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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Evolution and interplay of lithium metal interphase components revealed by experimental and theoretical studies

ABSTRACT: Lithium metal batteries (LMB) have high energy densities and are crucial for clean energy solutions. The characterization of lithium metal interphase is fundamentally and practically important but technically challenging. Taking advantage of synchrotron x-ray which has the unique capability of analyzing crystalline/amorphous phases quantitative-ly with statistical significance, we study the composition and dynamics of LMB interphase for a newly developed im-portant LMB electrolyte that is based on fluorinated ether. Pair distribution function analysis revealed the sequential role of anion and solvent in interphase formation during cycling. The relative ratio between Li2O and LiF first increases and then decreases during cycling, suggesting suppressed Li2O formation in both initial and long extended cycles. Theoretical studies revealed that in initial cycles, this is due to the energy barrier in many-electron transfer. In long extended cycles, the anion decomposition product Li2O encourages solvent decomposition by facilitating solvent adsorption on Li2O which is followed by concurrent depletion of both. This work highlights the important role of Li2O in transitioning from anion-derived interphase to a solvent-derived one.

Tan, Sha↗
DOE OSTI2024

Structure–Function Insights into Thermoresponsive Copolymers as Lanthanide Precipitants

The synthetic toolbox for stimuli-responsive polymers has broadened to include many tunable variables, making these materials applicable in diverse technologies. However, unraveling the key composition–structure–function relationships to facilitate ground-up design remains a challenge due to the inherent dispersity in sequence and conformations for synthetic polymers. We here present a systematic study of these relationships using a model system of copolymers with a thermoresponsive (N-isopropylacrylamide) backbone in addition to metal-chelating (acrylic acid) and hydrophobic structural comonomers and evaluate their efficiency at isolating technologically critical lanthanide ions. The efficiency of lanthanide ion extraction by precipitation was quantitated with a metallochromic dye to reveal trends relating copolymer hydrophobicity to improved separations. Further, we examined the role of different hydrophobic comonomers in dictating the solution-phase conformation of the polymer in the presence and absence of lanthanide ions, and we correlated key features of the hydrophobic comonomer to extraction efficiency. Lastly, we identified how the local proximity of thermoresponsive, chelating, and hydrophobic subunits facilitates metal extraction by manipulating the copolymer sequence with multiblock polymerization. Through mechanistic analysis, we propose a binding-then-assembly process through which metal ions are coprecipitated with macromolecular chelators.

Copolymers↗
DOE OSTI2025

Operando Unveiling of Hydrogen Spillover Mechanisms on Tungsten Oxide Surfaces

Hydrogen spillover is an important process in catalytic hydrogenation reactions, facilitating H 2 activation and modulating surface chemistry of reducible oxide catalysts. This study focuses on the operando unveiling of platinum-induced hydrogen spillover on monoclinic tungsten trioxide (γ-WO 3 ), employing ambient pressure X-ray photoelectron spectroscopy, density functional theory calculations and microkinetic modeling to investigate the dynamic evolution of surface states at varied temperatures. At room temperature, hydrogen spillover results in the formation of W 5+ and hydrogen intermediates (hydroxyl species and adsorbed water), facilitated by Pt metal clusters. With increasing temperature, water desorption, reverse hydrogen spillover and surface-to-bulk diffusion of hydrogen atoms compete with each other, leading initially to reoxidation and then further reduction of W atoms in the near-surface. The combined experimental results and simulations provide a comprehensive understanding of the mechanisms underlying hydrogen interaction with reducible metal oxides, lending insights of relevance to the design of enhanced hydrogenation catalysts.

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

Visible Light Photolysis at Single Atom Sites in Semiconductor Perovskite Oxides

Designing catalysts with well-defined active sites with chemical functionality responsive to visible light has significant potential for overcoming scaling relations limiting chemical reactions over heterogeneous catalyst surfaces. Visible light can be leveraged to facilitate the removal of strongly bound species from well-defined single cationic sites (Rh) under mild conditions (323 K) when they are incorporated within a photoactive perovskite oxide (Rh-doped SrTiO 3 ). CO, a key intermediate in many chemistries, forms stable geminal dicarbonyl Rh complexes (Rh + (CO) 2 ), that could act as site blockers or poisons during a catalytic cycle. For the first time, we demonstrate that CO removal can occur at mild temperatures (323 K) under low-energy red light (635 nm) irradiation, which is not possible for supported isolated-site Rh catalysts (0.2 wt % Rh/γ-Al 2 O 3 ). Photolysis of supported Rh + (CO) 2 complexes (e.g., 0.2 wt % Rh/γ-Al 2 O 3 ) has been demonstrated but is limited to high energy UV photons. Rigorous kinetic experiments elucidate disparate mechanisms for CO photodepletion from Rh-doped SrTiO 3 and supported isolated site Rh/γ-Al 2 O 3 . CO photodepletion from supported isolated site Rh/γ-Al 2 O 3 involves a direct metal to ligand charge transfer mechanism, whereas Rh-doped SrTiO 3 is governed by electron–hole pair formation in the perovskite. In this work, we show that under visible, low-energy red light, surface Rh species in Rh-doped SrTiO 3 introduce midgap energy states above the valence band that facilitate electronic excitations leading to surface CO removal. Isolated Rh sites in Rh-doped SrTiO 3 also exhibit exceptional stability under multiple CO photodepletion cycles. Overall, incorporating single sites into photoactive perovskite oxides is an effective strategy to influence surface chemistries with visible light.

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

Conformationally Adaptable Extractant Flexes Strong Lanthanide Reverse-Size Selectivity

Chemical selectivity is traditionally understood in the context of rigid molecular scaffolds with precisely defined local coordination and chemical environments that ultimately facilitate a given transformation of interest. By contrast, nature leverages dynamic structures and strong coupling to enable specific interactions with target species in otherwise complex media. Taking inspiration from nature, we demonstrate unconventional selectivity in the solvent extraction of light over heavy lanthanides using a conformationally flexible ligand called octadecyl acyclopa (ODA). This novel ligand forms pseudocyclic molecular complexes with lanthanide ions at organic/aqueous interfaces, revealed by vibrational sum frequency generation spectroscopy. These complexes are extracted into the organic phase, where femtosecond structural dynamics are probed by two-dimensional infrared spectroscopy and ab initio molecular dynamics simulations to mechanistically frame the macroscopic selectivity trends. We find larger-than-expected structural fluctuations and bond lengths for heavy Ln–ODA complexes that arise from an inability of ODA to contort around the smaller ions to satisfy all would-be bonding interactions, despite forming some individually strong bonds. This finding contrasts with the binding of ODA with lighter lanthanides where, despite individually weaker bonds, collective interactions manifest that minimize structural fluctuations and give rise to enhanced thermodynamic stability. Furthermore, these results point to a new paradigm where conformational dynamics and cumulative bonding interactions can be used to facilitate unconventional chemical transformations.

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

Titanium-, Nitrogen-Doped Carbon Flowers Catalyze Electrochemical Nitrate Reduction Reaction to Ammonia

An emerging design heuristic for electrochemical nitrate reduction (NO 3 RR) catalysts is synthesizing electron-deficient sites to facilitate binding of electron-rich NO 3 – . However, this rule has rarely been applied to metal-, nitrogen-doped carbon (MNC) catalysts. Titanium (Ti), with low electronegativity and high NO 3 RR reactivity, is a compelling MNC candidate. To date, atomically dispersed TiN x motifs have eluded synthesis due to the strong oxophilicity of Ti. Here, in this work, we leverage nitrogen-rich carbon flowers (CF) to overcome synthetic challenges and produce Ti-, N-doped carbon flower (TiCF) catalysts. Advanced materials characterization demonstrates that TiCF catalysts are a mixed phase material with 3/4 of Ti atoms in TiO 2 -like nanoparticles and 1/4 of Ti atoms in novel, atomically dispersed TiN x sites. TiCF achieves 61 ± 7% NH 3 -selectivity at −0.70 V vs RHE and 14 ± 5 mA/cm 2 to NH 3 formation (| j NH 3 |) at −0.85 V vs RHE in (0.1 M NaOH + 0.1 M NaNO 3 + 0.45 M Na 2 SO 4 ) electrolyte. Control studies show both CF morphology and Ti sites are essential for high NO 3 RR activity. Density functional theory calculations attribute the NO3RR reactivity to TiN x , which facilitates multiple bond formation with surface intermediates to promote favorable NH3 synthesis pathways. Thus, TiCF exhibits 60× higher | j NH 3 | values than bulk Ti and NH 3 yield rates (>0.06 mmol NH 3 /h/cm 2 ) that are competitive with state-of-the-art MNC catalysts (e.g., FeNC, CuNC). TiCF introduces a new class of Ti electrocatalysts, advancing the MNC design space and sustainable NH 3 production.

ammonia↗
DOE OSTI2025

Photon–photon chemical thermodynamics of frequency conversion processes in highly multimode systems

Abstract Frequency generation in highly multimode nonlinear optical systems is inherently a complex process, giving rise to an exceedingly convoluted landscape of evolution dynamics. While predicting and controlling the global conversion efficiencies in such nonlinear environments has long been considered impossible, here, we formally address this challenge even in scenarios involving a very large number of spatial modes. By utilizing fundamental notions from optical statistical mechanics, we develop a universal theoretical framework that effectively treats all frequency components as chemical reactants/products, capable of undergoing optical thermodynamic reactions facilitated by a variety of multi-wave mixing effects. These photon–photon reactions are governed by conservation laws that directly determine the optical temperatures and chemical potentials of the ensued chemical equilibria for each frequency species. In this context, we develop a comprehensive stoichiometric model and formally derive an expression that relates the chemical potentials to the optical stoichiometric coefficients, in a manner akin to atomic/molecular chemical reactions. This advancement unlocks new predictive capabilities that can facilitate the optimization of frequency generation in highly multimode photonic arrangements, surpassing the limitations of conventional schemes that rely exclusively on nonlinear optical dynamics. Notably, we identify a universal regime of Rayleigh–Jeans thermalization where an optical reaction at near-zero optical temperatures can promote the complete and entropically irreversible conversion of light to the fundamental mode at a target frequency. Our theoretical results are corroborated by numerical simulations in settings where second-harmonic generation, sum-frequency generation and four-wave mixing processes can manifest.

Optics↗
DOE OSTI2020

Functional genetic encoding of sulfotyrosine in mammalian cells

Protein tyrosine O -sulfation (PTS) plays a crucial role in extracellular biomolecular interactions that dictate various cellular processes. It also involves in the development of many human diseases. Regardless of recent progress, our current understanding of PTS is still in its infancy. To promote and facilitate relevant studies, a generally applicable method is needed to enable efficient expression of sulfoproteins with defined sulfation sites in live mammalian cells. Here we report the engineering, in vitro biochemical characterization, structural study, and in vivo functional verification of a tyrosyl-tRNA synthetase mutant for the genetic encoding of sulfotyrosine in mammalian cells. We further apply this chemical biology tool to cell-based studies on the role of a sulfation site in the activation of chemokine receptor CXCR4 by its ligand. Our work will not only facilitate cellular studies of PTS, but also paves the way for economical production of sulfated proteins as therapeutic agents in mammalian systems.

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

Mechanism and inhibition of Streptococcus pneumoniae IgA1 protease

Opportunistic pathogens such as Streptococcus pneumoniae secrete a giant metalloprotease virulence factor responsible for cleaving host IgA1, yet the molecular mechanism has remained unknown since their discovery nearly 30 years ago despite the potential for developing vaccines that target these enzymes to block infection. Here we show through a series of cryo-electron microscopy single particle reconstructions how the Streptococcus pneumoniae IgA1 protease facilitates IgA1 substrate recognition and how this can be inhibited. Specifically, the Streptococcus pneumoniae IgA1 protease subscribes to an active-site-gated mechanism where a domain undergoes a 10.0 Å movement to facilitate cleavage. Monoclonal antibody binding inhibits this conformational change, providing a direct means to block infection at the host interface. These structural studies explain decades of biological and biochemical studies and provides a general strategy to block Streptococcus pneumoniae IgA1 protease activity to potentially prevent infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A conformation-selective monoclonal antibody against a small molecule-stabilised signalling-deficient form of TNF

We have recently described the development of a series of small-molecule inhibitors of human tumour necrosis factor (TNF) that stabilise an open, asymmetric, signalling-deficient form of the soluble TNF trimer. Here, we describe the generation, characterisation, and utility of a monoclonal antibody that selectively binds with high affinity to the asymmetric TNF trimer–small molecule complex. The antibody helps to define the molecular dynamics of the apo TNF trimer, reveals the mode of action and specificity of the small molecule inhibitors, acts as a chaperone in solving the human TNF–TNFR1 complex crystal structure, and facilitates the measurement of small molecule target occupancy in complex biological samples. We believe this work defines a role for monoclonal antibodies as tools to facilitate the discovery and development of small-molecule inhibitors of protein–protein interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Self-assembly and regulation of protein cages from pre-organised coiled-coil modules

Coiled-coil protein origami (CCPO) is a modular strategy for the de novo design of polypeptide nanostructures. CCPO folds are defined by the sequential order of concatenated orthogonal coiled-coil (CC) dimer-forming peptides, where a single-chain protein is programmed to fold into a polyhedral cage. Self-assembly of CC-based nanostructures from several chains, similarly as in DNA nanotechnology, could facilitate the design of more complex assemblies and the introduction of functionalities. Here, we show the design of a de novo triangular bipyramid fold comprising 18 CC-forming segments and define the strategy for the two-chain self-assembly of the bipyramidal cage from asymmetric and pseudo-symmetric pre-organised structural modules. In addition, by introducing a protease cleavage site and masking the interfacial CC-forming segments in the two-chain bipyramidal cage, we devise a proteolysis-mediated conformational switch. This strategy could be extended to other modular protein folds, facilitating the construction of dynamic multi-chain CC-based complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Enabling reactive microscopy with MicroMator

Microscopy image analysis has recently made enormous progress both in terms of accuracy and speed thanks to machine learning methods and improved computational resources. This greatly facilitates the online adaptation of microscopy experimental plans using real-time information of the observed systems and their environments. Applications in which reactiveness is needed are multifarious. Here we report MicroMator, an open and flexible software for defining and driving reactive microscopy experiments. It provides a Python software environment and an extensible set of modules that greatly facilitate the definition of events with triggers and effects interacting with the experiment. We provide a pedagogic example performing dynamic adaptation of fluorescence illumination on bacteria, and demonstrate MicroMator’s potential via two challenging case studies in yeast to single-cell control and single-cell recombination, both requiring real-time tracking and light targeting at the single-cell level.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Molecular basis of β-lactam antibiotic resistance of ESKAPE bacterium E. faecium Penicillin Binding Protein PBP5

Abstract Penicillin-binding proteins (PBPs) are essential for the formation of the bacterial cell wall. They are also the targets of β-lactam antibiotics. In Enterococcus faecium , high levels of resistance to β-lactams are associated with the expression of PBP5, with higher levels of resistance associated with distinct PBP5 variants. To define the molecular mechanism of PBP5-mediated resistance we leveraged biomolecular NMR spectroscopy of PBP5 – due to its size (>70 kDa) a challenging NMR target. Our data show that resistant PBP5 variants show significantly increased dynamics either alone or upon formation of the acyl-enzyme inhibitor complex. Furthermore, these variants also exhibit increased acyl-enzyme hydrolysis. Thus, reducing sidechain bulkiness and expanding surface loops results in increased dynamics that facilitates acyl-enzyme hydrolysis and, via increased β-lactam antibiotic turnover, facilitates β-lactam resistance. Together, these data provide the molecular basis of resistance of clinical E. faecium PBP5 variants, results that are likely applicable to the PBP family.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems

Abstract Predicting complex dynamics in physical applications governed by partial differential equations in real-time is nearly impossible with traditional numerical simulations due to high computational cost. Neural operators offer a solution by approximating mappings between infinite-dimensional Banach spaces, yet their performance degrades with system size and complexity. We propose an approach for learning neural operators in latent spaces, facilitating real-time predictions for highly nonlinear and multiscale systems on high-dimensional domains. Our method utilizes the deep operator network architecture on a low-dimensional latent space to efficiently approximate underlying operators. Demonstrations on material fracture, fluid flow prediction, and climate modeling highlight superior prediction accuracy and computational efficiency compared to existing methods. Notably, our approach enables approximating large-scale atmospheric flows with millions of degrees, enhancing weather and climate forecasts. Here we show that the proposed approach enables real-time predictions that can facilitate decision-making for a wide range of applications in science and engineering.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A quantitative comparison of the fingerprint of twinned microstructures through surface and three-dimensional techniques

Assessing the fingerprint of a material’s microstructure is key for supporting materials design. With the emergence of a wide range of 3D characterization techniques, it is critical to understand the main differences in fingerprints reconstructed from 2D and 3D datasets. To this end, we introduce a graph-based microstructure reconstruction framework that enables structural comparisons of twin domain networks in high purity Ti using 3D and 2D electron backscatter diffraction. Insights into the structure of the twin networks are facilitated by combining statistical analysis of twin crystallography with visual and graphical analysis of the novel graph abstractions of the twins. We demonstrate that compared to 3D reconstructions, conventional 2D views of twinning miss key aspects of the microstructure including the high interconnectivity of domains into networks that span the full reconstruction volume. The reduced cross-grain and in-grain twin connectivity typically observed in 2D has notable implications on our understanding of how twinning mediates the plastic response of microstructures and how twin networks evolve. It is thus clear that 3D characterization is critical for accurately inferring both twin network morphologies as well as the key unit processes facilitating network formation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Extracellular filaments revealed by affinity capture cryogenic-electron tomography

Cryogenic-electron tomography (cryo-ET) has provided an unprecedented glimpse into the nanoscale architecture of cells by combining cryogenic preservation of biological structures with electron tomography. Micropatterning of extracellular matrix proteins is increasingly used as a method to prepare adherent cell types for cryo-ET as it promotes optimal positioning of cells and subcellular regions of interest for vitrification, cryo-focused ion beam (cryo-FIB) milling, and data acquisition. Here we demonstrate a micropatterning workflow for capturing minimally adherent cell types, human T cells and Jurkat cells, for cryo-FIB and cryo-ET. Our affinity capture system facilitated the nanoscale imaging of Jurkat cells, revealing extracellular filamentous structures. It improved workflow efficiency by consistently producing grids with a sufficient number of well-positioned cells for an entire cryo-FIB session. Affinity capture can be extended to facilitate high-resolution imaging of other adherent and non-adherent cell types with cryo-ET.

Biochemistry↗
DOE OSTI2025

Contrasting age-dependent leaf acclimation strategies drive vegetation greening across deciduous broadleaf forests in mid- to high latitudes

Increasing leaf area and extending vegetation growing seasons are two primary drivers of global greening, which has emerged as one of the most significant responses to climate change. However, it remains unclear how these two leaf acclimation strategies would vary across forests at a large spatial scale. Here, in this study, using multiple satellite-based datasets and field measurements, we analysed the temporal changes (Δ) in maximal leaf area index (LAI max ) and length of the growing season (LOS) from 2002 to 2021 across deciduous broadleaf forests (DBFs) in the middle to high latitudes. Contrary to the widely held assumption of coordination, our results revealed a negative correlation between ΔLAI max and ΔLOS. Notably, the trade-offs between ΔLAImax and ΔLOS were strongly explained by stand age. Younger DBFs, with lower baseline LAI max , predominantly located in eastern Asia, displayed an increase in LAI max with small changes in LOS. This acquisitive strategy facilitated younger DBFs to grow more photosynthetically efficient leaves with low leaf mass per area, enhancing their light use efficiency. Conversely, older DBFs with a higher baseline LAI max , primarily located in North America and Europe, extended their LOS by increasing leaf mass per area. This conservative strategy facilitated older DBFs to produce thicker, but less photosynthetically efficient leaves, resulting in decreased light use efficiency. Our findings offer new insights into the contrasting changes in leaf area and growing season length and highlight their divergent impacts on ecosystem functioning.

Wang, Fangyi [Sun Yat-Sen Univ., Zhuhai (China)]↗
DOE OSTI2026

Deep generative learning of magnetic frustration in artificial spin ice from magnetic force microscopy images

Increasingly large datasets of microscopic images with nanoscale resolution facilitate the development of machine learning methods to identify and analyze subtle physical phenomena embedded within the images. In this work, microscopic images of honeycomb lattice spin-ice samples serve as datasets from which we automate the calculation of net magnetic moments and directional orientations of spin-ice configurations. In the first stage of our workflow, machine learning models are trained to accurately predict magnetic moments and directions within spin-ice structures. Variational Autoencoders (VAEs), an emergent unsupervised deep learning technique, are employed to generate high-quality synthetic magnetic force microscopy (MFM) images and extract latent feature representations, thereby reducing experimental and segmentation errors. The second stage of proposed methodology enables precise identification and prediction of frustrated vertices and nanomagnetic segments, effectively correlating structural and functional aspects of microscopic images. This facilitates the design of optimized spin-ice configurations with controlled frustration patterns, enabling potential on-demand synthesis.

36 MATERIALS SCIENCE↗