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CAREER: Accurate, Reliable, and Routine First-Principles Prediction of the Structure and Stability of Molecular Crystal Polymorphs

CAREER: Accurate, Reliable, and Routine First-Principles Prediction of the Structure and Stability of Molecular Crystal Polymorphs
职业:对分子晶体多晶型物的结构和稳定性进行准确、可靠、常规的第一性原理预测
批准号:
1945676
负责人:
Robert DiStasio
金额:
$65.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-03-01 至 2025-02-28

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中文摘要
翻译
康奈尔大学的Robert A. DiStasio Jr.教授获得了化学系化学理论、模型和计算方法项目的奖项,他开发的方法能够准确可靠地预测分子晶体的结构和稳定性。分子晶体是一种无处不在的多用途材料,用于替代能源和环境科学,制药和医学,以及技术和工业。对于这些应用至关重要的是,分子晶体通常具有许多可接近的多晶型结构,这些结构在稳定性上几乎相同,但表现出截然不同的物理和化学性质。当用于提高设备性能或在替代能源应用中启用新功能时,这些独特的特性可能非常有益。多态的存在也可能具有破坏性和潜在的灾难性影响,例如,当一种药物意外地转化为未知的(和无活性的)多态时,从而减少了抗病(和可能挽救生命)形式的数量。DiStasio和他的研究小组正在开发精确可靠的方法,利用计算机模拟来预测基于量子和统计力学定律的分子晶体多晶的结构和稳定性。为此,DiStasio正在开发一个计算框架,以解决在新型能源解决方案和药物制剂中使用分子晶体多晶的新机会。DiStasio研究小组还在开发一个交互式分子动力学(MD)包,它允许所有水平的学生(K-12,本科生和研究生)可视化化学中遇到的抽象数学概念,并建立关于观察到的性质与物质微观结构之间复杂相互作用的物理和化学直觉。通过开发和利用结合量子和统计力学、数值分析和高性能计算的最先进的方法,DiStasio和他的研究小组正在创建一个理论和算法框架,该框架利用稀疏性,使生物、化学、物理和材料科学中感兴趣的复杂和大规模凝聚相系统的高精度从头算分子动力学(AIMD)模拟成为可能。该框架同时考虑了电子(包括复杂的交换相关效应)和原子核的量子力学性质,以及现实的实验条件(即有限的温度和压力),因此能够从第一性原理对所有热力学(和动力学)相关的分子晶体多晶的结构和稳定性进行准确、可靠和常规的预测。这些研究工作为增强对复杂多态能量景观的基本理解和基于预测第一性原理的晶体结构预测的常规使用铺平了道路,这两者对于获取分子晶体的巨大和大部分未开发的潜力至关重要。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
Professor Robert A. DiStasio Jr. of Cornell University is supported by an award from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry to develop methods which enable accurate and reliable predictions of the structure and stability of molecular crystals. Molecular crystals are ubiquitous and versatile materials that are used in alternative energy and the environmental sciences, pharmaceuticals and medicine, as well as technology and industry. Of crucial importance to these applications is the fact that molecular crystals often have many accessible polymorphs—alternative structures that are nearly identical in stability yet display drastically different physical and chemical properties. When used to improve device performance or enable novel functions in alternative energy applications, these distinct properties can be very beneficial. The existence of polymorphs can also have devastating and potentially catastrophic effects, e.g., when a pharmaceutical agent unexpectedly converts into an unknown (and inactive) polymorph, and thereby reduces the amount of the disease-fighting (and potentially life-saving) form. DiStasio and his research group are developing accurate and reliable methods which use computer simulations to predict the structures and stabilities of molecular crystal polymorphs based on the laws of quantum and statistical mechanics. In doing so, DiStasio is developing a computational framework that addresses new opportunities to use molecular crystal polymorphs in novel energy solutions and pharmaceutical agents. The DiStasio research group is also developing an interactive molecular dynamics (MD) package which allows students at all levels (K-12, undergraduate, and graduate) to visualize the abstract mathematical concepts encountered in chemistry, and to build physical and chemical intuition regarding the complex interplay between observed properties and the microscopic structure of matter.By developing and utilizing state-of-the-art methods that combine quantum and statistical mechanics, numerical analysis, and high-performance computing, DiStasio and his research group are creating a theoretical and algorithmic framework which exploits sparsity to enable highly accurate ab initio molecular dynamics (AIMD) simulations of complex and large-scale condensed-phase systems of interest throughout biology, chemistry, physics, and materials science. This framework simultaneously accounts for the quantum mechanical nature of the electrons (including sophisticated exchange-correlation effects) and the nuclei, as well as realistic experimental conditions (i.e., finite temperatures and pressures), and therefore enables accurate, reliable, and routine predictions of the structures and stabilities of all thermodynamically (and kinetically) relevant molecular crystal polymorphs from first principles. These research efforts pave the way towards an enhanced fundamental understanding of complex polymorphic energy landscapes and the routine use of predictive first-principles based crystal structure prediction, both of which are crucial to accessing the vast and largely unexplored potential of molecular crystals.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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