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All sources NASA NTRS DOE OSTI

DOE OSTI2023

Solving complex nanostructures with ptychographic atomic electron tomography

Abstract Transmission electron microscopy (TEM) is essential for determining atomic scale structures in structural biology and materials science. In structural biology, three-dimensional structures of proteins are routinely determined from thousands of identical particles using phase-contrast TEM. In materials science, three-dimensional atomic structures of complex nanomaterials have been determined using atomic electron tomography (AET). However, neither of these methods can determine the three-dimensional atomic structure of heterogeneous nanomaterials containing light elements. Here, we perform ptychographic electron tomography from 34.5 million diffraction patterns to reconstruct an atomic resolution tilt series of a double wall-carbon nanotube (DW-CNT) encapsulating a complex ZrTe sandwich structure. Class averaging the resulting tilt series images and subpixel localization of the atomic peaks reveals a Zr 11 Te 50 structure containing a previously unobserved ZrTe 2 phase in the core. The experimental realization of atomic resolution ptychographic electron tomography will allow for the structural determination of a wide range of beam-sensitive nanomaterials containing light elements.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Iridium metallene oxide for acidic oxygen evolution catalysis

Exploring new materials is essential in the field of material science. Especially, searching for optimal materials with utmost atomic utilization, ideal activities and desirable stability for catalytic applications requires smart design of materials’ structures. Herein, we report iridium metallene oxide: 1 T phase-iridium dioxide (IrO 2 ) by a synthetic strategy combining mechanochemistry and thermal treatment in a strong alkaline medium. This material demonstrates high activity for oxygen evolution reaction with a low overpotential of 197 millivolt in acidic electrolyte at 10 milliamperes per geometric square centimeter (mA cm geo –2 ). Together, it achieves high turnover frequencies of 4.2 s UPD –1 (3.0 s BET –1 ) at 1.50 V vs. reversible hydrogen electrode. Furthermore, 1T-IrO 2 also shows little degradation after 126 hours chronopotentiometry measurement under the high current density of 250 mA cm geo –2 in proton exchange membrane device. Theoretical calculations reveal that the active site of Ir in 1T-IrO 2 provides an optimal free energy uphill in *OH formation, leading to the enhanced performance. The discovery of this 1T-metallene oxide material will provide new opportunities for catalysis and other applications.

36 MATERIALS SCIENCE↗

NASA NTRS2005

Computational Materials Program for Alloy Design

The research program sponsored by this grant, "Computational Materials Program for Alloy Design", covers a period of time of enormous change in the emerging field of computational materials science. The computational materials program started with the development of the BFS method for alloys, a quantum approximate method for atomistic analysis of alloys specifically tailored to effectively deal with the current challenges in the area of atomistic modeling and to support modern experimental programs. During the grant period, the program benefited from steady growth which, as detailed below, far exceeds its original set of goals and objectives. Not surprisingly, by the end of this grant, the methodology and the computational materials program became an established force in the materials communitiy, with substantial impact in several areas. Major achievements during the duration of the grant include the completion of a Level 1 Milestone for the HITEMP program at NASA Glenn, consisting of the planning, development and organization of an international conference held at the Ohio Aerospace Institute in August of 2002, finalizing a period of rapid insertion of the methodology in the research community worlwide. The conference, attended by citizens of 17 countries representing various fields of the research community, resulted in a special issue of the leading journal in the area of applied surface science. Another element of the Level 1 Milestone was the presentation of the first version of the Alloy Design Workbench software package, currently known as "adwTools". This software package constitutes the first PC-based piece of software for atomistic simulations for both solid alloys and surfaces in the market.Dissemination of results and insertion in the materials community worldwide was a primary focus during this period. As a result, the P.I. was responsible for presenting 37 contributed talks, 19 invited talks, and publishing 71 articles in peer-reviewed journals, as detailed later in this Report.

Bozzolo, Guillermo↗

DOE OSTI2026

The scientific case for concurrent neutron and X-ray scattering and spectroscopy

The interrogation of materials with X-rays or neutrons to determine structure, energetics, and dynamics is fundamental to advancing physical and chemical materials science and enabling innovative material technologies. A persistent challenge in materials development is that progress depends on understanding structure and dynamics across multiple length and time scales in increasingly complex, multicomponent systems featuring interfaces, heterogeneity, and hierarchical organization. Despite rapidly growing demands on materials characterization, current experimental approaches are almost exclusively based on isolated X-ray or neutron scattering and spectroscopy, reflecting a paradigm largely unchanged for decades. To assess the scientific need for a new experimental paradigm, a 3-day workshop sponsored by the U.S. National Science Foundation (NSF) was held at the SpringHill Suites, San Jose, California, from June 2 to 4, 2022. The workshop brought together 70 national and international experts who critically evaluated opportunities enabled by concurrent neutron and X-ray (NeX) scattering, spectroscopy, and imaging experiments. The participants reached a clear consensus that establishing NeX capabilities is crucial for advancing the science of complex materials in the United States. This report illustrates the scientific drivers for NeX experiments through representative examples spanning biomaterials, energy materials, soft matter, nanomaterials, quantum materials, geoscience, and applied materials research. The complementarity of neutrons and X-rays is essential for robust model development and refinement, particularly in multiphase and multicomponent systems. While joint refinement of data from separate experiments is valuable, concurrent measurements uniquely eliminate uncertainties arising from sample evolution, environmental drift, and irreproducibility associated with experiments performed at different locations and times. Realizing NeX capabilities will require the development of new instrumentation, data analysis frameworks, and robust sample environments compatible with both neutron and X-ray probes. Addressing these challenges will enable unambiguous interpretation of complex materials behavior and open new frontiers in materials research.

X-ray↗

DOE OSTI2021

A representation-independent electronic charge density database for crystalline materials

In addition to being the core quantity in density functional theory, the charge density can be used in many tertiary analyses in materials sciences from bonding to assigning charge to specific atoms. The charge density is data-rich since it contains information about all the electrons in the system. With increasing utilization of machine-learning tools in materials sciences, a data-rich object like the charge density can be utilized in a wide range of applications. The database presented here provides a modern and user-friendly interface for a large and continuously updated collection of charge densities as part of the Materials Project. In addition to the charge density data, we provide the theory and code for changing the representation of the charge density which should enable more advanced machine-learning studies for the broader community.

36 MATERIALS SCIENCE↗

DOE OSTI2022

A representation-independent electronic charge density database for crystalline materials

Abstract In addition to being the core quantity in density-functional theory, the charge density can be used in many tertiary analyses in materials sciences from bonding to assigning charge to specific atoms. The charge density is data-rich since it contains information about all the electrons in the system. With the increasing prevalence of machine-learning tools in materials sciences, a data-rich object like the charge density can be utilized in a wide range of applications. The database presented here provides a modern and user-friendly interface for a large and continuously updated collection of charge densities as part of the Materials Project. In addition to the charge density data, we provide the theory and code for changing the representation of the charge density which should enable more advanced machine-learning studies for the broader community.

36 MATERIALS SCIENCE↗

DOE OSTI2020

A general mechanism for gel layer formation on borosilicate glass under aqueous corrosion

Mineral and glass dissolution is a scientific topic deeply investigated but incompletely understood and of a great interest for the geochemical and materials science communities. If the interfacial dissolution/reprecipitation mechanism seems to be applicable to most of silicate minerals, the debate remains open concerning glass. Here we studied two model glasses, a ternary borosilicate (CJ1) and the same glass doped with 4.1 mol% of Al2O3 (CJ2). The two glasses were altered at 90°C, pH 9, and in conditions far and close to saturation with respect to amorphous silica, to determine the initial and residual rates. Moreover, a specific experiment was conducted for a short duration with a solution highly enriched with 18O and 29Si isotopes to understand how passivating gels form. SEM, TEM and ToF-SIMS characterization, along with Monte Carlo simulations were used to understand the rate limiting reactions at play and infer the role of Al. We show that Al yields a slower matrix dissolution in dilute conditions. However, it slows down he formation and the maturation of the passivating gel and favors alteration by partial hydrolysis of Si and Al entities followed by in-situ reorganization/relaxation into a porous network. Unexpectedly, CJ1 experienced both interfacial dissolution/reprecipitation and partial hydrolysis followed by in situ reorganization of the silicate network during the course of a single experiment. This study offers a unified concept that can pave the way for the future development of a predictive kinetic model based on a detailed description of bond breaking and bond forming as a function of glass composition and alteration conditions.

Gin, Stephane↗

DOE OSTI2020

Roadmap on multiscale materials modeling

Modeling and simulation is transforming modern materials science, becoming an important tool for the discovery of new materials and material phenomena, for gaining insight into the processes that govern materials behavior, and, increasingly, for quantitative predictions that can be used as part of a design tool in full partnership with experimental synthesis and characterization. Modeling and simulation is the essential bridge from good science to good engineering, spanning from fundamental understanding of materials behavior to deliberate design of new materials technologies leveraging new properties and processes. This Roadmap presents a broad overview of the extensive impact computational modeling has had in materials science in the past few decades, and offers focused perspectives on where the path forward lies as this rapidly expanding field evolves to meet the challenges of the next few decades. The Roadmap offers perspectives on advances within disciplines as diverse as phase field methods to model mesoscale behavior and molecular dynamics methods to deduce the fundamental atomic-scale dynamical processes governing materials response, to the challenges involved in the interdisciplinary research that tackles complex materials problems where the governing phenomena span different scales of materials behavior requiring multiscale approaches. The shift from understanding fundamental materials behavior to development of quantitative approaches to explain and predict experimental observations requires advances in the methods and practice in simulations for reproducibility and reliability, and interacting with a computational ecosystem that integrates new theory development, innovative applications, and an increasingly integrated software and computational infrastructure that takes advantage of the increasingly powerful computational methods and computing hardware.

36 MATERIALS SCIENCE↗

DOE OSTI2022

2022 AI Testbed Expeditions Report

By exploiting the coherent properties of a light source, coherent diffraction imaging (CDI) is able to obtain the sample image at a nanoscale resolution using the measured diffraction pattern. Bragg Coherent Diffraction Imaging (BCDI) has become valuable for recovering the displacement and strain field of crystals, providing a valuable tool in material science and solid-state physics. X-ray ptychography is another emerging CDI technique that can produce a high-resolution image of the extended sample and has become popular in many research areas (e.g., materials science, biology, electronics, and optics characterization). CDI including BCDI and ptychography has become an established technique in Synchrotron Facilities including the Advanced Photon Source (APS) and will greatly benefit from the 100x coherent flux increase of the upcoming APS Upgrade (APSU). The current image formation process in CDI employs iterative phase retrieval algorithms, which is a time-consuming and computationally expensive process. Especially after APSU, the traditional iterative methods will not be able to match the experimental data acquisition speed. We employ deep learning (DL) approach to replace the iterative approaches, therefore allowing hundreds of times faster recovery of the object. We developed AutoPhaseNN, a DL-based approach which learns to solve the inverse problem without labeled data. Taking 3D BCDI as a representative technique, AutoPhaseNN has been demonstrated to be one hundred times faster than traditional iterative phase retrieval methods while providing comparable image quality. The current network is trained with 64 x 64 x 64 data size, to achieve higher resolution imaging, we will need to scale the network to input and train/infer 3D arrays of size 256 x 256 x 256 (today) and of size 2560x2560x2560 (APSU). However, the scalability of the network is restricted due to the memory-intensive training process. To perform the training for a 256 x 256 x 256 data size, the required memory exceeds the capacity of the current machine. In this project, we explore using Sambanova system to train the network for the direct data inversion for CDI.

36 MATERIALS SCIENCE↗

NASA NTRS2016

Levitation Technology in International Space Station Research

The International Space Station (ISS) is a unique multidisciplinary orbiting laboratory for science and technology research, enabling discoveries that benefit life on Earth and exploration of the universe. ISS facilities for containerless sample processing in Materials Science experiments include levitation devices with specimen positioning control while reducing containment vessel contamination. For example, ESA's EML (ElectroMagnetic Levitator), is used for melting and solidification of conductive metals, alloys, or semiconductors in ultra-high vacuum, or in high-purity gaseous atmospheres. Sample heating and positioning are accomplished through electromagnetic fields generated by a coil system. EML applications cover investigation of solidification and microstructural formation, evaluation of thermophysical properties of highly reactive metals (whose properties can be very sensitive to contamination), and examination of undercooled liquid metals to understand metastable phase convection and influence convection on structural changes. MSL utilization includes development of novel light-weight, high-performance materials. Another facility, JAXA's ELF (Electrostatic Levitation Furnace), is used to perform high temperature melting while avoiding chemical reactions with crucibles by levitating a sample through Coulomb force. ELF is capable of measuring density, surface tension, and viscosity of samples at high temperatures. One of the initial ELF investigations, Interfacial Energy-1, is aimed at clarification of interfacial phenomena between molten steels and oxide melts with industrial applications in control processes for liquid mixing. In addition to these Materials Science facilities, other ISS investigations that involve levitation employ it for biological research. For example, NASA's "Magnetic 3D Culturing and Bioprinting" investigation uses magnetic levitation for three-dimensional culturing and positioning of magnetized cells to generate spheroid assemblies for biomedical applications. Levitation is also used as a modeled microgravity ground analog in the NASA OsteoOmics ISS investigation, which tests whether magnetic levitation accurately simulates microgravity conditions by studying gravitational regulation of osteoblast and osteoclast genomics and metabolism. Elucidating the cellular mechanisms of bone loss in microgravity contributes to the understanding of bone loss in medical disorders on Earth, which may lead to development of preventive or therapeutic countermeasures. Thus, the ISS state-of-the-art laboratory offers various levitation capability platforms with applications for innovative research in Materials and Life Sciences disciplines, with benefits for humanity.

Guinart-Ramirez, Y.↗

DOE OSTI2022

Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules

Abstract Graph Convolutional Neural Network (GCNN) is a popular class of deep learning (DL) models in material science to predict material properties from the graph representation of molecular structures. Training an accurate and comprehensive GCNN surrogate for molecular design requires large-scale graph datasets and is usually a time-consuming process. Recent advances in GPUs and distributed computing open a path to reduce the computational cost for GCNN training effectively. However, efficient utilization of high performance computing (HPC) resources for training requires simultaneously optimizing large-scale data management and scalable stochastic batched optimization techniques. In this work, we focus on building GCNN models on HPC systems to predict material properties of millions of molecules. We use HydraGNN, our in-house library for large-scale GCNN training, leveraging distributed data parallelism in PyTorch. We use ADIOS, a high-performance data management framework for efficient storage and reading of large molecular graph data. We perform parallel training on two open-source large-scale graph datasets to build a GCNN predictor for an important quantum property known as the HOMO-LUMO gap. We measure the scalability, accuracy, and convergence of our approach on two DOE supercomputers: the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF) and the Perlmutter system at the National Energy Research Scientific Computing Center (NERSC). We present our experimental results with HydraGNN showing (i) reduction of data loading time up to 4.2 times compared with a conventional method and (ii) linear scaling performance for training up to 1024 GPUs on both Summit and Perlmutter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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 OSTI2021

Towards Predictive Plasma Science and Engineering through Revolutionary Multi-Scale Algorithms and Models (Final Report)

This report describes the high-level accomplishments from the Plasma Science and Engineering Grand Challenge LDRD at Sandia National Laboratories. The Laboratory has a need to demonstrate predictive capabilities to model plasma phenomena in order to rapidly accelerate engineering development in several mission areas. The purpose of this Grand Challenge LDRD was to advance the fundamental models, methods, and algorithms along with supporting electrode science foundation to enable a revolutionary shift towards predictive plasma engineering design principles. This project integrated the SNL knowledge base in computer science, plasma physics, materials science, applied mathematics, and relevant application engineering to establish new cross-laboratory collaborations on these topics. As an initial exemplar, this project focused efforts on improving multi-scale modeling capabilities that are utilized to predict the electrical power delivery on large-scale pulsed power accelerators. Specifically, this LDRD was structured into three primary research thrusts that, when integrated, enable complex simulations of these devices: (1) the exploration of multi-scale models describing the desorption of contaminants from pulsed power electrodes, (2) the development of improved algorithms and code technologies to treat the multi-physics phenomena required to predict device performance, and (3) the creation of a rigorous verification and validation infrastructure to evaluate the codes and models across a range of challenge problems. These components were integrated into initial demonstrations of the largest simulations of multi-level vacuum power flow completed to-date, executed on the leading HPC computing machines available in the NNSA complex today. These preliminary studies indicate relevant pulsed power engineering design simulations can now be completed in (of order) several days, a significant improvement over pre-LDRD levels of performance.

42 ENGINEERING↗

DOE OSTI2022

Challenges of Future Accelerators for Particle Physics Research

For over half a century, high-energy particle accelerators have been a major enabling technology for particle and nuclear physics research as well as sources of X-rays for photon science research in material science, chemistry and biology. Particle accelerators for energy and intensity Frontier research in particle and nuclear physics continuously push the accelerator community to invent ways to increase the energy and improve the performance of accelerators, reduce their cost, and make them more power efficient. The accelerator community has demonstrated imagination and creativity in developing a plethora of future accelerator ideas and proposals. The technical maturity of the proposed facilities ranges from shovel-ready to those that are still largely conceptual. At this time, over 100 contributed papers have been submitted to the Accelerator Frontier of the US particle physics decadal community planning exercise known as Snowmass’2021. These papers cover a broad spectrum of topics: beam physics and accelerator education, accelerators for neutrinos, colliders for Electroweak/Higgs studies and multi-TeV energies, accelerators for Physics Beyond Colliders and rare processes, advanced accelerator concepts, and accelerator technology for Radio Frequency cavities (RF), magnets, targets and sources. This paper provides an overview of the present state of accelerators for particle physics and gives a brief description of some of the major facilities that have been proposed, their perceived advantages and some of the remaining challenges.

43 PARTICLE ACCELERATORS↗

NASA NTRS1977

JPL basic research review

Current status, projected goals, and results of 49 research and advanced development programs at the Jet Propulsion Laboratory are reported in abstract form. Areas of investigation include: aerodynamics and fluid mechanics, applied mathematics and computer sciences, environment protection, materials science, propulsion, electric and solar power, guidance and navigation, communication and information sciences, general physics, and chemistry.

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NASA NTRS1988

Lessons learned in ground processing scientific and applications payloads at Kennedy Space Center

The payload ground processing of experiments which flew on the Shuttle is examined, including studies of atmosphere and earth observation, life science, advance technology, materials science, plasma physics, astrophysics and solar physics, astronomy, navigation and communication, and fluid mechanics. The process of designing and development payloads, the integration of instruments, carrier interface verification, and late servicing at the launch pad are discussed. The problems of cost, red tape, contamination, safety, and propriety protection are considered.

Elfrey, Priscilla↗

NASA NTRS1992

A senior manufacturing laboratory for determining injection molding process capability

The following is a laboratory experiment designed to further understanding of materials science. This subject material is directed at an upper level undergraduate/graduate student in an Engineering or Engineering Technology program. It is assumed that the student has a thorough understanding of the process and quality control. The format of this laboratory does not follow that which is normally recommended because of the nature of process capability and that of the injection molding equipment and tooling. This laboratory is instead developed to be used as a point of departure for determining process capability for any process in either a quality control laboratory or a manufacturing environment where control charts, process capability, and experimental or product design are considered important topics.

Wickman, Jerry L.↗

NASA NTRS1995

Aeronautical engineering: A continuing bibliography with indexes (supplement 316)

This bibliography lists 413 reports, articles, and other documents introduced into the NASA scientific and technical information system in April 1995. Subject coverage includes: aeronautics; mathematical and computer sciences; chemistry and material sciences; geosciences; design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics.

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