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CDS&E: Development of Methods for Molecular Simulation of Enantiomeric Separation and Metal-oxide Formation

CDS

基本信息

批准号：
1954648
负责人：
J. Daniel Gezelter
金额：
$ 48.64万
依托单位：
University of Notre Dame
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
起止时间：
2020-08-01 至 2023-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1954648&HistoricalAwards=false
关键词：
CDS&amp Development Methods Molecular Simulation

项目摘要

Professor J. Daniel Gezelter of the University of Notre Dame is supported by an award from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry to develop novel computer algorithms that model or predict molecular motion. These new methods will predict how molecules that are left- or right-handed versions of each other can be separated with relatively simple and inexpensive liquid flow devices. Gezelter’s lab also models the behavior of metallic surfaces in contact with reactant gases and solvents, particularly when there is a heat or energy imbalance between the two sides of the surface. These topics are of interest in the areas of energy efficiency (involving systems like catalytic converters), materials science (involving metallic nanoparticles), and specifically in the pharmaceutical industry, where important drug molecules often must be separated from their left- or right-handed forms to isolate the useful molecular component from one that is either ineffective or dangerous. In addition, Professor Gezelter is developing a new program for first-year science and engineering students who are either first generation college students or come to college from under-served populations. Some of these students are now conducting research on Notre Dame’s campus (including in Professor Gezelter's research group).Dr. Gezelter and his group are developing theoretical and computational methods for investigating enantiomeric separation, coupled charge and energy transport properties (e.g. thermoelectric properties and electron-phonon effects) and oxide-layer growth at interfaces. Three complementary areas of research are under investigation: methods for predicting and simulating enantiomeric separation in vortex flows, utilizing an overlapping bead model to predict rotation-translation coupling tensors for molecules in fluid flows, methods to include electrical current densities in molecular simulations using reverse non-equilibrium molecular dynamics (RNEMD), and a density readjusting embedded atom method (DR-EAM) for modeling oxide-layer growth on metal surfaces. The applications of these methods include separations of racemic mixtures of pharmaceutical molecules in shear-flow and vortex-flow devices, the growth of metal-oxide layers on functional catalysts at operating conditions, and the thermal conductance measurements on metallic particles that have been ligated and solvated in water solvent after excitation at the plasmon resonance.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.

圣母大学的J.丹尼尔·格泽尔特教授获得了化学系化学理论、模型和计算方法项目的一个奖项的支持，以开发模拟或预测分子运动的新型计算机算法。这些新方法将预测如何用相对简单和便宜的液体流动装置分离彼此的左手或右手分子。 Gezelter的实验室还模拟了金属表面与反应气体和溶剂接触的行为，特别是当表面两侧之间存在热量或能量不平衡时。这些主题在能源效率（涉及催化转化器等系统），材料科学（涉及金属纳米颗粒），特别是在制药行业，其中重要的药物分子通常必须从其左手或右手形式中分离出来，以将有用的分子组分与无效或危险的分子组分分离。此外，Gezelter教授正在为一年级的科学和工程专业学生开发一个新的项目，这些学生要么是第一代大学生，要么来自服务不足的人群。Gezelter博士和他的研究小组正在开发理论和计算方法，用于研究对映体分离、耦合电荷和能量传输特性（例如热电特性和电子-声子效应）以及界面处的氧化层生长。正在调查三个相辅相成的研究领域：用于预测和模拟涡流中对映体分离的方法，利用重叠珠模型预测流体流中分子的旋转-平移耦合张量的方法，使用反向非平衡分子动力学（RNEMD）在分子模拟中包括电流密度的方法，以及用于模拟金属表面上的氧化物层生长的密度再调整嵌入原子方法（DR-EAM）。这些方法的应用包括在剪切流和涡流装置中分离药物分子的外消旋混合物，在操作条件下在功能催化剂上生长金属氧化物层，以及在等离子体共振激发后在水溶剂中连接和溶剂化的金属颗粒的热导率测量。该奖项反映了NSF的法定使命，并被认为值得支持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。