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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

An Overview of the Microgravity Science Glovebox (MSG) Facility and the Research Performed in the MSG on the International Space Station (ISS)

The Microgravity Science Glovebox (MSG) is a double rack facility aboard the International Space Station (ISS) designed for investigation handling. The MSG has been operating on the ISS since July 2002 and is currently located in the Columbus Laboratory Module. The unique design of the facility allows it to accommodate science and technology investigations in a workbench type environment. The facility has an enclosed working volume that is held at a negative pressure with respect to the crew living area. This allows the facility to provide two levels of containment for small parts, particulates, fluids, and gases. This containment approach protects the crew from possible hazardous operations that take place inside the MSG work volume. Research investigations operating inside the MSG are provided a large 255 liter enclosed work space, 1000 watts of dc power via a versatile supply interface (120, 28, +/- 12, and 5 Vdc), 1000 watts of cooling capability, video and data recording and real time downlink, ground commanding capabilities, access to ISS Vacuum Exhaust and Vacuum Resource Systems, and gaseous nitrogen supply. These capabilities make the MSG one of the most utilized facilities on ISS. In fact, the MSG has been used for over 5000 hours of scientific payload operations. MSG investigations involve research in cryogenic fluid management, fluid physics, spacecraft fire safety, materials science, combustion, plant growth, and life support technologies. MSG is an ideal platform for science investigations and research required to advance the technology readiness levels (TRLs) applicable to the Constellation Program. This paper will provide an overview of the MSG facility, a synopsis of the research that has already been accomplished in the MSG, an overview of future investigations currently planned for operation in the MSG, and potential applications of MSG investigations that can provide useful data to the Constellation Program. In addition, this paper will address the role of the MSG facility in the ISS National Lab.

Spivey, Reggie↗
DOE OSTI2022

Probing topological phase transitions using high-harmonic generation

We report the prediction and realization of topological insulators have sparked great interest in experimental approaches to the classification of materials. The phase transition between non-trivial and trivial topological states is important, not only for basic materials science but also for next-generation technology, such as dissipation-free electronics. It is therefore crucial to develop advanced probes that are suitable for a wide range of samples and environments. Here we demonstrate that circularly polarized laser-field-driven high-harmonic generation is distinctly sensitive to the non-trivial and trivial topological phases in the prototypical three-dimensional topological insulator bismuth selenide. The phase transition is chemically initiated by reducing the spin–orbit interaction strength through the substitution of bismuth with indium atoms. We find strikingly different high-harmonic responses of trivial and non-trivial topological surface states that manifest themselves as a conversion efficiency and elliptical dichroism that depend both on the driving laser ellipticity and the crystal orientation. The origins of the anomalous high-harmonic response are corroborated by calculations using the semiconductor optical Bloch equations with pairs of surface and bulk bands. As a purely optical approach, this method offers sensitivity to the electronic structure of the material, including its nonlinear response, and is compatible with a wide range of samples and sample environments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2016

Overview of the Microgravity Science Glovebox (MSG) Facility and the Research Performed in the MSG

The Microgravity Science Glovebox (MSG) is a rack facility aboard the International Space Station (ISS) designed for investigation handling. The MSG was built by the European Space Agency (ESA) which also provides sustaining engineering support for the facility. The MSG has been operating on the ISS since July 2002 and is currently located in the US Laboratory Module. The unique design of the facility allows it to accommodate science and technology investigations in a "workbench" type environment. The facility has an enclosed working volume that is held at a negative pressure with respect to the crew living area. This allows the facility to provide two levels of containment for small parts, particulates, fluids, and gases. This containment approach protects the crew from possible hazardous operations that take place inside the MSG work volume. Research investigations operating inside the MSG are provided a large 255 liter enclosed work space, 1000 watts of direct current power via a versatile supply interface (120, 28, plus or minus 12, and 5 volts direct current), 1000 watts of cooling capability, video and data recording and real time downlink, ground commanding capabilities, access to ISS Vacuum Exhaust and Vacuum Resource Systems, and gaseous nitrogen supply. These capabilities make the MSG one of the most utilized facilities on ISS. The MSG has been used for over 27,000 hours of scientific payload operations. MSG investigations involve research in cryogenic fluid management, fluid physics, spacecraft fire safety, materials science, combustion, plant growth, biological studies and life support technology. The MSG facility is operated by the Payloads Operations Integration Center at Marshall Space Flight Center. Payloads may also operate remotely from different telescience centers located in the United States and Europe. The Investigative Payload Integration Manager (IPIM) is the focal to assist organizations that have payloads operating in the MSG facility. NASA provides an MSG engineering unit for payload developers to verify that their hardware is operating properly before actual operation on the ISS. This poster will provide an overview of the MSG facility, a synopsis of the research that has already been accomplished in the MSG, and an overview of video and biological upgrades. The author would like to acknowledge Teledyne Brown Engineering and the entire MSG Team for their inputs into this poster.

Jordan, Lee↗
DOE OSTI2022

High‐Resolution Electron Tomography of Ultrathin Boerdijk–Coxeter–Bernal Nanowire Enabled by Superthin Metal Surface Coating

Abstract The rapid advancement of transmission electron microscopy has resulted in revolutions in a variety of fields, including physics, chemistry, and materials science. With single‐atom resolution, 3D information of each atom in nanoparticles is revealed, while 4D electron tomography is shown to capture the atomic structural kinetics in metal nanoparticles after phase transformation. Quantitative measurements of physical and chemical properties such as chemical coordination, defects, dislocation, and local strain have been made. However, due to the incompatibility of high dose rate with other ultrathin morphologies, such as nanowires, atomic electron tomography has been primarily limited to quasi‐spherical nanoparticles. Herein, the 3D atomic structure of a complex core–shell nanowire composed of an ultrathin Boerdijk–Coxeter–Bernal (BCB) core nanowire and a noble metal thin layer shell deposited on the BCB nanowire surface is discovered. Furthermore, it is demonstrated that a new superthin noble metal layer deposition on an ultrathin BCB nanowire could mitigate electron beam damage using an in situ transmission electron microscope and atomic resolution electron tomography. The colloidal coating method developed for electron tomography can be broadly applied to protect the ultrathin nanomaterials from electron beam damage, benefiting both the advanced material characterizations and enabling fundamental in situ mechanistic studies.

Song, Xiaohui↗
NASA NTRS2008

An Overview of the Microgravity Science Glovebox (MSG) Facility, and the Gravity-Dependent Phenomena Research Performed in the MSG on the International Space Station (ISS)

The Microgravity Science Glovebox (MSG) is a double rack facility aboard the International Space Station (ISS) designed for gravity-dependent phenomena investigation handling. The MSG has been operating in the ISS US Laboratory Module since July 2002. The MSG facility provides an enclosed working area for investigation manipulation and observation, The MSG's unique design provides two levels of containment to protect the ISS crew from hazardous operations. Research investigations operating inside the MSG are provided a large 255 liter work volume, 1000 watts of dc power via a versatile supply interface (120, 28, +/-12, and 5 Vdc), 1000 watts of cooling capability, video and data recording and real time downlink, ground commanding capabilities, access to ISS Vacuum Exhaust and Vacuum Resource Systems, and gaseous nitrogen supply. With these capabilities, the MSG is an ideal platform for research required to advance the technology readiness levels (TRL) needed for the Crew Exploration Vehicle and the Exploration Initiative. Areas of research that will benefit from investigations in the MSG include thermal management, fluid physics, spacecraft fire safety, materials science, combustion, reaction control systems, in situ fabrication and repair, and advanced life support technologies. This paper will provide a detailed explanation of the MSG facility, a synopsis of the research that has already been accomplished in the MSG and an overview of investigations planning to operate in the MSG. In addition, this paper will address possible changes to the MSG utilization process that will be brought about by the transition to ISS as a National Laboratory.

Spivey, Reggie A.↗
DOE OSTI2022

Probing growth of metal–organic frameworks with X-ray scattering and vibrational spectroscopy

Nucleation and crystallization arising from liquid to solid phase are involved in a multitude of processes in fields ranging from materials science to biology. Controlling the thermodynamics and kinetics of growth is advantageous to help tune the formation of complex morphologies. In this report, we harness wide-angle X-ray scattering and vibrational spectroscopy to elucidate the mechanism for crystallization and growth of the metal–organic framework Co-MOF-74 within microscopic volumes enclosed in a capillary and an attenuated total reflection microchip reactor. The experiments reveal molecular and structural details of the growth processes, while the results of plane wave density functional calculations allow identification of lattice and linker modes in the formed crystals. Synthesis of the metal–organic framework with microscopic volumes leads to monodisperse and micron-sized crystals, in contrast to those typically observed under bulk reaction conditions. Reduction in the volume of reagents within the microchip reactor was found to accelerate the reaction rate. The coupling of spectroscopy with scattering to probe reactions in microscopic volumes promises to be a useful tool in the synthetic chemist's kit to understand chemical bonding and has potential in designing complex materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Blueprint for DOE Quantum Supercomputing: Ensuring U.S. Leadership in the Quantum Decade

Quantum computing stands at the threshold of a transformative decade, where the field will evolve from small-scale demonstrations toward practical scientific computing at scale. This Blueprint identifies fault-tolerant quantum computers (FTQCs) as a viable, scalable, and broadly applicable path to achieving “quantum scientific utility,” defined as solving scientifically valuable problems beyond the reach of conventional, classical computers. This capability is expected to show scientific demonstrations in the late 2020s and to mature in the early-to-mid 2030s. This Blueprint outlines a strategy to prepare the U.S. Department of Energy (DOE) for FTQCs and their integration into the U.S. national scientific computing infrastructure. Its purpose is to identify the steps, milestones, and research directions necessary for DOE to enable initial deployment of FTQCs in 2028 as a scientific tool for the nation and mature this capability into the 2030s. DOE has a long history of supporting quantum information science and technology, contributing significantly to research advancements, training a quantum-ready workforce, and providing access to early small-scale quantum hardware. Given recent demonstrations of logical operations on error-corrected logical qubits and the advancement of commercial hardware roadmaps, DOE should begin preparations for large-scale, fault-tolerant quantum computing deployment for DOE science missions. This Blueprint proposes that DOE focus on (1) deploying first-generation scientifically relevant quantum computers with at least 100 logical qubits and performing at least 10,000 to 100,000 hard logical operations in scientifically relevant calculations; (2) developing essential FTQC programming competencies, system software, and facility readiness; and (3) investing in cutting edge focused R&D that fosters breakthroughs in scientific applications, algorithms, and logical architectures needed to accelerate the advent of scientific utility. This effort will position DOE to transition to larger systems: production-scale quantum computers that comprise 1,000 to 10,000 logical qubits, perform 1 to 10 billion hard logical operations, and execute scientifically useful computations at scale. Achieving these goals will require DOE facilities to evolve with urgency to support scientific campaigns that integrate quantum and classical computing resources into efficient workflows, novel software and firmware environments for compiling and routing quantum programs on FTQC machines, and suitable infrastructure for quantum hardware. It will also require further development and optimization of scientific applications from the fields of materials science, quantum chemistry, and high-energy and nuclear physics. The Blueprint calls for transformative R&D and collective action to accelerate the advent of scientific quantum utility and bring it within reach by 2028.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2007

The Microgravity Science Glovebox (MSG), a Resource for Gravity-Dependent Phenomena Research on the International Space Station (ISS)

The Microgravity Science Glovebox (MSG) is a double rack facility aboard the International Space Station (ISS) designed for gravity-dependent phenomena investigation handling. The MSG has been operating in the ISS US Laboratory Module since July 2002. The MSG facility provides an enclosed working area for investigation manipulation and observation in the ISS. The MSG s unique design provides two levels of containment to protect the ISS crew from hazardous operations. Research investigations operating inside the MSG are provided a large 255 liter work volume, 1000 watts of dc power via a versatile supply interface (120,28, +/-12, and 5 Vdc), 1000 watts of cooling capability, video and data recording and real time downlink, ground commanding capabilities, access to ISS Vacuum Exhaust and Vacuum Resource Systems, and gaseous nitrogen supply. With these capabilities, the MSG is an ideal platform for research required to advance the technology readiness levels (TRL) needed for the Crew Exploration Vehicle and the Exploration Initiative. Areas of research that will benefit from investigations in the MSG include thermal management, fluid physics, spacecraft fire safety, materials science, combustion and reacting control systems, in situ fabrication and repair, and advanced life support technologies. This paper will provide a detailed explanation of the MSG facility, a synopsis of the research that has already been accomplished in the MSG, an overview of investigations planning to operate in the MSG, and possible augmentations that can be added to the MSG facility to further enhance the resources provided to investigations.

Spivey, Reggie A.↗
NASA NTRS2014

Crystal Growth of Ternary Compound Semiconductors in Low Gravity Environment

A low gravity material experiment will be performed in the Material Science Research Rack (MSRR) on International Space Station (ISS). There are two sections of the flight experiment: (I) crystal growth of ZnSe and related ternary compounds, such as ZnSeS and ZnSeTe, by physical vapor transport (PVT) and (II) melt growth of CdZnTe by directional solidification. The main objective of the project is to determine the relative contributions of gravity-driven fluid flows to the compositional distribution, incorporation of impurities and defects, and deviation from stoichiometry observed in the grown crystals as results of buoyancy-driven convection and growth interface fluctuations caused by irregular fluid-flows on Earth. The investigation consists of extensive ground-based experimental and theoretical research efforts and concurrent flight experimentation. This talk will focus on the ground-based studies on the PVT crystal growth of ZnSe and related ternary compounds. The objectives of the ground-based studies are (1) obtain the experimental data and conduct the analyses required to define the optimum growth parameters for the flight experiments, (2) perfect various characterization techniques to establish the standard procedure for material characterization, (3) quantitatively establish the characteristics of the crystals grown on Earth as a basis for subsequent comparative evaluations of the crystals grown in a low-gravity environment and (4) develop theoretical and analytical methods required for such evaluations. ZnSe and related ternary compounds have been grown by vapor transport technique with real time in-situ non-invasive monitoring techniques. The grown crystals have been characterized extensively by various techniques to correlate the grown crystal properties with the growth conditions.

Su, Ching-Hua↗
DOE OSTI2024

A Portable Miniature Cryogenic Environment for In Situ Neutron Diffraction

Neutron diffraction instruments offer a platform for materials science and engineering studies at extended temperature ranges far from ambient. As one of the widely used neutron sample environment types, cryogenic furnaces are usually bulky and complex, and they may need hours of beamtime overhead for installation, configuration, cooling, and sample change, etc. To reduce the overhead time and expedite experiments at the state-of-the-art high-flux neutron source, we developed a low-cost, miniature, and easy-to-use cryogenic environment (77–473 K) for in situ neutron diffraction. A travel-size mug serves for the environment where the samples sit inside. Immediate cooling and an isothermal dwell at 77 K are realized on the sample by direct contact with liquid N 2 in the mug. The designed Al inserts serve as the holder of samples and heating elements, alleviate the thermal gradient, and clear neutron pathways. Both a single-sample continuous measurement and multi-sample high-throughput measurements are demonstrated in this environment. High-quality and refinable in situ neutron diffraction patterns are acquired on model materials. The results quantify the orthorhombic-to-cubic phase transformation process in LiMn 2 O 4 and differentiate the anisotropic lattice thermal expansions and bond length evolutions between rhombohedral perovskite oxides with composition variation.

47 OTHER INSTRUMENTATION↗
NASA NTRS2007

The Microgravity Science Glovebox (MSG), a Resource for Gravity-Dependent Phenomena Research on the International Space Station (ISS)

The Microgravity Science Glovebox (MSG) is a double rack facility aboard the International Space Station (ISS) designed for gravity-dependent phenomena investigation handling. The MSG has been operating in the ISS US Laboratory Module since July 2002. The MSG facility provides an enclosed working area for investigation manipulation and observation in the ISS. The MSG's unique design provides two levels of containment to protect the ISS crew from hazardous operations. Research investigations operating inside the MSG are provided a large 255 liter work volume, 1000 watts of dc power via a versatile supply interface (120,28, plus or minus 12, and 5 Vdc), 1000 watts of cooling capability, video and data recording and real time downlink, ground commanding capabilities, access to ISS Vacuum Exhaust' and Vacuum Resource 'Systems, and gaseous nitrogen supply. With these capabilities, the MSG is an ideal platform for research required to advance the technology readiness levels (TRL) needed for the Crew Exploration Vehicle and the Exploration Initiative. Areas of research that will benefit from investigations in the MSG include thermal management, fluid physics, spacecraft fire safety, materials science, combustion and reacting control systems, in situ fabrication and repair, and advanced life support technologies. This paper will provide a detailed explanation of the MSG facility, a synopsis of the research that has already been accomplished in the MSG, an overview of investigations planning to operate in the MSG, and possible augmentations that can be added to-the MSG facility to further enhance the resources provided to investigations.

Spivey, Reggie A.↗
DOE OSTI2024

Active causal learning for decoding chemical complexities with targeted interventions

Abstract Predicting and enhancing inherent properties based on molecular structures is paramount to design tasks in medicine, materials science, and environmental management. Most of the current machine learning and deep learning approaches have become standard for predictions, but they face challenges when applied across different datasets due to reliance on correlations between molecular representation and target properties. These approaches typically depend on large datasets to capture the diversity within the chemical space, facilitating a more accurate approximation, interpolation, or extrapolation of the chemical behavior of molecules. In our research, we introduce an active learning approach that discerns underlying cause-effect relationships through strategic sampling with the use of a graph loss function. This method identifies the smallest subset of the dataset capable of encoding the most information representative of a much larger chemical space. The identified causal relations are then leveraged to conduct systematic interventions, optimizing the design task within a chemical space that the models have not encountered previously. While our implementation focused on the QM9 quantum-chemical dataset for a specific design task—finding molecules with a large dipole moment—our active causal learning approach, driven by intelligent sampling and interventions, holds potential for broader applications in molecular, materials design and discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Describing Point Defect Topology in 2D Energy Materials Through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. Here we employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science. ML is often not just a matter of straightforward application, and pretrained models proved ineffective in this case. Instead, we trained our own neural network (NN) and applied data augmentation techniques and fine-tuning to the training dataset. Since labeled microscopy data is often scarce, we developed training data from a previously published wide-frame MXene image, using customized Gaussian fitting to locate atomic positions. Our trained model was then applied to a large dataset of experimental images, enabling a statistical study of defect configurations across three samples prepared with different HF etchant concentrations (5%, 9.1%, and 12.5%), as shown in Fig. 1. This also allowed us to investigate local strain around vacancies, though we find that we are limited by the precision of measurements using high-angle annular dark field (HAADF) images, as shown in Fig. 2. This study demonstrates how ML enables large-scale, quantitative analysis of atomic defects - an otherwise infeasible task with traditional methods. While our NN was specialized for Ti3C2 MXenes, the pipeline we developed provides a foundation for future ML models tailored to other materials. Ultimately, we envision embedding the NN onto the microscope to give real-time feedback to the user. To make this a reality, continued work is necessary to fully understand the NN's capabilities and limitations. This study gets one step closer to our goals of automated experimentation moving away from traditional methods of manual labeling. As ML capabilities advance, we hope to continue adapting and applying these techniques in microscopy.

2D materials↗
DOE OSTI2021

An Open Combinatorial Diffraction Dataset Including Consensus Human and Machine Learning Labels with Quantified Uncertainty for Training New Machine Learning Models

Modern machine learning and autonomous experimentation schemes in materials science rely on accurate analysis of the data ingested by these models. Unfortunately, accurate analysis of the underlying data can be difficult, even for domain experts, complicating the training of the models intended to drive experiments. This is especially true when the goal is to identify the presence of weak signatures in diffraction or spectroscopic datasets. In this work, we examine a set of as-obtained diffraction data that track the phase transition from monoclinic to tetragonal in a Nb-doped VO2 film as a function of temperature and dopant concentration. We then task a set of domain experts and a set of machine learning experts with identifying which phase is present in each diffraction pattern manually and algorithmically, respectively; in both cases, the labels can vary dramatically, especially at the phase boundaries. We use the mode of the labels and the Shannon entropy as a method to capture, preserve and propagate consensus labels and their variance. Further we use the expert labels as a benchmark and demonstrate the use of Shannon entropy weighted scoring to test the performance of machine learning generated labels. Finally, we propose a material data challenge centered around generating improved labeling algorithms. This real-world dataset curated with expert labels can act as test bed for new algorithms. The raw data, annotations and code used in this study are all available online at data.gov and the interested reader is encouraged to replicate and improve the existing models

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Leveraging unlabeled SEM datasets with self-supervised learning for enhanced particle segmentation

Scanning Electron Microscopes (SEMs) are widely used in experimental science laboratories, often requiring cumbersome and repetitive user analysis. Automating SEM image analysis processes is highly desirable to address this challenge. In particle sample analysis, Machine Learning (ML) has emerged as the most effective approach for particle segmentation. However, the time-intensive process of manually annotating thousands of SEM images limits the applicability of supervised learning approaches. Self-Supervised Learning (SSL) offers a promising alternative by enabling knowledge extraction from raw, unlabeled data. This study presents a framework for evaluating SSL techniques in SEM image analysis, focusing on novel methods leveraging the ConvNeXtV2 architecture for particle detection. A dataset comprising 25,000 SEM images is curated to benchmark these proposed SSL methods. The results demonstrate that ConvNeXtV2 models, with varying parameter counts, consistently outperform other techniques in particle detection across different length scales, achieving up to a 34% reduction in relative error compared to established SSL methods. Furthermore, an ablation study explores the relationship between dataset size and SSL performance, providing actionable insights for practitioners regarding model selection and resource efficiency. This research advances the integration of SSL into autonomous analysis pipelines and supports its application in accelerating materials science discovery.

Rettenberger, Luca↗
DOE OSTI2021

Towards Efficient Uncertainty estimation in deep learning for robust energy prediction in crystal materials

In material science, recent studies have started to explore the potential of using deep learning to improve property prediction from high-fidelity simulations, e.g, density functional theory (DFT). However, the design spaces are sometimes too large and intractable to sample completely. This results in a critical question that is how to evaluate the confidence and robustness of the prediction. In this paper, we propose an efficient approach to estimate uncertainty in deep learning using a single forward pass and then apply it for robust prediction of the total energy in crystal lattice structures. Our approach is built upon the deep kernel learning (DKL) that originally introduces to leverage the expressiveness of deep neural networks as input with a probabilistic prediction of Gaussian processes (GPs) as output. Existing DKL methods have difficulties in the accuracy of predictive uncertainty, training stability, and scaling to large datasets, which lead to significant barriers in real-world applications. We propose to address these challenges by using an inducing point approximate GP in feature space combined with spectral normalization as a regularization. We finally demonstrate our robust performance on an artificial example and a real-world application from materials chemistry.

Bi, Sirui↗
DOE OSTI2024

Comparing first-principles density functionals plus corrections for the lattice dynamics of YBa 2 Cu 3 O 6

The enigmatic mechanism underlying unconventional high-temperature superconductivity, especially the role of lattice dynamics, has remained a subject of debate. Theoretical insights have long been hindered due to the lack of an accurate first-principles description of the lattice dynamics of cuprates. Recently, using the r2SCAN meta-generalized gradient approximation (meta-GGA) functional, we have been able to achieve accurate phonon spectra of an insulating cuprate YBa 2 Cu 3 O 6 and discover significant magnetoelastic coupling in experimentally interesting Cu–O bond stretching optical modes [Ning et al., Phys. Rev. B 107, 045126 (2023)]. We extend this work by comparing Perdew–Burke–Ernzerhof and r2SCAN performances with corrections from the on-site Hubbard U and the D4 van der Waals (vdW) methods, aiming at further understanding on both the materials science side and the density functional side. We demonstrate the importance of vdW and self-interaction corrections for accurate first-principles YBa 2 Cu 3 O 6 lattice dynamics. Since r2SCAN by itself partially accounts for these effects, the good performance of r2SCAN is now more fully explained. Finally, in addition, the performances of the Tao–Mo series of meta-GGAs, which are constructed in a different way from the strongly constrained and appropriately normed (SCAN) meta-GGA and its revised version r2SCAN, are also compared and discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2012

Microgravity Science Glovebox (MSG), Space Science's Past, Present and Future Aboard the International Space Station (ISS)

The Microgravity Science Glovebox (MSG) is a double rack facility aboard the International Space Station (ISS), which accommodates science and technology investigations in a "workbench' type environment. The MSG has been operating on the ISS since July 2002 and is currently located in the US Laboratory Module. In fact, the MSG has been used for over 10,000 hours of scientific payload operations and plans to continue for the life of ISS. The facility has an enclosed working volume that is held at a negative pressure with respect to the crew living area. This allows the facility to provide two levels of containment for small parts, particulates, fluids, and gases. This containment approach protects the crew from possible hazardous operations that take place inside the MSG work volume and allows researchers a controlled pristine environment for their needs. Research investigations operating inside the MSG are provided a large 255 liter enclosed work space, 1000 watts of dc power via a versatile supply interface (120, 28, + 12, and 5 Vdc), 1000 watts of cooling capability, video and data recording and real time downlink, ground commanding capabilities, access to ISS Vacuum Exhaust and Vacuum Resource Systems, and gaseous nitrogen supply. These capabilities make the MSG one of the most utilized facilities on ISS. MSG investigations have involved research in cryogenic fluid management, fluid physics, spacecraft fire safety, materials science, combustion, and plant growth technologies. Modifications to the MSG facility are currently under way to expand the capabilities and provide for investigations involving Life Science and Biological research. In addition, the MSG video system is being replaced with a state-of-the-art, digital video system with high definition/high speed capabilities, and with near real-time downlink capabilities. This paper will provide an overview of the MSG facility, a synopsis of the research that has already been accomplished in the MSG, and an overview of the facility enhancements that will shortly be available for use by future investigators.

Spivey, Reggie↗