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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

NEXAFS spectroscopy of alkylated benzothienobenzothiophene thin films at the carbon and sulfur K-edges

Alkylated benzothienobenzothiophenes are an important class of organic semiconductors that exhibit high performance in solution-processed organic field-effect transistors. In this work, we study the near-edge x-ray absorption fine-structure (NEXAFS) spectra of 2,7-didecyl[1]benzothieno[3,2-b][1]benzothiophene (C 10 -BTBT) at both the carbon and sulfur K-edges. Angle-resolved experiments of thin films are performed to characterize the dichroism associated with molecular orientation. First-principles calculations using the density functional theory-based many-body x-ray absorption spectroscopy (MBXAS) method are also performed to correlate the peaks observed and their dichroism with transitions to specific antibonding molecular orbitals. Interestingly, the dichroism of the dominant, lowest energy peak is opposite at the carbon and sulfur K-edges. While the low-energy peak at the carbon K-edge is assigned to carbon 1s → π* transitions with transition dipole moment (TDM) perpendicular to the planar BTBT core, the dominant low energy peak at the sulfur K-edge is assigned to sulfur 1s → σ* transitions with TDM oriented along the long axis of the BTBT core. These differences at the sulfur and carbon K-edges are understood through the MBAXS simulations that find a reordering of the energy of the lowest energy π* and σ* transitions at the sulfur K-edge due to the strong localization of the σ* orbital over the sulfur atom. This work highlights differences in the NEXAFS spectra of organic semiconductors at carbon and sulfur K-edges and provides new insights into peak assignment and x-ray dichroism relevant for studying the molecular orientation of organic semiconductor films.

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

Modeling of the metal–insulator transition temperature in alio-valently doped VO 2 through symbolic regression

The correlated semiconductor vanadium dioxide (VO 2 ) exhibits an insulator–metal transition (IMT) near room temperature, which is of interest in various device applications. Precise IMT temperature control is crucial to determine the use cases across technologies such as thermochromic windows, actuators for robots or neuronal oscillators. Doping the cation or anion sites can modulate the IMT by several tens of degrees and control hysteresis. However, modeling the effects of control parameters (e.g., doping concentration, type of dopants) is challenging due to complex experimental procedures and limited data, hindering the use of traditional data-driven machine learning approaches. Symbolic regression (SR) can bridge this gap by identifying nonlinear expressions connecting key input parameters to target properties, even with small data sets. In this work, we develop SR models to capture the IMT trends in VO 2 influenced by different dopant parameters. Using experimental data from the literature, our study reveals a dual nature of the IMT temperature with varying tungsten (W) doping concentrations. The symbolic model captures data trends and accounts for experimental variability, providing a complementary approach to first-principles calculations. Our feature-driven analysis across a broader class of dopants informs selectivity and provides qualitative insights into tuning phase transition properties valuable for neuromorphic computing and thermochromic windows.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Sparsified time-dependent Fourier neural operators for fusion simulations

This paper presents a sparsified Fourier neural operator for coupled time-dependent partial differential equations (ST-FNO) as an efficient machine learning surrogate for fluid and particle-based fusion codes such as NIMROD (Non-Ideal Magnetohydrodynamics with Rotation - Open Discussion) and GTC (Gyrokinetic Toroidal Code). ST-FNO leverages the structures in the governing equations and utilizes neural operators to represent Green's function-like numerical operators in the corresponding numerical solvers. Once trained, ST-FNO can rapidly and accurately predict dynamics in fusion devices compared with first-principle numerical algorithms. In general, ST-FNO represents an efficient and accurate machine learning surrogate for numerical simulators for multi-variable nonlinear time-dependent partial differential equations, with the proposed architectures and loss functions. The efficacy of ST-FNO has been demonstrated using quiescent H-mode simulation data from NIMROD and kink-mode simulation data from GTC. The ST-FNO H-mode results show orders of magnitude reduction in memory and central processing unit usage in comparison with the numerical solvers in NIMROD when computing fields over a selected poloidal plane. The ST-FNO kink-mode results achieve a factor of 2 reduction in the number of parameters compared to baseline FNO models without accuracy loss.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Scalable learning of potentials to predict time-dependent Hartree–Fock dynamics

We propose a framework to learn the time-dependent Hartree–Fock (TDHF) inter-electronic potential of a molecule from its electron density dynamics. Although the entire TDHF Hamiltonian, including the inter-electronic potential, can be computed from first principles, we use this problem as a testbed to develop strategies that can be applied to learn a priori unknown terms that arise in other methods/approaches to quantum dynamics, e.g., emerging problems such as learning exchange–correlation potentials for time-dependent density functional theory. We develop, train, and test three models of the TDHF inter-electronic potential, each parameterized by a four-index tensor of size up to 60 × 60 × 60 × 60. Two of the models preserve Hermitian symmetry, while one model preserves an eight-fold permutation symmetry that implies Hermitian symmetry. Across seven different molecular systems, we find that accounting for the deeper eight-fold symmetry leads to the best-performing model across three metrics: training efficiency, test set predictive power, and direct comparison of true and learned inter-electronic potentials. All three models, when trained on ensembles of field-free trajectories, generate accurate electron dynamics predictions even in a field-on regime that lies outside the training set. To enable our models to scale to large molecular systems, we derive expressions for Jacobian-vector products that enable iterative, matrix-free training.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Degradation of performance in ICF implosions due to Rayleigh–Taylor instabilities: A Hamiltonian perspective

The Rayleigh–Taylor instability (RTI) is an ubiquitous phenomenon that occurs in inertial-confinement-fusion (ICF) implosions and is recognized as an important limiting factor of ICF performance. To analytically understand the RTI dynamics and its impact on ICF capsule implosions, we develop a first-principle variational theory that describes an imploding spherical shell undergoing RTI. The model is based on a thin-shell approximation and includes the dynamical coupling between the imploding spherical shell and an adiabatically compressed fluid within its interior. Using a quasilinear analysis, we study the degradation trends of key ICF performance metrics (e.g., stagnation pressure, residual kinetic energy, and areal density) as functions of initial RTI parameters (e.g., the initial amplitude and Legendre mode), as well as the 1D implosion characteristics (e.g., the convergence ratio). We compare analytical results from the theory against nonlinear results obtained by numerically integrating the governing equations of this reduced model. Our findings emphasize the need to incorporate polar flows in the calculation of residual kinetic energy and demonstrate that higher convergence ratios in ICF implosions lead to significantly greater degradation of key performance metrics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Exploring direct photodetachment and photodissociation–photodetachment dynamics of platinum iodide anions (PtI n - , n = 2–5) using cryogenic photoelectron spectroscopy

The direct photodetachment and two-photon photodissociation–photodetachment processes of a series of PtI n - (n = 2–5) anions were systematically studied using cryogenic anion photoelectron spectroscopy and first-principles electronic structure calculations. The adiabatic/vertical detachment energies (ADEs/VDEs) of these anions were determined from their 193 nm photoelectron (PE) spectra, i.e., 3.54/3.63, 4.04/4.09, 4.33/4.36, and 4.37/4.41 eV for n = 2–5, respectively, and well reproduced by B3LYP-D3(BJ)/aug-cc-pVTZ-pp calculations. As the coordination number increases, the electron affinity (EA) of PtI n • (n = 2–5) neutrals (equivalent to the corresponding anion’s ADE) gradually increases, exceeding the EA of Cl at n = 3 and exhibiting superhalogen characteristics for n ≥ 3. Meanwhile, the ground state transition contributed from detaching electrons in the highest occupied molecular orbital gradually evolves from the central metal Pt to the iodine ligands. For the PtI 3 - anion, besides one-photon direct detachment, four distinct two-photon photodissociation–photodetachment channels were identified, and the competition between them was discussed.

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

Impact of classical statistics on thermal conductivity predictions of BAs and diamond using machine learning molecular dynamics

Machine learning interatomic potentials (MLIPs) have greatly enhanced molecular dynamics (MD) simulations, achieving near-first-principles accuracy in thermal conductivity studies. In this work, we reveal that this accuracy, observed in BAs and diamond at sub-Debye temperatures, stems from an accidental error cancelation: classical statistics overestimates specific heat while underestimating phonon lifetimes, balancing out in thermal conductivity predictions. However, this balance is disrupted when isotopes are introduced, leading MLIP-based MD to significantly underpredict thermal conductivity compared to experiments and quantum statistics-based Boltzmann transport equation. This discrepancy arises not from classical statistics affecting phonon–isotope scattering rates but from its impact on the interplay between phonon–isotope and phonon–phonon scattering in the normal scattering-dominated BAs and diamond. In conclusion, this work underscores the limitations of MLIP-based MD for thermal conductivity studies at sub-Debye temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Influence of surface chemistry on Li nucleation energetics on graphene-based surfaces

Lithium metal is a promising high-capacity anode material for solid-state batteries, but it typically suffers from poor cyclability. Carbon scaffold hosts have the potential to improve this performance due to their high electronic conductivity and large surface area, which facilitates lithium-ion adsorption and desorption. Scaffold surface chemistry is known to significantly influence performance outcomes, but the details of these interactions are not fully understood. Here, this study employs first-principles simulations to explore lithium transport and nucleation on graphene anodes with various surface chemistries. Using enhanced sampling techniques, ab initio molecular dynamics, and density functional theory calculations, we find that although surface chemistry has a minimal impact on lithium interfacial transport, it influences surface nucleation significantly. Both heteroatom dopants and intrinsic defects lower the nucleation barrier, creating a more favorable environment for lithium nucleation compared to pristine graphene. In addition, our results reveal a complex interplay between surface lithium concentration, lithium transport, and nucleation kinetics. These findings highlight the potential of surface modifications to precisely control nucleation processes on carbon-based anodes and provide design guidance for reducing dendrite formation and improving the cycle life of solid-state batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A curvature-based mechanism for the spontaneous emission of electromagnetic radiation at curved plasma–vacuum interfaces

In this work, we derive from first principles the dispersion relation for electromagnetic radiation that is spontaneously emitted at a 2D curved plasma–vacuum interface in the absence of both background and external electric and magnetic fields. This plasma geometry is motivated by plasmas generated through hypervelocity impact projectiles—an area that is of importance to satellite safety in the aerospace community, and may be of importance for the developing study of projectile impact-driven inertial confinement fusion. We find spontaneous radiation occurs when thermal surface waves propagate along the edge of a circular plasma, with a frequency lower than the plasma frequency and spatial decay proportional to 1/r. This is distinct from more well-known mechanisms of radiation, in which the radiation frequency is greater than or equal to the plasma frequency. This theory is validated against 2D, electromagnetic particle-in-cell simulations and shows reasonable agreement. Finally, we discuss the effects of plasma geometry and attribute the radiation generation mechanism to the acceleration of charged surface waves as they traverse azimuthally along a curved path.

Lau, Raymond (ORCID:0000000299318101)↗
DOE OSTI2025

Characterization of chromium impurities in β -Ga2O3

Chromium is a common transition-metal impurity that is easily incorporated during crystal growth. It is perhaps best known for giving rise to the 694.3 nm (1.786 eV) emission in Cr-doped Al2O3, exploited in ruby lasers. Chromium has also been found in monoclinic gallium oxide, a wide-bandgap semiconductor being pursued for power electronics. In this work, we thoroughly characterize the behavior of Cr in Ga2O3 through theoretical and experimental techniques. β-Ga2O3 samples are grown with the floating zone method and show evidence of a sharp photoluminescence signal, reminiscent of ruby. We calculate the energetics of formation of Cr from first principles, demonstrating that Cr preferentially incorporates as a neutral impurity on the octahedral site. Cr possesses a quartet ground-state spin and has an internal transition with a zero-phonon line near 1.8 eV. By comparing the calculated and experimentally measured luminescence lineshape function, we elucidate the role of coupling to phonons and uncover features beyond the Franck–Condon approximation. The combination of strong emission with a small Huang–Rhys factor of 0.05 and a technologically relevant host material renders Cr in Ga2O3 attractive as a quantum defect.

Turiansky, Mark E. (ORCID:0000000291543582)↗
DOE OSTI2025

Energy conservation in real-time nuclear–electronic orbital Ehrenfest dynamics

Real-time nuclear–electronic orbital Ehrenfest (RT-NEO-Ehrenfest) dynamics methods provide a first-principles approach for describing nonadiabatic molecular processes with nuclear quantum effects. For an efficient description of proton transfer within RT-NEO-Ehrenfest dynamics, the basis function center associated with the quantum proton can be allowed to move classically. Here, this traveling proton basis (TPB) approach effectively captures proton quantum dynamics, although its energy conservation behavior is not yet fully satisfactory. Two recently proposed TPB approaches, in principle, conserve the extended energy, which includes both the system energy and the kinetic energy associated with the proton basis function center. Herein, a thermostatted TPB approach is proposed to improve the conservation of the system energy, excluding the kinetic energy associated with the proton basis function center. In this approach, the quantum proton dynamics are modulated by dynamically rescaling the proton momentum operator to maintain the system energy conservation. With the excited-state intramolecular proton transfer of o-hydroxybenzaldehyde as an example, this approach is shown to significantly improve the system energy conservation while preserving the accuracy of the quantum proton dynamics as achieved in the original TPB approach.

Ehrenfest dynamics↗
DOE OSTI2025

A foundation model for atomistic materials chemistry

Atomistic simulations of matter, especially those that leverage first-principles (ab initio) electronic structure theory, provide a microscopic view of the world, underpinning much of our understanding of chemistry and materials science. Over the last decade or so, machine-learned force fields have transformed atomistic modeling by enabling simulations of ab initio quality over unprecedented time and length scales. However, early machine-learning (ML) force fields have largely been limited by (i) the substantial computational and human effort required to develop and validate potentials for each particular system of interest and (ii) a general lack of transferability from one chemical system to the next. Here, we show that it is possible to create a general-purpose atomistic ML model, trained on a public dataset of moderate size, that is capable of running stable molecular dynamics for a wide range of molecules and materials. We demonstrate the power of the MACE-MP-0 model-and its qualitative and at times quantitative accuracy-on a diverse set of problems in the physical sciences, including properties of solids, liquids, gases, chemical reactions, interfaces, and even the dynamics of a small protein. The model can be applied out of the box as a starting or "foundation" model for any atomistic system of interest and, when desired, can be fine-tuned on just a handful of application-specific data points to reach ab initio accuracy. Establishing that a stable force-field model can cover almost all materials changes atomistic modeling in a fundamental way: experienced users obtain reliable results much faster, and beginners face a lower barrier to entry. Foundation models thus represent a step toward democratizing the revolution in atomic-scale modeling that has been brought about by ML force fields.

Batatia, Ilyes↗
DOE OSTI2025

Facet-dependent structure and dissociation of water at pristine IrO 2 /water interfaces

Understanding the microscopic structure of water at metal oxide interfaces is crucial for advancing electrocatalysis. IrO 2 , specifically, has shown exceptional activity for electrochemical water oxidation, but we currently lack a fundamental understanding of how the surface structure of IrO 2 impacts water reactivity. In this work, we developed a machine learning potential trained to first-principles accuracy for modeling IrO 2 /water interfaces across different facets: (110), (100), (101), and (001). Using extensive machine learning molecular dynamics simulations, we investigated the spontaneous dissociation of water molecules at these interfaces. Our results reveal a distinct dissociation probability trend: (110) > (100) ≈ (101) > (001), which we attribute primarily to the reaction thermodynamics of surface water dissociation. A strong correlation is observed between the surface Ir–O bond distances and the dissociation probabilities, highlighting the role of surface geometry in modulating reactivity. As a consequence, the interfacial solvation structures and hydrogen bonding environments are dynamically tuned by the varying water dissociation capabilities across facets. This work elucidates how water dissociation energetics depend on surface orientation and interfacial structure, offering atomistic insights into manipulating reaction chemistry at electrocatalytic interfaces.

organic↗
DOE OSTI2026

Nuclear activation analysis of zirconium-90 isomeric and ground-state reactions at the OMEGA Laser Facility

Nuclear activation is a well-established technique for inferring neutron yields in laser direct-drive deuterium–tritium (DT) and deuterium–deuterium (D 2 ) implosions at the OMEGA Laser Facility. Zirconium has long been considered an excellent candidate for measuring DT neutron fusion yields by observing decays of the 90 Zr(n,2n) 89 Zr ground-state reaction. As it has a higher energy threshold than present activation detectors utilizing copper, zirconium provides a means to infer primary neutron yields that are less susceptible to being skewed due to neutron scattering within the experimental environment. However, with a 78.41-h half-life, it is not operationally practical to utilize this reaction for OMEGA experiments, which have a 1-h shot cycle. Zirconium’s 90 Zr(n,2n) 89 mZr reaction presents itself as a viable candidate to infer neutron yields within a shot cycle, given its half-life of 4.16 min. Here, we present an overview of the approach and methodology, utilizing first principles techniques, to infer the primary neutron yields from OMEGA DT fusion experiments by using both the isomeric and the ground-state reaction. Yields inferred from both reactions are compared, which are in good agreement between the two.

Activation analysis↗
DOE OSTI2026

Mott vs Kondo: Influence of various density functional based methods on the Ce isostructural phase transition mechanism

The cerium iso-structural phase transition (γ–α) is dominated by f-electron localization changes that results in a magnetic ordering change and a volume collapse. Generally, these physics are difficult to capture with ab initio and first principles methods. However, previous works have shown various methods to be successful in predicting at least some of the physics of the γ to α phase transition. Therefore, here, we perform a broad survey of density functional based methods across three levels of theory and types of functions [GGA (generalized gradient approximation), MetaGGA, and hybrid functionals] and compare the results, focusing on hydrostatic compression across the phase boundary at zero kelvin. For the methods that best reproduce experimental results, we directly probe the predicted mechanisms and frame the results in the Mott/Kondo debate, assessing how the underlying methods and assumptions of different functionals can assess the physical drivers in the phase transition, providing insight into the governing processes of this unique phase transition.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Molecular dynamics simulation of hydrodynamic transport coefficients in plasmas

Molecular dynamics simulations are used to calculate transport coefficients in a two-component plasma interacting through a repulsive Coulomb potential. The thermal conductivity, electrical conductivity, electrothermal coefficient, thermoelectric coefficient, and shear viscosity are computed using the Green–Kubo formalism over a broad range of Coulomb coupling strength, 0.01 ≤ Γ ≤ 140. Emphasis is placed on testing standard results of the Chapman–Enskog solution in the weakly coupled regime (Γ ≪ 1) using these first-principles simulations. As expected, the results show good agreement for Γ ≲ 0.1. However, this agreement is only possible if careful attention is paid to the definitions of linear constitutive relations in each of the theoretical models, a point that is often overlooked. For example, the standard Green–Kubo expression for thermal conductivity is a linear combination of thermal conductivity, electrothermal, and thermoelectric coefficients computed in the Chapman–Enskog formalism. Meaningful results for electrical conductivity are obtained over the full range of coupling strengths explored, but it is shown that potential and virial components of the other transport coefficients diverge in the strongly coupled regime (Γ ≫ 1). In this regime, only the kinetic components of the transport coefficients are meaningful for a classical plasma.

Electrical conductivity↗
DOE OSTI2026

Solvent effects on triplet yields in BODIPY-based photosensitizers

Here, we employ molecular dynamics simulations and quantum rate theories to elucidate the complex condensed-phase dynamics underpinning triplet-state formation in organic photosensitizers. Using models informed by first-principles calculations complete with a molecular representation of solvents of different polarities, we elucidate the interplay of the internal and environmental interactions underlying triplet yield. We find that triplet yields depend sensitively on the dielectric stabilization of the charge transfer intermediate that facilitates a transition into the triplet manifold. Our results illustrate the importance of molecularly detailed models in understanding the excited-state internal charge-transfer dynamics of photochemically relevant organic molecules.

Coello Escalante, Leonardo [University of Californ↗
DOE OSTI2026

Metal–bicarbonate ion pairing in alkaline aqueous solutions from multilevel embedded correlated wavefunction theory and molecular dynamics

In this work, we examine ion-pairing mechanisms of bicarbonates in alkaline aqueous solutions with the divalent metal ions most abundantly present in seawater, namely, Ca 2+ and Mg 2+ . We employ a rare-event enhanced sampling approach within first-principles molecular dynamics to explore regions of phase space spanning solvent-shared to contact ion pairs. Second-order Møller–Plesset perturbation theory (MP2) corrections are subsequently applied in an embedding framework (EMB) to refine the electronic structure of stationary states and associated reaction barriers along the free-energy profiles while retaining the extended solvent effects at the density functional theory (DFT) level. Ca 2+ –HCO 3 − was previously hypothesized to exist in a solvent-shared ion pair (SSHIP) by DFT studies with an endergonic contact ion pair (CIP) formation; however, our EMB-MP2 refinement of the DFT ion-pairing pathways reveals that Ca 2+ and HCO 3 − form a virtually barrier-free CIP in alkaline solutions, with even more energetic ease than the widely studied Ca–CO 3 ion pair. We find qualitative agreement between DFT and EMB-MP2 for Mg 2+ —unlike Ca 2+ , Mg 2+ refuses to shed its strong hydration shell, thereby preferring a SSHIP state with a significant activation barrier to crossover to the CIP forms—a trait reminiscent of ion pairing in Mg–CO 3 and closely related to the kinetic limitations underlying the famous subject of the dolomite problem. Our study highlights the importance of improved electronic structure descriptions of liquids, modeled as a condensed phase of matter lacking in long-range crystalline order. It also strongly suggests that Ca 2+ –HCO 3 − CIPs are likely precursors involved in prenucleation of CaCO 3 mineral formation in seawater.

Sharma, Vidushi [Princeton Plasma Physics Laborato↗