CAREER: Organic Materials Discovery with the Aid of Digital Crystallography
CAREER: Organic Materials Discovery with the Aid of Digital Crystallography
批准号:
2410178
负责人:
Qiang Zhu
金额:
$53.16万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2024
资助国家:
美国
项目状态:
未结题
起止时间:
2024-04-01 至 2027-08-31
中文摘要
该职业奖支持理论和计算研究以及教育活动,以促进对有机材料的理解。目前,开发具有目标物理性质的新型有机材料的系统预测模型在很大程度上是缺失的,因为分子可以在三维空间中以多种方式包装。本研究旨在开发一种新的计算方案,使基于现代晶体学的有机材料的更有效的发现。为了实现这一目标,PI将首先将复杂的晶体学数据数字化为保留有关分子堆积和晶体对称的关键信息的低维表示。其次,将开发一个计算管道,通过不同层次的理论来模拟有机材料。最后,新基础设施的力量将通过对具有优越机械和铁电性能的有机材料进行计算筛选来验证,这些有机材料可以在现代技术中找到潜在的应用。CAREER奖还为以促进开源软件开发为中心的教育和推广活动提供支持。具体目标包括:(1)培养计算物理学的本科生和研究生;(ii)为K-12学生举办科学计算和Python编程的夏令营/冬令营;(三)组织研讨会,学习晶体学和材料建模中的开源代码。该奖项旨在开发数字晶体学的计算管道,以加速小分子有机材料的发现,用于各种应用。如今,科学家们正在寻求通过使用化学和结构操作来改善有机材料的功能,设计空间可以大到天文数字。为了开发新的有机固体,晶体工程师求助于预测指南。然而,与无机晶体相比,由于复杂的分子堆积,从计算机模拟中系统地发现新的有机晶体仍然具有挑战性。在这个项目中,目标是通过对复杂晶体包装及其对物理性质的影响进行数据密集型研究,开发一种设计有机材料的新方法。具体而言,PI将基于现代数学理论引入有机晶体数据的数字化描述,并将其实现到开源代码PyXtal中。将开发一个计算管道,以允许从分子力学、机器学习到量子力学等不同层次的高通量材料建模。在此基础上,将进行具有优异机械强度和铁电性能的有机材料的计算筛选。这个CAREER项目的教育部分将以促进开源软件开发为中心。具体目标包括:(1)培养计算物理学的本科生和研究生;(ii)为K-12学生举办科学计算和Python编程的夏令营/冬令营;(三)组织研讨会,学习晶体学和材料建模中的开源代码。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
NONTECHNICAL SUMMARYThis CAREER award supports theoretical and computational research and educational activities to advance the understanding of organic materials. Currently, systematic predictive models for developing new organic materials with targeted physical properties are largely missing, due to the fact that molecules can be packed in enormous number of ways in the three dimensional space. This research aims to develop a new computational scheme that allows more efficient discovery of organic materials based on modern crystallography. To achieve this objective, the PI will first digitize the complex crystallographic data into low-dimensional representations that retain the key information about the molecular packing and crystal symmetry. Second, a computational pipeline will be developed to model the organic materials though different levels of theory. Finally, the power of the new infrastructure will be validated by conducting computational screening of organic materials with superior mechanical and ferroelectric properties that can find potential applications in modern technologies.This CAREER award also provides support for education and outreach activities that are centered on promoting open-source software development. Specific objectives include (i) training undergraduate and graduate students in computational physics; (ii) holding the summer/winter camps in scientific computing and Python programming for K-12 students; and (iii) organizing workshops for learning about open-source codes in crystallography and materials modeling.TECHNICAL SUMMARYThis CAREER award aims to develop a computational pipeline for digital crystallography that can speed up the discovery of small molecule organic materials for various applications. Nowadays, scientists are seeking to improve the functionalities of organic materials by using chemical and structural manipulations with a design space that can be astronomically large. To develop new organic solids, crystal engineers resort to predictive guidelines. However, systematically discovering new organic crystals from computer simulations remains challenging due to the complex molecular packing as compared to the inorganic counterpart. In this project, the goal is to develop a new approach to design organic materials by performing a data-intensive investigation of complex crystal packing and its impacts on the physical properties. Specifically, the PI will introduce a digitized description for organic crystal data based on modern mathematical theory and implement them into the open-source code PyXtal. A computational pipeline will be developed to allow high-throughput materials modeling at different levels from molecular mechanics, machine learning to quantum mechanics. Based on this infrastructure, computational screenings of organic materials with superior mechanical strength and ferroelectric properties will be conducted. The educational component of this CAREER project will be centered on promoting open-source software development. Specific objectives include (i) training undergraduate and graduate students in computational physics; (ii) holding the summer/winter camps in scientific computing and Python programming for K-12 students; and (iii) organizing workshops for learning about open-source codes in crystallography and materials modeling.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.
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CAREER: Organic Materials Discovery with the Aid of Digital Crystallography
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批准号:2142570
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项目类别:Continuing Grant
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资助金额:$53.16万
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财政年份:2022
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负责人:Qiang Zhu
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依托单位:
Collaborative Research: Atomic Level Structural Dynamics in Catalysts
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批准号:1940272
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项目类别:Continuing Grant
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资助金额:$32.5万
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财政年份:2019
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负责人:Qiang Zhu
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依托单位:
III: Small: Collaborative Research: Supporting Efficient Discrete Box Queries for Sequence Analysis on Large Scale Genome Databases
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批准号:1320078
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项目类别:Standard Grant
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资助金额:$22.23万
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财政年份:2013
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负责人:Qiang Zhu
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依托单位:
Wave-Structure Interaction of Floating Wind Turbines - A Combined Numerical and Experimental Investigation
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批准号:0967023
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项目类别:Standard Grant
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资助金额:$32.41万
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财政年份:2010
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负责人:Qiang Zhu
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依托单位:
CAREER: Performance of Skeleton-Reinforced Biomembranes in Locomotion
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批准号:0844857
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项目类别:Standard Grant
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资助金额:$44.91万
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财政年份:2009
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负责人:Qiang Zhu
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依托单位:
Collaborative Research: Supporting Efficient Similarity Searches for Multidimensional Non-ordered Discrete Data Spaces
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批准号:0414594
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项目类别:Standard Grant
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资助金额:$0.0万
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财政年份:2005
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负责人:Qiang Zhu
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依托单位:
Establishing Dynamic Cost Models for Multidatabase Systems
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批准号:9811980
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项目类别:Continuing Grant
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资助金额:$17.66万
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财政年份:1998
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负责人:Qiang Zhu
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依托单位:
海外基金