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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

CuXASNet: Rapid and accurate prediction of copper L-edge x-ray absorption spectra using machine learning

In this work, we have developed CuXASNet, a dense neural network that predicts simulated Cu -edge x-ray absorption spectra (XAS) from atomic structures. Featurization of the Cu local environment is performed using a component of M3GNet, a graph neural network developed for predicting the potential energy surface. CuXASNet is trained on simulated spectra from FEFF9 at the multiple scattering level of theory, and can predict the and edges for Cu sites to quantitative accuracy. To validate our approach, we compare 14 experimental spectra extracted from the literature with the predictions of CuXASNet. The agreement of CuXASNet with experiments is shown by an average mean absolute error of 0.125 and an average Spearman's correlation coefficient of 0.891, which is comparable to FEFF9's values of 0.131 and 0.898 for the same metrics. As such, CuXASNet can rapidly predict a large number of -edge XAS spectra at the same accuracy as FEFF9 simulations. This can be used as a drop-in replacement for multiple scattering codes for fast screening of candidate atomic structure models of a measured system. This model establishes a general framework for Cu XAS prediction, and can be extended to more computationally expensive levels of theory and to other transition metal edges.

36 MATERIALS SCIENCE↗
DOE OSTI2019

ASCR Workshop on In Situ Data Management

In January 2019, the U.S. Department of Energy, Office of Science program in Advanced Scientific Computing Research, convened a workshop to identify priority research directions for in situ data management (ISDM). The workshop defined ISDM as the practices, capabilities, and procedures to control the organization of data and enable the coordination and communication among heterogeneous tasks, executing simultaneously in a high-performance computing system, cooperating toward a common objective. The workshop revealed two primary, interdependent motivations for processing and managing data in situ. The first motivation is that the in situ methodology enables scientific discovery from a broad range of data sources over a wide scale of computing platforms: leadership-class systems, clusters, clouds, workstations, and embedded devices at the edge. The successful development of ISDM capabilities will benefit real-time decision-making, design optimization, and data-driven scientific discovery. The second motivation is the need to decrease data volumes. ISDM can make critical contributions to managing large data volumes from computations and experiments to minimize data movement, save storage space, and boost resource efficiency, often while simultaneously increasing scientific precision.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2016

Accelerated Climate Modeling for Energy (ACME) – Atmospheric Radiation Measurement (ARM) Climate Research Facility – Atmospheric System Research (ASR) Coordination Workshop, October 21–22, 2015

The Climate and Environmental Sciences Division (CESD) of the U.S. Department of Energy’s Office of Biological and Environmental Research focuses on advancing a robust predictive understanding of Earth’s climate and environmental systems to inform the development of sustainable solutions to the Nation’s energy and environmental challenges. CESD climate activities related to atmospheric processes include: observations through the Atmospheric Radiation Measurement (ARM) Climate Research Facility; atmospheric research and model parameterization development through the Atmospheric System Research (ASR) program; climate model development and climate research through the Accelerated Climate Modeling for Energy (ACME) project along with other computationally focused model-development activities within the CESD Earth System Modeling (ESM) program, and development of robust model analytical and testing frameworks at multiple scales through the Regional and Global Climate Modeling program. This workshop focused primarily on improving model treatment of atmospheric processes as a means to focus discussion and did not address research on terrestrial ecosystem and subsurface processes, which are also part of the CESD research portfolio.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Optimizing $\mathrm{ACRT}$ to reduce inclusion formation during the $\mathrm{VGF}$ growth of cadmium zinc telluride: I. Computational approach

Theoretical computations reveal insight into parameters that govern the accelerated crucible rotation technique (ACRT) applied to the gradient freeze (VGF) growth of cadmium zinc telluride (CZT). A metric based on the classic Mullins and Sekerka instability criterion is put forth that provides a quantitative means of assessing the impact of different ACRT rotation schedules on morphological stability and inclusion formation during CZT growth. Here this metric is employed in a 2-k factorial design of experiments that identifies the maximum rotation rate as the most important ACRT parameter, followed by the acceleration period and the rest period. Subsequent optimization of rotation schedule is performed for a specific VGF growth system, and mechanistic explanations are provided for the preferred ACRT schedule, which improves interface stability via slower rotation rates and longer acceleration periods than would be applied using classical ACRT schedules.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Electric field stimulates production of highly conductive microbial OmcZ nanowires

Multifunctional living materials are attractive due to their powerful ability to self-repair and replicate. However, most natural materials lack electronic functionality. Here we show that an electric field, applied to electricity-producing Geobacter sulfurreducens biofilms, stimulates production of cytochrome OmcZ nanowires with 1,000-fold higher conductivity (30 S cm -1 ) and threefold higher stiffness (1.5 GPa) than the cytochrome OmcS nanowires that are important in natural environments. Using chemical imaging-based multimodal nanospectroscopy, we correlate protein structure with function and observe pH-induced conformational switching to β-sheets in individual nanowires, which increases their stiffness and conductivity by 100-fold due to enhanced π-stacking of heme groups; this was further confirmed by computational modeling and bulk spectroscopic studies. These nanowires can transduce mechanical and chemical stimuli into electrical signals to perform sensing, synthesis and energy production. Overall, these findings of biologically produced, highly conductive protein nanowires may help to guide the development of seamless, bidirectional interfaces between biological and electronic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Liquid Metals as Plasma-facing Materials for Fusion Energy Systems: From Atoms to Tokamaks

The objective of our studies was to advance our fundamental understanding of liquid metals as plasma-facing materials for fusion energy systems, with a broad scope: from atoms to tokamaks. The flow of liquid metals offers solutions to significant problems of the plasma-facing materials for fusion energy systems. Candidate metals include lithium, tin, gallium, and their eutectic combinations. However, such liquid metal solutions can only be designed efficiently if a range of scientific and engineering issues are resolved that require advances in fundamental fluid dynamics, materials science and surface science. In our research we investigated a range of significant and timely problems relevant to current and proposed engineering designs for fusion reactors, including high-heat flux configurations that are being considered by leading fusion energy groups world-wide. Using experimental and theoretical tools spanning atomistic to continuum descriptions of liquid metals, and bridging surface chemistry, wetting/dewetting and flow, our research has advanced the science and engineering of fusion energy materials and systems. Specifically, we developed a combined experimental and theoretical program to investigate flows of liquid metals in fusion-relevant geometries, including equilibrium and stability of thin-film flows, e.g. wetting and dewetting, effects of electromagnetic and thermocapillary fields on liquid metal thin-film flows, and how chemical interactions and the properties of the surface are influenced by impurities and in turn affect the surface wetting characteristics, the surface tension, and its gradients. Because high-heat flux configurations produce evaporation and sputtering, which forces rearrangement of the liquid, and any dewetting exposes the substrate to damage from the plasma, our studies addressed such evaporatively driven liquid flows and measured and simulated properties of the different bulk phases and material interfaces. The range of our studies included (i) quantum mechanical calculations that allow inclusion of many thousands of atoms for the characterization of the interface of liquid metals exposed to continuous bombardment by deuterium and tritium as expected in fusion, (ii) molecular dynamics studies of the phase behavior of liquid metals, which (a) utilize thermodynamic properties computed using our quantum mechanical calculations and (b) establish material and wetting properties of the liquid metals, including relevant eutectics, (iii) experimental investigations of the surface science of liquid metals, interacting both with the solid substrate as well as gaseous species, and (iv) fluid dynamical studies that incorporate the material and surface science results of (ii) and (iii) in order to characterize flow in capillary porous materials and the thin-film flow along curved boundaries, both of which are potentially major components of plasma-facing materials. The outcome of these integrated studies was new understanding that enables developing design rules useful for future developments of the plasma-facing components critical to the success of fusion energy systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effective many-body interactions in reduced-dimensionality spaces through neural network models

Accurately describing properties of challenging problems in physical sciences often requires complex mathematical models that are unmanageable to tackle head on. Therefore, developing reduced-dimensionality representations that encapsulate complex correlation effects in many-body systems is crucial to advance the understanding of these complicated problems. However, a numerical evaluation of these predictive models can still be associated with a significant computational overhead. To address this challenge, in this paper we discuss a combined framework that integrates recent advances in the development of active-space representations of coupled cluster (CC) downfolded Hamiltonians with neural network approaches. The primary objective of this effort is to train neural networks to eliminate the computationally expensive steps required for evaluating hundreds or thousands of Hugenholtz diagrams, which correspond to multidimensional tensor contractions necessary for evaluating a many-body form of downfolded effective Hamiltonians. Using small molecular systems (the H 2 O and HF molecules) as examples, we demonstrate that training neural networks employing effective Hamiltonians for a few nuclear geometries of molecules can accurately interpolate or extrapolate their forms to other geometrical configurations characterized by different intensities of correlation effects. We also discuss differences between effective interactions that define CC downfolded Hamiltonians with those of bare Hamiltonians defined by Coulomb interactions in the active spaces. Published by the American Physical Society 2024

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

LSE-163: Data Products Definition Document

This document describes the data products and processing services to be delivered by the NSF-DOE Vera C. Rubin Observatory whilst performing the Legacy Survey of Space and Time (LSST). LSST will deliver three levels of data products and services. Prompt data products are computed and released within 24 hours of observation, and include images, difference images, catalogs of sources and objects detected in difference images, and catalogs of Solar System objects. Their primary purpose is to enable rapid follow-up of time-domain events. Data Release data products are computed during annual processing campaigns, and include well-calibrated single-epoch images, deep coadds, and catalogs of objects, sources, and forced sources, enabling static sky and precision time-domain science. The Science Platform will allow for the creation of User Generated data products and will enable science cases that greatly benefit from co-location of user processing and/or data within the Rubin Observatory Data Access Center. LSST will also devote 10% of observing time to programs with special cadence. Their data products will be created using the same software and hardware as Prompt and Data Release products. All data products will be made available using user-friendly databases and web services.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Vision 20/20: Simultaneous CT-MRI — Next chapter of multimodality imaging

Multimodality imaging systems such as positron emission tomography-computed tomography (PET-CT) and MRI-PET are widely available, but a simultaneous CT-MRI instrument has not been developed. Synergies between independent modalities, e.g., CT, MRI, and PET/SPECT can be realized with image registration, but such postprocessing suffers from registration errors that can be avoided with synchronized data acquisition. The clinical potential of simultaneous CT-MRI is significant, especially in cardiovascular and oncologic applications where studies of the vulnerable plaque, response to cancer therapy, and kinetic and dynamic mechanisms of targeted agents are limited by current imaging technologies. The rationale, feasibility, and realization of simultaneous CT-MRI are described in this perspective paper. The enabling technologies include interior tomography, unique gantry designs, open magnet and RF sequences, and source and detector adaptation. Based on the experience with PET-CT, PET-MRI, and MRI-LINAC instrumentation where hardware innovation and performance optimization were instrumental to construct commercial systems, the authors provide top-level concepts for simultaneous CT-MRI to meet clinical requirements and new challenges. Simultaneous CT-MRI fills a major gap of modality coupling and represents a key step toward the so-called “omnitomography” defined as the integration of all relevant imaging modalities for systems biology and precision medicine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Finding the missing pieces: filling gaps that impede the translation of omics data into models

High-throughput omics technologies such as DNA sequencing have made the sequencing and computational assembly of microbial genomes recovered from the environment relatively routine. Computational inference of the protein products encoded by these genomes, and the associated biochemical functions, should enable the accurate prediction and modeling of microbial metabolism, organismal interactions, and ecosystem processes. However, a lack of scalable, probabilistic protein annotation tools limits the full potential of modeling for understanding the metabolism and biogeochemical cycles of microbial communities. Our approach to improve inference of protein annotations and metabolic models relied on learning from and emulating expert manual curation, leveraging software engineering and data science best practices to scale up the throughput and accuracy of annotations and metabolic model construction, building software to objectively evaluate different annotation strategies, and more closely linking the protein annotation and metabolic model inference process. Outcomes of this research include several improved or new computational tools, including DRAM (Distilled and Refined Annotation of Metabolism) for annotating microbial genomes with protein function and metabolic traits, CAMPER (Curated Annotations for Microbial Polyphenol Enzymes and Reactions) for annotating key polyphenol metabolisms, EC-Bench for comprehensive and unbiased benchmarking of annotation tools, and several apps available via the DOE Systems Biology Knowledgebase (KBase) for building genome-scale metabolic models. We demonstrate that these tools allow us to scalably annotate and understand thousands of genomes for microbial communities from a variety of systems and test cases, including rivers, thawing permafrost, and gut microbiomes. All of these computational tools are available as open-source software, with most broadly and easily accessible to the scientific community via KBase apps.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Computational tools for the simulation and analysis of spin-polarized EPR spectra

The EPR spectra of paramagnetic species induced by photoexcitation typically exhibit enhanced absorptive and emissive features resulting from sublevel populations that differ from thermal equilibrium. The populations and the resulting spin polarization of the spectra are dictated by the selectivity of the photophysical process generating the observed state. Simulation of the spin-polarized EPR spectra is crucial in the characterization of both the dynamics of formation of the photoexcited state as well as its electronic and structural properties. EasySpin, the simulation toolbox for EPR spectroscopy, now includes extended support for the simulation of the EPR spectra of spin-polarized states of arbitrary spin multiplicity and formed by a variety of different mechanisms, including photoexcited triplet states populated by intersystem crossing, charge recombination or spin polarization transfer, spin-correlated radical pairs created by photoinduced electron transfer, triplet pairs formed by singlet fission and multiplet states arising from photoexcitation in systems containing chromophores and stable radicals. In this paper, we highlight EasySpin’s capabilities for the simulation of spin-polarized EPR spectra on the basis of illustrative examples from the literature in a variety of fields ranging across chemistry, biology, material science and quantum information science.

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

Design methodologies and engineering applications for ecosystem biomimicry: an interdisciplinary review spanning cyber, physical, and cyber-physical systems

Abstract Ecosystem biomimicry is a promising pathway for sustainable development. However, while typical form- and process-level biomimicry is prevalent, system-level ecosystem biomimicry remains a nascent practice in numerous engineering fields. This critical review takes an interdisciplinary approach to synthesize trends across case studies, evaluate design methodologies, and identify future opportunities when applying ecosystem biomimicry to engineering practices, including cyber systems (CS), physical systems (PS), and cyber-physical systems (CPS). After systematically sourcing publications from major databases, the papers were first analyzed at a meta level for their bibliographic context and for statistical correlations among categorical variables. Then, we investigated deeper into the engineering applications and design methodologies. Results indicate that CPS most frequently mimic organisms and ecosystems, while CS and PS frequently mimic populations-communities and molecules-tissues-organ systems, respectively (statistically highly significant). An indirect approach is most often used for mimicry at organizational levels from populations to ecosystems, while a direct approach frequently suits levels from molecules to organisms (highly significant). Dominant themes across engineering applications include symbiotic organism search algorithms for CS and ecological network analysis for CPS, while PS are highly diverse. For design methodologies, this work summarizes and details ten well-documented biomimetic process models among literature, which addresses an outdated concern for a lack of systematic methods for ecosystem biomimicry. In addition to the Biomimetics Standard ISO 18458, these methods include the Natural Step and Techno-Ecological Synergy framework, among others. Further, the analyses revealed future opportunities from less utilized design methods (e.g. interdisciplinary teams tackling indirect, ecosystem-level projects) to well-established engineering concepts ready for technological advancement (e.g. implementing membrane computing for physical applications). For future studies, this review provides a comprehensive reference for ecosystem biomimetic design practices and application opportunities across multiple engineering domains.

42 ENGINEERING↗
DOE OSTI2015

DShaper: An approach for handling missing low-Q data in pair distribution function analysis of nanostructured systems

In this work we discuss the potential problems and currently available solutions in modeling powder-diffraction based pair-distribution function (PDF) data from systems where morphological feature information content includes distances in the nanometer length scale, such as finite nanoparticles, nanoporous networks, and nanoscale precipitates in bulk materials. The implications of an experimental finite minimum Q-value are addressed by simulation, which also demonstrates the advantages of combining PDF data with small angle scattering data (SAS). In addition, we introduce a simple Fortran90 code, DShaper , which may be incorporated into PDF data fitting routines in order to approximate the so-called shape-function for any atomistic model.

36 MATERIALS SCIENCE↗
DOE OSTI2016

GPU acceleration of the Locally Selfconsistent Multiple Scattering code for first principles calculation of the ground state and statistical physics of materials

The Locally Self-consistent Multiple Scattering (LSMS) code solves the first principles Density Functional theory Kohn–Sham equation for a wide range of materials with a special focus on metals, alloys and metallic nano-structures. It has traditionally exhibited near perfect scalability on massively parallel high performance computer architectures. In this paper, we present our efforts to exploit GPUs to accelerate the LSMS code to enable first principles calculations of O(100,000) atoms and statistical physics sampling of finite temperature properties. We reimplement the scattering matrix calculation for GPUs with a block matrix inversion algorithm that only uses accelerator memory. Finally, using the Cray XK7 system Titan at the Oak Ridge Leadership Computing Facility we achieve a sustained performance of 14.5PFlop/s and a speedup of 8.6 compared to the CPU only code.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Path integral Monte Carlo calculation of the momentum distribution of the homogeneous electron gas at finite temperature

Path integral Monte Carlo (PIMC) simulations are employed to calculate the momentum distribution of the homogeneous electron gas at finite temperature. Open paths are introduced to sample off-diagonal elements of the real-space density matrix. Here it is demonstrated how the restricted PIMC method can be extended to incorporate open paths in order to allow for the simulations in fermionic systems where a sign problem is present. The computed momentum distribution shows significant deviations from behavior of free fermions when strong correlations are present but agrees with predictions from variational methods.

36 MATERIALS SCIENCE↗