Show simple item record

dc.contributor.advisorGómez-Gualdrón, Diego A.
dc.contributor.authorSchweitzer, Benjamin
dc.date.accessioned2018-12-27T15:56:02Z
dc.date.accessioned2022-02-03T13:12:31Z
dc.date.available2019-06-20T16:45:12Z
dc.date.available2022-02-03T13:12:31Z
dc.date.issued2018
dc.identifierSchweitzer_mines_0052N_11654.pdf
dc.identifierT 8647
dc.identifier.urihttps://hdl.handle.net/11124/172833
dc.descriptionIncludes bibliographical references.
dc.description2018 Fall.
dc.description.abstractHydrogen is a promising renewable fuel due to its carbon-free nature and relatively high energy content by mass. However, a major hurdle for its widespread adoption as a vehicular fuel is its low density at ambient conditions, posing a challenge for onboard storage. Toward fully realizing a cost-effective, hydrogen-powered fuel cell vehicle, the U.S. Department of Energy (DOE) has set a system-level hydrogen storage target of 30 g/L for 2020, which is expected to require storing around 60 g/L at the material-level. While considerable research has been performed on hydrogen storage materials, it is still unclear whether these storage demands can be met by physisorption-based hydrogen storage systems. To assess the viability of these targets, grand canonical Monte Carlo (GCMC) simulations were used to calculate 18,000+ hydrogen loadings in porous crystals featuring catecholate functionalities at different thermodynamic conditions. From the data, the effects of interaction strength on the deliverable capacity of the material were elucidated. The simulation data was also used to develop an artificial neural network (ANN) model to predict hydrogen loadings using the force field parameters, textural properties of the crystal and thermodynamic conditions as input. The model was used to explore optimal operating conditions for hydrogen storage beyond those initially simulated with GCMC. It was found that optimizing the H2-catecholate interaction strength allowed some porous crystals to achieve deliverable capacities of 60 g/L with a 100 bar/77K ↔ 5 bar/160K swing in pressure and temperature. Additionally, it was shown that other porous crystals can reach 95% of the above deliverable capacity with a storage pressure of only 20 bar as long as the H2-catecholate interaction strength is optimized.
dc.format.mediumborn digital
dc.format.mediummasters theses
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado School of Mines. Arthur Lakes Library
dc.relation.ispartof2018 - Mines Theses & Dissertations
dc.rightsCopyright of the original work is retained by the author.
dc.subjectcovalent organic frameworks
dc.subjectmachine learning
dc.subjectmolecular simulation
dc.subjecthydrogen storage
dc.subjectadsorption
dc.subjectmetal organic frameworks
dc.titleHydrogen storage in porous crystalline materials: insights on the role of interaction strength from simulation and machine learning
dc.typeText
dc.contributor.committeememberCarreon, Moises A.
dc.contributor.committeememberSum, Amadeu K.
dcterms.embargo.terms2019-06-20
dcterms.embargo.expires2019-06-20
thesis.degree.nameMaster of Science (M.S.)
thesis.degree.levelMasters
thesis.degree.disciplineChemical and Biological Engineering
thesis.degree.grantorColorado School of Mines
dc.rights.accessEmbargo Expires: 06/20/2019


Files in this item

Thumbnail
Name:
Schweitzer_mines_0052N_11654.pdf
Size:
5.323Mb
Format:
PDF

This item appears in the following Collection(s)

Show simple item record