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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 217 records · Page 12

Editorial: Artificial Intelligence and Machine Learning Applications in Plant Genomics and Genetics

In plants, as in other species, genotypic variation in combination with environmental variation leads to differences in the biochemical makeup of cells, measurable as molecular phenotypes. These in turn influence physiological and developmental traits such as organ formation and plant growth, and eventually traits relevant in agriculture, such as yield and stress tolerance. Thus, relating genotypes to phenotypes yields fundamental insights into the regulation of important processes in plant development and physiology, but also provides the ability to predict yield and quality traits in specific environments, which is essential in basic plant science and molecular breeding of resilient plants in changing environments.

59 BASIC BIOLOGICAL SCIENCES↗

Enhancement of chemical oscillations by self-generated convective flows

Chemical feedback loops in fluids can produce not only chemical oscillations, but also density variations that generate solutal buoyancy forces, which in turn initiate fluid flow. Using analytical and computational models, we herein examine how the reaction-induced flows alter the chemical oscillations in a fluid-filled chamber whose top and bottom walls are coated with different enzymes. Due to this chemo-fluidic coupling, the systems form oscillating flow patterns, which combine the characteristic size of the buoyancy-driven convection rolls with the frequency of the chemical oscillations. With changes in the distance between the enzyme-coated walls, the convective flows not only enhance or suppress the chemical oscillations, but also substantially increase the amplitude and frequency of the oscillations and extend the regime of the oscillatory behavior. These design principles can facilitate the development of artificial biochemical networks that act as chemical clocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Emergency Management of Tomorrow Research: Emergency Operations Center of the Future Tabletop Exercise Nashua, NH Tabletop Exercise

As part of the Emergency Management (EM) of Tomorrow Research (EMOTR) program, sponsored by the Department of Homeland Security (DHS) Science and Technology (S&T) Directorate, Pacific Northwest National Laboratory (PNNL) developed concepts for the Emergency Operations Center (EOC) of the Future to provide recommendations to assist DHS S&T in future decision-making with regards to research and development (R&D) and investments toward establishing a framework for a national, coordinated approach to EM. PNNL is conducting tabletop exercises (TTXs) designed to assess the impacts and benefits of emerging technologies on EM organizations.

99 GENERAL AND MISCELLANEOUS↗

Emergency Management of Tomorrow Research: Emergency Operations Center of the Future Seattle, WA Tabletop Exercise

As part of the Emergency Management (EM) of Tomorrow Research (EMOTR) program, sponsored by the Department of Homeland Security (DHS) Science and Technology (S&T) Directorate, Pacific Northwest National Laboratory (PNNL) developed concepts for the Emergency Operations Center (EOC) of the Future to provide recommendations to assist DHS S&T in future decision-making with regards to research and development (R&D) and investments toward establishing a framework for a national, coordinated approach to EM. PNNL is conducting tabletop exercises (TTXs) designed to assess the impacts and benefits of emerging technologies on EM organizations.

99 GENERAL AND MISCELLANEOUS↗

Deep learning for electron and scanning probe microscopy: From materials design to atomic fabrication

Machine learning and artificial intelligence (ML/AI) are rapidly becoming an indispensable part of physics research, with applications ranging from theory and materials prediction to high-throughput data analysis. In parallel, the recent successes in applying ML/AI methods for autonomous systems from robotics through self-driving cars to organic and inorganic synthesis are generating enthusiasm for the potential of these techniques to enable automated and autonomous experiment in imaging. Here, we discuss recent progress in application of machine learning methods in scanning transmission electron microscopy and scanning probe microscopy, from applications such as data compression and exploratory data analysis to physics learning to atomic fabrication.

36 MATERIALS SCIENCE↗

Seeking regularity from irregularity: unveiling the synthesis–nanomorphology relationships of heterogeneous nanomaterials using unsupervised machine learning

Nanoscale morphology of functional materials determines their chemical and physical properties. However, despite increasing use of transmission electron microscopy (TEM) to directly image nanomorphology, it remains challenging to quantify the information embedded in TEM data sets, and to use nanomorphology to link synthesis and processing conditions to properties. We develop an automated, descriptor-free analysis workflow for TEM data that utilizes convolutional neural networks and unsupervised learning to quantify and classify nanomorphology, and thereby reveal synthesis–nanomorphology relationships in three different systems. While TEM records nanomorphology readily in two-dimensional (2D) images or three-dimensional (3D) tomograms, we advance the analysis of these images by identifying and applying a universal shape fingerprint function to characterize nanomorphology. After dimensionality reduction through principal component analysis, this function then serves as the input for morphology grouping through unsupervised learning. We demonstrate the wide applicability of our workflow to both 2D and 3D TEM data sets, and to both inorganic and organic nanomaterials, including tetrahedral gold nanoparticles mixed with irregularly shaped impurities, hybrid polymer-patched gold nanoprisms, and polyamide membranes with irregular and heterogeneous 3D crumple structures. In each of these systems, unsupervised nanomorphology grouping identifies both the diversity and the similarity of the nanomaterial across different synthesis conditions, revealing how synthetic parameters guide nanomorphology development. Our work opens possibilities for enhancing synthesis of nanomaterials through artificial intelligence and for understanding and controlling complex nanomorphology, both for 2D systems and in the far less explored case of 3D structures, such as those with embedded voids or hidden interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

AENET–LAMMPS and AENET–TINKER : Interfaces for accurate and efficient molecular dynamics simulations with machine learning potentials

Machine-learning potentials (MLPs) trained on data from quantum-mechanics based first-principles methods can approach the accuracy of the reference method at a fraction of the computational cost. To facilitate efficient MLP-based molecular dynamics and Monte Carlo simulations, an integration of the MLPs with sampling software is needed. Here, we develop two interfaces that link the atomic energy network (ænet) MLP package with the popular sampling packages TINKER and LAMMPS. The three packages, ænet, TINKER, and LAMMPS, are free and open-source software that enable, in combination, accurate simulations of large and complex systems with low computational cost that scales linearly with the number of atoms. Scaling tests show that the parallel efficiency of the ænet–TINKER interface is nearly optimal but is limited to shared-memory systems. The ænet–LAMMPS interface achieves excellent parallel efficiency on highly parallel distributed memory systems and benefits from the highly optimized neighbor list implemented in LAMMPS. We demonstrate the utility of the two MLP interfaces for two relevant example applications: the investigation of diffusion phenomena in liquid water and the equilibration of nanostructured amorphous battery materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Energy Management Information Systems Technical Resources Report

Guide supports federal facility staff in understanding, designing, procuring, and implementing Energy Management Information Systems (EMIS) as a valuable component of their portfolio-level energy and water planning and management strategies. As a broad and rapidly evolving family of tools that monitor, analyze, and control building energy use and system performance, EMIS tools present significant opportunities for federal sector energy savings and improved operational performance. EMIS are at the forefront of transforming energy management best practices by providing building owners and operators with well-organized building performance and energy consumption data, enabling a host of analytic capabilities. These capabilities include portfolio-wide energy benchmarking, data visualization, and key performance indicator tracking; automated fault detection and diagnostics (AFDD); artificial intelligence for predictive analytics and control; automated measurement and verification of energy conservation measures; and supervisory control enabling automated system optimization and demand management.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Maturation of Rhodobacter capsulatus Multicopper Oxidase CutO Depends on the CopA Copper Efflux Pathway and Requires the cutF Product (Final Report)

The goal is to achieve a comprehensive understanding of the nature, mechanism of function and biogenesis of c-type cytochromes and their oligomeric complexes. These cytochrome are ubiquitous heme proteins that are required for cellular bioenergetics, including photosynthesis (Ps) and respiration (Res), which are central to chemical energy (ATP) production by oxidative- and photophosphorylation. We contribute to the molecular characterization of individual and membrane-integral cytochromes as parts of Ps and Res electron transport (ET) pathways, using the facultative phototrophic bacteria of as excellent models for multidisciplinary investigations. Supported by this grant we discovered novel membrane-bound cytochromes and cyts c complexes that are important for Ps- and Res-ET. We worked out their biogenesis including maturation (covalent heme addition) and assembly of mature subunits into complexes. These involve fundamental process found virtually in all organisms and are fundamental processes with major significance to the “Photosynthetic Systems” program of DOE-BES, because the cytochromes are integral components of natural energy production systems. Elucidation of basic principles, and the knowledge gained by their study greatly impact on our ability to design, engineer, and create new natural, bio-hybrid, bio-inspired and artificial systems to better capture light, transduce and store its energy with improved efficacy and are of broad significance.

14 SOLAR ENERGY↗

Hybrid Heterostructures to Generate Long-Lived and Mobile Photocarriers in Graphene

We report the generation of long-lived and highly mobile photocarriers in hybrid van der Waals heterostructures that are formed by monolayer graphene, few-layer transition metal dichalcogenides, and the organic semiconductor F 8 ZnPc. Samples are fabricated by dry transfer of mechanically exfoliated MoS 2 or WS 2 few-layer flakes on a graphene film, followed by deposition of F 8 ZnPc. Transient absorption microscopy measurements are performed to study the photocarrier dynamics. In heterostructures of F 8 ZnPc/few-layer-MoS 2 /graphene, electrons excited in F 8 ZnPc can transfer to graphene and thus be separated from the holes that reside in F 8 ZnPc. By increasing the thickness of MoS 2 , these electrons acquire long recombination lifetimes of over 100 ps and a high mobility of 2800 cm 2 V–1 s –1 . Graphene doping with mobile holes is also demonstrated with WS 2 as the middle layers. Furthermore, these artificial heterostructures can improve the performance of graphene-based optoelectronic devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

A microfluidic platform for the synthesis of polymer and polymer-protein-based protocells

In this study, we demonstrate the fabrication of polymersomes, protein-blended polymersomes, and polymeric microcapsules using droplet microfluidics. Polymersomes with uniform, single bilayers and controlled diameters are assembled from water-in-oil-in-water double-emulsion droplets. This technique relies on adjusting the interfacial energies of the droplet to completely separate the polymer-stabilized inner core from the oil shell. Protein-blended polymersomes are prepared by dissolving protein in the inner and outer phases of polymer-stabilized droplets. Cell-sized polymeric microcapsules are assembled by size reduction in the inner core through osmosis followed by evaporation of the middle phase. All methods are developed and validated using the same glass-capillary microfluidic apparatus. This integrative approach not only demonstrates the versatility of our setup, but also holds significant promise for standardizing and customizing the production of polymer-based artificial cells.

36 MATERIALS SCIENCE↗

Positive correlations between soil C stabilization and loss are regulated by roots, minerals, and microbes

Modern conceptual models of soil organic carbon (SOC) cycling place a strong focus on the microbe-mineral interactions that regulate C stabilization. However, the formation of ‘stable’ soil organic matter, which consists mainly of microbial residues bonded to mineral surfaces, is inextricably linked to C loss through microbial respiration. Therefore, what is the net impact of microbial metabolism on the total quantity of C held in the soil? To address this question, we constructed artificial root-soil systems to identify controls on C cycling across the plant-microbe-mineral continuum, simultaneously quantifying the formation of persistent mineral-associated C and C losses to respiration. Roots and minerals interacted to regulate these processes: while roots stimulated respiratory C losses and depleted mineral-associated C pools in low-activity clays, roots triggered formation of stable C in high-activity clays. Moreover, we observed a strong positive correlation between the formation of mineral-associated C and respiration. This suggests that the growth of persistent C pools which can resist subsequent disturbance comes at the expense of C loss from the system.

58 GEOSCIENCES↗

The United States Department of Energy and National Institutes of Health Collaboration: Medical Care Advances by Discovery in Radiation Detection

A National Institutes of Health (NIH) and U.S. Department of Energy (DOE) Office of Science virtual workshop on shared general topics was held in July of 2021 and reported on in this publication in January of 2023. Following the inaugural 2021 joint meeting representatives from the DOE Office of Science and NIH met to discuss organizing a second joint workshop that would concentrate on radiation detection to bring together teams from both agencies and their grantee populations to stimulate collaboration and efficiency. To meet this scientific mission within the NIH and DOE radiation detection space, the organizers assembled workshop sessions covering the state–of–the–art in cameras, detectors, and sensors for radiation external and internal (diagnostic and therapeutic) to human, data acquisition and electronics, image reconstruction and processing, and the application of artificial intelligence. NIH and DOE are committed to continuing the process of convening a joint workshop every 12–24 months. This Special Report recaps the findings of this second workshop. Beyond showing only the innovations and areas of success, important gaps in our knowledge were defined and presented. Finally, we summarize by defining four areas of greatest opportunity and need that emerged from the unique, dynamic dialogue the in–person workshop provided the attendees.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Structure-driven development of a biomimetic rare earth artificial metalloprotein

The 2011 discovery of the first rare earth–dependent enzyme in methylotrophic Methylobacterium extorquens AM1 prompted intensive research toward understanding the unique chemistry at play in these systems. This enzyme, an alcohol dehydrogenase (ADH), features a La 3+ ion closely associated with redox-active coenzyme pyrroloquinoline quinone (PQQ) and is structurally homologous to the Ca 2+ -dependent ADH from the same organism. AM1 also produces a periplasmic PQQ-binding protein, PqqT, which we have now structurally characterized to 1.46-Å resolution by X-ray diffraction. This crystal structure reveals a Lys residue hydrogen-bonded to PQQ at the site analogously occupied by a Lewis acidic cation in ADH. Accordingly, we prepared K 142 A- and K 142 D-PqqT variants to assess the relevance of this site toward metal binding. Isothermal titration calorimetry experiments and titrations monitored by UV–Vis absorption and emission spectroscopies support that K 142 D-PqqT binds tightly (Kd = 0.6 ± 0.2 μM) to La 3+ in the presence of bound PQQ and produces spectral signatures consistent with those of ADH enzymes. These spectral signatures are not observed for WT- or K 142 A-variants or upon addition of Ca 2+ to PQQ ⸦ K 142 D-PqqT. Addition of benzyl alcohol to La 3+ -bound PQQ ⸦ K 142 D-PqqT (but not Ca 2+ -bound PQQ ⸦ K 142 D-PqqT, or La 3+ -bound PQQ ⸦ WT-PqqT) produces spectroscopic changes associated with PQQ reduction, and chemical trapping experiments reveal the production of benzaldehyde, supporting ADH activity. By creating a metal binding site that mimics native ADH enzymes, we present a rare earth-dependent artificial metalloenzyme primed for future mechanistic, biocatalytic, and biosensing applications.

Science & Technology - Other Topics↗

A protein scaffold enables hydrogen evolution for a Ni-bisdiphosphine complex

We find that an artificial metalloenzyme acting as a functional biomimic of hydrogenase enzymes was activated by assembly via covalent attachment of the molecular complex, [Ni(PN glycine P) 2 ] 2- , within a structured protein scaffold. Electrocatalytic H2 production was observed from pH 3.0 to 10.0 for the artificial enzyme, while no electrocatalytic activity was observed for similar [Ni(PNP) 2 ] 2+ systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Emergency Management of Tomorrow Research: Emergency Operations Center of the Future Madison, WI Tabletop Exercise

As part of the Emergency Management (EM) of Tomorrow Research (EMOTR) program, sponsored by the Department of Homeland Security (DHS) Science and Technology (S&T) Directorate, Pacific Northwest National Laboratory (PNNL) developed concepts for the Emergency Operations Center (EOC) of the Future to provide recommendations to assist DHS S&T in future decision-making with regards to research and development (R&D) and investments toward establishing a framework for a national, coordinated approach to EM. PNNL is conducting tabletop exercises (TTXs) designed to assess the impacts and benefits of emerging technologies on EM organizations.

99 GENERAL AND MISCELLANEOUS↗