A simple constrained machine learning model for predicting high-pressure-hydrogen-compressor materials

Hattrick-Simpers, Jason R.; Choudhary, Kamal; Corgnale, Claudio

doi:10.1039/C8ME00005K

Title: A simple constrained machine learning model for predicting high-pressure-hydrogen-compressor materials

Journal Article · 11 June 2018 · Molecular Systems Design & Engineering

DOI: https://doi.org/10.1039/C8ME00005K · OSTI ID:1436892

^[1]; Choudhary, Kamal ^[1]; Corgnale, Claudio ^[2]

Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, USA
Greenway Energy LLC, Aiken, USA

Here we present the results of using techno-economic analysis as constraints for machine learning guided studies of new metal hydride materials.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: FOA-0001618/DESC00117076

OSTI ID:: 1436892

Journal Information:: Molecular Systems Design & Engineering, Journal Name: Molecular Systems Design & Engineering Vol. 3 Journal Issue: 3; ISSN 2058-9689

Publisher:: Royal Society of Chemistry (RSC)Copyright Statement

Country of Publication:: United Kingdom

Language:: English

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Cited by: 31 works

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