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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 1,405 records · Page 78

Shape Dependence of Pressure-Induced Phase Transition in CdS Semiconductor Nanocrystals

Understanding structural stability and phase transformation of nanoparticles under high pressure is of great scientific interest, as it is one of the crucial factors for design, synthesis, and application of materials. Even though high-pressure research on nanomaterials has been widely conducted, their shape-dependent phase transition behavior still remains unclear. Examples of phase transitions of CdS nanoparticles are very limited, despite the fact that it is one of the most studied wide band gap semiconductors. Here we have employed in-situ synchrotron wide-angle X-ray scattering (WAXS) and transmission electron microscopy (TEM) to investigate the high-pressure behaviors of CdS nanoparticles as a function of particle shapes. We observed that CdS nanoparticles transform from wurtzite to rocksalt phase at elevated pressure in comparison to their bulk counterpart. Phase transitions also vary with particle shape—rod-shaped particles show a partially reversible phase transition and the onset of the structural phase transition pressure decreases with decreasing surface-to-volume ratios, while spherical particles undergo irreversible phase transition with relatively low phase transition pressure. Additionally, TEM images of spherical particles exhibited sintering-induced morphology change after high-pressure compression. Calculations of the bulk modulus reveals that spheres are more compressible than rods in the wurtzite phase. These results indicate that the shape of the particle plays an important role in determining their high-pressure properties. Our study provides important insights into understanding of the phase-structure-property relationship, guiding future design and synthesis of nanoparticles for promising applications.

36 MATERIALS SCIENCE↗

Temperature and Solvent Effects on H 2 Splitting and Hydricity: Ramifications on CO 2 Hydrogenation by a Rhenium Pincer Catalyst

The catalytic hydrogenation of carbon dioxide holds immense promise for applications in sustainable fuel synthesis and hydrogen storage. Mechanistic studies that connect thermodynamic parameters with the kinetics of catalysis can provide new understanding and guide predictive design of improved catalysts. Reported here are thermochemical and kinetic analyses of a new pincer-ligated rhenium complex ( tBu POCOP)Re(CO) 2 ( tBu POCOP = 2,6-bis(di-tert-butylphosphinito)phenyl) that catalyzes CO 2 hydrogenation to formate with faster rates at lower temperature. Because the catalyst follows the prototypical “outer sphere” hydrogenation mechanism, comprehensive studies of temperature and solvent effects on the H 2 splitting and hydride transfer steps are expected to be relevant to many other catalysts. Strikingly large entropy associated with cleavage of H2 results in a strong temperature dependence on the concentration of [( tBu POCOP)Re(CO) 2 H] – present during catalysis, which is further impacted by changing the solvent from toluene to tetrahydrofuran to acetonitrile. New methods for determining the hydricity of metal hydrides and formate at temperatures other than 298 K were developed, providing insight into how temperature can influence the favorability of hydride transfer during catalysis. These thermochemical insights guided the selection of conditions for CO 2 hydrogenation to formate with high activity (up to 364 h –1 at 1 atm or 3330 h –1 at 20 atm of 1:1 H 2 CO 2 ). In cases where hydride transfer is the highest individual kinetic barrier, entropic contributions to outer sphere H 2 splitting lead to a unique temperature dependence: catalytic activity increases as temperature decreases in tetrahydrofuran (200-fold increase upon cooling from 50 to 0 °C) and toluene (4-fold increase upon cooling from 100 to 50 °C). Furthermore, the ramifications on catalyst structure-function relationships are discussed, including comparisons between “outer sphere” mechanisms and metal–ligand cooperation mechanisms.

14 SOLAR ENERGY↗

Structure and Synthesizability of Iron–Sulfur Metal–Organic Frameworks

Sulfur-based metal–organic frameworks (MOFs) and coordination polymers (CPs) are an emerging class of hybrid materials that have received growing attention due to their magnetic, conductive, and catalytic properties with potential applications in electrocatalysis and energy storage. In this work, we report a high-throughput virtual screening protocol to predict the synthesizability of candidate metal–sulfur MOFs/CPs by computing the thermodynamically stable structures resulting from a particular combination of metal cluster, linker, cation, and synthetic conditions. Free energies are computed by using all-atom classical mechanical thermodynamic integration. Low-free-energy structures are refined using ab initio density functional theory, and pair distribution functions and powder X-ray diffraction patterns are calculated to complement and guide experimental structure determination. We validate the computational approach by retrospective predictions of the stable structure produced by experimental syntheses, and a subsequent screen predicts Fe 4 S 4 -BDT–TPP as a new thermodynamically stable one-dimensional (1D) CP comprising a redox-active Fe 4 S 4 cluster, a 1,4-benzenedithiolate (BDT) linker, and a tetraphenylphosphonium (TPP) countercation. Furthermore, this material is experimentally synthesized, and the 1D chain structure of the crystal is confirmed using microcrystal electron diffraction. The computational screening pipeline is generically transferable to neutral and ionic MOFs/CPs comprising arbitrary metal clusters, linkers, cations, and synthetic conditions, and we make it freely available as an open source tool to guide and accelerate the discovery and engineering of novel porous materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-Throughput Discovery Illuminates Design Principles and Limits for Long-Lived Charged Species in Organic Electrolytes

The chemical stability of charged molecules in all-organic redox flow batteries (RFBs) is required for the prolonged operation of these devices. Molecular engineering and electrolyte optimization are used to mitigate parasitic reactions and extend the lifetimes of the charge carriers. However, how much can structural variation extend the lifetime? To probe this query, we designed a high-throughput kinetic study of the radical cation of N-methylphenothiazinium, guided by statistical sampling and learning algorithms. Using Argonne’s autonomous discovery facility, we conducted over 6,000 kinetic experiments with robotic sample preparation, parallel kinetic measurements, and machine learning inputs, testing 188 solvent molecules selected from a space of over 540 candidates from 11 chemical classes. Algorithmic selections guided us to stable solvent candidates, which were further tested in high concentration with and without supporting electrolyte. Our findings reveal the inherent difficulty of exceeding the current state of the art through solvent variation. The desired stability is statistically rare and poorly predictable. Among the many tested, only three solvents significantly outperformed our baseline, acetonitrile─and none by more than a factor of 3─suggesting a general challenge in achieving the necessary techno-economic targets. Furthermore, we suggest that self-discharge through solvent homolysis is the cause of the observed limitations. Several structural motifs contribute to >1,000 h half-life stability including molecular simplicity, symmetry, oxidation complement, and strategic fluorination. Importantly, this workflow establishes effective assays for diagnosing and predicting oxidative stress for highly stable liquid electrolytes in all batteries.

Batteries↗

Lower Hybrid Waves at the Magnetosheath Separatrix Region

Lower hybrid waves are investigated at the magnetosheath separatrix region in asymmetric guide field reconnection by using the Magnetospheric Multiscale (MMS) mission. Three of the four MMS spacecraft observe clear wave activities around the lower hybrid frequency across the magnetosheath separatrix, where a density gradient is present. The observed waves are consistent with generation by the lower hybrid drift instability. The characteristic properties of these waves include the following: (1) the waves propagate toward the x-line in the spacecraft frame due to the large out-of-plane magnetic field, which is in the same direction of the diamagnetic drift of the x-line; (2) the wave potential is about 20% of the electron temperature. Furthermore, these drift waves effectively produce cross-field particle diffusion, enabling the transport of magnetosheath electrons into the exhaust region. At last, we suggest that the lower hybrid waves at the magnetosheath separatrix region represent some unique features of asymmetric guide field reconnection, which is different from that widely observed at the magnetospheric side of magnetopause reconnection.

58 GEOSCIENCES↗

Lower-Hybrid-Drift Vortices in the Electron-Scale Magnetic Reconnection Layer

Lower-hybrid-drift waves driving vortical flows have recently been discovered in the electron current layer during magnetic reconnection in the terrestrial magnetotail. Yet, spacecraft measurements cannot address how pervasive the waves are. In this work, we perform three-dimensional particle-in-cell simulations of guide field reconnection to demonstrate that electron vortices driven by the lower-hybrid-drift instability (LHDI) are excited immediately downstream from the electron jet reversal in 3-D channels of enhanced electron outflow. The resulting fluctuations generate a series of alternating vortices, producing magnetic field perturbations opposing and enhancing the local guide field and causing kinking of the enhanced electron outflow and patches of increased current. Our results demonstrate for the first time that LHDI exists in the electron current layer and enhanced outflow channels, providing a conceptual breakthrough on the LHDI in reconnection.

58 GEOSCIENCES↗

Lower‐Hybrid Wave Structures and Interactions With Electrons Observed in Magnetotail Reconnection Diffusion Regions

Abstract We investigate waves close to the lower‐hybrid frequency in 12 magnetotail reconnection electron diffusion region (EDR) events with guide field levels of near‐zero to 30%. In about half of the events, the wave vector has a small component along the current sheet normal, consistent with known lower‐hybrid drift wave properties, but the perpendicular magnetic field fluctuations can be comparable or greater than the parallel component, a feature unique to the waves inside and adjacent to EDRs. Another new wave property is that the wave vector has a significant component along the current sheet normal in some events and completely along the normal for one event. In 1/4 of the events, the term has a significant contribution to the wave electric field, possibly a feature of lower‐hybrid waves more likely to exist in the diffusion region than further away from the X‐line. Electron temperature variations are correlated with the wave potential, due to wave electric field acceleration and crossings at the corrugated separatrix region with different amounts of mixing between reconnection inflowing and outflowing populations. The latter also leads to the anti‐correlation between parallel and perpendicular temperature components. Using four‐spacecraft measurements, the magnetic field line twisting is demonstrated by the correlated fluctuations in and . The lower‐hybrid wave in the EDR of weak guide field reconnection may be generated near separatrices and penetrate to the mid‐plane or locally generated, and the latter possibility is beyond the prediction of previous reconnection simulations.

79 ASTRONOMY AND ASTROPHYSICS↗

Electron‐Scale Reconnection in Three‐Dimensional Shock Turbulence

Abstract Magnetic reconnection has been observed in the transition region of quasi‐parallel shocks. In this work, the particle‐in‐cell method is used to simulate three‐dimensional reconnection in a quasi‐parallel shock. The shock transition region is turbulent, leading to the formation of reconnecting current sheets with various orientations. Two reconnection sites with weak and strong guide fields are studied, and it is shown that reconnection is fast and transient. Reconnection sites are characterized using diagnostics including electron flows and magnetic flux transport. In contrast to two‐dimensional simulations, weak guide field reconnection is realized. Furthermore, the current sheets in these events form in a direction almost perpendicular to those found in two‐dimensional simulations, where the reconnection geometry is constrained.

58 GEOSCIENCES↗

Observation of a Knotted Electron Diffusion Region in Earth's Magnetotail Reconnection

Magnetic reconnection is a fundamental plasma process that alters the magnetic field topology and releases magnetic energy. Most numerical simulations and spacecraft observations assume a two‐dimensional diffusion region, with the electron diffusion region (EDR) embedded in the same plane as the ion diffusion region (IDR) and a uniform guide field throughout. Using observations from Magnetospheric Multiscale mission, we report a non‐coplanar, knotted EDR in Earth's magnetotail current sheet. The reconnection plane of the knotted EDR deviates by approximately 38° from that of the IDR, with the guide field exhibiting both a 38° directional shift and a twofold increase in amplitude. Moreover, the Hall magnetic field is bipolar in the EDR but quadrupolar in the IDR, indicating different Hall current structures at electron and ion scales. These observations highlight the importance of three‐dimensional effects and illustrate the complexity of multiscale coupling between the EDR and IDR during reconnection studies.

diffusion region↗

Expanding the chemistry of borates with functional [BO 2 ]- anions

More than 3900 crystalline borates, including borate minerals and synthetic inorganic borates, in addition to a wealth of industrially-important boron-containing glasses, have been discovered and characterized. Of these compounds, 99.9 % contain only the traditional triangular BO 3 and tetrahedral BO 4 units, which polymerize into superstructural motifs. Herein, a mixed metal K 5 Ba 2 (B 10 O 17 ) 2 (BO 2 ) with linear BO 2 structural units was obtained, pushing the boundaries of structural diversity and providing a direct strategy toward the maximum thresholds of birefringence for optical materials design. 11 B solid-state nuclear magnetic resonance (NMR) is a ubiquitous tool in the study of glasses and optical materials; here, density functional theory-based NMR crystallography guided the direct characterization of BO 2 structural units. The full anisotropic shift and quadrupolar tensors of linear BO 2 were extracted from K 5 Ba 2 (B 10 O 17 ) 2 (BO 2 ) containing BO 2 , BO 3 , and BO 4 and serve as guides to the identification of this powerful moiety in future and, potentially, previously-characterized borate minerals, ceramics, and glasses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nucleic acid mediated activation of a short prokaryotic Argonaute immune system

A short prokaryotic Argonaute (pAgo) TIR-APAZ (SPARTA) defense system, activated by invading DNA to unleash its TIR domain for NAD(P) + hydrolysis, was recently identified in bacteria. We report the crystal structure of SPARTA heterodimer in the absence of guide-RNA/target-ssDNA (2.66 Å) and a cryo-EM structure of the SPARTA oligomer (tetramer of heterodimers) bound to guide-RNA/target-ssDNA at nominal 3.15–3.35 Å resolution. The crystal structure provides a high-resolution view of SPARTA, revealing the APAZ domain as equivalent to the N, L1, and L2 regions of long pAgos and the MID domain containing a unique insertion (insert57). Cryo-EM structure reveals regions of the PIWI (loop10-9) and APAZ (helix αN) domains that reconfigure for nucleic-acid binding and decrypts regions/residues that reorganize to expose a positively charged pocket for higher-order assembly. The TIR domains amass in a parallel-strands arrangement for catalysis. We visualize SPARTA before and after RNA/ssDNA binding and uncover the basis of its active assembly leading to abortive infection.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamic control and quantification of active sites on ceria for CO activation and hydrogenation

Ceria (CeO 2 ) is a widely used oxide catalyst, yet the nature of its active sites remains elusive. This study combines model and powder catalyst studies to elucidate the structure-activity relationships in ceria-catalyzed CO activation and hydrogenation. Well-defined ceria clusters are synthesized on planar CeO 2 (111) and exhibit dynamic and tunable ranges of Ce coordination numbers, which enhance their interaction with CO. Reduced ceria clusters (e.g., Ce 3 O 3 ) bind CO strongly and facilitate its dissociation, while near-stoichiometric clusters (e.g., Ce 3 O 7 ) adsorb CO weakly and promote oxidation via carbonate formation. Unlike planar ceria surfaces, supported ceria clusters exhibit dynamic properties and enhanced catalytic activity, that mimic those of powder ceria catalysts. Insight from model studies provide a method to quantify active sites on powder ceria and guide further optimization of ceria catalysts for syngas conversion. This work marks a leap toward model-guided catalyst design and highlights the importance of site-specific catalysis.

03 NATURAL GAS↗

Dynamic basis of supercoiling-dependent DNA interrogation by Cas12a via R-loop intermediates

The sequence specificity and programmability of DNA binding and cleavage have enabled widespread applications of CRISPR-Cas12a in genetic engineering. As an RNA-guided CRISPR endonuclease, Cas12a engages a 20-base pair (bp) DNA segment by forming a three-stranded R-loop structure in which the guide RNA hybridizes to the DNA target. Here we use single-molecule torque spectroscopy to investigate the dynamics and mechanics of R-loop formation of two widely used Cas12a orthologs at base-pair resolution. We directly observe kinetic intermediates corresponding to a ~5 bp initial RNA-DNA hybridization and a ~17 bp intermediate preceding R-loop completion, followed by transient DNA unwinding that extends beyond the 20 bp R-loop. The complex multistate landscape of R-loop formation is ortholog-dependent and shaped by target sequence, mismatches, and DNA supercoiling. A four-state kinetic model captures essential features of Cas12a R-loop dynamics and provides a biophysical framework for understanding Cas12a activity and specificity.

59 BASIC BIOLOGICAL SCIENCES↗

A systematic approach to generating accurate neural network potentials: the case of carbon

Abstract Availability of affordable and widely applicable interatomic potentials is the key needed to unlock the riches of modern materials modeling. Artificial neural network-based approaches for generating potentials are promising; however, neural network training requires large amounts of data, sampled adequately from an often unknown potential energy surface. Here we propose a self-consistent approach that is based on crystal structure prediction formalism and is guided by unsupervised data analysis, to construct an accurate, inexpensive, and transferable artificial neural network potential. Using this approach, we construct an interatomic potential for carbon and demonstrate its ability to reproduce first principles results on elastic and vibrational properties for diamond, graphite, and graphene, as well as energy ordering and structural properties of a wide range of crystalline and amorphous phases.

Chemistry↗

Hierarchical Multi-agent Large Language Model Reasoning for Autonomous Heterogeneous Catalyst Discovery

Artificial intelligence is reshaping scientific exploration, but most methods automate procedural tasks without engaging in scientific reasoning, limiting autonomy in discovery. We demonstrate that hierarchical agentic large language model reasoning can efficiently drive simulation and scientific exploration. Across two chemical applications, CO adsorption on Cu surface transition metal adatoms and on M–N–C catalysts, reasoning-guided exploration reduces required atomistic simulations by up to 90% relative to heuristic or random selection. Comparisons across single-agent, multi-agent, and stochastic baselines show that hierarchical strategies yield more coherent and information-efficient search trajectories. Reasoning traces reveal chemically grounded decisions that cannot be explained by semantic bias or stochastic sampling. We realize these agentic reasoning strategies in Materials Agents for Simulation and Theory in Electronic-structure Reasoning (MASTER), a multimodal system that translates natural language into density functional theory workflows. Altogether, multi-agent collaboration accelerates heterogeneous catalyst discovery and marks a step toward more autonomous, reasoning-guided scientific exploration.

30 DIRECT ENERGY CONVERSION↗

Bond-centric modular design of protein assemblies

Directional interactions that generate regular coordination geometries are a powerful means of guiding molecular and colloidal self-assembly, but implementing such high-level interactions with proteins remains challenging due to their complex shapes and intricate interface properties. Here we describe a modular approach to protein nanomaterial design inspired by the rich chemical diversity that can be generated from the small number of atomic valencies. We design protein building blocks using deep learning-based generative tools, incorporating regular coordination geometries and tailorable bonding interactions that enable the assembly of diverse closed and open architectures guided by simple geometric principles. Experimental characterization confirms the successful formation of more than 20 multicomponent polyhedral protein cages, two-dimensional arrays and three-dimensional protein lattices, with a high (10%–50%) success rate and electron microscopy data closely matching the corresponding design models. Due to modularity, individual building blocks can assemble with different partners to generate distinct regular assemblies, resulting in an economy of parts and enabling the construction of reconfigurable networks for designer nanomaterials.

Biomaterials – proteins↗

Structural constraint integration in a generative model for the discovery of quantum materials

Billions of organic molecules have been computationally generated, yet functional inorganic materials remain scarce due to limited data and structural complexity. Here, in this work, we introduce Structural Constraint Integration in a GENerative model (SCIGEN), a framework that enforces geometric constraints, such as honeycomb and kagome lattices, within diffusion-based generative models to discover stable quantum materials candidates. SCIGEN enables conditional sampling from the original distribution, preserving output validity while guiding structural motifs. This approach generates ten million inorganic compounds with Archimedean and Lieb lattices, over 10% of which pass multistage stability screening. High-throughput density functional theory calculations on 26,000 candidates shows over 95% convergence and 53% structural stability. A graph neural network classifier detects magnetic ordering in 41% of relaxed structures. Furthermore, we synthesize and characterize two predicted materials, TiPd 0.22 Bi 0.88 and Ti 0.5 Pd 1.5 Sb, which display paramagnetic and diamagnetic behaviour, respectively. Our results indicate that SCIGEN provides a scalable path for generating quantum materials guided by lattice geometry.

36 MATERIALS SCIENCE↗

Operando microscopy for neuromorphic hardware

Microscopy techniques can uncover the physical properties and dynamic behaviours of materials, driving the discovery of emergent phenomena and guiding the design of next-generation computing hardware. As artificial intelligence becomes pervasive, the demand for high-performance materials to support sustainable information technologies is growing. Here, this Review highlights state-of-the-art imaging from electron and X-ray to optical techniques to probe the dynamics of neuromorphic materials, including operando characterization of devices. We examine design principles for neuromorphic materials, along with obstacles that hinder their development. Emphasis is placed on spatially and temporally resolved approaches that capture state changes including phase transitions, ferroic switching and spin-wave propagation that emulate biological components such as neurons, synapses and their connectivity. We discuss challenges in operando characterization and the integration of artificial intelligence-driven analysis for feedback-guided material discovery. Finally, we outline opportunities for real-time imaging of neuromorphic systems, paving the way towards adaptive, brain-inspired hardware.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗