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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Microgravity science experiment integration - When the PI and the PED differ

This paper addresses issues related to the integration of principal investigators (PIs) and payload-element developers (PEDs) for conducting effective microgravity experiments. The Crystal Growth Furnace (CGF) is used as an example to demonstrate the key issues related to the integration of a PI's sample into a facility run by a different organization. Attention is given to the typical preflight timeline, documentation required for experimental implementation, and hardware deliverables. A flow chart delineates the payload-integration process flow, and PI inputs required for an experiment include equipment and procedure definitions, detailed design and fabrication of the experiment-specific equipment, and specifications of the contract-end item. The present analysis is of interest to the coordination of effective microgravity experiments on the Space Station Freedom that incorporate PIs and PEDs from different organizations.

Baer-Peckham, M. S.↗
DOE OSTI2025

Integrating Experiments and Simulations to Reveal Anisotropic Growth Mechanisms and Interfaces of a One-Dimensional Zeolite

Zeolites are nanoporous crystalline materials critical for diverse industrial applications, yet their growth mechanisms are poorly understood. Here, this study presents a novel integrated framework combining experimental synthesis, high-resolution imaging, coarse-grained molecular dynamics simulations, and computer vision to uncover the mechanisms of growth of SSZ-24, a 1D channel zeolite. We demonstrate how synthesis conditions, such as temperature and reactant concentration, govern crystal anisotropy and surface roughness with growth dynamics differing markedly by crystallographic orientation. Along the channels, growth involves minimal energy barriers and rapid nucleation, resulting in rough surfaces. In contrast, growth perpendicular to the channels requires cooperative molecular organization and is highly sensitive to thermodynamic and kinetic conditions, yielding smooth anisotropic surfaces under low driving forces. By simulating transmission electron microscopy (TEM) images, we bridge molecular-scale simulations with experimental observations, identifying distinct growth mechanisms along different crystal planes. This work offers molecular-level insights into zeolite crystallization, advancing the rational design of nanoporous materials. The integration of cross-disciplinary methodologies establishes a transformative framework for optimizing zeolite synthesis, with implications for broader classes of materials.

Bertolazzo, Andressa A. [Univ. of Utah, Salt Lake ↗
DOE OSTI2026

Reimagining metal-organic framework discovery: Integrating experiment, computation, and artificial intelligence

The traditional development of novel metal–organic frameworks (MOFs) is often hindered by challenges such as synthetic accessibility and time- and resource-intensive experimentation. High-throughput, automated experimental and computational techniques have enabled rapid chemical space exploration and theoretical MOF design. When combined with artificial intelligence (AI), these methods can be used to lead autonomous laboratories to new frontiers for MOF discovery, where these materials can be designed for a specific application, efficiently synthesized, characterized, and evaluated. Here, this perspective highlights the role of AI in advancing automated MOF synthesis and characterization, computational MOF design and screening, and the integration of these approaches within autonomous workflows to ultimately enable the MOF laboratories of the future.

Gaidimas, Madeleine A. [Northwestern University, E↗
DOE OSTI2025

Antiviral discovery using sparse datasets by integrating experiments, molecular simulations, and machine learning

Computational methods have demonstrated success in identifying virucidal agents, effectively contributing to the discovery of novel virucidal molecules. In this study, we developed a machine learning (ML) model, trained on a small dataset, to predict inhibitors of human enterovirus 71 (EV71), a pathological agent that causes severe disease in children and immunocompromised adults. Despite the dataset’s limitation, comprising of only 36 compounds tested, our ML framework demonstrated significant predictive capability. Notably, experimental validation revealed that five out of the eight compounds predicted by our model from the Chinese cosmetic material list exhibited virucidal activity. The inhibitor effects displayed by the main active compounds were further confirmed by molecular dynamics simulation. This underscores the potential of our AI-driven approach to bypass data constraints in identifying active molecules against viral pathogens.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Sensitivity of an integrated experiment to uncertainty in the high explosive equations of state

Traditionally, hydrodynamics simulations are performed with a single equation-of-state (EOS) to describe each material. These EOSs typically have a physics-informed functional form with adjustable parameters that are calibrated in order to replicate small-scale data. However, because the calibration data have uncertainty and there are typically inherent degeneracies in fitting the EOS, there are actually multiple EOSs that might be consistent with calibration data. In this work, we perform uncertainty quantification (UQ) for the reactant and product equations of state for the high explosive PBX 9501 to yield an ensemble of EOSs that match the uncertain small-scale calibration data. We then simulate an experiment of an explosively formed penetrator repeatedly with different EOSs to both validate the UQ analysis and determine the effects of EOS uncertainty on the prediction of quantities of interest in the experiment. In general, we find good agreement between the simulation predictions and the experimental measurements, and we identify an EOS variable that contributes most directly to the spread in the predictions as the EOSs are varied.

36 MATERIALS SCIENCE↗
DOE OSTI2024

TEX-Cl: Integral Experiment Execution of Thermal/Epithermal eXperiments using Highly Enriched Uranium with Polyethylene and Chloride Absorbers

This report documents the experimental configurations and measurements performed for IER-499, TEX with chlorine (TEX-Cl). TEX-Cl is a variant of the TEX-HEU campaign and utilizes highly enriched uranium fuel, high-density polyethylene (HDPE) moderators and reflectors, and interstitial NaCl salt absorbers. These experiments probe the chlorine (from the sodium chloride) absorption cross section in the thermal and intermediate neutron energy regimes, with a small portion in the fast neutron energy regime. Three configurations were selected by maximizing the sensitivity in k eff to the needs of Y-12 for their electrorefining operations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Integral Experiments Request 441 CED-3b Summary Report

Under IER-441, critical experiments were done with and without tantalum test rods within a central test region surrounded by 7uPCX fuel rods. The experiments were done in new critical assembly hardware designed to support the 7uPCX fuel in a 1.02 cm triangular-pitched array. Appendix I is a draft of section 1 of the ICSBEP benchmark evaluation of the experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Integral Experiment Request 441 CED-4a Summary Report

Under IER-441, critical experiments were done with and without tantalum test rods within a central test region surrounded by 7uPCX fuel rods. The experiments were done in new critical assembly hardware designed to support the 7uPCX fuel in a 1.02 cm triangular-pitched array

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Increased Fidelity and Associated Computational cost of Detailed Integral Experiment Benchmarks [Slides]

It does not seem like the system is significantly more sensitive to diameters of components near the center of the core. Intuitively it is, but was not detectable with simulations run to a Monte Carlo k eff uncertainty of 0.00002. The system is more sensitive to heights of components near the center of the core. Most (if not all) Zeus style benchmarks have perturbed core component heights individually.

42 ENGINEERING↗