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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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DOE OSTI2022

A GeoHealth Call to Action: Moving Beyond Identifying Environmental Injustices to Co-Creating Solutions

As marginalized communities continue to bear disproportionate impacts from environmental hazards, we urgently call for researchers and institutions to elevate the principles of Environmental Justice. The American Geophysical Union (AGU) GeoHealth section supports members' engagement in health-related community-engaged and community-led transdisciplinary research. We highlight intersectional research that provides examples and actions for both individuals and organizations on community science and trust building, removing barriers created by scientific agency priorities and career expectations, and opportunities in education and policy. Justice does not start or end at one meeting; this is ongoing work that is active, evolving, and an ethical responsibility of AGU's membership.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

International network of nuclear structure and decay data evaluators

Compilation, evaluation and dissemination of nuclear data are arduous tasks that rely on contributions from experts in both the basic and applied sciences communities whose efforts are coordinated by the International Atomic Energy Agency (IAEA). The Evaluated Nuclear Structure Data File (ENSDF) includes the most extensive and comprehensive set of nuclear structure and decay data evaluations performed by the international network of Nuclear Structure and Decay Data evaluators (NSDD) under the auspices of the IAEA. In this report we describe the recent NSDD activities supported by the IAEA and provide some future perspectives.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Modular cell-free expression plasmids to accelerate biological design in cells

Industrial biotechnology aims to produce high-value products from renewable resources. This can be challenging because model microorganisms—organisms that are easy to use like Escherichia coli—often lack the machinery required to utilize desired feedstocks like lignocellulosic biomass or syngas. Non-model organisms, such as Clostridium, are industrially proven and have desirable metabolic features but have several hurdles to mainstream use. Namely, these species grow more slowly than conventional laboratory microbes, and genetic tools for engineering them are far less prevalent. To address these hurdles for accelerating cellular design, cell-free synthetic biology has matured as an approach for characterizing non-model organisms and rapidly testing metabolic pathways in vitro. Unfortunately, cell-free systems can require specialized DNA architectures with minimal regulation that are not compatible with cellular expression. In this work, we develop a modular vector system that allows for T7 expression of desired enzymes for cell-free expression and direct Golden Gate assembly into Clostridium expression vectors. Utilizing the Joint Genome Institute’s DNA Synthesis Community Science Program, we designed and synthesized these plasmids and genes required for our projects allowing us to shuttle DNA easily between our in vitro and in vivo experiments. We next validated that these vectors were sufficient for cell-free expression of functional enzymes, performing on par with the previous state-of-the-art. Lastly, we demonstrated automated six-part DNA assemblies for Clostridium autoethanogenum expression with efficiencies ranging from 68% to 90%. We anticipate this system of plasmids will enable a framework for facile testing of biosynthetic pathways in vitro and in vivo by shortening development cycles.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Designing and Utilizing Material Acceleration Platforms: Need for Workforce Development

In the quest to accelerate scientific discovery, the materials science field is rapidly moving toward the implementation of robotics and artificial intelligence driven workflows. Our recent summer school “Future Labs: Robotic Synthesis Coupled with Machine Learning for Energy Materials” provided learning opportunities for students, researchers, and educators in the materials science community. We describe this experience and provide our perspective on which new directions could be pursued to enable the future workforce to acquire cross-disciplinary skills.

Educational policy↗
DOE OSTI2025

Computing virtual dark-field X-ray microscopy images of complex discrete dislocation structures from large-scale molecular dynamics simulations

Dark-field X-ray microscopy (DFXM) is a novel diffraction-based imaging technique that non-destructively maps the local deformation from crystalline defects in bulk materials. While studies have demonstrated that DFXM can spatially map 3D defect geometries, it is still challenging to interpret DFXM images of the high-dislocation-density systems relevant to macroscopic crystal plasticity. This work develops a scalable forward model to calculate virtual DFXM images for complex discrete dislocation structure(s) (DDS) obtained from atomistic simulations. Our new DDS-DFXM model integrates a non-singular formulation for calculating the local strain from the DDS and an efficient geometrical optics algorithm for computing the DFXM image from the strain field. We apply the model to complex DDS obtained from a large-scale mol­ecular dynamics simulation of compressive loading on single-crystal silicon. Simulated DFXM images exhibit prominent contrast for dislocation features between the multiple slip systems, demonstrating the potential of DFXM to resolve features from dislocation multiplication. In conclusion, the integrated DDS-DFXM model provides a toolbox for DFXM experimental design and image interpretation in the context of bulk crystal plasticity for a range of measurements across shock plasticity and the broader materials science community.

X-ray imaging↗
DOE OSTI2024

tomoCAM : fast model-based iterative reconstruction via GPU acceleration and non-uniform fast Fourier transforms

X-ray-based computed tomography is a well established technique for determining the three-dimensional structure of an object from its two-dimensional projections. In the past few decades, there have been significant advancements in the brightness and detector technology of tomography instruments at synchrotron sources. These advancements have led to the emergence of new observations and discoveries, with improved capabilities such as faster frame rates, larger fields of view, higher resolution and higher dimensionality. These advancements have enabled the material science community to expand the scope of tomographic measurements towards increasingly in situ and in operando measurements. In these new experiments, samples can be rapidly evolving, have complex geometries and restrictions on the field of view, limiting the number of projections that can be collected. In such cases, standard filtered back-projection often results in poor quality reconstructions. Iterative reconstruction algorithms, such as model-based iterative reconstructions (MBIR), have demonstrated considerable success in producing high-quality reconstructions under such restrictions, but typically require high-performance computing resources with hundreds of compute nodes to solve the problem in a reasonable time. Here, tomoCAM , is introduced, a new GPU-accelerated implementation of model-based iterative reconstruction that leverages non-uniform fast Fourier transforms to efficiently compute Radon and back-projection operators and asynchronous memory transfers to maximize the throughput to the GPU memory. The resulting code is significantly faster than traditional MBIR codes and delivers the reconstructive improvement offered by MBIR with affordable computing time and resources. tomoCAM has a Python front-end, allowing access from Jupyter -based frameworks, providing straightforward integration into existing workflows at synchrotron facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

ROBIN (RuciO/BIgData Express/SENSE) A Next-Generation High-Performance Data Service Platform

Increasingly, scientific research discoverydepends on the analysis of extremely large amounts of data. Thisdata is gathered through very large scientific instruments, verylarge numbers of small devices, and mid-scale instruments.These devices generate exponentially increasing volumes of data.Such data is often obtained, analyzed, stored, visualized, andtransferred at and among sites world-wide by largecollaborations of science communities. Managing and movingextremely large volumes of data across today’s networks is aspecial multidimensional challenge. Also, existing datamanagement and movement services and tools often areinadequate to address all specific requirements. This paperdescribes the various components of this challenge and howthose issues can be addressed by ROBIN, a uniquecomprehensive set of integrated services designed specificallyfor managing and moving extremely large amounts of data overlong distances, e.g., thousands of miles around the globe. Thispaper also describes the results of initial experiments using thatset of integrated services.

Wu, Wenji↗
DOE OSTI2022

Preface for the special collection commemorating the career of Pat Thiel

This Special Collection in the Journal of Vacuum Science and Technology A (JVST A) has been compiled to commemorate the career of Professor Patricia (Pat) Thiel as a scientific leader in the international surface science community. Pat passed away in September 2020 due to breast cancer. This Collection includes 26 articles from colleagues, collaborators, and former Thiel group members. The topics overlap Pat’s scientific interests and advances in areas that include chemisorption, reconstruction, and complex formation on metal surfaces; submonolayer nucleation and growth and kinetic roughening of epitaxial thin films; coarsening of surface nanostructures; intercalation; surface phenomena for intermetallics including quasicrystals; and atomic-scale friction. We wish to thank the authors for their contributions towards producing this impressive Special Collection.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

FORGE: Pre-Training Open Foundation Models for Science

Large language models (LLMs) are poised to revolutionize the way we conduct scientific research. However, both model complexity and pre-training cost are impeding effective adoption for the wider science community. Identifying suitable scientific use cases, finding the optimal balance between model and data sizes, and scaling up model training are among the most pressing issues that need to be addressed. In this study, we provide practical solutions for building and using LLM-based foundation models targeting scientific research use cases. We present an end-to-end examination of the effectiveness of LLMs in scientific research, including their scaling behavior and computational requirements on Frontier, the first Exascale supercomputer. We have also developed for release to the scientific community a suite of open foundation models called FORGE with up to 26B parameters using 257B tokens from over 200M scientific articles, with performance either on par or superior to other state-of-the-art comparable models. We have demonstrated the use and effectiveness of FORGE on scientific downstream tasks. Our research establishes best practices that can be applied across various fields to take advantage of LLMs for scientific discovery.

Yin, Junqi↗
DOE OSTI2024

The Extraordinary March 2022 East Antarctica “Heat” Wave. Part I: Observations and Meteorological Drivers

Abstract Between 15 and 19 March 2022, East Antarctica experienced an exceptional heat wave with widespread 30°–40°C temperature anomalies across the ice sheet. This record-shattering event saw numerous monthly temperature records being broken including a new all-time temperature record of −9.4°C on 18 March at Concordia Station despite March typically being a transition month to the Antarctic coreless winter. The driver for these temperature extremes was an intense atmospheric river advecting subtropical/midlatitude heat and moisture deep into the Antarctic interior. The scope of the temperature records spurred a large, diverse collaborative effort to study the heat wave’s meteorological drivers, impacts, and historical climate context. Here we focus on describing those temperature records along with the intricate meteorological drivers that led to the most intense atmospheric river observed over East Antarctica. These efforts describe the Rossby wave activity forced from intense tropical convection over the Indian Ocean. This led to an atmospheric river and warm conveyor belt intensification near the coastline, which reinforced atmospheric blocking deep into East Antarctica. The resulting moisture flux and upper-level warm-air advection eroded the typical surface temperature inversions over the ice sheet. At the peak of the heat wave, an area of 3.3 million km 2 in East Antarctica exceeded previous March monthly temperature records. Despite a temperature anomaly return time of about 100 years, a closer recurrence of such an event is possible under future climate projections. In Part II we describe the various impacts this extreme event had on the East Antarctic cryosphere. Significance Statement In March 2022, a heat wave and atmospheric river caused some of the highest temperature anomalies ever observed globally and captured the attention of the Antarctic science community. Using our diverse collective expertise, we explored the causes of the event and have placed it within a historical climate context. One key takeaway is that Antarctic climate extremes are highly sensitive to perturbations in the midlatitudes and subtropics. This heat wave redefined our expectations of the Antarctic climate. Despite the rare chance of occurrence based on past climate, a future temperature extreme event of similar magnitude is possible, especially given anthropogenic climate change.

Wille, Jonathan D.↗
DOE OSTI2024

Ultrahigh-resolution mass spectrometry data associated with the manuscript “A functional microbiome catalog crowdsourced from North American rivers"

This data package is associated with the publication “A functional microbiome catalog crowdsourced from North American rivers” submitted to Nature (Borton et al., 2024); (https://www.biorxiv.org/content/10.1101/2023.07.22.550117v1). Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires understanding the spatial drivers of river microbiomes. However, the unifying microbial determinants governing river biogeochemistry are hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we employed a community science effort to accelerate the sampling of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). GROWdb is a publicly available resource that paves the way for watershed predictive modeling and microbiome-based management practices. This resource profiled the identity, distribution, function, and expression of thousands of microbial genomes across rivers covering 90% of United States watersheds. We identified the most cosmopolitan microbiome members, while also revealing local drivers of strain endemism across ecological dimensions. We provide the first evidence that microbial functional trait expression followed the tenets of the River Continuum Concept, suggesting the structure and function of river microbiomes is predictable. The Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) data were one of many different data types used in establishing the ecological dimensions along which different microbes were detected .This data package only contains the processed FTICR-MS data associated with this manuscript; all other data is accessible via Zenodo (https://zenodo.org/records/8173287), GitHub (https://github.com/jmikayla1991/Genome-Resolved-Open-Watersheds-database-GROWdb), KBase (https://doi.org/10.25982/109073.30/1895615), and NCBI via Bioproject PRJNA946291.This dataset consists of (1) a file-level metadata (flmd) file; (2) a data dictionary (dd) file; (3) a readme; (4) three Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) processed data files (a ‘data’ file containing peak-by-sample observations, a ‘mol’ file containing peak metadata, and a transformation profile containing transformation-by-sample observations). All files are .csv or .pdf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Thermodynamic equilibrium and kinetic fundamentals of oxide dissolution in aqueous solution

Dissolution of oxides in aqueous solutions is fundamentally important for a range of applications and a critical process that determines the chemical durability of industrial ceramics, the performance of nuclear waste forms, and the chemical weathering of minerals. The thermodynamic equilibrium and kinetics of dissolution reactions are key to determining the rate at which oxides dissolve. The increase in collaborative research across disciplines in materials research necessitates a common background to tackle shared scientific problems across different fields. This review selectively examines the fundamentals of dissolution theories that have been developed in chemistry, geochemistry, and materials science, and assembles them into a single collective document for the broader materials science community. Applications of the theories are highlighted using examples from specific areas, but can be similarly applied to other areas. Challenges and future research needs for a predictive-level understanding are discussed in light of the current literature.

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

Recent advances in the global rare-earth supply chain

The current global rare-earth element (REE) supply chain is highly imbalanced and tightly controlled by just a few countries. Such an imbalance of the critical metals supply chain poses a significant challenge to the energy-transition strategies and the national security of many countries. As such, this issue of MRS Bulletin delves into the materials science aspects of the REE supply chain, including fundamental REE mineralogy, REE separation and extraction, REE mining economics, the environmental impacts of REE mining and processing, and circular economy potential for REEs. This issue of MRS Bulletin is meant to inform the materials science community of some of the constraints on REE production from the mining of ore deposits, through processing technologies, and then finally, the possibility of recycling.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Studies of surface adsorbate electronic structure and femtochemistry at the fundamental length and time scales. Final report

The electronic structure and ultrafast (10-15 s-femtosecond timescale) electron dynamics were investigated for clean and atom/molecule covered metal surfaces. The studies were performed by scanning tunneling microscopy (STM) to measure the structure of adsorbed atoms and molecules on metal surfaces, and to investigate their electronic properties. The electronic structure of the observed molecular networks was calculated by electronic structure theory in collaboration with Prof. Jin Zhao, who is a long-time collaborator, a Professor at the University of Science and Technology of China, and holds an Adjunct Professorship at the University of Pittsburgh. We also investigated the electronic properties of C60 molecules when they are templated by corrugated black phosphorous surfaces. We found unexpected charge delocalization that is enabled by the templating. This research was done in collaboration with Professor Min Feng at the Wuhan University, and who also holds an Adjunct Professorship at the University of Pittsburgh. Moreover, the electronic structure and electron dynamics in metal surfaces were investigated by time-resolved photoemission electron spectroscopy. The focus of ultrafast spectroscopy has been on the plasmonic response of silver surfaces. One direction has been to develop multidimensional (energy, momentum, and time) photoelectron spectroscopy of the coherent response of solid surfaces. This method was applied to study the collective electron excitations known generally as plasmons, which screen optical fields from penetration into metals. Although this collective response has been known for more than 60 years and is used extensively to deposit optical energy into metals, how this happens is poorly known. We investigated the plasmonic response of silver at the point where the dielectric response passes through zero and bulk plasmon is excited by light. We discovered that the plasmon excitation decays by exciting electrons from the Fermi level of a metal, which is contrary to what is believed in the plasmonic science community. This research has been performed in collaboration with Dr. Marcel Reutzel, who was a postdoctoral fellow working on this research at the University of Pittsburgh, and now has a faculty position at the University of Göttingen in Germany. Prof. Branko Gumhalter from the Institute of Physics in Zagreb contributed on the theory of plasmonic decay processes. Furthermore, we investigated the Floquet engineering of electronic bands in metals leading to multiphoton photoemission and above threshold photoemission. Finally, we demonstrated that it is possible to change the electronic structure of metals by application of optical fields. Our studies indicated that this happens on subfemtosecond time scale and could potentially be used in ultrafast information processing and quantum computation. Related document information

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Artificial Intelligence for Isotopes: Report on the 2022 Workshop on Artificial Intelligence for Isotope R&D and Production

The Department of Energy Isotope Program (DOE IP) hosted a virtual workshop on Artificial Intelligence (AI) for Isotope R&D and Production on March 17 and April 14, 2022. The purpose of the workshop was for DOE IP to further its understanding of the potential roles for and subsequent opportunities to incorporate AI into its activities. The workshop brought over 80 participants together from both the AI and isotope science communities. Participants contributed ideas through plenary talks, lightning talks, and breakout discussion sessions. The primary focus of all discussions was related to isotope production and processing. However, isotope enrichment, workforce development, and supply chain management were also discussed. This report documents the information presented and discussed at the workshop.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

TEX-HEU: Integral Experiment Execution with Polyethylene at Very Low Temperatures

The low-temperature variant of the TEX HEU (called Low-Temperature TEX or sometimes LT TEX) campaign is a highly anticipated and necessary experimental series by the greater nuclear science community. Fundamentally, the need for low-temperature integral experiments is required to perform validation of cross sections below room temperature. There has been substantial international interest in low-temperature benchmarks to validate below room temperature cross sections, namely talks given at the 2019 International Conference on Nuclear Criticality (ICNC): UK (Watson, 2019), France (Milin, 2019), and UK (Gan & Wilson, 2019). Additionally, NCSP funded thermal scattering laws (TSLs) were produced by North Carolina State University and require low-temperature benchmarks to validate them. Validation of low-temperature cross sections is also necessary for criticality safety applications. One particularly important application is to ensure that during transportation, fissile materials must remain subcritical under normal ambient conditions which is defined as temperatures down to -40°C/°F by the United States 10 CRF 71 as well as a regulation put forward by the International Atomic Energy Agency (IAEA).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

The right conditions for high-precision dynamic temperature and heat capacity measurement via pyrometry and conductivity

The pursuit of accurate bulk temperature T under extreme conditions has been a long-standing goal of the high pressure science community, complicated by a lack of data to inform models. To reach these extremely high-pressure, high-temperature (high P − T) conditions, a combination of dynamic and heated static experiments (e.g., diamond or gem anvil cel experiments) are used. For example, in a diamond anvil cell (DAC) experiment, a sample placed in the DAC is first pressurized. Following pressurization, the sample T is increased either by heating the entire DAC (usually using resistive heating, and limited to ∼1000K) or by applying intense laser power to the sample surfaces. In a dynamic experiment, the process of pressurizing the sample also heats it. In the case of shock physics experiments, such heating is substantial, easily reaching thousands of Kelvin; in our work we have seen T ∼17000K. Most methods of measuring temperature at ambient are not compatible with experiments under these high-pressure, high-temperature conditions: thermocouples break, melt, or have conductivity properties that differ from ambient where they are calibrated; thermometers would melt; both are too slow. As a result most methods are based on non-contact techniques such as x-ray diffraction broadening, neutron scattering, or optical methods. Of these, optical methods using the visible and near-infrared region of the spectrum are the most commonly used as the sources and detectors are readily available. In the case of optical methods the optical depth, and therefore the measurement location, is limited to the surface. When a window or anvil material is used, heat flows from the sample into the window/anvil. Likewise, if the sample undergoes a change in thermodynamic state, such as expansion upon release, different T may be expected. As a result, the surface or apparent temperature T app measurement will differ from the bulk or interior temperature that is desired. This surface measurement must be related to the bulk measurement using thermal transport models and material models. While it is tempting to conclude that one should just use x-ray methods that directly probe the interior, even these methods have been shown to depend on thermal transport and material models. Regardless of the method used to create the high P − T condition, therefore, we must understand the role of thermal transport and material models upon our interpretation of the T measurement, as well as the errors and uncertainties associated with the choice of models used in the analysis. This is a substantial area of research and this paper is by no means a complete survey of the relevant sources of uncertainty. For example, we have yet to begin to address alternate transport models in a detailed manner (e.g., Tan-Ahrens), or the many models that use additional layers to approximate melting, turbulence, or epitaxial phenomena). Likewise, we have not explored the impact upon uncertainty of thermal models that use temperature-dependent thermal transport coefficients, or the wide range of material models that can be applied. Instead, this paper focuses on using one simple model, the Urtiew-Grover model, to understand the sources of error in T measurement so that we may identify how best to focus future research efforts to return the best improvements and avoid working on over-optimizing a single type of measurement. To this end, we work through some of the best and worst case scenarios for T measurement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗