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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Protein Data Bank (PDB): Fifty-three years young and having a transformative impact on science and society

This review article describes the co-evolution of structural biology as a discipline and the Protein Data Bank (PDB), established in 1971 as the first open-access data resource in biology by like-minded structural scientists. As the PDB archive grew in size and scope to encompass macromolecular crystallography, NMR spectroscopy, and cryo-electron microscopy, new technologies were developed to ingest, validate, curate, store, and distribute the information. Community engagement ensured that the needs of structural biologists (data depositors) and data consumers were met. Today, the archive houses more than 230,000 experimentally determined structures of proteins, nucleic acids, and macromolecular machines and their complexes with one another and small-molecule ligands. Aggregate costs of PDB data preservation are ~1% of the cost of structure determination. The enormous impact of PDB data on basic and applied research and education across the natural and medical sciences is presented and highlighted with illustrative examples. Enablement of de novo protein structure prediction (AlphaFold2, RoseTTAfold, OpenFold, etc.) is the most widely appreciated benefit of having a corpus of rigorously validated, expertly curated 3D biostructure data.

bioinformatics↗
DOE OSTI2025

Probing Carbon Mineralization Mechanisms in Pore and Bulk Fluids by Harnessing Architected Calcium Silicates

The ability to synthesize materials with well-controlled pore structures gives us unprecedented control over probing fluid interactions with reactive interfaces and advancing calibrated insights into coupled chemo-morphological interactions. One of the primary challenges in developing crystalline silicate materials lies in achieving ordered pore structures. Existing approaches of producing amorphous mesoporous metal silicates via sol–gel methods and heat-treatment of these materials to produce crystalline phases cause the pore structures in the amorphous phases to collapse. To overcome this challenge, carbon coating of amorphous mesoporous calcium silicate particles is carried out to retain the pore structure, while the material is heated to produce crystalline calcium silicate with calcium sulfate inclusions. The pore diameter in these materials is about 3.9 nm, with a surface area and a pore volume of 28.75 m 2 /g and 0.092 cm 2 /g, respectively. The mechanisms of carbon mineralization are investigated by reacting architected calcium silicate with 1 M Na 2 CO 3 and monitoring the evolution in the structural phases using operando wide-angle X-ray scattering (WAXS) measurements. Formation of stable calcium carbonate polymorph or calcite and metastable calcium carbonate polymorph or vaterite in pore and bulk fluids, respectively, resulting from the reaction between Na 2 CO 3 and CaSiO 3 , are noted. The mechanisms associated with carbon mineralization are delineated using ReaxFF molecular dynamics (MD) simulations. The surface dissolution reaction is initiated by 2H + ions that replace a Ca 2+ ion in the Ca–silicate matrix. Ca 2+ ions in the solution initially react with water to form calcium hydroxide and eventually form calcium (bi)carbonate. A slow and gradual increase in the formation of sodium silicate in the solution resulting from the reactions of silicic acid or the silicon dioxide reaction with sodium hydroxide is noted. When carbon mineralization occurs in environments bearing interfacial fluids, calcite is the dominant calcium carbonate polymorph, as determined using experiments with pore fluids and molecular-scale simulations. In conclusion, these studies provide fundamental insights into the mechanisms underlying the carbon mineralization of calcium silicate informed by experiments and molecular-scale simulations.

Calcium↗
DOE OSTI2025

A Note to Reviewers Suggesting Post-reaction Catalyst Characterization: Know What You’re Asking For

Here, we highlight examples of post-reaction characterization in thermo- and electrocatalysis to present the challenges in obtaining reliable data to answer specific questions about the true identity of the active site and/or catalyst deactivation/degradation. We use this editorial to suggest to reviewers that, when formulating comments to authors that involve materials characterization after reaction testing, they should consider what specific, meaningful information can be attained or what targeted question can be answered that adds value to the individual paper and to the field in general, and how to reasonably obtain that data. In contrast, reviewers should avoid vague, open-ended comments that suggest unguided post-reaction characterization that would not add significant value to the report and, similarly, avoid comments that are substantial enough that they could form the basis of an entirely separate report.

36 MATERIALS SCIENCE↗
DOE OSTI2025

ReaxFF Parameter Set for Boron Clusters and Icosahedral Boron Crystals: Comparison with Density Functional Theory and Machine-Learning Potentials

Icosahedral boron materials, which include regular icosahedra of 12 boron atoms have gained increasing attention due to their potential applications as superhard materials, semiconductors, and energy storage media. However, the synthesis of high quality crystals of these materials has been a major barrier to the development of these applications. To enable computational prediction of synthesis conditions yielding high-quality icosahedral boron crystals, herein we tested and refined a set of ReaxFF parameters for the nucleation and growth of such crystals. We focused on matching the relative energies of small boron clusters obtained by density functional theory since such small clusters and similar motifs are likely present in crystal nuclei and at the interface of growing crystals. Using a training set of B 80 clusters, including a low-energy core–shell structure containing a B 12 icosahedron core and a high-energy single-shell structure produced in preliminary ReaxFF simulations, the ReaxFF parameter set was refined to better reproduce energies calculated by density functional theory (DFT). Among existing ReaxFF parameter sets and the machine-learning interatomic potentials MACE-MP-0, MACE-MP-0b3, MACE-MPA-0, PFP v7.0.0, and SevenNet-MF-ompa, only our new parameter set and PFP v7.0.0 correctly ranked these B 80 clusters. This refinement led to improved agreement with DFT for a test set of 58 clusters consisting of 8–103 boron atoms. Furthermore, our refined parameter set yielded greater local icosahedral structure than the previously existing ReaxFF parameter set for larger scale simulations of crystallization from supercooled liquid boron. Additionally, simulations of solid boron in contact with molten nickel using our refined ReaxFF parameters yielded a boron solubility value that agrees moderately well with experimental expectations, while the previous boron parameters gave a value that was much too low.

boron↗
DOE OSTI2026

Atomic-Scale Imaging of Lithium Vacancies in a Battery Cathode by Multislice Electron Ptychography

Atomic-resolution imaging of battery materials is critical for identification of local defects and structural variations, which are tied to battery performance. However, since battery materials are, by design, optimized to allow ion motion in response to an applied electric field, they are also very sensitive to radiation damage by an electron beam. Image resolution is therefore severely constrained by the dose applied. Here, we show that multislice electron ptychography (MEP) can provide sub-ångström lateral resolution images of both light and heavy elements of a Li-ion battery cathode, along with nanometer-scale depth information and greater dose efficiency than conventional electron microscopy methods. Using the depth-sectioning capability of MEP, we have been able to obtain direct visualizations of Li vacancy clusters, atom column by atom column, in Li x Ni 0.33 Mn 0.33 Co 0.33 O 2 (NMC111) cathodes. This capability to track Li distributions will be valuable in understanding, informing, and optimizing electrode material design for ion storage and transfer.

batteries↗
DOE OSTI2025

Dissolved CO 2 Modulates the Electrochemical Capacitance on Gold Electrodes

The presence of CO 2 at an electrified interface between an aqueous electrolyte and a metal electrode is the prerequisite for many electrochemical CO 2 capture technologies. To understand the behavior of dissolved CO 2 at an aqueous electrified interface, we characterized the electrochemical interface of planar gold electrodes with cyclic voltammetry, electrochemical impedance spectroscopy (EIS), electrochemical surface plasmon resonance (EC–SPR), and attenuated total reflectance surface-enhanced infrared spectroscopy (ATR–SEIRAS). Under all investigated conditions, we observed a decrease in the electrochemical capacitance upon saturation of the electrolyte with CO 2 , as compared to an electrolyte saturated with Ar. EIS and EC–SPR showed that this capacitance reduction was also potential dependent: it reached a minimum near the point of zero charge and became more significant as the applied potential moved further away from the point of zero charge. Hybrid quantum–classical simulations of the gold/aqueous electrolyte interface indicate that bicarbonate decreases the capacitance and modifies the composition of the electric double layer. In addition to the binding of bicarbonate under positive bias, we propose that molecular CO 2 can be induced by applied potential to concentrate in the diffuse layer of the electric double layer, leading to a reduction in the electrochemical capacitance under both negative and positive bias. Furthermore, this work advances the understanding of non-Faradaic effects of dissolved CO 2 at aqueous electrified interfaces of relevance for electrochemical CO 2 capture.

25 ENERGY STORAGE↗
DOE OSTI2025

Design of Twisted Two-Dimensional Heterostructures and Performance Regulation Descriptor for Electrocatalytic Ammonia Production from Nitric Oxide

The electrocatalytic reduction of nitric oxide (NO) to ammonia (NH 3 ) represents an attractive alternative for valorizing waste NO streams (NORR). However, discovering efficient catalysts for NO-to-NH 3 conversion remains challenging. We have designed metal-intercalated twisted graphene-BN heterostructures, in which metal atoms act as electron-transfer bridges. The twisted configuration facilitates cross-interface charge transfer, redistributing electrons from the graphene–metal interface to the metal–BN interface and BN surface. This electronic modulation enables boron atom adjacent to the metal center in BN to serve as active sites, promoting strong chemisorption and enhanced activation of NO. After high-throughput screening of the stability and NO capture ability of various transition metal-intercalated twisted heterostructures, we have investigated systematically the NORR pathways across 30 candidates. The results show that the rBN-Ti-Gθ and rBN-V-Gθ heterostructures exhibit exceptional NO-to-NH 3 catalytic performance under optimized twisting conditions. Additionally, using sure independence screening and sparsifying operator (SISSO) for model training, we propose a descriptor and establish a relationship between the twist angle and catalytic activity. This study bridges the gap in applying twisted heterostructures to NORR electrocatalysis and provides new insights and strategies for designing high-performance NORR catalysts.

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

The Role of Dislocations in the Anelasticity of the Upper Mantle

Dislocation‐based dissipation mechanisms potentially control the viscoelastic response of Earth's upper mantle across a variety of geodynamic contexts, including glacial isostatic adjustment, postseismic creep, and seismic‐wave attenuation. However, there is no consensus on which dislocation‐based, microphysical process controls the viscoelastic behavior of the upper mantle. Although both intergranular (plastic anisotropy) and intragranular (backstress) mechanisms have been proposed, there is currently insufficient laboratory data to discriminate between those mechanisms. Here, we present the results of forced‐oscillation experiments in a deformation‐DIA apparatus at confining pressures of 3–7 GPa and temperatures of 298–1370 K. Our experiments tested the viscoelastic response of polycrystalline olivine—the main constituent of the upper mantle—at stress amplitudes from 70 to 2,800 MPa. Mechanical data are complemented by microstructural analyses of grain size, crystallographic preferred orientation, and dislocation density. We observe amplitude‐ and frequency‐dependent attenuation and modulus relaxation and find that numerical solutions of the backstress model match our results well. Therefore, we argue that interactions among dislocations, rather than intergranular processes (e.g., plastic anisotropy or grain boundary sliding), control the viscoelastic behavior of polycrystalline olivine in our experiments. In addition, we present a linearized version of the constitutive equations of the backstress model and extrapolate it to conditions typical of seismic‐wave propagation in the upper mantle. Our extrapolation demonstrates that the backstress model can explain the magnitude of seismic‐wave attenuation in the upper mantle, although some modification is required to explain the weak frequency dependence of attenuation observed in nature and in previous experimental work.

Hein, Diede [Univ. of Minnesota, Minneapolis, MN (↗
DOE OSTI2026

Multidimensional Distributional Neural Network Output Demonstrated in Super‐Resolution of Surface Wind Speed

Accurate quantification of uncertainty in neural network predictions remains a central challenge for scientific applications involving high-dimensional, correlated data. While existing methods capture either aleatoric or epistemic uncertainty, few offer closed-form, multidimensional distributions that preserve spatial correlation while remaining computationally tractable. In this work, we present a framework for training neural networks with a multidimensional Gaussian loss, generating a closed-form predictive distribution over outputs informed by non-identically distributed training data. Our approach captures aleatoric uncertainty by iteratively estimating the means and covariance matrices, and is demonstrated on a super-resolution example out-of-training-sample. We leverage a Fourier representation of the covariance matrix to stabilize network training and preserve spatial correlation. We introduce a novel regularization strategy—referred to as information sharing—that interpolates between image-specific and global covariance estimates, enabling convergence of the super-resolution downscaling network trained on image-specific distributional loss functions. This framework allows for efficient sampling, explicit correlation modeling, and extensions to more complex distribution families all without disrupting prediction performance. We demonstrate the method on a surface wind speed downscaling task and discuss its broader applicability to uncertainty-aware prediction in scientific models.

17 WIND ENERGY↗
DOE OSTI2026

A conveyor-belt magneto-optical trap of CaF

Achieving high-density samples of laser-cooled molecules is a critical step toward advancing applications in precision measurements, ultracold chemistry and quantum science. We report the experimental realization of a high-density conveyor-belt magneto-optical trap for calcium monofluoride (CaF) molecules. The obtained highly-compressed cloud has a mean radius of 64(5) μm and a peak number density of 3.6(5) × 10 10 cm −3 , a 600-fold increase over the conventional red-detuned MOTs of CaF, and the densest molecular MOT observed to date. Subsequent loading of these molecules into an optical dipole trap yields up to 2.6 × 10 4 trapped molecules at a temperature of 14(2) μK with a peak phase-space density of ~ 2.4 × 10 −6 . This opens new possibilities for a range of applications utilizing high-density, optically trapped ultracold molecules.

Yu, Scarlett S. [Harvard Univ., Cambridge, MA (Uni↗
DOE OSTI2025

Electron ptychography reveals a ferroelectricity dominated by anion displacements

Sodium niobate, a lead-free ferroic material, hosts delicately balanced, competing order parameters, including ferroelectric states that can be stabilized by epitaxial strain. Here we show that the resulting macroscopic ferroelectricity exhibits an unconventional microscopic structure using multislice electron ptychography. This technique overcomes multiple scattering artefacts limiting conventional electron microscopy, enabling both lateral spatial resolution beyond the diffraction limit and recovery of three-dimensional structural information. These imaging capabilities allow us to separate the ferroelectric interior of the sample from the relaxed surface structure and identify the soft phonon mode and related structural distortions with picometre precision. Unlike conventional ferroelectric perovskites, we find that the polar distortion in this material involves minimal distortions of the cation sublattices and is instead dominated by anion displacements relative to the niobium sublattice. We establish limits on film thickness for interfacial octahedral rotation engineering and directly visualize a random octahedral rotation pattern, arising from the flat dispersion of the associated phonon mode.

ferroelectrics and multiferroics↗
DOE OSTI2026

Mechanical behaviour of additively manufactured metals

Additive manufacturing is reshaping the production of engineering components in diverse industries, such as the automotive, aerospace, defense, and biomedical sectors, by offering unprecedented design flexibility. The non-equilibrium processing conditions of additive manufacturing generate materials with unique microstructures and tailored mechanical properties that are often unattainable through conventional routes. This review focuses on recent advances in additively manufactured metals that demonstrate distinctive mechanical behaviors, including strength-ductility synergy, microstresses and gradient plasticity, fracture and fatigue resistance, and high-temperature creep performance. Here, we examine the mechanisms and micromechanical effects arising from the heterogeneous microstructures fabricated by additive manufacturing, to guide the design of a wide range of high-performance structural materials. Furthermore, we discuss critical research needs and emerging opportunities in process control, alloy design, advanced characterization, high-fidelity computational modeling, and machine learning aimed at achieving exceptional mechanical properties in additively manufactured metals.

Additive Manufacturing↗
DOE OSTI2026

Perspective: Magnon-magnon coupling in hybrid magnonics

The internal coupling of magnetic excitations (magnons) with themselves has created a new research sub-field in hybrid magnonics, i.e., magnon-magnon coupling, which focuses on materials discovery and engineering for probing and controlling magnons in a coherent manner. This is enabled by, one, the abundant mechanisms of introducing magnetic interactions, with examples of exchange coupling, dipolar coupling, Ruderman–Kittel–Kasuya–Yosida (RKKY) coupling, and Dzyaloshinskii–Moriya interaction (DMI) coupling, and two, the vast knowledge of how to control magnon band structure, including field and wavelength dependences of frequencies, for determining the degeneracy of magnon modes with different symmetries. In particular, we discuss how magnon-magnon coupling is implemented in various materials systems, with examples of magnetic bilayers, synthetic antiferromagnets, nanomagnetic arrays, layered van der Waals magnets, and (DMI spin-orbit torque materials) in magnetic multilayers. Here, we then introduce new concept of applications for these hybrid magnonic materials systems, with examples of frequency up/down conversion and magnon-exciton coupling, and discuss what properties are desired for achieving those applications.

Materials science↗
DOE OSTI2026

Supercharging simulation-based inference for Bayesian optimal experimental design

Abstract Bayesian optimal experimental design (BOED) seeks to maximize the expected information gain (EIG) of experiments. This requires a likelihood estimate, which in many settings is intractable. Simulation-based inference (SBI) provides powerful tools for this regime. However, existing work explicitly connecting SBI and BOED is restricted to a single contrastive EIG bound. We show that the EIG admits multiple formulations which can directly leverage modern SBI density estimators, encompassing neural posterior, likelihood, and ratio estimation. Building on this perspective, we define a novel EIG estimator using neural likelihood estimation. Further, we identify optimization as a key bottleneck of gradient based EIG maximization and show that a simple multi-start parallel gradient ascent procedure can substantially improve reliability and performance. With these innovations, our SBI-based BOED methods are able to match or outperform by up to 22% existing state-of-the-art approaches across standard BOED benchmarks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Super-Resolution Ptychography with Small Segmented Detectors

To overcome the spatial resolution limit set by aperture-limited diffraction in traditional scanning transmission electron microscopy, microscopists have developed ptychography enabled by iterative phase retrieval algorithms and high-dynamic-range pixel array detectors. Current detector designs are limited by the data rate off chip, so a high-pixel-count detector has a proportionally lower frame rate than the few-segment detectors used for differential phase contrast (DPC) imaging. This slower acquisition speed leads to heightened vulnerability to scan noise, drift, and potential sample damage. This creates opportunities for repurposing fast segmented detectors for ptychography by trading a reduction in reciprocal space pixels for an increase in real space pixels. Here, we explore a strategy of oversampling in real space and instead apply detector pixel upsampling during the reconstruction process. Further, we demonstrate the viability of achieving super-resolution ptychography on thin objects using only 2 × 2 detector pixels, surpassing the resolution of integrated DPC (iDPC) imaging. With optimization using simulated datasets and experiments on MoTe 2 /WSe 2 bilayer moiré superlattices, we achieved super-resolution ptychography reconstructions under rapid acquisition conditions (37.5 pA, 1 μs dwell time), yielding over 50% improvements in contrast and information limit compared to annular dark field and iDPC imaging on the same detectors.

2D materials↗
DOE OSTI2025

Classical optimization with imaginary-time block encoding on quantum computers: The MaxCut problem

Optimization problems in finance, physics, and computer science are typically very hard to tackle in classical computing; quantum computing could help speed up computations and provide efficient methods for tackling large problems. Typically, to treat a problem with a quantum computer, the optimal solution is cast as the ground state of a diagonal Hamiltonian. Here, we develop a method, called imaginary-time evolution block encoding (ITE-BE), based on a recent imaginary-time algorithm, which requires no variational parameter optimization, as all parameters can be derived analytically from the target Hamiltonian. We also demonstrate that our method can be successfully combined with other quantum algorithms such as the quantum approximate optimization algorithm (QAOA). For illustration, here we study the MaxCut problem. We find that the QAOA ansatz increases the postselection success of ITE-BE, and shallow QAOA circuits, when boosted with ITE-BE, achieve better performance than deeper QAOA circuits. For the special case of the transverse initial state, we adapt our block-encoding scheme to allow for a deterministic application of the first layer of the circuit.

Zhong, Dawei [University of Southern California, L↗
DOE OSTI2025

Atacama Cosmology Telescope: DR6 gravitational lensing and SDSS BOSS cross-correlation measurement and constraints on gravity with the 𝐸 𝐺 statistic

We derive new constraints on the 𝐸 𝐺 statistic as a test of gravity, combining the cosmic microwave background (CMB) lensing map estimated from Data Release 6 (DR6) of the Atacama Cosmology Telescope with Sloan Digital Sky Survey III Baryon Oscillation Spectroscopic Survey (SDSS BOSS) CMASS and LOWZ galaxy data. We develop an analysis pipeline to measure the cross-correlation between CMB lensing maps and galaxy data, following a blinding policy and testing the approach through null and consistency checks. By testing the equivalence of the spatial and temporal gravitational potentials, the 𝐸 𝐺 statistic can distinguish Λ⁢ CDM from alternative models of gravity. We find 𝐸 𝐺 ⁡(𝑧 eff = 0.555) = 0.3⁢1$^{+0.06}_{−0.05}$ for Atacama Cosmology Telescope (ACT) and CMASS data at 68.28% confidence level, and 𝐸 𝐺 ⁡(𝑧 eff = 0.316) = 0.4⁢9$^{+0.14}_{−0.11}$ for the ACT and LOWZ. Systematic errors are estimated to be 3% and 4%, respectively. Including CMB lensing information from Planck PR4 results in 𝐸 𝐺 ⁡(𝑧 eff = 0.555) = 0.3⁢4$^{+0.05}_{−0.05}$ with CMASS and 𝐸 𝐺 ⁡(𝑧 eff = 0.316) = 0.4⁢3$^{+0.11}_{−0.09}$ with LOWZ. These are consistent with predictions for the Λ⁢ CDM model that best fits the Planck CMB anisotropy and SDSS BOSS baryon acoustic oscillations (BAO), where 𝐸$^{GR}_{𝐺⁡}$(𝑧 eff =0.555) =0.401 ± 0.005 for CMB lensing combined with CMASS and 𝐸$^{GR}_{𝐺}$⁡(𝑧 eff = 0.316) = 0.452 ± 0.005 combined with LOWZ. We also find 𝐸 𝐺 to be scale independent, with probability to exceed >5%, as predicted by general relativity. The methods developed in this work are also applicable to improved future analyses with upcoming spectroscopic galaxy samples and CMB lensing measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Possible unconventional surface superconductivity in the half-Heusler compound YPtBi

Here, we report an extensive study of the noncentrosymmetric half-Heusler superconductor YPtBi, revealing an unusual relation between bulk superconductivity and the possible appearance of surface superconductivity on the (111) oriented surface, at temperatures up to three times the bulk transition temperature. Transport measurements confirmed the low carrier density of the material and its bulk superconducting transition, which was also observed in ac susceptibility through mutual inductance (MI) measurements. However, a weak signature of superconductivity in the MI measurements appeared much above the bulk transition temperature, which was further observed in scanning tunneling spectroscopy, pointing to a possible surface superconducting state. Polar Kerr effect measurements suggest that while the bulk superconductor may exhibit an unusual nodal superconducting state, only the surface state breaks time reversal symmetry. Complementary tunneling measurements on LuPtBi are used to establish the observations on YPtBi, while density-functional theory calculations may shed light on the origin of this unusual surface state.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗