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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Considerations about future hard x-ray area detectors

X-ray sources continue to advance in both intensity and temporal domains, thereby opening new ways to analyze the structure and properties of matter, provided that the resultant x-ray images can be efficiently and quantitatively recorded. In this perspective we focus on specific limitations of pixel area x-ray detectors. Although pixel area x-ray detectors have also advanced in recent years, many experiments are still detector limited. Specifically, there is need for detectors that can acquire successive images at GHz rates; detectors that can accurately measure both single photon and millions of photons per pixel in the same image at frame rates of hundreds of kHz; and detectors that efficiently capture images of very hard x-rays (20 keV to several hundred keV). The data volumes and data rates of state-of-the-art detection exceeds most practical data storage options and readout bandwidths, thereby necessitating on-line processing of data prior to, or in lieu of full frame readouts.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Predicting material microstructure evolution via data-driven machine learning

The recent rapid rise in data-driven practices in the materials science domain has led to the development of efficient, generalizable, and accurate approaches for several applications, including: material property prediction, mining (micro)structure- property and (micro)structure-processing relationships, and characterization of material microstructures. Central to the materials science domain is linking microstructure to properties and performance, and critical to building such linkages is understanding how microstructures evolve as a function of environmental exposure or processing conditions (e.g., time, temperature, applied stress or strain, irradiation). This preview article summarizes recent work on the development of recurrent neural networks for predicting spatio-temporal microstructure evolution detailed by Yang et al in their manuscript entitled 'Self-supervised Learning and Prediction of Microstructure Evolution with Recurrent Neural Networks'.

machine learning (ML), materials characterization↗
DOE OSTI2024

Mechanistic Insights Revealed by YbtPQ in the Occluded State

Recently, several ATP-binding cassette (ABC) importers have been found to adopt the typical fold of type IV ABC exporters. Presumably, these importers would function under the transport scheme of “alternating access” like those exporters, cycling through inward-open, occluded, and outward-open conformations. Understanding how the exporter-like importers move substrates in the opposite direction requires structural studies on all the major conformations. To shed light on this, here we report the structure of yersiniabactin importer YbtPQ from uropathogenic Escherichia coli in the occluded conformation trapped by ADP-vanadate (ADP-Vi) at a 3.1 Å resolution determined by cryo-electron microscopy. The structure shows unusual local rearrangements in multiple helices and loops in its transmembrane domains (TMDs). In addition, the dimerization of the nucleotide-binding domains (NBDs) promoted by the vanadate trapping is highlighted by the “screwdriver” action at one of the two hinge points. These structural observations are rare and thus provide valuable information to understand the structural plasticity of the exporter-like ABC importers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Thermal Stability of π-Conjugated n -Ethylene-Glycol-Terminated Quaterthiophene Oligomers: A Computational and Experimental Study

This work represents a joint computational and experimental study on a series of $\textit{n}$-ethylene glycol (PEO$\textit{n}$)-terminated quaterthiophene (4T) oligomers for 1 < $\textit{n}$ < 10 to elucidate their self-assembly behavior into a smectic-like lamellar phase. This study builds on an earlier study for $\textit{n}$ = 4 that showed that our model predictions were consistent with experimental data on the melting behavior and structure of the lamellar phase, with the latter consisting of crystal-like 4T domains and liquid-like PEO4 domains. The present study aims to understand how the length of the terminal PEO$\textit{n}$ chains modulates the disordering temperature of the lamellar phase and hence the relative stability of the ordered structure. In this work, a simplified bilayer model, where the 4T domains are not explicitly described, is put forward to efficiently estimate the disordering effect of the PEO domains with increasing n; this method is first validated by correctly predicting that layers of alkyl (PE)-capped 4T oligomers (for 1 < $\textit{n}$ < 10) stay ordered at room temperature. Both 4T-domain implicit and explicit model simulations reveal that the order-disorder temperature decreases with the length of the PEO capping chains, as the associated increase in conformational entropy drives a tendency toward disorder that overtakes the cohesive energy, keeping the ordered packing of the 4T domains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

CDRL: Certification-Driven Reinforcement Learning for Neutrino Flavor Model Discovery

Many scientific discovery problems require searching combinatorial hypothesis spaces under complex domain constraints. Reinforcement learning (RL) offers a promising approach, but existing methods rely on scalar rewards that provide limited information about why candidate solutions fail, leading agents to repeatedly explore invalid regions. We introduce Certification-Driven Reinforcement Learning (CDRL), a framework that leverages structured feedback from symbolic reasoning tools. When a candidate violates domain constraints, these tools produce certificates identifying the actions responsible for failure. CDRL converts these certificates into reusable constraints that eliminate classes of invalid solutions and guide exploration toward valid regions. We evaluate CDRL on neutrino flavor model discovery in theoretical particle physics, where the hypothesis space exceeds $10^{26}$ possible models, and compare it with the state-of-the-art RL approach previously used for this task. Across three theory spaces, CDRL achieves up to 1.95$\times$ higher valid model rates and up to 6.33$\times$ higher neutrino model rates while evaluating up to 4$\times$ fewer candidates. We further extract 40 interpretable rules from search trajectories using a post-hoc decision-tree framework and show that reusing them as soft constraints yields gains of up to 2$\times$ in valid model rates and 3$\times$ in neutrino model discovery across all three theory spaces. These results suggest that CDRL uncovers reusable structure in combinatorial search spaces and provides a general framework for scientific model discovery.

Jha, Piyush [Georgia Tech., Atlanta; Georgia Tech]↗
DOE OSTI2020

The effects of stress, temperature and facet structure on growth of { 10 1 &#xAF; 2 } twins in Mg: a molecular dynamics and phase field study

The present study focuses on the roles of structure, stress and temperature on the mobility of facets bounding twin domains and on the overall impact on the growth kinetics of { 10 1 &#xAF; 2 } twins in Mg. We first use molecular dynamics simulations (MD) to study the relationship between interface structures, stress, temperature and mobility. As facets can exhibit distinct atomic scale structures, we also quantify the effect of stress relaxation mediated by misfit dislocations on the mobility of the basal-prismatic interface. The information gathered for ten different facets is used to calibrate an anisotropic phase field model predicting the effects of temperature and stress on the kinetics and shape of a growing { 10 1 &#xAF; 2 } 3D twin, by comparison with MD data. The comparative analysis suggests that, as compared to simulations of individual facets, the effective mobility of facets can be significantly different during growth of a 3D twin. This can be attributed to the complex three-dimensional internal stress state of the twin and to coupling in facet motion triggered by facet junctions. As such, by directly fitting both the twin growth kinetics and morphology as predicted by MD for different stresses and temperatures, we can identify a limited set of rate-limiting facets that control twin growth and morphology, and measure their effective mobility.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Targeting the Spike Receptor Binding Domain Class V Cryptic Epitope by an Antibody with Pan-Sarbecovirus Activity

Novel therapeutic monoclonal antibodies (MAbs) must accommodate comprehensive breadth of activity against diverse sarbecoviruses and high neutralization potency to overcome emerging variants. Here, in this study, we report the crystal structure of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) receptor binding domain (RBD) in complex with MAb WRAIR-2063, a moderate-potency neutralizing antibody with exceptional sarbecovirus breadth, that targets the highly conserved cryptic class V epitope. This epitope overlaps substantially with the spike protein N-terminal domain (NTD) -interacting region and is exposed only when the spike is in the open conformation, with one or more RBDs accessible. WRAIR-2063 binds the RBD of SARS-CoV-2 WA-1, all variants of concern (VoCs), and clade 1 to 4 sarbecoviruses with high affinity, demonstrating the conservation of this epitope and potential resiliency against variation. We compare structural features of additional class V antibodies with their reported neutralization capacity to further explore the utility of the class V epitope as a pan-sarbecovirus vaccine and therapeutic target.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Design Rules of the Mixing Phase and Impacts on Device Performance in High-Efficiency Organic Photovoltaics

In nonfullerene acceptor- (NFA-) based solar cells, the exciton splitting takes place at both domain interface and donor/acceptor mixture, which brings in the state of mixing phase into focus. The energetics and morphology are key parameters dictating the charge generation, diffusion, and recombination. It is revealed that tailoringthe electronic properties of the mixing region by doping with larger-bandgap components could reduce the density of state but elevate the filling state level, leading to improved open-circuit voltage ( V OC ) and reduced recombination. The monomolecular and bimolecular recombinations are shown to be intercorrelated, which show a Gaussian-like relationship with V OC and linear relationship with short-circuit current density ( J SC ) and fill factor (FF). The kinetics of hole transfer and exciton diffusion scale with J SC similarly, indicating the carrier generation in mixing region and crystalline domain are equally important. From the morphology perspective, the crystalline order could contribute to V OC improvement, and the fibrillar structure strongly affects the FF. These observations highlight the importance of the mixing region and its connection with crystalline domains and point out the design rules to optimize the mixing phase structure, which is an effective approach to further improve device performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Structural Basis of Clostridium perfringens Enterotoxin Activation and Oligomerization by Trypsin

Clostridium perfringens enterotoxin (CpE) is a β-pore forming toxin that disrupts gastrointestinal homeostasis in mammals by binding membrane protein receptors called claudins. Although structures of CpE fragments bound to claudins have been determined, the mechanisms that trigger CpE activation and oligomerization that lead to the formation of cytotoxic β-pores remain undetermined. Proteolysis of CpE in the gut by trypsin has been shown to play a role in this and subsequent cytotoxicity processes. Here, we report solution structures of full-length and trypsinized CpE using small-angle X-ray scattering (SAXS) and crystal structures of trypsinized CpE and its C-terminal claudin-binding domain (cCpE) using X-ray crystallography. Mass spectrometry and SAXS uncover that removal of the CpE N-terminus by trypsin alters the CpE structure to expose areas that are normally unexposed. Crystal structures of trypsinized CpE and cCpE reveal unique dimer interfaces that could serve as oligomerization sites. Moreover, comparisons of these structures to existing ones predict the functional implications of oligomerization in the contexts of cell receptor binding and β-pore formation. This study sheds light on trypsin’s role in altering CpE structure to activate its function via inducing oligomerization on its path toward cytotoxic β-pore formation. Its findings can incite new approaches to inhibit CpE-based cytotoxicity with oligomer-disrupting therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Microemulsions as Emerging Electrolytes: The Correlation of Structure to Electrochemical Response

We describe the structural studies of microemulsions (μEs) prepared from water, toluene, butanol, and polysorbate 20 (PS20) that we recently used as electrolytes. Small-angle neutron scattering was used to monitor the development of the bicontinuous system as a function of the water-to-surfactant mass ratio on a constant oil-to-surfactant dilution line, revealing how the domain size, correlation length, amphiphilicity factor, and bending moduli change with composition. Kratky and Porod analyses are also employed, providing further structural detail of the scattering domains. Here, we demonstrate that controlling the water-to-surfactant ratio with a constant oil-to-surfactant dilution affects the bicontinuous phase, reveals a sizeable compositional region with structural similarities, and provides insight into the correlation of structure to physical properties. Voltammetric results are presented to examine how the evolution of the bicontinuous structure formed in a μE prepared from water, toluene, butanol, and PS20 contributes to the electrochemical response. These findings, therefore, provide essential information that will guide the formulation of μEs as electrolytes for energy storage.

25 ENERGY STORAGE↗
DOE OSTI2025

Bridging the Gap Between Astronomical Datasets: From Proof-of-Concept to AI Model Deployment with Domain Adaptation

Artificial Intelligence is transforming astrophysics, from studying stars and galaxies to analyzing cosmic large-scale structures. However, a critical challenge arises when AI models trained on simulations or past observational data are applied to new observation— leading to domain shifts, reduced robustness, and increased uncertainty of model predictions. This talk will explore these issues, highlighting examples such as galaxy morphology classification and cosmological parameter inference, where AI struggles to adapt across different datasets. We will discuss domain adaptation as a strategy to improve model generalization and mitigate biases—essential for making AI-driven discoveries reliable. Notably, these challenges extend beyond astrophysics, affecting AI applications across physics and other scientific domains. Addressing them is essential for maximizing AI’s impact in advancing scientific research.

Ćiprijanović, Aleksandra [Fermilab]↗
DOE OSTI2023

Nodavirus RNA replication crown architecture reveals proto-crown precursor and viral protein A conformational switching

Positive-strand RNA viruses replicate their genomes in virus-induced membrane vesicles, and the resulting RNA replication complexes are a major target for virus control. Nodavirus studies first revealed viral RNA replication proteins forming a 12-fold symmetric “crown” at the vesicle opening to the cytosol, an arrangement recently confirmed to extend to distantly related alphaviruses. Using cryoelectron microscopy (cryo-EM), we show that mature nodavirus crowns comprise two stacked 12-mer rings of multidomain viral RNA replication protein A. Each ring contains an ~19 nm circle of C-proximal polymerase domains, differentiated by strikingly diverged positions of N-proximal RNA capping/membrane binding domains. The lower ring is a “proto-crown” precursor that assembles prior to RNA template recruitment, RNA synthesis, and replication vesicle formation. In this proto-crown, the N-proximal segments interact to form a toroidal central floor, whose 3.1 Å resolution structure reveals many mechanistic details of the RNA capping/membrane binding domains. In the upper ring, cryo-EM fitting indicates that the N-proximal domains extend radially outside the polymerases, forming separated, membrane-binding “legs.” The polymerase and N-proximal domains are connected by a long linker accommodating the conformational switch between the two rings and possibly also polymerase movements associated with RNA synthesis and nonsymmetric electron density in the lower center of mature crowns. The results reveal remarkable viral protein multifunctionality, conformational flexibility, and evolutionary plasticity and insights into (+)RNA virus replication and control.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Cryo-EM structures of DNA-free and DNA-bound BsaXI: architecture of a Type IIB restriction–modification enzyme

Abstract We have determined multiple cryogenic electron microscopy (cryo-EM) structures of the Type IIB restriction–modification enzyme BsaXI. Such enzymes cleave DNA on both sides of their recognition sequence and share features of Types I, II, and III restriction systems. BsaXI forms a heterotrimeric (RM)2S assemblage in the presence and absence of bound DNA. Two unique structural motifs—a multi-helical “knob” and a long antiparallel double-helical “paddle”—are involved in DNA binding and cleavage. Binding of the DNA target triggers a large conformational change from an ‘open’ to ‘closed’ configuration, resulting in a mixture of two different conformations with respect to the positioning of the S subunit and its target recognition domains on the enzyme’s bipartite DNA target site. Structure-guided mutagenesis studies implicated two clusters of residues in the RM subunit as being critical for DNA cleavage, both are located proximal to a DNA cleavage site. One corresponds to a canonical PD-(D/E)xK endonuclease site in the N-terminal endonuclease domain, while the other corresponds to residues clustered within the paddle motif (near to the C-terminal end of the RM subunit). This analysis facilitates a comparison of three potential mechanisms by which such enzymes cleave DNA on each side of the bound target.

Shen, Betty W.↗
DOE OSTI2025

Toward engineering lattice structures with the material point method (MPM)

This study examines the potential of two variants of the material point method—the generalized interpolation material point (GIMP) and dual domain material point (DDMP) methods—in developing a robust computational framework for engineering lattice structures under different loading conditions. The study begins with assessing the ability of the two methods in predicting elastic buckling phenomena using column geometries with and without initial geometric imperfections. The results indicate that both methods effectively capture buckling phenomena when initial geometric imperfections are introduced. After this verification step, we create several models of tetrahedral lattice structures with varying strut diameter and orientation and subject them to quasi-static loading. We then validate the numerical results using laboratory test results. The results show that, while both methods accurately predict load–displacement curves in the pre-buckling regime, their predictive capabilities diminish in the post-buckling regime. Through visual comparison between the numerical and experimental deformed shapes, it appears that the discrepancies between model and experimental results are attributed to initial geometric imperfections in the lattices that occurred during 3D printing. We then establish a second set of lattice models where different types of initial geometric imperfections are considered. The results from these models show that imperfections have a negligible influence in the pre-buckling regime but affect the behavior considerably in the post-buckling regime. As a final step in this work, we subject the lattice models to impact loading and employ hypothetical soft and stiff materials. These results show that the lattice stiffness, which depends on material stiffness, strut diameter, and orientation, significantly influences the ability of a lattice structure to resist impact. In particular, we find that a stiffer lattice (i.e., one made with a stiff material and thicker struts) is capable of absorbing more energy than a softer one during impact. Although material nonlinearities, inelasticity, and detailed contact formulations are not considered in this study, the findings obtained herein lay the groundwork for engineering lattice structures under extreme loading conditions through a simulation-driven framework based on particle-based methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Conformational Changes of RORγ During Response Element Recognition and Coregulator Engagement

The retinoic acid receptor-related orphan receptor γ (RORγ) is a ligand-dependent transcription factor of the nuclear receptor super family that underpins metabolic activity, immune function, and cancer progression. Despite being a valuable drug target in health and disease, our understanding of the ligand-dependent activities of RORγ is far from complete. Like most nuclear receptors, RORγ must recruit coregulatory protein to enact the RORγ target gene program. To date, a majority of structural studies have been focused exclusively on the RORγ ligand-binding domain and the ligand-dependent recruitment of small peptide segments of coregulators. Herein, we examine the ligand-dependent assembly of full length RORγ:coregulator complexes on cognate DNA response elements using structural proteomics and small angle x-ray scattering. The results from our studies suggest that RORγ becomes elongated upon DNA recognition, preventing long range interdomain crosstalk. We also determined that the DNA binding domain adopts a sequence-specific conformation, and that coregulatory protein may be able to ‘sense’ the ligand- and DNA-bound status of RORγ. We propose a model where ligand-dependent coregulator recruitment may be influenced by the sequence of the DNA to which RORγ is bound. Overall, the efforts described herein will illuminate important aspects of full length RORγ and monomeric orphan nuclear receptor target gene regulation through DNA-dependent conformational changes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

The congenital APOA1 K107del mutation disrupts the lipid-free conformation of monomeric APOA1 and impairs oligomerization

Apolipoprotein A-I (APOA1) oligomerization is thought to be essential for high-density lipoprotein (HDL) formation and metabolism. Naturally occurring mutations can disrupt normal APOA1 folding and self-association, leading to dysfunctional HDL formation and cardiovascular disease. The congenital APOA1 variant p.K131del (APOA1 K107del ) has been associated with cardiovascular pathologies such as low HDL-cholesterol levels and aortic amyloidosis, and multiple studies indicate structural changes in APOA1 conformation underlie associated dysfunction. In the current study, we confirmed that APOA1 K107del exhibits no notable defect in lipid-binding. However, using polyacrylamide gel electrophoresis (PAGE) and size-exclusion chromatography (SEC), we found that loss of lysine 107 resulted in a remarkable shift in the distribution of APOA1 oligomers with a much higher proportion of monomers present in APOA1 K107del compared to wild-type APOA1. Further investigation using quantitative cross-linking revealed a major disruption of interactions in helical regions reported to participate in domain swaps necessary for proper self-association. This structural disruption appears to impair N- and C-termini interactions and dynamics that lead to non-specific aggregation. In conclusion, these findings support the hypothesis that lysine 107 is critical for proper folding and self-association of lipid-free APOA1 which could impact HDL biogenesis.

APOA1 (p.K131del)↗
DOE OSTI2021

Structures of two novel crystal forms of Aspergillus oryzae alpha amylase (taka-amylase)

The structures of Aspergillus oryzae α-amylase were determined in a tetragonal crystal, having one molecule as asymmetric unit, and a monoclinic crystal with two molecules as asymmetric unit. Both crystal forms were obtained from trace contaminants of an old commercial lipase preparation. Structures were determined and refined to 1.65 Å and 1.43 Å resolution respectively. The latter crystal has a non-crystallographic (NCS) twofold axis within the asymmetric unit. Glycosylation at Asn197 is evident, and in the tetragonal crystal can be seen to include three, partially disordered sugar residues following the initial N-acetyl glucosamine (NAG). Superposition of the tetragonal crystal model on the α-amylases from Bacillus subtilis (PDB:1BAG), pig pancreas (PDB:3L2L), and barley (PDB:1AMY), show a high degree of coincidence, particularly for the (β/α)8-barrel domains, and especially within the active site. Using this structural agreement between amylases, we extrapolated the binding model of a six residue, limit dextrin found in pig pancreas α-amylase to the A. oryzae enzyme model, which predicts substrate interacting amino acid residues.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Shift Happens: Building Robust AI Models with Domain Adaptation

Artificial Intelligence (AI) is revolutionizing physics research—from probing the large-scale structure of the Universe to modeling subatomic interactions and fundamental forces. Yet, a major challenge persists: AI models trained on simulations or old experiment / astronomical survey often perform poorly when applied to new data—exposing issues of dataset (domain) shift, model robustness, and uncertainty in predictions. This summer school session will introduce students to common challenges in applying AI across domains and present solutions based on domain adaptation—a set of techniques designed to improve model generalization under domain shift. We will cover foundational ideas, practical strategies, and current research frontiers in this area. Through examples in astrophysics, we'll explore how domain adaptation can help bridge the gap between synthetic and real-world data, improve trust in model outputs, and advance scientific discovery. The concepts discussed are broadly applicable across physics and other scientific disciplines, making this a valuable topic for anyone interested in building robust, transferable AI models for science.

Ciprijanovic, A. [Fermilab] (ORCID:000000031281719↗