Extending the Time and Length Scale of Electronic Structure Methods Through Force Matching

通过力匹配扩展电子结构方法的时间和长度范围

• 批准号: 2245371
• 负责人: Feng Wang
• 金额: $ 44.05万
• 依托单位: University of Arkansas
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-01 至 2026-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2245371&HistoricalAwards=false
• 关键词: Extending; Time; Length; Scale; Electronic

WIth support from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry, Professor Feng Wang of the University of Arkansas at Fayetteville is developing a new method to connect forces from quantum mechanics to the understanding chemical properties. While any property, in principle, can be computed with the fundamental equations of quantum mechanics, such computations quickly become too complex to be practical. The new method, adaptive force matching (AFM), maps such first principles calculations to simple mathematical expressions and thus allow macroscopic properties of materials to be computed with a tractable computational cost. Specfic systems to be studied by the Wang research team will involve predictions of solubility, of minerology processes under cryogenic conditions, and of properties of microporous crystals. The research is expected to have long range scientific broader impacts in functional materials, and even potentially drug design and planetary science. Dr. Feng Wang will also train next generation scientists with a collaboration between the departments of chemistry and theatre, where students in chemistry will be mentored by master of fine arts students for engaging presentations of chemistry concepts. Educational videos will be produced as part of this collaboration.Under this award, Professor Feng Wang and his research group are developing methods that will extend the time and length scale of electronic structure calculations to enable predictive simulations of ensemble properties and of slow dynamics. The adaptive force matching method maps potential energy surfaces of electronic structure methods computed in the condensed phase to simple molecular mechanics energy expressions. The advantage of this technique is to enable molecular dynamics simulations at larger length and time scales on a potential energy surface that remains accurate to the reference electronic structure. In the proposed work, further development of AFM will incorporate better regularization of parameters through cross validations and Baysesian inference. A new method to treat polarization is also being developed. The method will be used to predict solubilities of molecular liquids, to study mineralogical processes under cryogenic conditions, and to compute properties of microporous 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.

在化学理论，模型和计算方法计划的支持下，费耶特维尔阿肯色大学阿肯色大学的冯王教授正在开发一种新方法，将从量子力学与了解化学特性的力量联系起来。虽然原则上的任何属性都可以使用量子力学的基本方程来计算，但这种计算迅速变得太复杂而无法实用。新方法（自适应力匹配（AFM））将这些第一原理计算映射到简单的数学表达式，从而允许材料的宏观特性以易处理的计算成本计算。王研究团队将研究的特定系统将涉及溶解度，低温条件下的矿物学过程以及微孔晶体的性质的预测。 预计该研究将在功能材料，甚至潜在的药物设计和行星科学方面具有长期的科学影响。 Feng Wang博士还将通过化学和戏剧部门之间的合作培训下一代科学家，在这里，美术硕士学生将指导化学专业的学生，​​以参与化学概念的演讲。 教育视频将作为这项合作的一部分制作。在此奖项之后，Feng Wang教授及其研究小组正在开发方法，这些方法将延长电子结构计算的时间和长度规模，以实现整体属性和缓慢动态的预测模拟。自适应力匹配方法将在凝结相计算的电子结构方法的势能表面映射到简单分子力学能量表达式。 该技术的优点是在势能表面上以更大的长度和时间尺度启用分子动力学模拟，该势能表面仍然准确地符合参考电子结构。在拟议的工作中，AFM的进一步开发将通过交叉验证和Baysesian推论更好地正规化参数。还开发了一种治疗极化的新方法。该方法将用于预测分子液体的溶解度，在低温条件下研究矿物学过程，并计算微孔晶体的特性。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和广泛影响的评估来通过评估来支持的。