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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

An Accuracy-Maximization Approach for Claims Classifiers in Document Content Analytics for Cybersecurity

This paper presents our research approach and findings towards maximizing the accuracy of our classifier of feature claims for cybersecurity literature analytics, and introduces the resulting model ClaimsBERT. Its architecture, after extensive evaluations of different approaches, introduces a feature map concatenated with a Bidirectional Encoder Representation from Transformers (BERT) model. We discuss deployment of this new concept and the research insights that resulted in the selection of Convolution Neural Networks for its feature mapping aspects. We also present our results showing ClaimsBERT to outperform all other evaluated approaches. This new claims classifier represents an essential processing stage within our vetting framework aiming to improve the cybersecurity of industrial control systems (ICS). Furthermore, in order to maximize the accuracy of our new ClaimsBERT classifier, we propose an approach for optimal architecture selection and determination of optimized hyperparameters, in particular the best learning rate, number of convolutions, filter sizes, activation function, the number of dense layers, as well as the number of neurons and the drop-out rate for each layer. Fine-tuning these hyperparameters within our model led to an increase in classification accuracy from 76% obtained with BertForSequenceClassification’s original model to a 97% accuracy obtained with ClaimsBERT.

Ameri, Kimia (ORCID:0000000328791871)↗
DOE OSTI2020

Measuring the dynamic response of the thylakoid architecture in plant leaves by electron microscopy

The performance of the photosynthesis machinery in plants, including light harvesting, electron transport, and protein repair is controlled by structural changes of the thylakoid membrane system inside the chloroplasts. In particular, the structure of the stacked grana area of thylakoid membranes is highly dynamic, changing in response to different environmental cues such as light intensity. For example, the aqueous thylakoid lumen enclosed by thylakoid membranes in grana has been documented to swell in the presence of light. However, light-induced alteration of the stromal gap in the stacked grana (partition gap) and of the unstacked stroma lamellae have not been well characterized. Light-induced changes of the entire thylakoid membrane system including the lumen in both stacked and unstacked domains as well as the partition gap are presented here, and the functional implications are discussed. This structural analysis was made possible by development of a robust semi-automated image analysis method combined with optimized plant tissue fixation techniques for transmission electron microscopy generating quantitative structural results for the analysis of thylakoid ultrastructure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Machine learning-based discovery of molecular descriptors that control polymer gas permeation

While machine learning has found increasing use in predicting the properties of polymeric materials with only a knowledge of chain architecture, determining the molecular factors underpinning properties (“interpretable AI”) has remained less well explored. We show that encoding chain chemistry in commonly employed formats, e.g., binary-valued fingerprints, leads to uniqueness issues during the hashing process to save storage space. This is because the hashing algorithm can map several chemical moieties into the same bit. These issues carry over into the ML algorithms, especially for “inverse” design and interpretable AI, and cannot be avoided by changing the length of the fingerprint. Using MACCS key featurizations of monomer repeats resolves some of these issues, and we show that a few substructures consistently appear in top features for maximizing permeability across several gases and ML models. These are carbon–carbon double bonds (as in polyacetylenes) especially when they are associated with methyl groups (found in branching architectures). Here these results, derived from the limited data set of ~ 500 polymers with experimental gas permeation data, are in agreement with physical insight and thus provide a robust foundation which could further enable study of these material classes through detailed experiments and simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Controlled synthesis of hierarchically-structured hybrid materials through peptoid engineering

This disclosure concerns a method for making a hybrid organic/inorganic material having an architecture. The method includes combining a peptoid comprising a sequence of N-substituted glycine residues and an inorganic material or inorganic material precursor to form a hybrid organic/inorganic material comprising the peptoid and the inorganic material, the hybrid organic/inorganic material having an architecture based at least in part on the peptoid sequence. The hybrid organic/inorganic materials include a cluster of nanoparticles of an inorganic material and peptoids, the cluster formed by random attachment of nanoparticles to one another by peptoid-peptoid and peptoid-nanoparticle surface interactions, wherein the hybrid material has an architecture based at least in part on the peptoid sequence.

Chen, Chun-Long↗
DOE OSTI2021

A pathway to desired functionalities in vertically aligned nanocomposites and related architectures

Epitaxial vertically aligned nanocomposites (VANs) and their related architectures have shown many intriguing features that are not available from conventional two-dimensional planar multilayers and heterostructures. The ability to control constituent, interface, microstructure, strain, and defects based on VANs has enabled the multiple degrees of freedom to manipulate the optical, magnetic, electrochemical, electronic, ionic, and superconducting properties for specific applications. This field has rapidly expanded from the interest in oxide:oxide to oxide:metal, metal:nitride and nitride:nitride systems. To achieve unparalleled properties of the materials, three-dimensional super-nanocomposites based on a hybrid of VAN and multilayer architectures have been recently explored as well. The challenges and opportunities of VAN films are also discussed in this article.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Real-time plasma monitoring framework for advanced plasma control and ML-research in DIII-D

Real-time and adaptive plasma control is crucial for robust tokamak operation, requiring sensitivity and tolerance measurements of the plasma state. This paper presents the implementation of an integrated real-time plasma monitoring framework on the DIII-D tokamak to support advanced control approaches, including machine-learning (ML) methods. The system is built on the SHIELD framework, a high-performance modular architecture that provides a unified pipeline for integrating diverse diagnostics. The framework leverages high-bandwidth digitizers, fast numerical processing, and deterministic, low-latency interconnects to stream high-fidelity data from diagnostics such as electron cyclotron emission (ECE), beam emission spectroscopy (BES), CO interferometers, and a visible tangential divertor camera (TangTV). The system’s validity is demonstrated through direct comparisons of real-time and offline data. Furthermore, we present two key applications of the developed plasma monitoring system with ML-based plasma control strategies, including real-time divertor detachment and active Alfvén Eigenmode control. As a result, this work presents a robust and scalable approach for integrating high-frequency, multidimensional diagnostics into advanced control algorithms for future fusion devices.

AI/ML↗
DOE OSTI2025

Potential-Controlled Deposition of Multilayer CO 2 Reduction Catalyst Films onto Silicon Photoelectrodes Demonstrates Thickness-Dependent Catalytic Rates

Covalently attaching molecular catalysts to semiconductor surfaces yields promising hybrid photoelectrode architectures for reducing CO 2 to higher-value carbon products. Polymeric molecular catalyst films have higher loading densities than their monolayer counterparts, promising greater rates of solar fuel production. Using photoassisted diazonium electrografting, multilayered films of a Re(apbpy)(CO) 3 Cl CO 2 -reduction catalyst were attached to low-doped p-type Si (pSi). Parallel characterization of the newly formed films with ellipsometry, XPS, and ICP-MS revealed that catalyst loading increased with increasingly negative applied grafting potentials (Vgraft), providing us an experimental test bed to study the effects of film thickness on photocatalytic performance. Controlled-potential electrolysis experiments showed enhanced CO evolution rates on all photoelectrodes with increasingly negative applied potentials (V app ), with thicker films exhibiting the greatest rates of enhancement. Competitive proton reduction reactions at the Si surface were not strongly linked to V app but dependent on film thickness, with thicker films showing increased CO-to-H 2 production ratios.

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

Supramolecular Tuning Enables Selective Oxygen Reduction Catalyzed by Cobalt Porphyrins for Direct Electrosynthesis of Hydrogen Peroxide

Abstract We report a supramolecular strategy for promoting the selective reduction of O 2 for direct electrosynthesis of H 2 O 2 . We utilized cobalt tetraphenylporphyrin (Co‐TPP), an oxygen reduction reaction (ORR) catalyst with highly variable product selectivity, as a building block to assemble the permanently porous supramolecular cage Co‐PB‐1(6) bearing six Co‐TPP subunits connected through twenty‐four imine bonds. Reduction of these imine linkers to amines yields the more flexible cage Co‐rPB‐1(6). Both Co‐PB‐1(6) and Co‐rPB‐1(6) cages produce 90–100 % H 2 O 2 from electrochemical ORR catalysis in neutral pH water, whereas the Co‐TPP monomer gives a 50 % mixture of H 2 O 2 and H 2 O. Bimolecular pathways have been implicated in facilitating H 2 O formation, therefore, we attribute this high H 2 O 2 selectivity to site isolation of the discrete molecular units in each supramolecule. The ability to control reaction selectivity in supramolecular structures beyond traditional host–guest interactions offers new opportunities for designing such architectures for a broader range of catalytic applications.

Smith, Peter T.↗
DOE OSTI2020

Supramolecular Tuning Enables Selective Oxygen Reduction Catalyzed by Cobalt Porphyrins for Direct Electrosynthesis of Hydrogen Peroxide

Abstract We report a supramolecular strategy for promoting the selective reduction of O 2 for direct electrosynthesis of H 2 O 2 . We utilized cobalt tetraphenylporphyrin (Co‐TPP), an oxygen reduction reaction (ORR) catalyst with highly variable product selectivity, as a building block to assemble the permanently porous supramolecular cage Co‐PB‐1(6) bearing six Co‐TPP subunits connected through twenty‐four imine bonds. Reduction of these imine linkers to amines yields the more flexible cage Co‐rPB‐1(6). Both Co‐PB‐1(6) and Co‐rPB‐1(6) cages produce 90–100 % H 2 O 2 from electrochemical ORR catalysis in neutral pH water, whereas the Co‐TPP monomer gives a 50 % mixture of H 2 O 2 and H 2 O. Bimolecular pathways have been implicated in facilitating H 2 O formation, therefore, we attribute this high H 2 O 2 selectivity to site isolation of the discrete molecular units in each supramolecule. The ability to control reaction selectivity in supramolecular structures beyond traditional host–guest interactions offers new opportunities for designing such architectures for a broader range of catalytic applications.

Smith, Peter T.↗
DOE OSTI2020

Efficient Control of Atom Arrangement in Ternary Metal Chalcogenide Nanoparticles Using Precursor Oxidation State

Controlling both the concentration and the distribution of elements in a given material is often crucial to extracting and optimizing synergistic properties of the various constituents. An interesting class of such multielement materials is metal chalcogenide nanoparticles, which exhibit a wide range of composition-dependent optoelectronic properties including both bandgap-mediated processes and localized surface plasmon resonance properties, each of which is useful in applications ranging from energy conversion to sensing. Because metal chalcogenide nanoparticles can support several different metal elements in a variety of chalcogen lattices, this material class has particularly benefited from the ability to control both atom concentration and atom arrangement to tailor final particle properties. The primary method to access complex, multimetallic chalcogenide particles is via a postsynthetic cation exchange strategy. One-pot syntheses have been less explored to access these complex particles, although this route is desirable for economy and scalability. In this work, we compare the composition and morphology outcomes from cation exchange and one-pot preparation approaches using a Cu/Ag/Se system, which is already known to exhibit both binary and ternary metal chalcogenide phases. We show that at similar concentrations of the two metal cations, initial reaction conditions for the one-pot method yield multicomponent nanoparticles, whereas cation exchange yields homogeneous ternary metal chalcogenide structures. We then show that by tuning the precursor oxidation state for the one-pot method, this approach can be used to access homogeneous ternary metal chalcogenide particles that are similar in atom arrangement to the particles obtained using cation exchange. Taken together, our results demonstrate reliable synthetic methods that yield a variety of controlled compositions and composition morphologies in the Cu/Ag/Se system. Importantly, we demonstrate that this entire collection of architectures can all be accessed via a one-pot method simply by modifying metal precursor chemistry. The mechanistic insights gained and the resulting streamlined syntheses outlined indicate pathways to easily scaled, highly tailorable syntheses for rapid translation into downstream technologies.

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

The structural basis for regulation of the glutathione transporter Ycf1 by regulatory domain phosphorylation

Yeast Cadmium Factor 1 (Ycf1) sequesters heavy metals and glutathione into the vacuole to counter cell stress. Ycf1 belongs to the ATP binding cassette C-subfamily (ABCC) of transporters, many of which are regulated by phosphorylation on intrinsically-disordered domains. The regulatory mechanism of phosphorylation is still poorly understood. Here, we report two cryo-EM structures of Ycf1 at 3.4 Å and 4.0 Å resolution in inward-facing open conformations that capture previously unobserved ordered states of the intrinsically disordered regulatory domain (R-domain). R-domain phosphorylation is clearly evident and induces a topology promoting electrostatic and hydrophobic interactions with Nucleotide Binding Domain 1 (NBD1) and the Lasso motif. These interactions stay constant between the structures and are related by rigid body movements of the NBD1/R-domain complex. Biochemical data further show R-domain phosphorylation reorganizes the Ycf1 architecture and is required for maximal ATPase activity. Together, we provide insights into how R-domains control ABCC transporter activity.

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

Cryo-EM structure of a methanogen nitrogenase-PII protein supercomplex

Abstract Nitrogenases are metalloenzymes that catalyze the reduction of atmospheric dinitrogen to ammonia, sustaining the global nitrogen cycle. While bacterial nitrogenase has been extensively characterized, the architecture and regulation of archaeal nitrogenases remain unknown despite longstanding evidence of nitrogen fixation in methanogens. Here we report a 3.1 Å cryo-electron microscopy structure of a native nitrogenase–PII protein supercomplex from Methanosarcina acetivorans. The structure reveals an unprecedented assembly of three NifDK heterotetramers bridged by six NifI1,2 heterotrimeric PII complexes, which sterically block NifH association and lock the enzyme in an inactive state. The NifI complexes display asymmetric binding of ADP and 2-oxoglutarate, coupling nitrogenase inhibition directly to cellular energy and nitrogen status. Addition of 2-oxoglutarate and ATP releases the NifI complexes, stimulating a threefold increase in NifDK activity in vitro. This higher-order architecture uncovers a previously unrecognized regulatory strategy in methanogens, in which PII proteins drive nitrogenase oligomerization to control activity. The discovery that nitrogenase activity may be modulated through direct assembly into higher-order structures opens new avenues for exploring nitrogenase evolution, regulation, and biotechnological applications. One sentence summary Discovery of a nitrogenase-PII protein supercomplex in methanogens, uncovering a metabolite-gated assembly mechanism for nitrogenase inhibition.

Nitrogenase, Electron Transfer, Methanogen↗
DOE OSTI2025

Virtual Power Plants: Pilots, Challenges, and Innovations Shaping Future Development

Virtual Power Plants (VPPs) aggregate distributed energy resources (DERs) to provide grid services traditionally delivered by centralized power plants. This article reviews the current state of VPP deployment, highlighting business models, compensation mechanisms, and global pilot projects. While VPPs offer benefits such as grid flexibility, resilience, and cost savings, challenges remain in communication infrastructure, regulatory frameworks, market access, and customer engagement. To address these, we propose a scalable, privacy-preserving hierarchical VPP architecture that coordinates with distribution utilities and preserves customer data. We also present the Integrated T&D Control Room of the Future as a key test bed for validating and accelerating VPP adoption. These innovations can help transition VPPs from pilot programs to integral components of a modern, reliable power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Diversity, taxonomy, and evolution of archaeal viruses of the class Caudoviricetes

The archaeal tailed viruses (arTV), evolutionarily related to tailed double-stranded DNA (dsDNA) bacteriophages of the class Caudoviricetes , represent the most common isolates infecting halophilic archaea. Only a handful of these viruses have been genomically characterized, limiting our appreciation of their ecological impacts and evolution. Here, we present 37 new genomes of haloarchaeal tailed virus isolates, more than doubling the current number of sequenced arTVs. Analysis of all 63 available complete genomes of arTVs, which we propose to classify into 14 new families and 3 orders, suggests ancient divergence of archaeal and bacterial tailed viruses and points to an extensive sharing of genes involved in DNA metabolism and counterdefense mechanisms, illuminating common strategies of virus–host interactions with tailed bacteriophages. Coupling of the comparative genomics with the host range analysis on a broad panel of haloarchaeal species uncovered 4 distinct groups of viral tail fiber adhesins controlling the host range expansion. The survey of metagenomes using viral hallmark genes suggests that the global architecture of the arTV community is shaped through recurrent transfers between different biomes, including hypersaline, marine, and anoxic environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Reflectin: Protein Driver of Dynamically Tunable Biophotonics; New Paradigm for Tunably Reconfigurable Materials

We discovered that the reflectins, with architecture and sequences unlike those of any other proteins known, exhibit a novel interplay between signal-controlled nucleation and growth of dynamically arrested liquid-liquid phase-segregated assemblies that uniquely enables the continuous and precise fine-tuning of physical properties governing the color and brightness of light reflected from the membrane-enclosed nanostructures that contain them. Our research included high-resolution structural analyses conducted at the DOE-BES user facilities of the Stanford Synchrotron Light Source and LBL National Laboratory’s Molecular Foundry, leveraging their capabilities for time-resolved SAXS and cryo-TEM with our ongoing genetic engineering, biophysical and computational analyses to identify the structural determinants and mechanisms governing the dynamic behaviors of the reflectins. We augmented these methods with EPR analyses that revealed for the first time the existence of a specific pathway of reflectin assembly. Using dynamic light scattering and continuously monitored circular dichroism and Raman microscopy, we elucidated the progression of structural changes underlying the mechanisms of signal-induced condensation, folding, assembly, liquefaction, dynamic arrest, regulation and reversal.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Magnon confinement in epitaxial antiferromagnetic oxide heterostructures.

Magnons, the quanta of spin waves, have been extensively studied in a range of materials for spintronics, particularly for non-volatile logic-in-memory devices. Controlling magnons in conventional antiferromagnets and harnessing them in practical applications, however, remains a challenge. Here, we demonstrate highly efficient magnon transport in a LaFeO3/ BiFeO3/ LaFeO3 all-antiferromagnetic system, which can be controlled electrically, making it highly desirable for energy-efficient computation. Leveraging spin-orbit-driven spin-charge transduction, we demonstrate that this material architecture permits magnon confinement in ultrathin antiferromagnets, enhancing the output voltage generated by magnon transport by several orders of magnitude, which provides a pathway to enable magnetoelectric memory and logic functionalities. Additionally, the non-volatility of output voltage enables ultralowpower logic-in-memory processing, where magnonic devices can be efficiently reconfigured via electrically controlled magnon spin currents within magnetoelectric channels.

Husain, Sajid↗
DOE OSTI2021

A Cyber-Physical Anomaly Detection for Wide-Area Protection Using Machine Learning

Wide-area protection scheme (WAPS) provides system-wide protection by detecting and mitigating small and large-scale disturbances that are difficult to resolve using local protection schemes. As this protection scheme is evolving from a substation-based distributed remedial action scheme (DRAS) to the control center-based centralized RAS (CRAS), it presents severe challenges to their cybersecurity because of its heavy reliance on an insecure grid communication, and its compromise would lead to system failure. This article presents an architecture and methodology for developing a cyber-physical anomaly detection system (CPADS) that utilizes synchrophasor measurements and properties of network packets to detect data integrity and communication failure attacks on measurement and control signals in CRAS. The proposed machine leaning-based methodology applies a rules-based approach to select relevant input features, utilizes variational mode decomposition (VMD) and decision tree (DT) algorithms to develop multiple classification models, and performs final event identification using a rules-based decision logic. Here, we have evaluated the proposed methodology of CPADS using the IEEE 39 bus system for several performance measures (accuracy, recall, precision, and F-measure) in a cyber-physical testbed environment. Furthermore, our experimental results reveal that the proposed algorithm (VMD-DT) of CPADS outperforms the existing machine learning classifiers during noisy and noise-free measurements while incurring an acceptable processing overhead.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

SoS-SDQN: System of Systems Software-defined Quantum Networking

Quantum networks are needed for quantum domain applications that may run across different network deployments - point-to-point, multi-node networks, and possibly across inter-domain quantum networks, like the quantum internet. Unlike classical computing networks, quantum networks involve heterogeneous systems nodes that currently require local and manual control. This needs a unified control approach to help them integrate, work seamlessly, and have global knowledge. Software-defined Networking (SDN) has been successfully leveraged in classical networking for seamless and software-driven control of network infrastructure and packet switching, but not in management of quantum network applications across heterogeneous systems. In this paper, we review the current state of the art and present early developments of a System-of-Systems Software-defined Quantum Networking architecture (SoS-SDQN), a generic architecture that supports software-driven quantum network experiments across heterogeneous quantum systems. The architecture modifies the generic SDN to address the domain requirements of quantum networks and proposes a multilevel SDQN to provide a global view of network status, running applications, and control of incorporated heterogeneous quantum systems. We also design and implement a SoS SouthBound Quantum Interface (SoS-SBQI), a quantum infrastructure protocol that abstracts automation of applications across the network.

Alnajjar, Anees [ORNL] (ORCID:0000000237101601)↗