CAREER: Correlated Superconductors under Extreme Conditions
CAREER: Correlated Superconductors under Extreme Conditions
批准号:
2142801
负责人:
Cheng-Chien Chen
金额:
$45.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-02-01 至 2027-01-31
中文摘要
点击翻译按钮获取中文摘要
英文摘要
NONTECHNICAL SUMMARYThis CAREER award supports computational and theoretical research and education on modeling superconductors in which electrons interact with each other strongly or are subjected to extreme conditions such as intense light illumination and high pressure. Superconductivity is a quantum phenomenon that allows electricity to flow with zero resistance below some critical temperature. Superconductors have several existing applications such as magnetic resonance imaging devices, quantum computers, and magnetic levitation trains. However, broad-scale utilization of superconducting technology is currently limited, because most existing materials become superconducting at very low temperatures under normal conditions. Recent experiments have shown that critical temperatures of superconductors can be boosted under extreme conditions of exposure to intense lasers or ultrahigh pressures. However, the underlying mechanisms for these experimental observations have largely remained elusive. In this project, the PI will employ and develop advanced computational techniques to tackle the challenges associated with understanding the mechanisms of superconductivity under extreme conditions. The main research goal is to provide a fundamental theoretical understanding to guide experiments in characterizing and discovering new materials that become superconducting when exposed to intense light or high-pressures. The research will help expedite the modeling and discovery of new materials that become superconducting at higher temperatures, thus offering opportunities to revolutionize the industries of energy, transportation, and information technology.This award also supports various education and outreach activities. The PI will (i) train both undergraduate and graduate students in computational physics, data science, and materials science research, (ii) deliver corresponding interdisciplinary courses by integrating research with teaching, and (iii) broaden the participation of groups traditionally underrepresented in Science, Technology, Engineering, and Mathematics (STEM) disciplines and organize science summer camps for Birmingham high-school and community college students, in order to engage them at early stages towards STEM careers.TECHNICAL SUMMARYThis CAREER award supports research and education in theoretical and computational studies of correlated superconductors under extreme conditions. The materials to explore include unconventional superconductors like the cuprates and iron selenides, and conventional superconductors yet with substantial correlation physics manifest in the electronic structures. The PI will investigate phase diagrams and light-induced superconductivity of correlated Hamiltonians, such as the extended Hubbard and Hubbard-Holstein models. The objectives are to show that metastable superconducting phase at equilibrium can dominate at nonequilibrium, and that exotic pairing symmetry can be selectively enhanced by a tailored laser pump. The PI will also model the use of strain and pressure as tuning knobs to control topological superconductors. Furthermore, the PI will investigate whether correlation effects in rare-earth hydrides can potentially help achieve superconductors with high critical temperatures at reduced pressures. To tackle the challenges in studying the above systems, the PI will employ and develop advanced numerical techniques including large-scale exact diagonalization, first-principles evolutionary structure prediction, and novel data science approaches, such as dataflow computing, time series regression, and graph neural networks. The research activities will advance the understanding and control of correlated superconductors under nonequilibrium and strained environments, and help expedite the modeling and discovery of new superconductors with high critical temperatures.This award also supports various education and outreach activities. The PI will (i) train both undergraduate and graduate students in computational physics, data science, and materials science research, (ii) deliver corresponding interdisciplinary courses by integrating research with teaching, and (iii) broaden the participation of underrepresented STEM groups and organize science summer camps for Birmingham high-school and community college students, in order to engage them at early stages towards STEM careers.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(6)
专著(0)
科研奖励(0)
会议论文
登录
查看更多内容
DOI:
10.1038/s41535-022-00496-w
发表时间:
2022-09
期刊:
npj Quantum Materials
影响因子:
5.7
作者:
[Ekaterina M. Pärschke;Wei-Chih Chen;R. Ray;Cheng-Chien Chen]
通讯作者:
Ekaterina M. Pärschke;Wei-Chih Chen;R. Ray;Cheng-Chien Chen
DOI:
10.1103/physrevb.108.064514
发表时间:
2022-06
期刊:
Physical Review B
影响因子:
3.7
作者:
[Wei-Chih Chen;Yao Wang;Cheng-Chien Chen]
通讯作者:
Wei-Chih Chen;Yao Wang;Cheng-Chien Chen
DOI:
10.1038/s43588-023-00471-w
发表时间:
2023-07
期刊:
Nature Computational Science
影响因子:
--
作者:
[D. Yan;Adam D. Smith;Cheng-Chien Chen]
通讯作者:
D. Yan;Adam D. Smith;Cheng-Chien Chen
DOI:
10.1103/physrevb.108.174514
发表时间:
2023-05
期刊:
Physical Review B
影响因子:
3.7
作者:
[Adam D. Smith;S. Harris;R. Camata;D. Yan;Cheng-Chien Chen]
通讯作者:
Adam D. Smith;S. Harris;R. Camata;D. Yan;Cheng-Chien Chen
DOI:
10.1038/s41535-022-00492-0
发表时间:
2022-08
期刊:
npj Quantum Materials
影响因子:
5.7
作者:
[Qian Xiao;Wenliang Zhang;T. Asmara;Dong Li;Qizhi Li;Shi-Yue Zhang;Y. Tseng;Xiaoli Dong;]
通讯作者:
Qian Xiao;Wenliang Zhang;T. Asmara;Dong Li;Qizhi Li;Shi-Yue Zhang;Y. Tseng;Xiaoli Dong;
Travel Grant for NSF Frontera LRAC Award: Technical Coordination with TACC and Attendance to a PI Meeting
-
批准号:2031563
-
项目类别:Standard Grant
-
资助金额:$0.81万
-
财政年份:2020
-
负责人:Cheng-Chien Chen
-
依托单位:
RII Track-4: Big Data and Massive Computation Approaches to Non-Equilibrium Dynamics of Strongly Correlated Materials
-
批准号:1738698
-
项目类别:Standard Grant
-
资助金额:$22.21万
-
财政年份:2017
-
负责人:Cheng-Chien Chen
-
依托单位:
海外基金