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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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A multi-scale cognitive interaction model of instrument operations at the Linac Coherent Light Source

The Linac Coherent Light Source (LCLS) is the world’s first x-ray free electron laser. It is a scientific user facility operated by the SLAC National Accelerator Laboratory, at Stanford, for the U.S. Department of Energy. As beam time at LCLS is extremely valuable and limited, experimental efficiency—getting the most high quality data in the least time—is critical. Our overall project employs cognitive engineering methodologies with the goal of improving experimental efficiency and increasing scientific productivity at LCLS by refining experimental interfaces and workflows, simplifying tasks, reducing errors, and improving operator safety and stress. Here, in this study, we describe a multi-agent, multi-scale computational cognitive interaction model of instrument operations at LCLS. Our model simulates the aspects of human cognition at multiple cognitive and temporal scales, ranging from seconds to hours, and among agents playing multiple roles, including instrument operator, real time data analyst, and experiment manager. The model can roughly predict impacts stemming from proposed changes to operational interfaces and workflows. Example results demonstrate the model’s potential in guiding modifications to improve operational efficiency. We discuss the implications of our effort for cognitive engineering in complex experimental settings and outline future directions for research. The model is open source, and the videos of the supplementary material provide extensive detail.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

An essential bifunctional enzyme in Mycobacterium tuberculosis for itaconate dissimilation and leucine catabolism

Mycobacterium tuberculosis (Mtb) is the etiological agent of tuberculosis. One-fourth of the global population is estimated to be infected with Mtb, accounting for ~1.3 million deaths in 2017. As part of the immune response to Mtb infection, macrophages produce metabolites with the purpose of inhibiting or killing the bacterial cell. Itaconate is an abundant host metabolite thought to be both an antimicrobial agent and a modulator of the host inflammatory response. However, the exact mode of action of itaconate remains unclear. Here, we show that Mtb has an itaconate dissimilation pathway and that the last enzyme in this pathway, Rv2498c, also participates in l-leucine catabolism. Our results from phylogenetic analysis, in vitro enzymatic assays, X-ray crystallography, and in vivo Mtb experiments, identified Mtb Rv2498c as a bifunctional β-hydroxyacyl-CoA lyase and that deletion of the rv2498c gene from the Mtb genome resulted in attenuation in a mouse infection model. Altogether, this report describes an itaconate resistance mechanism in Mtb and an l-leucine catabolic pathway that proceeds via an unprecedented (R)-3-hydroxy-3-methylglutaryl-CoA (HMG-CoA) stereospecific route in nature.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Structure and Function of REP34 Implicates Carboxypeptidase Activity in Francisella tularensis Host Cell Invasion

Francisella tularensis is the etiological agent of tularemia, or rabbit fever. Although F. tularensis is a recognized biothreat agent with broad and expanding geographical range, its mechanism of infection and environmental persistence remain poorly understood. Previously, we identified seven F. tularensis proteins that induce a rapid encystment phenotype (REP) in the free-living amoeba, Acanthamoeba castellanii. Encystment is essential to the pathogen's long term intracellular survival in the amoeba. Here, we characterize the cellular and molecular function of REP34, a REP protein with a mass of 34 kDa. A REP34 knock-out strain of F. tularensis has a reduced ability to both induce encystment in A. castellanii and invade human macrophages. We determined the crystal structure of REP34 to 2.05-Å resolution and demonstrate robust carboxypeptidase B-like activity for the enzyme. REP34 is a zinc-containing monomeric protein with close structural homology to the metallocarboxypeptidase family of peptidases. REP34 possesses a novel topology and substrate binding pocket that deviates from the canonical funnelin structure of carboxypeptidases, putatively resulting in a catalytic role for a conserved tyrosine and distinct S1' recognition site. Taken together, these results identify REP34 as an active carboxypeptidase, implicate the enzyme as a potential key F. tularensis effector protein, and may help elucidate a mechanistic understanding of F. tularensis infection of phagocytic cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Pathogenesis of Chapare Virus in Cynomolgus Macaques

Chapare virus (CHAPV) is an emerging New World arenavirus that is the causative agent of Chapare hemorrhagic fever (CHHF) responsible for recent outbreaks with alarmingly high case fatality rates in Bolivia near the Brazilian border. Here, we describe a nonhuman primate (NHP) model of CHHF infection which represents an essential tool to understand this emerging biological threat agent. Cynomolgus macaques challenged intravenously with CHAPV develop clinical disease, which recapitulates several key features of human CHHF. All subjects lost weight and had clinical scores following CHAPV challenge. Notably, one of four NHPs developed lethal disease with viral hepatitis and hemorrhagic features. Clinical chemistry and hematology revealed leukopenia, anemia, thrombocytopenia, and increased transaminase levels. In all four subjects, viremia was detectable for the first week following challenge and viral RNA was detectable in serum and many tissues persisting 35 days-post challenge. Several medical countermeasures (MCM) have efficacy against CHAPV infection in vitro, but the current model for MCM testing and approval of new drugs is reliant on the availability of animal models. This work lays the foundation for future CHHF MCM development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Light yield quenching and quenching remediation in liquid scintillator detectors

Quenching of light emission from an LAB based scintillator by the addition of organic amines and carboxylic acids is examined. Chemical functional groups of the quenching agents play an important role in this reduction. It is shown that "salt" formation at a 1:1 mole ratio in a mixed amine-acid system, reduces quenching by a factor of ~ 2. Supporting NMR spectra are presented. Finally, this "quenching neutralization" has the potential to reduce the light loss incurred when metals complexed with quenching agents are loaded into organic scintillators.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Towards a RAG-based summarization for the Electron Ion Collider

Abstract The complexity and sheer volume of information — encompassing documents, papers, data, and other resources — from large-scale experiments demand significant time and effort to navigate, making the task of accessing and utilizing these varied forms of information daunting, particularly for new collaborators and early-career scientists.To tackle this issue, a Retrieval Augmented Generation (RAG)-based Summarization AI for EIC (RAGS4EIC) is under development. This AI-Agent not only condenses information but also effectively references relevant responses, offering substantial advantages for collaborators. Our project involves a two-step approach: first, querying a comprehensive vector database containing all pertinent experiment information; second, utilizing a Large Language Model (LLM) to generate concise summaries enriched with citations based on user queries and retrieved data. We describe the evaluation methods that use RAG assessments (RAGAs) scoring mechanisms to assess the effectiveness of responses. Furthermore, we describe the concept of prompt template based instruction-tuning which provides flexibility and accuracy in summarization. Importantly, the implementation relies on LangChain [1], which serves as the foundation of our entire workflow. This integration ensures efficiency and scalability, facilitating smooth deployment and accessibility for various user groups within the Electron Ion Collider (EIC) community. This innovative AI-driven framework not only simplifies the understanding of vast datasets but also encourages collaborative participation, thereby empowering researchers. As a demonstration, a web application has been developed to explain each stage of the RAG Agent development in detail. The application can be accessed athttps://rags4eic-ai4eic.streamlit.app.[A tagged version of the source code can be found inhttps://github.com/ai4eic/EIC-RAG-Project/releases/tag/AI4EIC2023_PROCEEDING.]

Instruments & Instrumentation↗
DOE OSTI2023

A TOPAS model for lens-based proton radiography

Abstract Objective. Proton Radiography can be used in conjunction with proton therapy for patient positioning, real-time estimates of stopping power, and adaptive therapy in regions with motion. The modeling capability shown here can be used to evaluate lens-based radiography as an instantaneous proton-based radiographic technique. The utilization of user-friendly Monte Carlo program TOPAS enables collaborators and other users to easily conduct medical- and therapy- based simulations of the Los Alamos Neutron Science Center (LANSCE). The resulting transport model is an open-source Monte Carlo package for simulations of proton and heavy ion therapy treatments and concurrent particle imaging. Approach. The four-quadrupole, magnetic lens system of the 800-MeV proton beamline at LANSCE is modeled in TOPAS. Several imaging and contrast objects were modelled to assess transmission at energies from 230–930 MeV and different levels of particle collimation. At different proton energies, the strength of the magnetic field was scaled according to βγ, the inverse product of particle relativistic velocity and particle momentum. Main results. Materials with high atomic number, Z, (gold, gallium, bone-equivalent) generated more contrast than materials with low-Z (water, lung-equivalent, adipose-equivalent). A 5-mrad collimator was beneficial for tissue-to-contrast agent contrast, while a 10-mrad collimator was best to distinguish between different high-Z materials. Assessment with a step-wedge phantom showed water-equivalent path length did not scale directly according to predicted values but could be mapped more accurately with calibration. Poor image quality was observed at low energies (230 MeV), but improved as proton energy increased, with sub-mm resolution at 630 MeV. Significance. Proton radiography becomes viable for shallow bone structures at 330 MeV, and for deeper structures at 630 MeV. Visibility improves with use of high-Z contrast agents. This modality may be particularly viable at carbon therapy centers with accelerators capable of delivering high energy protons and could be performed with carbon therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Discovering mechanisms for materials microstructure optimization via reinforcement learning of a generative model

Abstract The design of materials structure for optimizing functional properties and potentially, the discovery of novel behaviors is a keystone problem in materials science. In many cases microstructural models underpinning materials functionality are available and well understood. However, optimization of average properties via microstructural engineering often leads to combinatorically intractable problems. Here, we explore the use of the reinforcement learning (RL) for microstructure optimization targeting the discovery of the physical mechanisms behind enhanced functionalities. We illustrate that RL can provide insights into the mechanisms driving properties of interest in a 2D discrete Landau ferroelectrics simulator. Intriguingly, we find that non-trivial phenomena emerge if the rewards are assigned to favor physically impossible tasks, which we illustrate through rewarding RL agents to rotate polarization vectors to energetically unfavorable positions. We further find that strategies to induce polarization curl can be non-intuitive, based on analysis of learned agent policies. This study suggests that RL is a promising machine learning method for material design optimization tasks, and for better understanding the dynamics of microstructural simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Reinforcement learning pulses for transmon qubit entangling gates

The utility of a quantum computer is highly dependent on the ability to reliably perform accurate quantum logic operations. For finding optimal control solutions, it is of particular interest to explore model-free approaches, since their quality is not constrained by the limited accuracy of theoretical models for the quantum processor—in contrast to many established gate implementation strategies. In this work, we utilize a continuous control reinforcement learning algorithm to design entangling two-qubit gates for superconducting qubits; specifically, our agent constructs cross-resonance and CNOT gates without any prior information about the physical system. Using a simulated environment of fixed-frequency fixed-coupling transmon qubits, we demonstrate the capability to generate novel pulse sequences that outperform the standard cross-resonance gates in both fidelity and gate duration, while maintaining a comparable susceptibility to stochastic unitary noise. We further showcase an augmentation in training and input information that allows our agent to adapt its pulse design abilities to drifting hardware characteristics, importantly, with little to no additional optimization. Our results exhibit clearly the advantages of unbiased adaptive-feedback learning-based optimization methods for transmon gate design.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

From natural language to control signals: a conceptual framework for semantic channel finding in complex experimental infrastructure

Modern experimental platforms such as particle accelerators, fusion devices, telescopes, and industrial process control systems expose tens to hundreds of thousands of control and diagnostic channels, accumulated over decades of hardware evolution. Operators and AI systems alike depend on informal expert knowledge, inconsistent naming conventions, and scattered documentation to locate the signals required for monitoring, troubleshooting, and automated control, creating a persistent bottleneck for reliability, scalability, and emerging language-model-driven interfaces. We formalize semantic channel finding, the task of mapping natural-language intent to concrete control-system signals, as a general problem in complex experimental infrastructure, and introduce a four-paradigm conceptual framework to guide architecture selection based on facility-specific data regimes. The paradigms span (i) direct in-context lookup over small, curated channel dictionaries, (ii) constrained hierarchical navigation through structured trees, (iii) interactive agent exploration using iterative reasoning and tool-based database queries, and (iv) ontology-grounded semantic search that decouples channel meaning from facility-specific naming conventions. We demonstrate the practical feasibility of each paradigm through proof-of-concept implementations at four operational facilities spanning two orders of magnitude in scale: from compact free-electron lasers to large synchrotron light sources, operating under diverse control-system architectures ranging from clean hierarchical naming schemes to legacy environments with decades of heterogeneous conventions. Where evaluated against expert-curated operational queries, these instantiations achieve 90%–97% accuracy, validating the framework’s applicability across real-world deployment scenarios. To accelerate adoption across the broader scientific and industrial control-system community, we release open-source, plug-and-play implementations of all three interactive paradigms-direct lookup, hierarchical navigation, and middle-layer exploration-within the Osprey framework, together with tools for channel database generation, interactive testing, and minimal-configuration deployment. This work establishes semantic channel finding as a foundational capability for human-centric and agentic AI interfaces at large-scale facilities, providing both a systematic framework for architecture design and practical resources to enable adoption without building custom infrastructure from scratch.

channel finding↗
DOE OSTI2023

Two disulfide-reducing pathways are required for the maturation of plastid c -type cytochromes in Chlamydomonas reinhardtii

Abstract In plastids, conversion of light energy into ATP relies on cytochrome f, a key electron carrier with a heme covalently attached to a CXXCH motif. Covalent heme attachment requires reduction of the disulfide-bonded CXXCH by CCS5 and CCS4. CCS5 receives electrons from the oxidoreductase CCDA, while CCS4 is a protein of unknown function. In Chlamydomonas reinhardtii, loss of CCS4 or CCS5 yields a partial cytochrome f assembly defect. Here, we report that the ccs4ccs5 double mutant displays a synthetic photosynthetic defect characterized by a complete loss of holocytochrome f assembly. This defect is chemically corrected by reducing agents, confirming the placement of CCS4 and CCS5 in a reducing pathway. CCS4-like proteins occur in the green lineage, and we show that HCF153, a distant ortholog from Arabidopsis thaliana, can substitute for Chlamydomonas CCS4. Dominant suppressor mutations mapping to the CCS4 gene were identified in photosynthetic revertants of the ccs4ccs5 mutants. The suppressor mutations yield changes in the stroma-facing domain of CCS4 that restore holocytochrome f assembly above the residual levels detected in ccs5. Because the CCDA protein accumulation is decreased specifically in the ccs4 mutant, we hypothesize the suppressor mutations enhance the supply of reducing power through CCDA in the absence of CCS5. We discuss the operation of a CCS5-dependent and a CCS5-independent pathway controlling the redox status of the heme-binding cysteines of apocytochrome f.

Genetics & Heredity↗
DOE OSTI2024

Human-in-the-Loop: The Future of Machine Learning in Automated Electron Microscopy

Machine learning (ML) methods are progressively gaining acceptance in the electron microscopy community for de-noising, semantic segmentation, and dimensionality reduction of data post-acquisition. The introduction of the application programming interfaces (APIs) by major instrument manufacturers now allows the deployment of ML workflows in microscopes, not only for data analytics but also for real-time decision-making and feedback for microscope operation. However, the number of use cases for real-time ML remains remarkably small. Furthermore, we discuss some considerations in designing ML-based active experiments and pose that the likely strategy for the next several years will be human-in-the-loop automated experiments (hAE). In this paradigm, the ML learning agent directly controls beam position and image and spectroscopy acquisition functions, and a human operator monitors experiment progression in real and feature space of the system and tunes the policies of the ML agent to steer the experiment toward specific objectives.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Identification of a ligand binding hot spot and structural motifs replicating aspects of tyrosyl-DNA phosphodiesterase I (TDP1) phosphoryl recognition by crystallographic fragment cocktail screening

Tyrosyl DNA-phosphodiesterase I (TDP1) repairs type IB topoisomerase (TOP1) cleavage complexes generated by TOP1 inhibitors commonly used as anticancer agents. TDP1 also removes DNA 3' end blocking lesions generated by chain-terminating nucleosides and alkylating agents, and base oxidation both in the nuclear and mitochondrial genomes. Combination therapy with TDP1 inhibitors is proposed to synergize with topoisomerase targeting drugs to enhance selectivity against cancer cells exhibiting deficiencies in parallel DNA repair pathways. A crystallographic fragment screening campaign against the catalytic domain of TDP1 was conducted to identify new lead compounds. Crystal structures revealed two fragments that bind to the TDP1 active site and exhibit inhibitory activity against TDP1. These fragments occupy a similar position in the TDP1 active site as seen in prior crystal structures of TDP1 with bound vanadate, a transition state mimic. Using structural insights into fragment binding, several fragment derivatives have been prepared and evaluated in biochemical assays. These results demonstrate that fragment-based methods can be a highly feasible approach toward the discovery of small-molecule chemical scaffolds to target TDP1, and for the first time, we provide co-crystal structures of small molecule inhibitors bound to TDP1, which could serve for the rational development of medicinal TDP1 inhibitors.

Lountos, George T.↗
DOE OSTI2020

Regeneration of critical-sized defects, in a goat model, using a dextrin-based hydrogel associated with granular synthetic bone substitute

Abstract The development of injectable bone substitutes (IBS) have obtained great importance in the bone regeneration field, as a strategy to reach hardly accessible defects using minimally invasive techniques and able to fit to irregular topographies. In this scenario, the association of injectable hydrogels and bone graft granules is emerging as a well-established trend. Particularly, in situ forming hydrogels have arisen as a new IBS generation. An in situ forming and injectable dextrin-based hydrogel (HG) was developed, aiming to act as a carrier of granular bone substitutes and bioactive agents. In this work, the HG was associated to a granular bone substitute (Bonelike®) and implanted in goat critical-sized calvarial defects (14 mm) for 3, 6 and 12 weeks. The results showed that HG improved the handling properties of the Bonelike® granules and did not affect its osteoconductive features, neither impairing the bone regeneration process. Human multipotent mesenchymal stromal cells from the umbilical cord, extracellular matrix hydrolysates and the pro-angiogenic peptide LLKKK18 were also combined with the IBS. These bioactive agents did not enhance the new bone formation significantly under the conditions tested, according to micro-computed tomography and histological analysis.

Pereira, Isabel↗
DOE OSTI2022

DNA Sequence-Based Identification of Fusarium : A Work in Progress

Accurate species-level identification of an etiological agent is crucial for disease diagnosis and management because knowing the agent’s identity connects it with what is known about its host range, geographic distribution, and toxin production potential. This is particularly true in publishing peer-reviewed disease reports, where imprecise and/or incorrect identifications weaken the public knowledge base. This can be a daunting task for phytopathologists and other applied biologists that need to identify Fusarium in particular, because published and ongoing multilocus molecular systematic studies have highlighted several confounding issues. Paramount among these are: (i) this agriculturally and clinically important genus is currently estimated to comprise more than 400 phylogenetically distinct species (i.e., phylospecies), with more than 80% of these discovered within the past 25 years; (ii) approximately one-third of the phylospecies have not been formally described; (iii) morphology alone is inadequate to distinguish most of these species from one another; and (iv) the current rapid discovery of novel fusaria from pathogen surveys and accompanying impact on the taxonomic landscape is expected to continue well into the foreseeable future. To address the critical need for accurate pathogen identification, our research groups are focused on populating two web-accessible databases (FUSARIUM-ID v.3.0 and the nonredundant National Center for Biotechnology Information nucleotide collection that includes GenBank) with portions of three phylogenetically informative genes (i.e., TEF1, RPB1, and RPB2) that resolve at or near the species level in every Fusarium species. The objectives of this Special Report, and its companion in this issue ( Torres-Cruz et al. 2022 ), are to provide a progress report on our efforts to populate these databases and to outline a set of best practices for DNA sequence-based identification of fusaria.

Plant Sciences↗
DOE OSTI2020

Elucidating Anthracnose Resistance Mechanisms in Sorghum—A Review

Sorghum (Sorghum bicolor) is the fifth most cultivated cereal crop in the world, traditionally providing food, feed, and fodder, but more recently also fermentable sugars for the production of renewable fuels and chemicals. The hemibiotrophic fungal pathogen Colletotrichum sublineola, the causal agent of anthracnose disease in sorghum, is prevalent in the warm and humid climates where much of the sorghum is cultivated and poses a serious threat to sorghum production. The use of anthracnose-resistant sorghum germplasm is the most environmentally and economically sustainable way to protect sorghum against this pathogen. Even though multiple anthracnose resistance loci have been mapped in diverse sorghum germplasm in recent years, the diversity in C. sublineola pathotypes at the local and regional levels means that these resistance genes are not equally effective in different areas of cultivation. This review summarizes the genetic and cytological data underlying sorghum’s defense response and describes recent developments that will enable a better understanding of the interactions between sorghum and C. sublineola at the molecular level. This includes releases of the sorghum genome and the draft genome of C. sublineola, the use of next-generation sequencing technologies to identify gene expression networks activated in response to infection, and improvements in methodologies to validate resistance genes, notably virus-induced and transgenic gene silencing approaches.

Plant Sciences↗
DOE OSTI2020

Chelation Modeling: The Use of Ad Hoc Models and Approaches to Overcome a Dose Assessment Challenge

Here, chelating agents are administered to treat significant intakes of radioactive elements such as plutonium, americium, and curium. These drugs may be used as a medical countermeasure after radiological accidents and terrorist acts. The administration of a chelating agent, such as Ca-DTPA or Zn-DTPA, affects the actinide's normal biokinetics. It enhances the actinide's rate of excretion, posing a dose assessment challenge. Thus, the standard biokinetic models cannot be directly applied to the chelation-affected bioassay data in order to assess the radiation dose. The present study reviews the scientific literature, from the early 1970s until the present, on the different studies that focused on developing new chelation models and/or modeling of bioassay data affected by chelation treatment. Although scientific progress has been achieved, there is currently no consensus chelation model available, even after almost 50 y of research. This review acknowledges the efforts made by different research groups, highlighting the different methodology used in some of these studies. Finally, this study puts into perspective where we were, where we are, and where we are heading in regards to chelation modeling.

61 RADIATION PROTECTION AND DOSIMETRY↗