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Deep Impact will impact the comet Tempel-1 on July 4, 2005. The impact event will be clearly visible from small telescopes on Earth, especially in the IR bands. When combined with observations taken from the Flyby spacecraft, this science data set will provide unique insight into the materials and structure within the comet, and the strength of the surface.
What automated composite laminate manufacturing isWhy automation is of interest in science applicationsHow composite automation is being considered for science instrument applicationsAnd, about test data showing high stiffness materials processed with automation results in reduced material strength while stiffness and coefficient of thermal expansion are mostly unaffected.
The science objectives of increasingly ambitious space missions require meeting stringent contamination requirements. Contamination transport models are based on established principles such as Fick’s law for contamination diffusion within the source material, Arrhenius factors to account for temperature variations and free molecular transport for spacecraft operating in vacuum. In addition to the science principles, empirical data obtained from ASTM E1559 testing is used for engineering contamination modeling. The ASTM E1559 test provides outgassing rate data for materials at expected spacecraft temperatures during a mission. Multiple quartz crystal microbalances (QCMs) can be operated at different temperatures to measure the amount of contamination condensation that can occur on various spacecraft surfaces. At the conclusion of the ASTM E1559 test a thermo-gravimetric assessment (TGA) can be performed by heating the QCMs at a linear rate to obtain contamination desorption data. This TGA data provides a wealth of information that can be incorporated into contamination models. A method for applying this data is presented.
All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.
The goal of this project was to develop plutonium metallography capabilities and establish workflows for characterization at PNNL’s Radiological Processing Facility (RPL). Developing and expanding on this capability opens more opportunities for PNNL to better support science through collaborations with other labs, plants, and sites withing the Department of Energy Complex and through programs within the National Nuclear Security Administration. This project established metallography equipment in an air glovebox, polishing protocols, as well as radiological and facility controls and procedures so that gram quantities of plutonium metal could be analyzed on multiple characterization tools. Data was collected and analyzed on two different delta phase plutonium - Gallium samples and a calciothermically reduced alpha plutonium metal using a combination of optical and electron microscopy, powder X-ray diffraction, and atom probe tomography. This report highlights the metallography capabilities, some preliminary data collections, and plans at PNNL to support plutonium material science.
Long term stability of spacecraft materials when exposed to the space environment continues to be a major area of investigation. The natural and induced environment surrounding a spacecraft can decrease material performance and limit useful lifetimes. The Optical Properties Monitor (OPM) experiment provided the capability to perform the important flight testing of materials and was flown on the Russian Mir Station to study the long term effects of the natural and induced space environment on materials. The core of the OPM in-flight analysis was three independent optical instruments. These instruments included an integrating sphere spectral reflectometer, a vacuum ultraviolet spectrometer, and a Total Integrated Scatter instrument. The OPM also monitored selected components of the environment including molecular contamination. The OPM was exposed on the exterior of the Mir Docking Module for approximately 8-1/2 months. This report describes the OPM experiment, a brief background of its development, program organization, experiment description, mission overview including space environment definition, performance overview, materials data including flight and ground data, in-depth post flight analysis including ground analysis measurements and a summary discussion of the findings and results.
Optical imaging is important for many NASA science missions. Even though complex optical systems have advanced, the optics, based on conventional glass and mirrors, require components that are thick, heavy and expensive. As the need for higher performance expands, glass and mirrors are fast approaching the point where they will be too large, heavy and costly for spacecraft, especially small satellite systems. NASA Langley Research Center is developing a wide range of novel nano-layered synthesized materials that enable the development and fabrication of ultralight weight optical device systems that enable many NASA missions to collect science data imagery using small satellites. In addition to significantly reducing weight, the nano-layered synthesized materials offer advantages in performance, size, and cost.
Optically addressable spin defects have emerged as the leading platforms for quantum sensing and communication in solid-state systems. While traditional efforts have concentrated on a focused set of well-studied defects, recent advances in high-throughput computational methods have shown promise for large-scale exploration of defects across diverse semiconductor hosts. By cataloging key properties of quantum defects in computational databases, high-throughput screening techniques can systematically suggest and design novel candidates. In this article, we highlight recent advances in data-driven quantum defect design aimed at addressing critical materials science challenges such as host materials selection, defect stability, and desirable electronic and optical properties. Here, we emphasize the importance of electronic-structure-guided searches across various materials and illustrate how high-throughput computations contribute to our understanding of design principles for quantum defects. Additionally, we outline ongoing challenges and emerging opportunities in this rapidly developing field.
Non-proprietary proposal abstracts of Phase 1 Small Business Innovation Research (SBIR) projects supported by NASA are presented. Projects in the fields of aeronautical propulsion, aerodynamics, acoustics, aircraft systems, materials and structures, teleoperators and robots, computer sciences, information systems, data processing, spacecraft propulsion, bioastronautics, satellite communication, and space processing are covered.
This systems report describes how the Optical Properties Monitor (OPM) experiment was developed. Pertinent design parameters are discussed, along with mission information and system requirements to successfully complete the mission. Environmental testing was performed on the OPM to certify it for spaceflight. This testing included vibration, thermal vacuum, electromagnetic interference and conductance, and toxicity tests. Instrument and monitor subsystem performances, including the reflectometer, vacuum ultraviolet, total integrated scatter, atomic oxygen monitor, irradiance monitor, and molecular contamination monitor during the mission are discussed. The OPM experiment was launched aboard the Space Shuttle on mission STS-81 in January 1997 and transferred to the Mir space station. An extravehicular activity (EVA) was performed in April 1997 to attach the OPM experiment to the outside of the Mir/Shuttle Docking Module for space environment exposure. The OPM conducted in situ measurements of a number of material samples. These data may be found in the OPM Science Report. OPM was retrieved during an EVA in January 1998 and was returned to Earth on board the Space Shuttle on mission STS-89.
The scientific objective of the Isothermal Dendritic Growth Experiment (IDGE) is to test fundamental assumptions about dendritic solidification of molten materials. "Dendrites"-- from the ancient Greek word for tree--are tiny branching structures that form inside molten metal alloys when they solidify during manufacturing. The size, shape, and orientation of the dendrites have a major effect on the strength, ductility (ability to be molded or shaped), and usefulness of an alloy. Nearly all of the cast metal alloys used in everyday products (such as automobiles and airplanes) are composed of thousands to millions of tiny dendrites. Gravity, present on Earth, causes convection currents in molten alloys that disturb dendritic solidification and make its precise study impossible. In space, gravity is negated by the orbiting of the space shuttle. Consequently, IDGE (which was conducted on the space shuttle) gathered the first precise data regarding undisturbed dendritic solidification. IDGE is a microgravity materials science experiment that uses an apparatus which was designed, built, tested, and operated by people from the NASA Lewis Research Center. This experiment was conceived by the principal investigator, Professor Martin E. Glicksman, from Rensselaer Polytechnic Institute in Troy, New York. The experiment was a team effort of Lewis civil servants, contractors from Aerospace Design & Fabrication Inc. (ADF), and personnel at Rensselaer.
A viewgraph presentation on the properties of materials used for the development of the James Webb Space Telescope is shown. The topics include: 1) James Webb Space Telescope (JWST) Overview; 2) Integrated Science Instrument Module (ISIM) Materials Development; and 3) Capturing Essential Data.
Topics covered include: Computer-Aided Design and Engineering; Electronic Components and Circuits; Electronic Systems; Test and Measurement; Physical Sciences; Materials; Computer Programs; Mechanics; Machinery/Automation; Manufacturing/Fabrication; Mathematics and Information Sciences; Data Acquisition.
Here, a recently commissioned five-analyzer Johann spectrometer at the Inner Shell Spectroscopy beamline (8-ID) at the National Synchrotron Light Source II (NSLS-II) is presented. Designed for hard X-ray photon-in/photon-out spectroscopy, the spectrometer achieves a resolution in the 0.5–2 eV range, depending on the element and/or emission line, providing detailed insights into the local electronic and geometric structure of materials. It serves a diverse user community, including fields such as physical, chemical, biological, environmental and materials sciences. This article details the mechanical design, alignment procedures and data-acquisition scheme of the spectrometer, with a particular focus on the continuous asynchronous data-acquisition approach that significantly enhances experimental efficiency.
The NMDC is a sustainable data discovery platform that promotes open science and shared-ownership across a broad and diverse community of researchers, funders, publishers, societies, and other collaborators. The NMDC aims to enable multi-omic microbiome research to accelerate scientific discovery. The NMDC is a Department of Energy funded program that is a collaboration between 3 National Laboratories: Lawrence Berkeley National Laboratory (LBNL), Los Alamos National Laboratory (LANL), and Pacific Northwest National Laboratory (PNNL).
A review and interlaboratory comparison of secondary ion mass spectrometry (SIMS) data obtained by laboratories participating in the International Technical Nuclear Forensics Working Group (ITWG) 7th Collaborative Material Exercise (CMX-7) has been conducted. The analyzed materials were two uranium compounds in powder form and two pieces of uranium metal. The instruments used in this comparison were a small-geometry (SG) SIMS, CAMECA IMS 7f from the Research Centre Rez, and a large-geometry (LG) SIMS, CAMECA IMS 1280 from Los Alamos National Laboratory. Despite the differences in instruments and analytical procedures, e.g., sample preparation, SIMS setups, and data post-processing, there was good agreement for the 234 U/ 238 U, 235 U/ 238 U, and 236 U/ 238 U ratios in the analyzed materials. The main difference was in the precision, which was, as expected, higher for the LG-SIMS. In addition, a comparison between the laboratories was also made for the image processing algorithms applied to raw data acquired in automated particle measurement (APM) mode. In conclusion, the result of this comparison has led to identification of best practices for setting up parameters of the APM software.
Since March 1, 1989, attention was concentrated on the extraction of ilmenite from extraterrestrial materials and on the planning and development of laboratory facilities for carbonyl extraction of ferrous metal alloys. Work under three subcontracts was administered by this project: (1) electrolytic production of oxygen from molten lunar materials; (2) microwave processing of lunar materials; and (3) production of a resource-oriented space science data base.
Topics include: a technology focus on data acquisition, electronic components and systems, software, materials, mechanics, machinery/automation, physical sciences, book and reports, motion control, and a special section of Photonics Tech Briefs.