Perspective, we review the growing landscape of many-body QED methods, including Hartree–Fock, density functional theory (QEDFT), time-dependent DFT (QED-TDDFT), configuration interaction (QED-CI), complete active space (QED-CASSCF), coupled cluster (QED-CC), quantum Monte Carlo (QED-QMC), and density matrix renormalization group (QED-DMRG), highlighting recent developments and implementations. We further explore real-time methods, gradient and Hessian formalisms, and the integration of nonadiabatic nuclear dynamics. Applications range from benchmark simulations of polaritonic chemistry to quantum simulations on emerging quantum hardware. We conclude by outlining future directions for theory development and interdisciplinary efforts at the interface of quantum chemistry, condensed matter, and quantum optics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Characterizing Defect Dynamics in Silicon Carbide Using Symmetry-Adapted Collective Variables and Machine Learning Interatomic Potentials

Silicon carbide (SiC) divacancies are attractive candidates for spin-defect qubits possessing long coherence times and optical addressability. The high activation barriers associated with SiC defect formation and motion pose challenges for their study by first-principles molecular dynamics. In this work, we develop and deploy machine learning interatomic potentials (MLIPs) to accelerate defect dynamics simulations while retaining ab initio accuracy. We employ an active learning strategy comprising symmetry-adapted collective variable discovery and enhanced sampling to compile configurationally diverse training data, calculation of energies and forces using density functional theory (DFT), and training of an E(3)-equivariant MLIP based on the Allegro model. Here, the trained MLIP reproduces DFT-level accuracy in defect transition activation free energy barriers, enables the efficient and stable simulation of multidefect 216-atom supercells, and permits an analysis of the temperature dependence of defect thermodynamic stability and formation/annihilation kinetics to propose an optimal annealing temperature to maximally stabilize VV divacancies.

Computer simulations↗
DOE OSTI2026

Charge Transport in Solvated Donor–Acceptor Functionalized Peptoids: Molecular Dynamics and Rate Theory

Scalable solar-energy conversion requires photoactive materials that combine the efficiency of natural photosynthetic systems with the stability and processability needed for practical applications. Achieving reliable charge transport in soft, self-assembled organic materials remains challenging, as structural fluctuations and environmental effects strongly influence charge-transfer (CT) rates. Here, we present a broadly applicable computational framework for evaluating CT rates in the condensed phase, combining Fermi’s golden rule rate theory with inputs from all-atom molecular dynamics (MD) simulations and first-principles electronic-structure calculations. The approach does not rely on system-specific parametrization and is applicable to a wide range of soft and disordered materials. We demonstrate the applicability and usefulness of the framework on redox-active peptoids functionalized with iron–porphyrin (Fe–P) complexes, a bioinspired platform with programmable donor–acceptor units and tunable three-dimensional organization. The calculated CT rates exhibit strong sensitivity to molecular conformation, with variations spanning several orders of magnitude. This dependence is shown to arise from the pronounced variation in diabatic electronic coupling with the relative orientations and separations of the Fe–P complexes across the conformational ensemble. The framework provides a consistent route for connecting atomistic structure to CT kinetics in the condensed phase and enables analysis of structure–rate relations in organic semiconducting systems.

Charge transfer↗