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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Theory-Guided X-ray Absorption Spectroscopy Approach for Identifying Active Sites in Atomically Dispersed Transition-Metal Catalysts

Atomically dispersed supported metal catalysts offer new properties and the benefits of maximized metal accessibility and utilization. The characterization of these materials, however, remains challenging. Using atomically dispersed platinum supported on crystalline MgO (chosen for its well-defined bonding sites) as a prototypical example, we demonstrate in this work how systematic density functional theory calculations for assessing all the potentially stable platinum sites, combined with automated analysis of extended X-ray absorption fine structure (EXAFS) spectra, leads to unbiased identification of isolated, surface-enveloped platinum cations as the catalytic species for CO oxidation. The catalyst has been characterized by atomic-resolution imaging and EXAFS and high-energy resolution fluorescence detection X-ray absorption near edge spectroscopy. The proposed platinum sites are in agreement with experiment. This theory-guided workflow leads to rigorously determined structural models and provides a more detailed picture of the structure of the catalytically active site than what is currently possible with conventional EXAFS analyses. As this approach is efficient and agnostic to the metal, support, and catalytic reaction, we posit that it will be of broad interest to the materials characterization and catalysis communities.

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

Dimensional Evolution Guides Property Control in the A n Cu 4– n TiS 4 Semiconductor Series

Through progressive reduction of the three-dimensional (3D) covalent network of Cu 4 TiS 4 , we isolate seven new members of the A n Cu 4–n TiS 4 family (A = alkali metal; n = 0–4), spanning 3D, 2D, 1D, and 0D structural fragments. The dimensional reduction is rational, as it preserves the edge-sharing connectivity between [CuS 4 ] 7– and [TiS 4 ] 4– tetrahedra across the series. This structural evolution is driven by the stepwise substitution of Cu with alkali metals, guiding the formation of fragments with reduced dimensionality. The effects of “n” and “A” on the crystal structures, stabilities, electronic structures, and optoelectronic properties are profound, demonstrating that the manipulation of alkali metal size and A n Cu 4–n TiS 4 stoichiometry enables predictable variations in structure and properties. For example, the n = 0 and n = 4 end members of the A n Cu 4–n TiS 4 family set the range of achievable band gaps with 2.00 eV for Cu 4 TiS 4 , 2.60 eV for Na 4 TiS 4 , and intermediate values for the n = 1–3 members. Notably, CsCu 3 TiS 4 exhibits exceptional air stability and congruent melting, with density functional theory (DFT) calculating moderate hole and electron effective masses in specific crystallographic directions (mh = 1.24m 0 , me = 0.87m 0 ). Additionally, A 3 CuTiS 4 (A = Na, K, Rb) displays direct band gap behavior and long photoluminescence lifetimes of 2.3–8.6 μs, and K 3 CuTiS 4 has a PLQY of 5.19%. These findings underscore the potential of the A n Cu 4–n TiS 4 family for applications in optoelectronics and demonstrate widely applicable design concepts that unveil rational stoichiometries within a given composition space to generate a series of crystal structures related through an evolving covalent dimensionality that corresponds to a predictable electronic structure and property progression.

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

Diffusion Model-Guided Inverse Design of Bimetallic Catalysts for Ammonia Decomposition

In the past decade, artificial intelligence and deep learning have played increasingly prominent roles in materials design and discovery. Among these, generative AI models, known for their ability to create unique and complex structures, have emerged as state-of-the-art tools for materials screening due to their high efficiency and low computational cost. In catalysis, one of the major challenges is identifying promising material candidates within an immense chemical space. This challenge can be addressed using generative approaches, such as diffusion-based inverse design models. In this study, we present a machine learning-guided workflow that employed a diffusion model for the inverse design of bimetallic alloy catalysts for low-carbon ammonia decomposition, a key reaction for ammonia emission control and sustainable hydrogen production. Catalyst candidates were evaluated using nitrogen adsorption energy as the key descriptor, inspired by multiscale modeling. The proposed workflow identified low-cost, environmentally friendly catalysts with excellent catalytic performance, which have been validated theoretically and experimentally. Our framework decoupled the generative and property-prediction components, enhancing both flexibility and accuracy in the catalytic material design process.

Adsorption↗
DOE OSTI2021

macroMS: Image-Guided Analysis of Random Objects by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Mass spectrometry imaging is well-suited to characterizing sample surfaces for their chemical content in a spatially resolved manner. However, when the surface contains small objects with significant empty spaces between them, more efficient approaches to sample acquisition are possible. Image-guided mass spectrometry (MS) enables high-throughput analysis of a diverse range of sample types, such as microbial colonies, liquid microdroplets, and others, by recognizing and analyzing selected location targets in an image. Here, we describe an imaging protocol and macroMS, an online software suite that can be used to enhance MS measurements of macroscopic samples that are imaged by a camera or a flatbed scanner. Furthermore, the web-based tool enables users to find and filter targets from the optical images, correct optical distortion issues for improved spatial location of selected targets, input the custom geometry files into an MS device to acquire spectra at the selected locations, and finally, perform limited data analysis and use visualization tools to aid locating samples containing compounds of interest. Using the macroMS suite, an enzyme mutant library of Saccharomyces cerevisiae and nL droplet arrays of Escherichia coli and Pseudomonas fluorescens have been assayed at a rate of ~2 s/sample.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Electron Mixing and Isotropization in the Exhaust of Asymmetric Magnetic Reconnection With a Guide Field

In this work, we investigate an exhaust crossing of asymmetric guide field reconnection observed by Magnetospheric Multiscale (MMS) mission at Earth's dayside magnetopause. One MMS spacecraft (MMS 4) observes multicomponent electron distributions, including two counterstreaming electron beams, while the other three MMS spacecraft, with a separation of ~30 km, record nearly isotropic electron distributions. As counterstreaming electrons are unstable for the electron two-stream instability, our observations suggest that the electrostatic waves generated by the fast-growing electron two-stream instability can contribute to the rapid isotropization of electron distributions in the reconnection exhaust, indicating that wave-particle interactions play an important role in electron dynamics.

58 GEOSCIENCES↗
DOE OSTI2020

Lower Hybrid Drift Waves During Guide Field Reconnection

Generation and propagation of lower hybrid drift wave (LHDW) near the electron diffusion region (EDR) during guide field reconnection at the magnetopause is studied with data from the Magnetospheric Multiscale mission and a theoretical model. Inside the current sheet, the electron beta (β e ) determines which type of LHDW is excited. Inside the EDR, where the electron beta is high (β e ~5), the long-wavelength electromagnetic LHDW is observed propagating obliquely to the local magnetic field. In contrast, the short-wavelength electrostatic LHDW, propagating nearly perpendicular to the magnetic field, is observed slightly away from the EDR, where β e is small (~0.6). These observed LHDW features are explained by a local theoretical model, including effects from the electron temperature anisotropy, finite electron heat flux, electrostatics, and parallel current. The short-wavelength LHDW is capable of generating significant drag force between electrons and ions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Generation of a Strong Parallel Electric Field and Embedded Electron Jet in the Exhaust of Moderate Guide Field Reconnection

Abstract Magnetospheric Multiscale observed an extended current layer concurrent with a strong parallel electric field. The current layer is embedded in the reconnection exhaust and is consistent with an extended magnetized jet expected in roughly symmetric moderate guide field reconnection. The strong parallel electric field observed at the jet balances a strong gradient in the parallel electron pressure caused by a transition between magnetized electrons with T e ‖ > T e ⊥ on one side of the jet and demagnetized, roughly isotropic electrons across the thin current layer. Simulation results show how this transition can occur and how the associated electron pressure gradients in Ohm's law balance the parallel electric field.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

The Helicity Sign of Flux Transfer Event Flux Ropes and Its Relationship to the Guide Field and Hall Physics in Magnetic Reconnection at the Magnetopause

Flux Transfer Events (FTEs) are transient magnetic flux ropes typically found at the Earth's magnetopause on the dayside. While it is known that FTEs are generated by magnetic reconnection, it remains unclear how the details of magnetic reconnection controls their properties. A recent study showed that the helicity sign of FTEs positively correlates with the east-west (B y ) component of the Interplanetary Magnetic Field (IMF). With data from the Cluster and Magnetospheric Multiscale missions, we performed a statistical study of 166 quasi force-free FTEs. We focus on their helicity sign and possible association with upstream solar wind conditions and local magnetic reconnection properties. Using both in situ data and magnetic shear modeling, we find that FTEs whose helicity sign corresponds to the IMF B y are associated with moderate magnetic shears while those that do not correspond to the IMF B y are associated with higher magnetic shears. While uncertainty in IMF propagation to the magnetopause may lead to randomness in the determination of the flux rope core field and helicity, we rather propose that for small IMF B y , which corresponds to high shear and low guide field, the Hall pattern of magnetic reconnection determines the FTE core field and helicity sign. In that context we explain how the temporal sequence of multiple X-line formation and the reconnection rate are important in determining the flux rope helicity sign. This work highlights a fundamental connection between kinetic processes at work in magnetic reconnection and the macroscale structure of FTEs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Structure-guided design of pure orthosteric inhibitors of αIIbβ3 that prevent thrombosis but preserve hemostasis

A prevailing dogma is that inhibition of vascular thrombosis by antagonizing platelet integrin αIIbβ3 cannot be achieved without compromising hemostasis, thus causing serious bleeding and increased morbidity and mortality. It is speculated that these adverse outcomes result from drug-induced activating conformational changes in αIIbβ3 but direct proof is lacking. Here, we report the structure-guided design of peptide Hr10 and a modified form of the partial agonist drug tirofiban that act as “pure” antagonists of αIIbβ3, i.e., they no longer induce the conformational changes in αIIbβ3. Both agents inhibit human platelet aggregation but preserve clot retraction. Hr10 and modified tirofiban are as effective as partial agonist drugs in inhibiting vascular thrombosis in humanized mice, but neither causes serious bleeding, establishing a causal link between partial agonism and impaired hemostasis. Pure orthosteric inhibitors of αIIbβ3 may thus provide safer alternatives for human therapy, and valuable tools to probe structure–activity relationships in integrins.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Theory-guided design of high-entropy alloys with enhanced strength-ductility synergy

Abstract Metallic alloys have played essential roles in human civilization due to their balanced strength and ductility. Metastable phases and twins have been introduced to overcome the strength-ductility tradeoff in face-centered cubic (FCC) high-entropy alloys (HEAs). However, there is still a lack of quantifiable mechanisms to predict good combinations of the two mechanical properties. Here we propose a possible mechanism based on the parameter κ, the ratio of short-ranged interactions between closed-pack planes. It promotes the formation of various nanoscale stacking sequences and enhances the work-hardening ability of the alloys. Guided by the theory, we successfully designed HEAs with enhanced strength and ductility compared with other extensively studied CoCrNi-based systems. Our results not only offer a physical picture of the strengthening effects but can also be used as a practical design principle to enhance the strength-ductility synergy in HEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Guided anisotropic oxygen transport in vacancy ordered oxides

Abstract Anisotropic and efficient transport of ions under external stimuli governs the operation and failure mechanisms of energy-conversion systems and microelectronics devices. However, fundamental understanding of ion hopping processes is impeded by the lack of atomically precise materials and probes that allow for the monitoring and control at the appropriate time- and length- scales. In this work, using in-situ transmission electron microscopy, we directly show that oxygen ion migration in vacancy ordered, semiconducting SrFeO 2.5 epitaxial thin films can be guided to proceed through two distinctly different diffusion pathways, each resulting in different polymorphs of SrFeO 2.75 with different ground electronic properties before reaching a fully oxidized, metallic SrFeO 3 phase. The diffusion steps and reaction intermediates are revealed by means of ab-initio calculations. The principles of controlling oxygen diffusion pathways and reaction intermediates demonstrated here may advance the rational design of structurally ordered oxides for tailored applications and provide insights for developing devices with multiple states of regulation.

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

Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystems

Abstract Accurate and cost-effective quantification of the carbon cycle for agroecosystems at decision-relevant scales is critical to mitigating climate change and ensuring sustainable food production. However, conventional process-based or data-driven modeling approaches alone have large prediction uncertainties due to the complex biogeochemical processes to model and the lack of observations to constrain many key state and flux variables. Here we propose a Knowledge-Guided Machine Learning (KGML) framework that addresses the above challenges by integrating knowledge embedded in a process-based model, high-resolution remote sensing observations, and machine learning (ML) techniques. Using the U.S. Corn Belt as a testbed, we demonstrate that KGML can outperform conventional process-based and black-box ML models in quantifying carbon cycle dynamics. Our high-resolution approach quantitatively reveals 86% more spatial detail of soil organic carbon changes than conventional coarse-resolution approaches. Moreover, we outline a protocol for improving KGML via various paths, which can be generalized to develop hybrid models to better predict complex earth system dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Probing the limits of genetic recoding using multi-omics-guided evolution

Engineering the genetic code—by reassigning multiple of the 64 natural codons—enables making organisms resistant to all viruses, preventing genetic information exchange, and allowing the biosynthesis of genetically encoded unnatural polymers. However, synonymous codon replacement—recoding—is frequently lethal, and how recoding impacts fitness remains poorly explored. Here, we explore these effects using genome synthesis, directed evolution, and genome-transcriptome-translatome-proteome co-profiling on multiple synthetic Escherichia coli genomes. We construct six partially recoded E. coli strains bearing up to 45.8% of a synthetic genome with a deleterious 57-codon genetic code. As our analyses revealed widespread defects—including unassigned codons in Syn61 and Syn57—we apply multi-omics to revise our genome design and mitigate defects. Using multi-omics, we show that recoding induces transcriptional and translational changes leading to fitness defects under hundreds of conditions. Finally, we develop a multi-omics-guided evolution strategy that rapidly restores fitness, enabling genome synthesis with radical changes.

Nyerges, Akos [Harvard Medical School, Boston, MA ↗
DOE OSTI2026

Resolving root causes of experiment discrepancies guided by machine learning

Abstract Scientists rely on accurate experimental data to explain nature and then harness this knowledge for applications addressing human needs. However, discrepancies between experiments of the same observable can impede scientific progress if one does not understand the underlying causes. Here, we developed a process that unravels data discrepancies by first using Bayesian machine learning to relate discrepancies to few of many, potentially biasing metadata features that encode experiment procedures. This machine learning output guides human experts to study discrepancy causes by simulating suspicious aspects of historical experiments or designing modern ones to address open questions. The study findings then lead to rejecting or correcting historical data on firm scientific bases. This process is demonstrated for the energy spectrum of neutrons emitted promptly (<1 ns) after fission of 252 Cf, a trusted nuclear physics Standard. It reduces the spread in experimental 252 Cf spectra by up to a factor of 6.

Neudecker, D. (ORCID:0000000339200627)↗
DOE OSTI2026

Machine-learning guided search for phonon-mediated superconductivity in boron and carbon compounds

We present a workflow that iteratively combines ab-initio calculations with a machine-learning (ML) guided search for superconducting compounds with both dynamical stability and instability from imaginary phonon modes, the latter of which have been largely overlooked in previous studies. Electron-phonon coupling (EPC) properties and critical temperature (T c ) of 417 boron, carbon, and borocarbide compounds have been calculated with density functional perturbation theory (DFPT) and isotropic Eliashberg approximation. Our study addresses T c convergence of Brillouin zone sampling with an ansatz test, stabilizing imaginary phonon modes for significant EPC contributions, and comparing the performance of two ML models, especially when including compounds of dynamical instability. We predict a few promising superconducting compounds with formation energy just above the ground state convex hull, such as Ca 5 B 3 N 6 (35 K), TaNbC 2 (28.4 K), Nb 3 B 3 C (16.4 K), Y 2 B 3 C 2 (4.0 K), Pd 3 CaB (7.0 K), MoRuB 2 (15.6 K), RuVB 2 (15.0 K), RuSc 3 C 4 (6.6 K) among others.

Nepal, Niraj K. [Ames Laboratory (AMES), Ames, IA ↗
DOE OSTI2022

A single-atom library for guided monometallic and concentration-complex multimetallic designs

Atomically dispersed single-atom catalysts have the potential to bridge heterogeneous and homogeneous catalysis. Dozens of single-atom catalysts have been developed, and they exhibit notable catalytic activity and selectivity that are not achievable on metal surfaces. Although promising, there is limited knowledge about the boundaries for the monometallic single-atom phase space, not to mention multimetallic phase spaces. Here, single-atom catalysts based on 37 monometallic elements are synthesized using a dissolution-and-carbonization method, characterized and analyzed to build the largest reported library of single-atom catalysts. In conjunction with in situ studies, we uncover unified principles on the oxidation state, coordination number, bond length, coordination element and metal loading of single atoms to guide the design of single-atom catalysts with atomically dispersed atoms anchored on N-doped carbon. We utilize the library to open up complex multimetallic phase spaces for single-atom catalysts and demonstrate that there is no fundamental limit on using single-atom anchor sites as structural units to assemble concentration-complex single-atom catalyst materials with up to 12 different elements. Furthermore, our work offers a single-atom library spanning from monometallic to concentration-complex multimetallic materials for the rational design of single-atom catalysts.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Computation-guided optimization of split protein systems

Splitting bioactive proteins into conditionally reconstituting fragments is a powerful strategy for building tools to study and control biological systems. However, split proteins often exhibit a high propensity to reconstitute, even without the conditional trigger, limiting their utility. Current approaches for tuning reconstitution propensity are laborious, context-specific or often ineffective. Here, we report a computational design strategy grounded in fundamental protein biophysics to guide experimental evaluation of a sparse set of mutants to identify an optimal functional window. We hypothesized that testing a limited set of mutants would direct subsequent mutagenesis efforts by predicting desirable mutant combinations from a vast mutational landscape. This strategy varies the degree of interfacial destabilization while preserving stability and catalytic activity. We validate our method by solving two distinct split protein design challenges, generating both design and mechanistic insights. Furthermore, this new technology will streamline the generation and use of split protein systems for diverse applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Azobenzene-based sinusoidal surface topography drives focal adhesion confinement and guides collective migration of epithelial cells

Surface topography is a key parameter in regulating the morphology and behavior of single cells. At multicellular level, coordinated cell displacements drive many biological events such as embryonic morphogenesis. However, the effect of surface topography on collective migration of epithelium has not been studied in detail. Mastering the connection between surface features and collective cellular behaviour is highly important for novel approaches in tissue engineering and repair. Herein, we used photopatterned microtopographies on azobenzene-containing materials and showed that smooth topographical cues with proper period and orientation can efficiently orchestrate cell alignment in growing epithelium. Furthermore, the experimental system allowed us to investigate how the orientation of the topographical features can alter the speed of wound closure in vitro. Our findings indicate that the extracellular microenvironment topography coordinates their focal adhesion distribution and alignment. These topographic cues are able to guide the collective migration of multicellular systems, even when cell–cell junctions are disrupted.

59 BASIC BIOLOGICAL SCIENCES↗