基本信息
浏览量:21
职业迁徙
个人简介
My group's research is centered on computational materials science, and specifically first-principles quantum mechanical simulation tools. These computational tools have advanced to the point now where materials may be "synthesized virtually", with their properties predicted on a computer before ever being synthesized in a laboratory. These tools also open the field of "materials informatics" where we can use machine learning tools to explore materials datasets and discover new materials. In this work, we are working towards a goal of being able to suggest new materials in the same way that Netflix and Amazon can recommend movies or books.
While the types of materials problems amenable to these tools is extremely wide, we are currently interested in a variety of materials problems with a focus on materials for alternative energies and sustainability (hydrogen, batteries, light-weight metals, fuel cells, thermoelectrics). Current topics of interest include the discovery of novel hydrogen storage materials, phase transformations in metallic and ceramic alloys, microstructural evolution during aging, and the theoretical prediction of new materials.
Another key research interest involves methodologies for linking atomistic and microstructural length scales. Though first-principles methods are powerful, they are also computationally quite demanding. Current state-of-the-art resources limits the system sizes that one can study to around a few hundred atoms. We have worked on methods that couple first-principles with Monte Carlo methods (capable of simulating millions of atoms), phase-field microstructural models, and CALPHAD calculation of phase diagram tools. These types of hybrid methods are yielding truly predictive models of microstructural evolution and mechanical properties in novel materials.
While the types of materials problems amenable to these tools is extremely wide, we are currently interested in a variety of materials problems with a focus on materials for alternative energies and sustainability (hydrogen, batteries, light-weight metals, fuel cells, thermoelectrics). Current topics of interest include the discovery of novel hydrogen storage materials, phase transformations in metallic and ceramic alloys, microstructural evolution during aging, and the theoretical prediction of new materials.
Another key research interest involves methodologies for linking atomistic and microstructural length scales. Though first-principles methods are powerful, they are also computationally quite demanding. Current state-of-the-art resources limits the system sizes that one can study to around a few hundred atoms. We have worked on methods that couple first-principles with Monte Carlo methods (capable of simulating millions of atoms), phase-field microstructural models, and CALPHAD calculation of phase diagram tools. These types of hybrid methods are yielding truly predictive models of microstructural evolution and mechanical properties in novel materials.
研究兴趣
论文共 817 篇作者统计合作学者相似作者
按年份排序按引用量排序主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
Journal of the American Chemical Society (2024)
Physical Review Materialsno. 5 (2024)
arxiv(2024)
引用0浏览0引用
0
0
Nature synthesis (2024)
Advanced functional materials (2024)
CHEMISTRY OF MATERIALS (2024)
加载更多
作者统计
#Papers: 816
#Citation: 50280
H-Index: 107
G-Index: 202
Sociability: 7
Diversity: 3
Activity: 480
合作学者
合作机构
D-Core
- 合作者
- 学生
- 导师
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn