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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Tuning the Conformations of an M4L4 Cage and Their Impact on Catalysis

Enzymes catalyze chemical reactions with remarkable rate enhancements and selectivity. Supramolecular catalysis seeks to understand and emulate these outcomes, leveraging noncovalent interactions, electric fields, and controlled active site microenvironments to enhance catalysis in an enzyme-like fashion. The effects of conformational dynamics on supramolecular catalysts and assemblies are, however, relatively unexplored, despite their crucial role in enzyme rate enhancement. Here, we elucidate the conformational landscape of a model M4L4 supramolecular host through a rational approach: stabilizing a high-energy conformer through distal ligand modification and a transient intermediate state through symmetry-matched guest encapsulation, as well as tuning the conformer distribution through same-charge metal exchange at the host vertices. Each of these structural modifications induces a substantial shift in the host's conformational landscape, offering insights into the rational design of conformationally dynamic cages and enzymes. Although the thermodynamic properties of the dynamic Ga4L412- cage can be influenced by temperature, solvent, and guest binding, we find that conformational change occurs on a time scale that renders it rate-limiting in a model catalytic reaction, precluding rate enhancement through conformational selection. This concept is illustrated by locking the catalytically inactive conformer to a high-energy conformer that is catalytically competent. These findings demonstrate that precise modulation of the conformational landscape of supramolecular hosts provides an effective strategy for controlling their catalytic activity and binding.

Catalysis↗
DOE OSTI2024

Design and Evaluation of Pyridinyl Sulfonyl Piperazine LpxH Inhibitors with Potent Antibiotic Activity Against Enterobacterales

Enterobacterales, a large order of Gram-negative bacteria, including Escherichia coli and Klebsiella pneumoniae, are major causes of urinary tract and gastrointestinal infections, pneumonia, and other diseases in healthcare settings and communities. ESBL-producing Enterobacterales and carbapenem-resistant Enterobacterales can break down commonly used antibiotics, with some strains being resistant to all available antibiotics. This public health threat necessitates the development of novel antibiotics, ideally targeting new pathways in these bacteria. Gram-negative bacteria possess an outer membrane enriched with lipid A, a saccharolipid that serves as the membrane anchor of lipopolysaccharides and the active component of the bacterial endotoxin, causing septic shock. The biosynthesis of lipid A is crucial for the viability of Gram-negative bacteria, and as an essential enzyme in this process, LpxH has emerged as a promising target for developing novel antibiotics against multidrugresistant Gram-negative pathogens. Here, we report the development of pyridinyl sulfonyl piperazine LpxH inhibitors. Among them, ortho-substituted pyridinyl compounds significantly boost LpxH inhibition and antibiotic activity over the original phenyl series. Structural and QM/MM analyses reveal that these improved activities are primarily due to the enhanced interaction between F141 of the LpxH insertion lid and the pyridinyl group. Incorporation of the N-methyl-N-phenyl-methanesulfonamide moiety into the pyridinyl sulfonyl piperazine backbone results in JHLPH- 106 and JH-LPH-107, both of which exhibit potent antibiotic activity against wild-type Enterobacterales such as K. pneumoniae and E. coli. JH-LPH-107 exhibits a low rate of spontaneous resistance and a high safety window in vitro, rendering it an excellent lead for further clinical development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Simulation of Microcapsule Transport in Fractured Media Using Coupled CFD‐DEM

Geothermal energy is sustainable and gaining momentum as a solution to energy crises and environmental issues. However, challenges like production temperature and thermal breakthrough can impact geothermal project efficiency. One innovative solution to alleviate the thermal breakthrough is to inject polymer-based materials that are encapsulated in microcapsules into fractures to modify fracture permeability and prevent preferential flow. In our study, we utilized a coupled computational fluid dynamics and discrete element method to simulate the transport of microcapsules under various scenarios controlled by microcapsule size, microcapsule concentration, and fracture roughness. For a smooth fracture, the results indicate that small microcapsules can travel through a smooth fracture regardless of their concentrations. Large microcapsules can transport through a smooth fracture when present in lower concentrations. However, medium and mixed-size microcapsules tend to cause the sealing of a smooth fracture, irrespective of their concentrations. For a rough fracture, the transport of microcapsules is complicated by their interactions with the rough fracture walls. The presence of two sealing positions in a rough fracture adds further complexity to this transport phenomenon. The size and concentration of microcapsules control one sealing location, while the rough fracture walls determine the other sealing location. The rough walls substantially affect microcapsule transport, rendering the role of microcapsule size and concentration less significant. The simulation results suggest that complex fracture surfaces significantly elevate the occurrence of sealing behavior. To mitigate sealing behavior within more complex fractures, it would be beneficial to use smaller and lower concentrations of microcapsules.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Learning Physically Interpretable Atmospheric Models From Data With WSINDy

The multiscale and turbulent nature of Earth's atmosphere has historically rendered accurate weather modeling a hard problem. Recently, there has been an explosion of interest surrounding data-driven approaches to weather modeling, which in many cases show improved forecasting accuracy and computational efficiency when compared to traditional methods. However, many of the current data-driven approaches employ highly parameterized neural networks, often resulting in uninterpretable models and limited gains in scientific understanding. In this work, we address the interpretability problem by explicitly discovering partial differential equations governing atmospheric phenomena, identifying symbolic mathematical models with direct physical interpretations. The purpose of this paper is to demonstrate that, in particular, the weak-form sparse identification of nonlinear dynamics (WSINDy) algorithm can learn effective atmospheric models from both simulated and assimilated data. Our approach adapts the standard WSINDy algorithm to work with high-dimensional fluid data of arbitrary spatial dimension.

58 GEOSCIENCES↗
DOE OSTI2024

Electrothermal mineralization of per- and polyfluoroalkyl substances for soil remediation

Abstract Per- and polyfluoroalkyl substances (PFAS) are persistent and bioaccumulative pollutants that can easily accumulate in soil, posing a threat to environment and human health. Current PFAS degradation processes often suffer from low efficiency, high energy and water consumption, or lack of generality. Here, we develop a rapid electrothermal mineralization (REM) process to remediate PFAS-contaminated soil. With environmentally compatible biochar as the conductive additive, the soil temperature increases to >1000 °C within seconds by current pulse input, converting PFAS to calcium fluoride with inherent calcium compounds in soil. This process is applicable for remediating various PFAS contaminants in soil, with high removal efficiencies ( >99%) and mineralization ratios ( >90%). While retaining soil particle size, composition, water infiltration rate, and cation exchange capacity, REM facilitates an increase of exchangeable nutrient supply and arthropod survival in soil, rendering it superior to the time-consuming calcination approach that severely degrades soil properties. REM is scaled up to remediate soil at two kilograms per batch and promising for large-scale, on-site soil remediation. Life-cycle assessment and techno-economic analysis demonstrate REM as an environmentally friendly and economic process, with a significant reduction of energy consumption, greenhouse gas emission, water consumption, and operation cost, when compared to existing soil remediation practices.

Science & Technology - Other Topics↗
DOE OSTI2025

An impermeable copper surface monolayer with high-temperature oxidation resistance

Despite numerous efforts involving surface coating, doping, and alloying, maintaining surface stability of metal at high temperatures without compromising intrinsic properties has remained challenging. Here, we present a pragmatic method to address the accelerated oxidation of Cu, Ni, and Fe at temperatures exceeding 200 °C. Inspired by the concept that oxygen (O) itself can effectively obstruct the pathway of O infiltration, this study proposes the immobilization of O on the metal surface. Through extensive calculations considering various elements (C, Al, Si, Ge, Ga, In, and Sn) to anchor O on Cu surfaces, Si emerges as the optimal element. The theoretical findings are validated through systematic sputtering deposition experiments. The introduction of anchoring elements to reinforce Cu–O bonds enables the formation of an atomically thin barrier on the Cu surface, rendering it impermeable to O even at high temperatures (400 °C) while preserving its intrinsic conductivity. This oxidation resistance, facilitated by the impermeable atomic monolayer, opens promising opportunities for researchers and industries to overcome limitations associated with the use of oxidizable metal films.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Structural basis for the subtype-selectivity of K Ca 2.2 channel activators

Small-conductance (K Ca 2.2) and intermediate-conductance (K Ca 3.1) Ca 2+ -activated K + channels are gated by a Ca 2+ -calmodulin dependent mechanism. NS309 potentiates the activity of both K Ca 2.2 and K Ca 3.1, while rimtuzalcap selectively activates K Ca 2.2. Rimtuzalcap has been used in clinical trials for the treatment of spinocerebellar ataxia and essential tremor. We report cryo-electron microscopy structures of NS309-bound K Ca 2.2 and K Ca 3.1, in addition to structures of rimtuzalcap-bound K Ca 2.2 and mutant K Ca 3.1_R355K. The different conformations of calmodulin and the cytoplasmic HC helices in the two channels underlie the subtype-selectivity of rimtuzalcap for K Ca 2.2. NS309 binds to pre-existing pockets in both channels, while the bulkier rimtuzalcap binds in an induced-fit pocket in K Ca 2.2 requiring conformational changes. In K Ca 2.2, calmodulin’s N-lobes are sufficiently far apart to enable conformational changes to accommodate either NS309 or rimtuzalcap. In K Ca 3.1, calmodulin’s N-lobes are closer to each other and constrained by K Ca 3.1’s HC helices, which allows binding of NS309 but not rimtuzalcap. Replacement of arginine-355 in K Ca 3.1’s HB helix with lysine (K Ca 3.1_R355K) allows the binding of rimtuzalcap and renders the mutant channel sensitive to rimtuzalcap. These structures provide a framework for structure-based drug design targeting K Ca 2.2 channels.

Nam, Young-Woo [Chapman Univ., Irvine, CA (United ↗
DOE OSTI2026

Amplified response of cavity-coupled quantum-critical systems

A quantum critical point develops when matter undergoes a continuous transformation between distinct ground states at absolute zero. It hosts pronounced quantum fluctuations, which render the system highly susceptible to external perturbations. While light-matter coupling has rapidly moved forward as a means to probe and control quantum materials, the capacity of quantum critical fluctuations in the photon-mediated responses has been largely unexplored. Here we advance the notion that directly coupling a quantum critical mode to a quantized cavity field dramatically facilitates the realization of the elusive superradiant phase transition in equilibrium, circumventing at once the key obstacles that have prevented its attainment in spite of decades of pursuit. The superradiant phase transition develops far below the ultrastrong regime of light-matter couplings, and the transition is accompanied by the light-matter hybrid system showing strongly enhanced intrinsic squeezing and amplified quantum Fisher information. We also identify candidate cavity quantum materials platforms for validating the proposed effect. Our findings suggest a general principle by which quantum criticality amplifies the response to cavity photons. They also demonstrate that cavity coupling accesses the elevated quantum entanglement of the underlying matter at quantum criticality, thereby pointing to a pathway towards realizing the potential of highly collective quantum materials to expand the capacities of quantum information science.

Sur, Shouvik [Rice Univ., Houston, TX (United Stat↗
DOE OSTI2023

A physics informed bayesian optimization approach for material design: application to NiTi shape memory alloys

Abstract The design of materials and identification of optimal processing parameters constitute a complex and challenging task, necessitating efficient utilization of available data. Bayesian Optimization (BO) has gained popularity in materials design due to its ability to work with minimal data. However, many BO-based frameworks predominantly rely on statistical information, in the form of input-output data, and assume black-box objective functions. In practice, designers often possess knowledge of the underlying physical laws governing a material system, rendering the objective function not entirely black-box, as some information is partially observable. In this study, we propose a physics-informed BO approach that integrates physics-infused kernels to effectively leverage both statistical and physical information in the decision-making process. We demonstrate that this method significantly improves decision-making efficiency and enables more data-efficient BO. The applicability of this approach is showcased through the design of NiTi shape memory alloys, where the optimal processing parameters are identified to maximize the transformation temperature.

Chemistry↗
DOE OSTI2026

Machine learning pipeline for denoising low signal-to-noise ratio and out-of-distribution transmission electron microscopy datasets

High-resolution transmission electron microscopy (HRTEM) is crucial for observing material’s structural and morphological evolution at Angstrom scales, but the electron beam can alter these processes. Devices such as CMOS-based direct-electron detectors operating in electron-counting mode can be utilized to substantially reduce the electron dosage. However, the resulting images often lead to a low signal-to-noise ratio, which requires frame integration that sacrifices temporal resolution. Several machine learning (ML) models have been recently developed to successfully denoise HRTEM images. Yet, these models are often computationally expensive, and their inference speeds on GPUs are outpaced by the imaging speed of advanced detectors, precluding in situ analysis. Furthermore, the performance of these denoising models on datasets with imaging conditions that deviate from the training datasets has not been evaluated. To mitigate these gaps, we propose a new self-supervised ML denoising pipeline specifically designed for time-series HRTEM images. This pipeline integrates a blind-spot convolution neural network with pre-processing and post-processing steps, including drift correction and low-pass filtering. Results demonstrate that our model outperforms various other ML and non-ML denoising methods in noise reduction and contrast enhancement, leading to improved visual clarity of atomic features. Additionally, the model is drastically faster than U-Net-based ML models and demonstrates excellent out-of-distribution generalization. The model’s computational inference speed is in the order of milliseconds per image, rendering it suitable for application in in-situ HRTEM experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Extending the computational reach of a superconducting qutrit processor

Quantum computing with qudits is an emerging approach that exploits a larger, more connected computational space, providing advantages for many applications, including quantum simulation and quantum error correction. Nonetheless, qudits are typically afflicted by more complex errors and suffer greater noise sensitivity which renders their scaling difficult. In this work, we introduce techniques to tailor arbitrary qudit Markovian noise to stochastic Weyl–Heisenberg channels and mitigate noise that commutes with our Clifford and universal two-qudit gate in generic qudit circuits. We experimentally demonstrate these methods on a superconducting transmon qutrit processor, and benchmark their effectiveness for multipartite qutrit entanglement and random circuit sampling, obtaining up to 3× improvement in our results. To the best of our knowledge, this constitutes the first-ever error mitigation experiment performed on qutrits. Our work shows that despite the intrinsic complexity of manipulating higher-dimensional quantum systems, noise tailoring and error mitigation can significantly extend the computational reach of today’s qudit processors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Plasmon-enhanced ultralow-threshold solid-state triplet fusion upconversion

Triplet fusion upconversion has potential applications in solar cells, photoredox catalysis, additive manufacturing and bioimaging. However, solid-state upconversion systems have struggled to measure up to their solution-phase counterparts, often requiring enormous optical power densities to operate at the maximum efficiency. Here we substantially improve the performance of upconversion films through excitation with surface plasmons that propagate along a planar silver-film interface, leading to an absorption enhancement that reduces the intensity threshold I th by a factor of 19 and enhances the external quantum efficiency by a factor of 17. From this, we achieve I th values as low as 3.4 mW cm −2 and an external quantum efficiency up to 0.094%. To demonstrate real-world viability, we couple the upconversion film to plasmons generated by the near-field of excitons in an organic light-emitting diode. As a result, this scheme is then used to fabricate a white-emitting organic light-emitting diode where blue emission sources from plasmon-excited upconversion, achieving a high colour rendering index of 86.2 and setting precedent for blue emission in the absence of high-energy polarons or triplets.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Optomechanical self-organization in a mesoscopic atom array

Increasing the number of particles in a system often leads to qualitative changes in its properties, such as breaking of symmetries and the appearance of phase transitions. This renders a macroscopic system fundamentally different from its individual microscopic constituents. Lying between these extremes, mesoscopic systems exhibit microscopic fluctuations that influence behaviour on longer length scales, leading to critical phenomena and dynamics. Therefore, tracing the properties of well-controlled mesoscopic systems can help bridge the gap between an exact description of few-body microscopic systems and the emergent description of many-body systems. Here we explore the mesoscopic signatures of an optomechanical self-organization phase transition using arrays of cold atoms inside an optical cavity. By precisely engineering atom–cavity interactions, we reveal how critical behaviour depends on the atom number, identify characteristic dynamical behaviours in the self-organized regime and observe a finite optomechanical susceptibility at the critical point. These findings advance our understanding of particle-number- and time-resolved properties of phase transitions in mesoscopic systems.

Atomic and molecular interactions with photons↗
DOE OSTI2025

Visible-to-THz near-field nanoscopy

Optical microscopy has a key role in research, development and quality control across a wide range of scientific, technological and medical fields. However, diffraction limits the spatial resolution of conventional optical instruments to about half the illumination wavelength. A technique that surpasses the diffraction limit in the wide spectral range between visible and terahertz frequencies is scattering-type scanning near-field optical microscopy (s-SNOM). The basis of s-SNOM is an atomic force microscope in which the tip is illuminated with light from the visible to the terahertz spectral range. By recording the elastically tip-scattered light while scanning the sample below the tip, s-SNOM yields near-field optical images with a remarkable resolution of 10 nm, simultaneously with the standard atomic force microscopic topography image. This resolution is independent of the illumination wavelength, rendering s-SNOM a versatile nanoimaging and nanospectroscopy technique for fundamental and applied studies of materials, structures and phenomena. This Review presents an overview of the fundamental principles governing the measurement and interpretation of near-field contrasts and discusses key applications of s-SNOM. We also showcase emerging developments that enable s-SNOM to operate under various environmental conditions, including cryogenic temperatures, electric and magnetic fields, electrical currents, strain and liquid environments. Furthermore, all these recent developments broaden the applicability of s-SNOMs for exploring fundamental solid-state and quantum phenomena, biological matter, catalytic reactions and more.

Hillenbrand, Rainer [CIC nanoGUNE BRTA and Departm↗
DOE OSTI2025

Diet outperforms microbial transplant to drive microbiome recovery in mice

A high-fat, low-fibre Western-style diet (WD) induces microbiome dysbiosis characterized by reduced taxonomic diversity and metabolic breadth, which in turn increases risk for a wide array of metabolic, immune and systemic pathologies. Recent work has established that WD can impair microbiome resilience to acute perturbations such as antibiotic treatment, although little is known about the mechanism of impairment and the specific consequences for the host of prolonged post-antibiotic dysbiosis. Here, in this study, we characterize the trajectory by which the gut microbiome recovers its taxonomic and functional profile after antibiotic treatment in mice on regular chow (RC) or WD, and find that only mice on RC undergo a rapid successional process of recovery. Metabolic modelling indicates that a RC diet promotes the development of syntrophic cross-feeding interactions, whereas in mice on WD, a dominant taxon monopolizes readily available resources without releasing syntrophic byproducts. Intervention experiments reveal that an appropriate dietary resource environment is both necessary and sufficient for rapid and robust microbiome recovery, whereas microbial transplant is neither. Furthermore, prolonged post-antibiotic dysbiosis in mice on WD renders them susceptible to infection by the intestinal pathogen Salmonella enterica serovar Typhimurium. Our data challenge widespread enthusiasm for faecal microbiota transplant (FMT) as a strategy to address dysbiosis, and demonstrate that specific dietary interventions are, at a minimum, an essential prerequisite for effective FMT, and may afford a safer, more natural and less invasive alternative.

Kennedy, M. S. [University of Chicago, IL (United ↗
DOE OSTI2024

Enabling high-throughput enzyme discovery and engineering with a low-cost, robot-assisted pipeline

Abstract As genomic databases expand and artificial intelligence tools advance, there is a growing demand for efficient characterization of large numbers of proteins. To this end, here we describe a generalizable pipeline for high-throughput protein purification using small-scale expression in E. coli and an affordable liquid-handling robot. This low-cost platform enables the purification of 96 proteins in parallel with minimal waste and is scalable for processing hundreds of proteins weekly per user. We demonstrate the performance of this method with the expression and purification of the leading poly(ethylene terephthalate) hydrolases reported in the literature. Replicate experiments demonstrated reproducibility and enzyme purity and yields (up to 400 µg) sufficient for comprehensive analyses of both thermostability and activity, generating a standardized benchmark dataset for comparing these plastic-degrading enzymes. The cost-effectiveness and ease of implementation of this platform render it broadly applicable to diverse protein characterization challenges in the biological sciences.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Broadband coherent XUV light from e − / e + microbunching in an intense laser pulse

Attosecond pulses of coherent extreme ultraviolet (XUV) light are instrumental for investigating subatomic dynamics and can be produced using a free-electron laser (FEL). It has been suggested that an optical FEL, which employs a laser pulse in place of a conventional undulator, could enable a dramatically more compact implementation of such a light source. Yet, the high electron density and subsequent high emittance implied by an optical FEL makes this concept challenging to realize with an electron beam. There has been impressive progress in recent years producing collimated dense and relativistic beams of electrons and positrons in the laboratory. As we demonstrate here, the inherent stability of a quasi-neutral electron-positron beam mitigates Coulomb expansion, and renders it a promising alternative source of coherent light. Specifically, we show via computer simulations that broadband coherent light in the XUV domain, which takes the form of 8-as pulses at 92-as intervals, can be generated by microbunching of relativistic electrons and positrons in a laser pulse. This process occurs over a sub-millimeter length scale, enabling the development of light sources which are orders-of-magnitude more compact than existing sources, with potential applications in physics, chemistry, biology, and industry.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

How fast ions mitigate turbulence and enhance confinement in tokamak fusion plasmas

Along with high temperature and density, magnetic fusion requires good confinement and a degree of transport control for thermal plasmas. Meanwhile, fast ions are generated by the external heating used to raise plasma temperature and by the fusion reactions. As a result, the fusion plasmas are effectively rendered into systems with two coexisting populations of main interest — namely, the fast ions and the thermal plasma. Interestingly, several recent experiments indicate that the fast-ion population can improve the confinement of the thermal plasmas by mitigating turbulence. Here, in this Review, we describe the physical mechanisms that underpin the improved confinement and discuss recent experimental results in terms of these mechanisms.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗