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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Thermodynamic Control of Activity Patterns in Cytoskeletal Networks

Biological materials, such as the actin cytoskeleton, exhibit remarkable structural adaptability to various external stimuli by consuming different amounts of energy. In this Letter, we use methods from large deviation theory to identify a thermodynamic control principle for structural transitions in a model cytoskeletal network. Specifically, we demonstrate that biasing the dynamics with respect to the work done by nonequilibrium components effectively renormalizes the interaction strength between such components, which can eventually result in a morphological transition. Further, our work demonstrates how a thermodynamic quantity can be used to renormalize effective interactions, which in turn can tune structure in a predictable manner, suggesting a thermodynamic principle for the control of cytoskeletal structure and dynamics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Superfluorescence from Electron-Hole Plasma at Moderate Temperatures of 175 K

Superfluorescence, a cooperative coherent spontaneous emission, is of great importance to the understanding of many-body correlation in optical processes. Even though superfluorescence has been demonstrated in many diverse systems, it is hard to observe in electron-hole plasma (EHP) due to its rapid dephasing and hence needs strong magnetic fields or complex microcavities. Herein, we report the first experimental observation of superfluorescence from EHP up to a moderate temperature of 175 K without external stimuli in a coupled metal halide perovskite quantum dots film. The EHP exhibits macroscopic quantum coherence through spontaneous synchronization. The coherence of the excited state decays by superfluorescence, which is redshifted 40 meV from the spontaneous emission with a ~1700 times faster decay rate and exhibits quadratic fluence dependence. Notably, the excited state population's delayed growth and abrupt decay, which are strongly influenced by the pump fluence and the Burnham-Chiao ringing, are the characteristics of the superfluorescence. Our findings will open up a new frontier for cooperative emission and light beam-based technologies.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS↗
DOE OSTI2025

Giant Nonreciprocity and Gyration through Modulation-Induced Hatano-Nelson Coupling in Integrated Photonics

Asymmetric energy exchange interactions, also known as Hatano-Nelson type couplings, enable the study of non-Hermitian physics and associated phenomena like the non-Hermitian skin effect and exceptional points (EPs). Since these interactions are by definition nonreciprocal, there have been very few options for implementations in integrated photonics. Here, in this work, we show that asymmetric couplings are readily achievable in integrated photonic systems through time-domain dynamic modulation. We experimentally study this concept using a two-resonator photonic molecule produced in a lithium niobate on insulator platform that is electro-optically modulated by rf stimuli. We demonstrate the dynamic tuning of the Hatano-Nelson coupling between the resonators, surpassing the asymmetry that has been achieved in previous work, to reach an EP for the first time. We are additionally able to flip the relative sign of the couplings for opposite directions by going past the EP. Using this capability, we show that the through-chain transport can be configured to exhibit both giant (~60 dB) optical contrast as well as photonic gyration or nonreciprocal π phase contrast.

42 ENGINEERING↗
DOE OSTI2022

Unusual magnetic and transport properties in HoMn 6 Sn 6 kagome magnet

Here, with intricate lattice structures, kagome materials are an excellent platform to study various fascinating topological quantum states. In particular, kagome materials, revealing large responses to external stimuli such as pressure or magnetic field, are subject to special investigation. Here we study the kagome-net HoMn 6 Sn 6 magnet that undergoes paramagnetic to ferrimagnetic transition (below 376 K) and reveals spin-reorientation transition below 200 K. In this compound, we observe the topological Hall effect and substantial contribution of anomalous Hall effect above 100 K. We unveil the pressure effects on magnetic ordering at a low magnetic field from the pressure tunable magnetization measurement. By utilizing high-resolution angle-resolved photoemission spectroscopy, Dirac-like dispersion at the high-symmetry point K is revealed in the vicinity of the Fermi level, which is well supported by the first-principles calculations. Our investigation will pave the way to understanding the magnetotransport and electronic properties of various rare-earth-based kagome magnets.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Topological Hall effect in CeAlGe

The Weyl semimetal CeAlGe is a promising material to study nontrivial topologies in real and momentum space due to the presence of a topological magnetic phase. Our results at ambient pressure show that the electronic properties of CeAlGe are extremely sensitive to small stoichiometric variations. In particular, the topological Hall effect (THE) present in CeAlGe is absent in some samples of almost identical chemical composition. The application of external pressure favors the antiferromagnetic ground state. It also induces a THE where it was not visible at ambient pressure. Furthermore, a small pressure is sufficient to drive the single region of the THE in magnetic fields into two different ones. Our results reveal an extreme sensitivity of the electronic properties of CeAlGe to tiny changes in its chemical composition, leading to a high tunability by external stimuli. We can relate this sensitivity to a shift in the Fermi level and to domain walls.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Emergent topological quasiparticle kinetics in constricted nanomagnets

The ubiquitous domain wall kinetics under magnetic field or current application describes the dynamic properties in nanostructured magnets. However, when the geometrical size of a nanomagnetic system is constricted to the limiting domain wall length scale, the competing energetics between anisotropy, exchange, and dipolar interactions can cause emergent kinetics due to quasiparticle relaxation, similar to bulk magnets of atomic origin. This paper presents a joint experimental and theoretical study to support this argument: constricted nanomagnets, made of antiferromagnetic and paramagnetic neodymium thin film with honeycomb motif, reveal fast kinetic events at picosecond timescales due to the relaxation of topological quasiparticles that persist to low temperature in the absence of any external stimuli. This discovery is especially important considering the fact that paramagnets or antiferromagnets have no net magnetization. Yet, the kinetics in neodymium nanostructures is quantitatively similar to that found in ferromagnetic counterparts and only varies with the thickness of the specimen. This suggests that a universal, topological quasiparticle-mediated dynamical behavior can be prevalent in nanoscopic magnets, irrespective of the nature of the underlying magnetic material.

Guo, Jiasen↗
DOE OSTI2025

Light-Induced Reorientation Transition in an Antiferromagnetic Semiconductor

Because of the lack of a net magnetic moment, antiferromagnets possess a unique robustness to external magnetic fields and are thus predicted to play an important role in future magnetic technologies. However, this robustness also makes them quite difficult to control, and the development of novel methods to manipulate these systems with external stimuli is a fundamental goal of antiferromagnetic spintronics. In this work, we report evidence for a metastable reorientation of the order parameter in an antiferromagnetic semiconductor triggered by an ultrafast quench of the equilibrium order via photoexcitation above the band gap. The metastable state forms less than 10 ps after the excitation pulse, and persists for longer than 150 ps before decaying to the ground state via thermal fluctuations. Importantly, this transition cannot be induced thermodynamically, and requires the system to be driven out of equilibrium. Broadly speaking, this phenomenology is ultimately the result of large magnetoelastic coupling in combination with a relatively low symmetry of the magnetic ground state. Since neither of these properties are particularly uncommon in magnetic materials, the observations presented here imply a generic path toward novel device technology enabled by ultrafast dynamics in antiferromagnets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Rapid detection of rare events from in situ X-ray diffraction data using machine learning

High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk form. These methods are often combined with external stimuli such as thermo-mechanical loading to take snapshots of the evolving microstructure and attributes over time. However, the extreme data volumes and the high costs of traditional data acquisition and reduction approaches pose a barrier to quickly extracting actionable insights and improving the temporal resolution of these snapshots. This article presents a fully automated technique capable of rapidly detecting the onset of plasticity in high-energy X-ray microscopy data. The technique is computationally faster by at least 50 times than the traditional approaches and works for data sets that are up to nine times sparser than a full data set. This new technique leverages self-supervised image representation learning and clustering to transform massive data sets into compact, semantic-rich representations of visually salient characteristics ( e.g. peak shapes). These characteristics can rapidly indicate anomalous events, such as changes in diffraction peak shapes. It is anticipated that this technique will provide just-in-time actionable information to drive smarter experiments that effectively deploy multi-modal X-ray diffraction methods spanning many decades of length scales.

Zheng, Weijian↗
DOE OSTI2025

The varying temperature- and pressure-induced phase transition pathways in hybrid improper ferroelectric Sr 3 Sn 2 O 7

A variable-temperature and pressure single-crystal diffraction study of hybrid improper ferroelectric Sr 3 Sn 2 O 7 is reported. In combination with symmetry analysis, we reveal that the application of pressure and temperature induce distinct phase transition pathways, driven by a differing response of the octahedral rotations to these stimuli. Contrary to what has been previously predicted, we observe the ferroelectric to paraelectric phase transition between 10.17(18) and 12.13(14) GPa, meaning the hybrid improper ferroelectric phase remains stable to significantly higher pressures than expected.

Ferroelectrics↗
DOE OSTI2023

Determining biomolecular structures near room temperature using X-ray crystallography: concepts, methods and future optimization

For roughly two decades, cryocrystallography has been the overwhelmingly dominant method for determining high-resolution biomolecular structures. Competition from single-particle cryo-electron microscopy and micro-electron diffraction, increased interest in functionally relevant information that may be missing or corrupted in structures determined at cryogenic temperature, and interest in time-resolved studies of the biomolecular response to chemical and optical stimuli have driven renewed interest in data collection at room temperature and, more generally, at temperatures from the protein–solvent glass transition near 200 K to ∼350 K. Fischer has recently reviewed practical methods for room-temperature data collection and analysis [Fischer (2021), Q. Rev. Biophys. 54 , e1]. Here, the key advantages and physical principles of, and methods for, crystallographic data collection at noncryogenic temperatures and some factors relevant to interpreting the resulting data are discussed. For room-temperature data collection to realize its potential within the structural biology toolkit, streamlined and standardized methods for delivering crystals prepared in the home laboratory to the synchrotron and for automated handling and data collection, similar to those for cryocrystallography, should be implemented.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Counter Data Paucity through Adversarial Invariance Encoding: A Case Study on Modeling Battery Thermal Runaway

Lithium-ion batteries, widely used for their durability and high energy storage, face the risk of internal short circuits leading to catastrophic thermal runaway events. These events, triggered by external stimuli like mechanical loads, pose safety concerns in applications such as electric vehicles. Detecting and understanding thermal runaway events is crucial, but physics-driven models struggle to explain the non-linear evolution of battery temperature during these events, considering factors like material composition and state-of-charge. Due to the rarity of these events and the cost of data collection, we propose a deep learning (DL) model to predict battery temperature responses during thermal runaway. The challenge lies in the scarcity of data, making traditional DL models prone to overfitting and learning low-quality representations of the complex process.Our approach introduces a novel few-shot architecture that incorporates an adversarially governed invariant encoding process. This architecture aims to distill "invariant" relationships by addressing distributional shifts in data across various battery properties, facilitating the detection of thermal runaway events. Specifically, our results demonstrate that deep learning models conditioned on these "invariant" representations outperform state-of-the-art baselines, achieving a remarkable 96.8% performance improvement in terms of the popular metric MAPE. This framework presents a promising direction for enhancing battery safety modeling, particularly in the context of rare and complex events like thermal runaway. Our code and code and dataset used for the paper are public1.

Tabassum, Anika [ORNL] (ORCID:0000000254600955)↗
DOE OSTI2021

Algorithm-Driven Advances for Scientific CT Instruments: From model-based to deep learning-based approaches

Multiscale 3D characterization is widely used by materials scientists to further their understanding of the relationships between microscopic structure and macroscopic function. Scientific computed tomography (SCT) instruments are one of the most popular choices for 3D nondestructive characterization of materials at length scales ranging from the angstrom scale to the micron scale. These instruments typically have a source of radiation (such as electrons, X-rays, or neutrons) that interacts with the sample to be studied and a detector assembly to capture the result of this interaction (see Figure 1 ). A collection of such high-resolution measurements is made by reorienting the sample, which is mounted on a specially designed stage/holder after which reconstruction algorithms are used to produce the final 3D volume of interest. The specific choice of which instrument to use depends on the desired resolution and properties of the materials being imaged. Additionally, the end goal of SCT scans includes determining the morphology, chemical composition, or dynamic behavior of materials when subjected to external stimuli. In summary, SCT instruments are powerful tools that enable 3D characterization across multiple length scales and play a critical role in furthering the understanding of the structure–function relationships of different materials.

42 ENGINEERING↗
DOE OSTI2026

NeuroCoreX: An Open-Source FPGA-Based Spiking Neural Network Emulator with On-Chip Learning

Spiking Neural Networks (SNNs) are computational models inspired by the event-driven communication and connectivity patterns of biological neural circuits. They enable high energy efficiency and natural support for diverse architectures ranging from layered networks to small-world and graphstructured topologies. In this work, we introduce NeuroCoreX, an open-source, FPGA-based spiking neural network emulator that provides real-time, on-chip learning and flexible network organization. NeuroCoreX supports both feedforward sensory inputs streamed directly from sensors or PCs via UART and recurrent on-chip connectivity, enabling simultaneous processing and learning from external stimuli and internal network dynamics-capabilities rarely available in existing FPGA SNN platforms. The system implements a Leaky Integrate-and-Fire (LIF) neuron model with current-based synapses and supports pair-based STDP learning on both feedforward and recurrent synapses. A lightweight Python interface enables interactive configuration, live monitoring, weight read-back, and experiment control. Importantly, NeuroCoreX is tightly integrated with the SuperNeuroMAT simulator, allowing SNN models to be transferred seamlessly from software to hardware for hardware-in-the-loop development. By combining real-time plasticity, flexible connectivity, and an open-source VHDL implementation, NeuroCoreX provides an extensible and accessible platform for neuromorphic research, algorithm-hardware co-design, and energy-efficient edge intelligence.

Gautam, Ashish [ORNL]↗
DOE OSTI2021

Biological mechanisms may contribute to soil carbon saturation patterns

Increasing soil organic carbon (SOC) storage is a key strategy to mitigate rising atmospheric CO 2 , yet SOC pools often appear to saturate, or increase at a declining rate, as carbon (C) inputs increase. Soil C saturation is commonly hypothesized to result from the finite amount of reactive mineral surface area available for retaining SOC, and is accordingly represented in SOC models as a physicochemically determined SOC upper limit. However, mineral-associated SOC is largely microbially generated. In this perspective, we present the hypothesis that apparent SOC saturation patterns could emerge as a result of ecological constraints on microbial biomass—for example, via competition or predation—leading to reduced C flow through microbes and a reduced rate of mineral-associated SOC formation as soil C inputs increase. Microbially explicit SOC models offer an opportunity to explore this hypothesis, yet most of these models predict linear microbial biomass increases with C inputs and insensitivity of SOC to input rates. Synthesis of 54 C addition studies revealed constraints on microbial biomass as C inputs increase. Different hypotheses limiting microbial density were embedded in a three-pool SOC model without explicit limits on mineral surface area. As inputs increased, the model demonstrated either no change, linear, or apparently saturating increases in mineral-associated and particulate SOC pools. Taken together, our results suggest that microbial constraints are common and could lead to reduced mineral-associated SOC formation as input rates increase. We conclude that SOC responses to altered C inputs—or any environmental change—are influenced by the ecological factors that limit microbial populations, allowing for a wider range of potential SOC responses to stimuli. Understanding how biotic versus abiotic factors contribute to these patterns will better enable us to predict and manage soil C dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Functional Adaptation of LPS-affected Dentoalveolar Fibrous Joints in Rats

We report the functional interplay between cementum of the root and alveolar bone of the socket is tuned by a uniquely positioned 70–80 µm wide fibrous and lubricious ligament in a dentoalveolar joint (DAJ). In this study, structural and biomechanical properties of the DAJ, periodontal ligament space (PDL-space also known as the joint space), alveolar bone of the socket, and cementum of the tooth root that govern the biomechanics of a lipopolysaccharide (LPS)-affected DAJ were mapped both in space and time. The hemi-maxillae from 20 rats (4 control at 6 weeks of age, 4 control and 4 LPS-affected at 12 weeks of age, 4 control and 4 LPS-affected at 16 weeks of age) were investigated using a hybrid technique; micro-X-ray computed tomography (5 µm resolution) in combination with biomechanical testing in situ. Temporal variations in bone and cementum volume fractions were evaluated. Trends in mineral apposition rates (MAR) in additional six Sprague Dawley rats (3 controls, 3 LPS-affected) were revealed by transforming spatial fluorochrome signals to functional growth rates (linearity factor - RW) of bone, dentin, and cementum using a fast Fourier transform on fluorochrome signals from 100-µm hemi-maxillae sections. An overall change in LPS-affected DAJ biomechanics (a 2.5–4.5X increase in tooth displacement and 2X tooth rotation at 6 weeks, no increase in displacement and a 7X increase in rotation at 12 weeks; 27% increase in bone effective strain at 6 weeks and 11% at 12 weeks relative to control) was associated with structural changes in the coronal regions of the DAJ (15% increase in PDL-space from 0 to 6 weeks but only 5% from 6 to 12 weeks compared to control). A significant increase (p < 0.05) in PDL-space between ligated and age-matched control was observed. The bone fraction of ligated at 12 weeks was significantly lower than its age-matched control, and no significant differences (p > 0.05) between groups were observed at 6 weeks. Cementum in the apical regions grew faster but nonlinearly (11% and 20% increase in cementum fraction (CF) at 6 and 12 weeks) compared to control. Alveolar bone revealed site-specific nonlinear growth with an overall increase in MAR (108.5 µm/week to 126.7 µm/week after LPS treatment) compared to dentin (28.3 µm/week in control vs. 26.1 µm/week in LPS-affected) and cementum (126.5 µm/week in control vs. 119.9 µm/week in LPS-affected). A significant increase in CF (p < 0.05) in ligated specimens was observed at 6 weeks of age. Anatomy-specific responses of cementum and bone to the mechano-chemo stimuli, and their collective temporal contribution to observed changes in PDL-space were perpetuated by altered tooth movement. Data highlight the “resilience” of DAJ function through the predominance of nonlinear growth response of cementum, changes in PDL-space, and bone architecture. Despite the significant differences in bone and cementum architectures, data provided insights into the reactionary effects of cementum as a built-in compensatory mechanism to reestablish functional competence of the DAJ. The spatial shifts in architectures of alveolar bone and cementum, and consequently ligament space, highlight adaptations farther away from the site of insult, which also is another novel insight from this study. These adaptations when correlated within the context of joint function (biomechanics) illustrate that they are indeed necessary to sustain DAJ function albeit being pathological.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

OSCA1 is an osmotic specific sensor: a method to distinguish Ca 2+ -mediated osmotic and ionic perception

Genetic mutants defective in stimulus-induced Ca 2+ increases have been gradually isolated, allowing the identification of cell-surface sensors/receptors, such as the osmosensor OSCA1. However, determining the Ca 2+ -signaling specificity to various stimuli in these mutants remains a challenge. For instance, less is known about the exact selectivity between osmotic and ionic stresses in the osca1 mutant. Here, we have developed a method to distinguish the osmotic and ionic effects by analyzing Ca 2+ increases, and demonstrated that osca1 is impaired primarily in Ca 2+ increases induced by the osmotic but not ionic stress. We recorded Ca 2+ increases induced by sorbitol (osmotic effect, OE) and NaCl/CaCl 2 (OE + ionic effect, IE) in Arabidopsis wild-type and osca1 seedlings. Here we assumed the NaCl/CaCl 2 total effect (TE) = OE + IE, then developed procedures for Ca 2+ imaging, image analysis and mathematic fitting/modeling, and found osca1 defects mainly in OE. The osmotic specificity of osca1 suggests that osmotic and ionic perceptions are independent. The precise estimation of these two stress effects is applicable not only to new Ca 2+ -signaling mutants with distinct stimulus specificity but also the complex Ca 2+ signaling crosstalk among multiple concurrent stresses that occur naturally, and will enable us to specifically fine tune multiple signal pathways to improve crop yields.

Arabidopsis↗
DOE OSTI2025

A split ribozyme system for in vivo plant RNA imaging and genetic engineering

RNA plays a central role in plants, governing various cellular and physiological processes. Monitoring its dynamic abundance provides a discerning understanding of molecular mechanisms underlying plant responses to internal (developmental) and external (environmental) stimuli, paving the way for advances in plant biotechnology to engineer crops with improved resilience, quality and productivity. In general, traditional methods for analysis of RNA abundance in plants require destructive, labour-intensive and time-consuming assays. To overcome these limitations, we developed a transformative innovation for in vivo RNA imaging in plants. Specifically, we established a synthetic split ribozyme system that converts various RNA signals to orthogonal protein outputs, enabling in vivo visualisation of various RNA signals in plants. We demonstrated the utility of this system in transient expression experiments (i.e., leaf infiltration in Nicotiana benthamiana ) to detect RNAs derived from transgenes and tobacco rattle virus, respectively. Also, we successfully engineered a split ribozyme-based biosensor in Arabidopsis thaliana for in vivo visualisation of endogenous gene expression at the cellular level, demonstrating the feasibility of multi-scale (e.g., cellular and tissue level) RNA imaging in plants. Furthermore, we developed a platform for easy incorporation of different protein outputs, allowing for flexible choice of reporters to optimise the detection of target RNAs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Phytosulfokine downregulates defense‐related WRKY transcription factors and attenuates pathogen‐associated molecular pattern‐triggered immunity

SUMMARY Phytosulfokine (PSK) is a plant growth‐promoting peptide hormone that is perceived by its cell surface receptors PSKR1 and PSKR2 in Arabidopsis. Plants lacking the PSK receptors show phenotypes consistent with PSK signaling repressing some plant defenses. To gain further insight into the PSK signaling mechanism, comprehensive transcriptional profiling of Arabidopsis treated with PSK was performed, and the effects of PSK treatment on plant defense readouts were monitored. Our study indicates that PSK's major effect is to downregulate defense‐related genes; it has a more modest effect on the induction of growth‐related genes. WRKY transcription factors (TFs) emerged as key regulators of PSK‐responsive genes, sharing commonality with a pathogen‐associated molecular pattern (PAMP) responses, flagellin 22 (flg22), but exhibiting opposite regulatory directions. These PSK‐induced transcriptional changes were accompanied by biochemical and physiological changes that reduced PAMP responses, notably mitogen‐activated protein kinase (MPK) phosphorylation (previously implicated in WRKY activation) and the cell wall modification of callose deposition. Comparison with previous studies using other growth stimuli (the sulfated plant peptide containing sulfated tyrosine [PSY] and Pseudomonas simiae strain WCS417) also reveals WRKY TFs' overrepresentations in these pathways, suggesting a possible shared mechanism involving WRKY TFs for plant growth–defense trade‐off.

Liu, Dian [Biochemistry and Molecular Biophysics T↗