상세정보
Export to Refworks부가기능
An Optimization Framework for Nanomaterials Design
상세 프로파일
| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | An Optimization Framework for Nanomaterials Design. |
| 개인저자 | Hanselman, Christopher L. |
| 단체저자명 | Carnegie Mellon University. Chemical Engineering. |
| 발행사항 | [S.l.]: Carnegie Mellon University., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 174 p. |
| 기본자료 저록 | Dissertations Abstracts International 81-05B. Dissertation Abstract International |
| ISBN | 9781392747049 |
| 학위논문주기 | Thesis (Ph.D.)--Carnegie Mellon University, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 81-05, Section: B.
Advisor: Gounaris, Chrysanthos E. |
| 이용제한사항 | This item must not be sold to any third party vendors. |
| 요약 | Ongoing developments in the synthesis of nanostructured materials have led to a boom in the number of fabricatable nanomaterials. However, while there is a large body of work on how to fabricate increasingly complex nanostructures, there are relatively few systematic approaches for selecting which structures to fabricate so as to optimize for a particular functionality. In this thesis, we present a generic framework for modeling the design of nanostructured materials as mathematical optimization problems. Our work takes advantage of results from computationally demanding models (e.g. energies from quantum chemical calculations or kinetics from Monte Carlo simulations) from which it regresses simplified structure-function relationships that can be used in conjunction with a supervisory optimization algorithm to guide the design of highly functional nanostructures. We develop detailed mathematical optimization models for extended heterogeneous catalyst surfaces, doped perovskite oxygen carriers, and Wigner crystals while highlighting the ability of our approach to address a wide range of other material systems. In addition to detailed models, we have developed a general purpose Python package called MatOpt for streamlining the process of specifying optimizing materials and for lowering the barriers for applying mathematical optimization to materials problems. Our work provides systematic approaches for managing the combinatorial complexity of the nanomaterials design space and demonstrates the value of process systems engineering principles applied in new contexts. |
| 일반주제명 | Chemical engineering. Applied mathematics. Materials science. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
