CAREER: Developing Wavefunction-based Quantum Chemistry for Solids
CAREER: Developing Wavefunction-based Quantum Chemistry for Solids
批准号:
2045046
负责人:
James Shepherd
金额:
$64.83万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-06-01 至 2026-05-31
中文摘要
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英文摘要
With support from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry, and the Established Program to Stimulate Competitive Research (EPSCoR) Dr. James Shepherd of the University of Iowa will be developing high-accuracy ground-state wavefunction electronic structure methods for the prediction of bulk properties of solids. Novel quantum materials have the potential to drive technological change due to the unique properties they possess as a result of the specific nature of their electronic structure. Examples of these materials include catalysts and semiconductors. When computational chemists are able to faithfully model the electronic structure of these compounds, they can contribute to the rational design of materials alongside experimentalists. The Shepherd research group is pursuing tools that enable quicker and more accurate such calculations. These tools are expected to advance our theoretical understanding of how electrons interact in solids. The Shepherd research group is also developing a course-based undergraduate research program using an evidence-based design philosophy. This program will train undergraduate STEM (Science, Technology, Engineering and Mathematics) majors in the computer-aided design of new materials commensurate with the uptick in interest in computationally guided materials design in academia and industry. Additionally, the program will seek to improve retention of students in STEM majors, especially of those students from underrepresented groups.In this project, Dr. James Shepherd and his research group at the University of Iowa are working to improve high accuracy computational chemistry methods, such as coupled cluster theory and full configuration interaction quantum Monte Carlo. The widespread adoption of these methods is prevented by finite size errors, which arise from trying to simulate real systems with a limited number of atoms. The Shepherd research group is systematically studying the physical origin of these errors; removing these errors for wavefunction-based quantum chemistry; and leveraging these technologies to study catalyst and semiconductor design.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
Machine learning for a finite size correction in periodic coupled cluster theory calculations
周期性耦合簇理论计算中有限尺寸修正的机器学习
DOI:
10.1063/5.0086580
发表时间:
2022
期刊:
The Journal of Chemical Physics
影响因子:
--
作者:
[Weiler, Laura, Mihm, Tina, Shepherd, James J.]
通讯作者:
Shepherd, James J.
海外基金