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A description will be made of the current materials science program within the microgravity research division. This presentation will be made at a plenary session of the biennial materials Science Conference.
Abstract Efficiently extracting data from tables in the scientific literature is pivotal for building large‐scale databases. However, the tables reported in materials science papers exist in highly diverse forms; thus, rule‐based extractions are an ineffective approach. To overcome this challenge, the study presents MaTableGPT, which is a GPT‐based table data extractor from the materials science literature. MaTableGPT features key strategies of table data representation and table splitting for better GPT comprehension and filtering hallucinated information through follow‐up questions. When applied to a vast volume of water splitting catalysis literature, MaTableGPT achieves an extraction accuracy (total F1 score) of up to 96.8%. Through comprehensive evaluations of the GPT usage cost, labeling cost, and extraction accuracy for the learning methods of zero‐shot, few‐shot, and fine‐tuning, the study presents a Pareto‐front mapping where the few‐shot learning method is found to be the most balanced solution owing to both its high extraction accuracy (total F1 score >95%) and low cost (GPT usage cost of 5.97 US dollars and labeling cost of 10 I/O paired examples). The statistical analyses conducted on the database generated by MaTableGPT revealed valuable insights into the distribution of the overpotential and elemental utilization across the reported catalysts in the water splitting literature.
The Office of Biological and Physical Research (OBPR) is moving aggressively to align programs, projects, and products with the vision for space exploration. Research in advanced materials is a critical element in meeting exploration goals. Research in low gravity materials science in OBPR is being focused on top priority needs in support of exploration: 1) Space Radiation Shielding; 2) In Situ Resource Utilization; 3) In Situ Fabrication and Repair; 4) Materials Science for Spacecraft and Propulsion Systems; 5) Materials Science for Advanced Life Support Systems. Roles and responsibilities in low gravity materials research for exploration between OBPR and the Office of Exploration Systems are evolving.
The current NASA microgravity materials science flight research program is reviewed focusing on crystal growth experiments, solidification fundamentals, and thermophysical property measurements of materials. It is noted that most of the hardware which is utilized in joint international cooperation is flown on the International Microgravity Laboratory series of Spacelab missions. The Microgravity Science and Applications Program establishes a framework for the cooperative utilization of the SSF.
Graph deep learning models, which incorporate a natural inductive bias for atomic structures, are of immense interest in materials science and chemistry. Here, we introduce the Materials Graph Library (MatGL), an open-source graph deep learning library for materials science and chemistry. Built on top of the popular Deep Graph Library (DGL) and Python Materials Genomics (Pymatgen) packages, MatGL is designed to be an extensible “batteries-included” library for developing advanced model architectures for materials property predictions and interatomic potentials. At present, MatGL has efficient implementations for both invariant and equivariant graph deep learning models, including the Materials 3-body Graph Network (M3GNet), MatErials Graph Network (MEGNet), Crystal Hamiltonian Graph Network (CHGNet), TensorNet and SO3Net architectures. MatGL also provides several pre-trained foundation potentials (FPs) with coverage of the entire periodic table, and property prediction models for out-of-box usage, benchmarking and fine-tuning. Finally, MatGL integrates with PyTorch Lightning to enable efficient model training.
Ceramics and ceramic engineering - zirconium oxygen carbon system, solid state ceramics, surface phenomena, radiation effects, and processing
Effects of various energy environments on zirconium-oxygen-carbon system, solid state ceramics, surface properties, and ceramic materials processing
The accurate measurement of density in both liquid and solid samples is of considerable interest to Principal Investigators with materials science experiments slated for the ISS. The work to be described is an innovative application of a conventional industrial nondestructive evaluation instrument. Traditional applications of industrial computed tomography (CT) rely on reconstructing cross sections of large structures to provide two-dimensional planar views which can identify defects such as porosity, or other material anomalies. This has been done on microgravity materials science experiments to check the integrity of ampoule-cartridge assemblies for safety purposes. With a substantially monoenergetic flux, as can be obtained with a radioactive cobalt source, there will be a direct correlation between absorption and density. Under such conditions it then becomes possible to make accurate measurements of density throughout a sample, and even when the sample itself is enclosed within a furnace and a safety required cartridge. Such a system has been installed at Kennedy Space Center (KSC) and is available to PIs to examine samples before and after flight. The CT system is being used to provide density information for two purposes. Firstly, the determination of density changes from liquid to solid is vital information to the PI for purposes of modeling the solidification behavior of his sample, and to engineers who have to design containment ampoules and must allow for shrinkage and other volume changes that may occur during processing. While such information can be obtained by pycnometric measurements, the possibility of using a furnace installed on the CT system enables one to examine potentially dangerous materials having high vapor pressures, while not needing visible access to the material. In addition, uniform temperature can readily be obtained, and the system can be controlled to ramp up, hold, and ramp down while collecting data over a wide range of parameters automatically. Results of initial tests on low melting point elements such as gallium, indium and tin will be presented, and the intent is to proceed to compounds such as InSb, HgCdTe and CdTe. Alloys such as Pb-Sb (PI - Poirier, U AZ) and Cu-Al (PI - Trivedi, Ames Lab.), which are the subjects of flight experiments, will also be examined. The second application is the conversion of measured density values directly to composition. This was successfully done with the mercury cadmium telluride alloys grown on the second and fourth United States Microgravity Payload (USMP-2 and USMP-4) missions by Lehoczky. CdTe values along the length of the boules were obtained at KSC prior to cutting the sample, and could have been obtained prior to its removal from the cartridge and ampoule. Examples of the data obtained will be shown. It is anticipated that several of the materials science PIs will avail themselves of the technique described, initially for determining densities prior to flight, and then to acquire early quantitative data on the compositional variation within their samples.
A materials science experiment has been developed and readied for operation aboard the International Space Station (ISS). Components of this experiment are onboard ISS and area awaiting the flight of science samples. The goal of the experiment is to understand the dynamics of Ostwald ripening, also known as coarsening, a process that occurs in nearly any two-phase mixture found in nature. Attempts to obtain experimental data in ground-based laboratories are hindered due to the presence of gravity, which introduces material transport modes other than that of the coarsening phenomenon. This introduces adjustable parameters in the formulation of theory. The original Coarsening in Solid-Liquid Mixtures (CSLM) mission, which flew on the Space Shuttle in 1997, produced data from a coarsened eutectic alloy. Unfortunately, both the science matrix and the hardware, while nominally functional, did not account adequately for operations in microgravity. A significantly redesigned follow-on experiment, CSLM-2 has been developed to redress the inadequacies of the original experiment. This paper reviews the CSLM-2 project: its history, science goals, flight hardware implementation, and planned operations and analysis
Machine intelligence has the potential to revolutionize materials science, enabling autonomous synthesis, self-driving characterization, and accelerated modeling. However, despite the promise, successful implementation of these methods in day-to-day research remains a challenge. This talk will delve into the reasons behind this, exploring how truly intelligent experiments are hindered by opaque experiment control, a lack of domain-specific models, and human-centric design. Through a focus on the characterization of next-generation microelectronics and energy storage materials, I will share insights from both successful and failed attempts to implement machine intelligence. We will then explore the next steps necessary to unlock the full potential of machine intelligence in materials science, creating a future where intelligent systems work seamlessly alongside researchers to drive innovation and discovery.
Article to be sent to Advanced Materials and Processes, journal of ASM International, as attached. This is a news-type technical journal for a large organization of scientists, engineers, salesmen, and managers. The article is quite general, meant to be an introduction to the properties of nanotubes. This is a materials science organization, therefore the article is geared toward using nanotubes for materials uses. Pictures have not been included in this version.
Microgravity materials processing experiments provide an opportunity to perform scientific research in an environment which allows one to observe various phenomena without the masking effects of gravity-driven convective flows, buoyancy, or contaminating influences of walled containers. Even for the most experienced scientists, it is still difficult to predict beforehand, whether or not microgravity experimentation can be successfully performed in space and achieve solutions to problems which are not attainable in 1 g. Consequently, experimentation in ground based facilities which are capable of simulating, in somewhat lesser time frames and to a lesser degree of microgravity, provides a unique low-cost approach to determine the feasibility of continuing research in a particular experiment. The utilization of these facilities in developing the full requirements for a space experiment does present a very cost-effective approach to microgravity experimentation. The Drop Tube Facility at Marshall Space Flight Center (MSFC) provides an excellent test bed for containerless processing experiments such as described here. These facilities have demonstrated for a number of years the capability to develop insight into space experiments involving containerless processing, rapid solidification, and wetting phenomena through the use of lower-cost ground facilities. Once sufficient data has been obtained, then a space-based experiment can be better defined.
The microgravity materials program was nearly eliminated in the middle of the aughts due to budget constraints. Hardware developments were eliminated. Some investigators with experiments that could be performed using ISS partner hardware received continued funding. Partnerships were established between US investigators and ESA science teams for several investigations. ESA conducted peer reviews on the proposals of various science teams as part of an ESA AO process. Assuming he or she was part of a science team that was selected by the ESA process, a US investigator would submit a proposal to NASA for grant funding to support their part of the science team effort. In a similar manner, a US materials investigator (Dr. Rohit Trivedi) is working as a part of a CNES selected science team. As funding began to increase another seven materials investigators were selected in 2010 through an NRA mechanism to perform research related to development of Materials Science Research Rack investigations. One of these has since been converted to a Glovebox investigation.
On January 14, 2004, the President of the United States announced a new vision for the United States civil space program. The Administrator of the National Aeronautics and Space Administration (NASA) has the responsibility to implement this new vision. The President also created a Presidential Commission 'to obtain recommendations concerning implementation of the new vision for space exploration.' The President's Commission recognized that achieving the exploration objectives would require significant technical innovation, research, and development in focal areas defined as 'enabling technologies.' Among the 17 enabling technologies identified for initial focus were advanced structures; advanced power and propulsion; closed-loop life support and habitability; extravehicular activity system; autonomous systems and robotics; scientific data collection and analysis; biomedical risk mitigation; and planetary in situ resource utilization. The Commission also recommended realignment of NASA Headquarters organizations to support the vision for space exploration. NASA has aggressively responded in its planning to support the vision for space exploration and with the current considerations of the findings and recommendations from the Presidential Commission. This presentation will examine the transformation and realignment activities to support the vision for space exploration that are underway in the microgravity materials science program. The heritage of the microgravity materials science program, in the context of residence within the organizational structure of the Office of Biological and Physical Research, and thematic and sub-discipline based research content areas, will be briefly examined as the starting point for the ongoing transformation. Overviews of future research directions will be presented and the status of organizational restructuring at NASA Headquarters, with respect to influences on the microgravity materials science program, will be discussed. Additional information is included in the original extended abstract.
Abstract Large language models (LLMs) are reshaping many aspects of materials science and chemistry research, enabling advances in molecular property prediction, materials design, scientific automation, knowledge extraction, and more. Recent developments demonstrate that the latest class of models are able to integrate structured and unstructured data, assist in hypothesis generation, and streamline research workflows. To explore the frontier of LLM capabilities across the research lifecycle, we review applications of LLMs through 32 total projects developed during the second annual LLM hackathon for applications in materials science and chemistry, a global hybrid event. These projects spanned seven key research areas: (1) molecular and material property prediction, (2) molecular and material design, (3) automation and novel interfaces, (4) scientific communication and education, (5) research data management and automation, (6) hypothesis generation and evaluation, and (7) knowledge extraction and reasoning from the scientific literature. Collectively, these applications illustrate how LLMs serve as versatile predictive models, platforms for rapid prototyping of domain-specific tools, and much more. In particular, improvements in both open source and proprietary LLM performance through the addition of reasoning, additional training data, and new techniques have expanded effectiveness, particularly in low-data environments and interdisciplinary research. As LLMs continue to improve, their integration into scientific workflows presents both new opportunities and new challenges, requiring ongoing exploration, continued refinement, and further research to address reliability, interpretability, and reproducibility.
Project MAUS is a part of the German material sciences program and provides autonomous payloads for the Space Shuttle. These payloads are housed in canisters which are identical with those of NASA's Get-Away-Special program. The main components of the hardware are: a standard system consisting of power supply, experiment control, data acquisition and the experiment modules containing experiment specific hardware. So far, three MAUS modules with experiments from the area of material sciences have been flown as GAS payloads.
Understanding and predicting the properties of inorganic materials is crucial for accelerating advancements in materials science and driving applications in energy, electronics and beyond. Integrating material structure data with language-based information through multimodal large language models (LLMs) offers great potential to support these efforts by enhancing human–artificial intelligence interaction. However, a key challenge lies in integrating atomic structures at full resolution into LLMs. In this work, we introduce MatterChat, a versatile structure-aware multimodal LLM that unifies material structural data and textual inputs into a single cohesive model. MatterChat uses a bridging module to effectively align a pretrained universal machine learning interatomic potential with a pretrained LLM, reducing training costs and enhancing flexibility. Our results demonstrate that MatterChat greatly improves performance in material property prediction and human–artificial intelligence interaction, surpassing general-purpose LLMs such as GPT-4. We also demonstrate its usefulness in applications such as more advanced scientific reasoning and step-by-step material synthesis.
The facilities at the Microgravity Materials Science Laboratory (MMSL) at the Lewis Research Center, created to offer immediate and low-cost access to ground-based testing facilities for industrial, academic, and government researchers, are described. The equipment in the MMSL falls into three categories: (1) devices which emulate some aspect of low gravitational forces, (2) specialized capabilities for 1-g development and refinement of microgravity experiments, and (3) functional duplicates of flight hardware. Equipment diagrams are included.