Development of Sustainable Superhard Materials

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dc.contributor.advisorBrgoch, Jakoah
dc.contributor.committeeMemberGuloy, Arnold M.
dc.contributor.committeeMemberJacobson, Allan J.
dc.contributor.committeeMemberLubchenko, Vassiliy
dc.contributor.committeeMemberGrabow, Lars C.
dc.creatorMansouritehrani, Aria 1991-
dc.creator.orcid0000-0003-1968-0379
dc.date.accessioned2020-01-06T23:56:11Z
dc.date.createdMay 2019
dc.date.issued2019-05
dc.date.submittedMay 2019
dc.date.updated2020-01-06T23:56:11Z
dc.description.abstractHard and superhard materials are essential for a myriad of scientific, biomedical, and industrial applications. Their ability to resist indentation stems from a complex relationship among the crystal structure, chemical composition, and microstructure. One of the main difficulties in modeling the mechanical properties is that hardness is influenced by many factors, which requires extensive calculations to account for the multiple length scales ranging from local atomic interactions to long length scales encompassing microstructure. Consequently, it is not possible to employ one single method to predict the hardness of inorganic solids for various chemical systems. As a result, most known superhard materials have either been discovered through trial-and-error or by following simple design rules limiting the development of the field. This contribution employs a combination of computational methods to identify hardness theories, machine learning techniques to screen for optimal materials, and experimental tools to verify theoretical predictions in route to developing new superhard materials. First, the influence of vacancies is explored on the mechanical behavior of ultraincompressible hard transition metal sub-nitrides through density functional theory. These studies show the synthetic conditions can be tuned to limit the occurrence of adverse vacancy softening mechanisms. Then, a methodology is developed to screen for hard materials based on high-throughput density functional theory calculations. Sustainability parameters have also been included to ensure the targeted compositions are sustainable. A machine learning method is further developed which allows the screening of more than 118,000 compounds for the highest possible hardness. The procedure highlighted two compounds, ReWC<sub>0.8</sub> and Mo<sub>0.9</sub>W<sub>1.1</sub>BC, and their subsequent synthesis and characterization confirmed they are both ultraincompressible and nearly superhard. Further examining the solid-solution behavior of Mo<sub>2-x</sub>W<sub>x</sub>BC showed the variation of hardness and revealed a unique balance between hardness, ductility, and sustainability which can be tuned based on transition metal ratio. Finally, the mechanism of simultaneous ductility and hardness is explored in Mo<sub>2</sub>BC using first-principles stress-strain curves and monitoring the electronic perturbation along the deformation path. Together this dissertation provides insights on deformation mechanisms, pinpoints crystal chemical traits that generate high hardness, and provides methodologies to accelerate the advancement of hard and superhard materials.
dc.description.departmentChemistry, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.citationPortions of this document appear in: A. Mansouri Tehrani, J. Brgoch, Hard and Superhard Materials: A Computational Perspective, J. Solid State Chem. 271, 47-58, 2019. And in: A. Mansouri Tehrani, L. Ghadbeigi, J. Brgoch, T. D. Sparks, Balancing Mechanical Properties and Sustainability in the Search for Superhard Materials, Integr. Mater. Manuf. Innov. 2017. And in: A. Mansouri Tehrani, J. Brgoch, Impact of Vacancies on the Mechanical Properties of Ultra-Incompressible, Hard Rhenium Subnitrides: Re2N and Re3N. Chem. Mater., 2017, 29, 2542-2549. And in: A. Mansouri Tehrani, A. O. Oliynyk, M. Parry, Z. Rizvi, S. Couper, F. Lin, L. Miyagi, T. D. Sparks, J. Brgoch, Machine learning directed Search for Ultraincompressible, High Hardness Materials. J. Am. Chem. Soc. 2018 140,9844-9853.
dc.identifier.urihttps://hdl.handle.net/10657/5799
dc.language.isoeng
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. UH Libraries has secured permission to reproduce any and all previously published materials contained in the work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectSuperhard materials
dc.subjectSolid-state chemistry
dc.titleDevelopment of Sustainable Superhard Materials
dc.type.dcmiText
dc.type.genreThesis
local.embargo.lift2021-05-01
local.embargo.terms2021-05-01
thesis.degree.collegeCollege of Natural Sciences and Mathematics
thesis.degree.departmentChemistry, Department of
thesis.degree.disciplineChemistry
thesis.degree.grantorUniversity of Houston
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

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