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CAREER: Automating Construction of Polarizable, Flexible, Nonreactive Force-Fields for Metal-Organic Frameworks & Applications to Helium and Solar Water Splitting Gas Purificat

职业：自动构建金属有机框架的可极化、柔性、非反应性力场

基本信息

批准号：
1555376
负责人：
Thomas Manz
金额：
$ 40.02万
依托单位：
New Mexico State University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2016
资助国家：
美国
起止时间：
2016-04-15 至 2022-03-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1555376&HistoricalAwards=false
关键词：
CAREER Automating Construction Polarizable Flexible

项目摘要

NONTECHNICAL SUMMARYThis CAREER award supports computational and theoretical research and education in predicting candidate materials for gas separation. Solar water splitting is a renewable energy source that could be used to reduce greenhouse gas emissions. In solar water splitting, sunlight energy is captured by turning water into hydrogen and oxygen gases. Hydrogen is a clean fuel that generates only water when burned. In this project, the PI and his team of student researchers will use computational modeling to predict high performance membrane materials for separating the gaseous products of solar water splitting. The PI's approach may lead to more efficient and lower cost hydrogen producing devices for energy applications.Membrane materials will also be predicted for the application to purify helium from naturally occurring gases. Helium is traditionally purified by liquefying it at extremely cold temperatures, but enormous energy is required to cool to these temperatures. The PI's team will develop computational methods to search a recently published database of metal-organic framework materials to identify molecule sieves having pore sizes and other characteristics suitable for helium purification. They will further develop computational methods to model gas separations in membranes made from these materials. This should reduce energy requirements during helium purification, by allowing part of the gas purification to be performed at moderate temperatures. The computational methods developed in this project will be made publically available in software tools developed by the PI's group.Educational activities are an important part of this project. The PI will train graduate and undergraduate students in computational materials science methods. Graduate students will perform doctoral dissertation research extending the capabilities of computational methods. The PI and graduate students will develop YouTube videos explaining computational materials science at levels appropriate to K to 12 and undergraduate students and the general public. They will also prepare training modules to be disseminated through Nanohub.org and that explain computational materials science techniques to graduate students and professionals. The PI and graduate students will perform outreach to middle and high school students by being science fair judges. Students from under-represented groups will be involved in the project. TECHNICAL SUMMARYThis CAREER award supports computational and theoretical research and education in predicting candidate materials for gas separation. The PI and students will research strategies to automatically parameterize flexible, polarizable force-fields from quantum chemistry calculations. These force-fields will be used in classical molecular dynamics and Monte Carlo simulations of metal-organic frameworks to compute gas diffusion constants and adsorption isotherms. A database of experimentally known metal-organic framework crystal structures will be screened to identify metal-organic framework-based materials suitable for purifying (a) helium from naturally occurring gas sources and (b) hydrogen gas from solar water splitting. Cryogenic distillation is currently the primary helium purification method. Using helium-selective membranes instead for all or portions of this purification could dramatically reduce energy requirements. Solar water splitting is an environmentally friendly and renewable hydrogen gas source. Wireless solar water splitting uses particles immersed in liquid to cogenerate a hydrogen and oxygen gas mixture with trace water vapor. Wireless solar water splitting could offer higher gas generation rates per volume than wired solar water splitting containing distinct anode and cathode compartments. This project will enable more widespread use of wireless solar water splitting (and wired solar water splitting with small anode-cathode gap distance) by identifying suitable metal-oxide framework-based materials for hydrogen-oxygen-water gas separations. Because constructing mechanically robust membranes from pure metal-oxide framework crystals is difficult, the PI will aim to predict easier-to-fabricate mixed matrix membranes containing metal-oxide framework crystals embedded in mechanically robust polymers. Prior metal-oxide framework studies showed framework flexibility that sometimes impacts gas diffusion constants by orders of magnitude. The key scientific challenge is to develop computationally efficient, automated methods to construct accurate flexible force-fields. To achieve this, the PI's research team will combine (1) the Density Derived Electrostatic and Chemical method for computing net atomic charges and other atomic properties with (2) a modification of Tkatchenko-Scheffler self-consistent dispersion screening to compute polarizabilities and dispersion coefficients with (3) a modification of the quick force-field (QuickFF) method for computing flexibility parameters. By computing system-specific force-field parameters, this approach should achieve higher accuracy than generic force-fields. The computational methods developed in this project will be made publically available in software tools developed by the PI's group.Educational activities are an important part of this project. The PI will train graduate and undergraduate students in computational materials science methods. Graduate students will perform doctoral dissertation research extending the capabilities of computational methods. The PI and graduate students will develop YouTube videos explaining computational materials science at levels appropriate to K to 12 and undergraduate students and the general public. They will also prepare training modules to be disseminated through Nanohub.org and that explain computational materials science techniques to graduate students and professionals. The PI and graduate students will perform outreach to middle and high school students by being science fair judges. Students from under-represented groups will be involved in the project.