Results for “UF3” | Engineering Papers

NASA NTRS2000

A Technology Demonstration Experiment for Laser Cooled Atomic Clocks in Space

We have been developing a laser-cooling apparatus for flight on the International Space Station (ISS), with the intention of demonstrating linewidths on the cesium clock transition narrower than can be realized on the ground. GLACE (the Glovebox Laser- cooled Atomic Clock Experiment) is scheduled for launch on Utilization Flight 3 (UF3) in 2002, and will be mounted in one of the ISS Glovebox platforms for an anticipated 2-3 week run. Separate flight definition projects funded at NIST and Yale by the Micro- gravity Research Division of NASA as a part of its Laser Cooling and Atomic Physics (LCAP) program will follow GLACE. Core technologies for these and other LCAP missions are being developed at JPL, with the current emphasis on developing components such as the laser and optics subsystem, and non-magnetic vacuum-compatible mechanical shutters. Significant technical challenges in developing a space qualifiable laser cooling apparatus include reducing the volume, mass, and power requirements, while increasing the ruggedness and reliability in order to both withstand typical launch conditions and achieve several months of unattended operation. This work was performed at the Jet Propulsion Laboratory under a contract with the National Aeronautics and Space Administration.

Klipstein, W. M.↗

NASA NTRSDate not supplied

Hierarchical screening for Li-based solid electrolytes using fast, interpretable machine-learned potentials

Li-based solid-state electrolyte materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. The prohibitive cost of high-throughput screening with DFT has lead to the development of surrogate models using geometric analysis, empirical potentials, and descriptors for ionic transport. Here, I will discuss a hierarchical screening approach for identifying promising materials using a combination of density functional theory, bond-valence methods, and machine learning potentials generated with the Ultra-Fast Force Fields (UF3) framework. We show how the inexpensive bond-valence method can be used to guide the generation of training samples for machine learning, in addition to filtering candidates. Finally, we apply the hierarchical workflow to screen for ionic conductivity across a database of Li-containing compounds.

Materials discovery↗

NASA NTRSDate not supplied

Hierarchical Screening for Li-Based Solid Electrolytes Using Fast, Interpretable Machine-Learned Potentials

Li-based solid-state electrolyte materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. The prohibitive cost of high-throughput screening with DFT has lead to the development of surrogate models using geometric analysis, empirical potentials, and descriptors for ionic transport. Here, I will discuss a hierarchical screening approach for identifying promising materials using a combination of density functional theory, bond-valence methods, and machine learning potentials generated with the Ultra-Fast Force Fields (UF3) framework. We show how the inexpensive bond-valence method can be used to guide the generation of training samples for machine learning, in addition to filtering candidates.

Materials discovery↗