Ab initio molecular dynamics with quantum nuclear effects: potential surfaces and gradients from on-the-fly fragment based electronic structure methods

具有量子核效应的从头算分子动力学：基于电子结构方法的动态片段的势表面和梯度

• 批准号: 1665336
• 负责人: Srinivasan Iyengar
• 金额: $ 43.5万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1665336&HistoricalAwards=false
• 关键词: Ab; initio; molecular; dynamics; quantum

Srinivasan S. Iyengar of Indiana University is supported by an award from the Chemical Theory, Models and Computational Methods program. Many problems at the forefront of energy, environmental and biological research demand the quantum mechanical treatment of electrons and nuclei. But the detailed quantum description of such problems is much too complex even in today?s high performance computing environment. This is because the computational complexity in these problems grows exponentially with system size, which makes them intractable. Iyengar and his research group are developing new computational methods to address these issues. These methods are poised to have major impact on the study of a wide class of problems in biological enzymes, atmospheric chemistry and materials science including study of hydrogen transfer in polymer electrolyte fuel cells. The methods are at the forefront of modern computational quantum chemistry and chemical physics. Hence students in the PI's group have the opportunity to learn and develop new theoretical methods and apply these methods to important practical problems. The results, involving computer codes as well as novel scientific ideas are widely disseminated to the scientific community. Specifically, the computer programs when completed will appear as part of the NSF-funded SEAGrid science gateway. In addition, the PI continues to initiate participation and mentoring of freshman by chemistry faculty. The PI further envisions homogenizing the chemistry curriculum by developing student directed web-based learning methods to connect the sub-disciplines of chemistry and achieve a continuous rather than discrete education of undergraduates. Computing accurate classical trajectories and potential surfaces in agreement with high levels of electronic structure for complex chemical systems is a major challenge in computational chemistry and chemical physics. Iyengar and co-workers are making contributions in this area, including the development of on-the-fly molecular dynamics methods that allow accurate treatment of electronic structure at the MP2 and Coupled Cluster level, using methods that scale like DFT. Furthermore, they are computing potential surfaces for quantum-mechanical nuclear degrees of freedom that are in good agreement with higher levels of electronic structure methods such as MP2 and Coupled Cluster, at computational costs comparable to DFT. While ab initio molecular dynamics (AIMD) methods are appealing because they do not need an a priori fitted potential surface, this advantage is normally precluded since on-the-fly evaluation of potential and forces is a strong computational constraint. Hence most implementations of AIMD are limited to density functional theoretic (DFT) treatment of electronic structure. The goal of this project is to alleviate this computational constraint and make AIMD more routinely and broadly applicable using efficient methods that allow higher levels of electronic structure, post-Hartree-Fock accuracy. Specifically, the proposal deals with (a) the development of new methods to efficiently compute on-the-fly electronic structure for AIMD and Car-Parrinello-like methods in agreement with MP2, Coupled Cluster and other post-Hartree-Fock methods, (b) the computation of potential surfaces using these approaches to facilitate on-the-fly quantum dynamics. Chemical problems to be studied include, (i) the study conformation dynamics and vibrational properties of protonated water clusters, and (ii) the determination of accurate potential surfaces for reaction paths and quantum wave packet dynamics studies on hydrogen transfer reactions involved in the oxidation pathways of hydroxyl-isoprene, which is a biogenic volatile organic compound.

印第安纳大学的 Srinivasan S. Iyengar 获得了化学理论、模型和计算方法项目的奖项支持。 能源、环境和生物研究前沿的许多问题需要对电子和原子核进行量子力学处理。但即使在当今的高性能计算环境中，此类问题的详细量子描述也过于复杂。这是因为这些问题的计算复杂性随着系统规模的增加呈指数增长，这使得它们变得棘手。 艾扬格和他的研究小组正在开发新的计算方法来解决这些问题。这些方法将对生物酶、大气化学和材料科学中的一系列问题的研究产生重大影响，包括聚合物电解质燃料电池中氢转移的研究。 这些方法处于现代计算量子化学和化学物理学的前沿。因此，PI小组的学生有机会学习和发展新的理论方法，并将这些方法应用于重要的实际问题。涉及计算机代码以及新颖的科学思想的结果被广泛传播给科学界。具体来说，计算机程序完成后将作为 NSF 资助的 SEAGrid 科学网关的一部分出现。此外，PI继续发起化学教师对新生的参与和指导。 PI 进一步设想通过开发学生导向的基于网络的学习方法来连接化学子学科，实现化学课程的同质化，并实现本科生的连续而不是离散的教育。计算与复杂化学系统的高水平电子结构一致的精确经典轨迹和势表面是计算化学和化学物理中的主要挑战。 艾扬格和他的同事正在这一领域做出贡献，包括开发动态分子动力学方法，允许使用 DFT 等缩放方法精确处理 MP2 和耦合簇级别的电子结构。此外，他们正在计算量子力学核自由度的潜在表面，这与 MP2 和耦合簇等更高级别的电子结构方法非常一致，计算成本与 DFT 相当。虽然从头分子动力学 (AIMD) 方法很有吸引力，因为它们不需要先验拟合的势表面，但这种优势通常被排除，因为势和力的动态评估是一个强大的计算约束。因此，AIMD 的大多数实现仅限于电子结构的密度泛函理论 (DFT) 处理。 该项目的目标是减轻这种计算限制，并使用允许更高水平的电子结构和后 Hartree-Fock 精度的有效方法使 AIMD 更加常规和广泛适用。具体来说，该提案涉及 (a) 开发新方法，以有效计算 AIMD 和类 Car-Parrinello 方法的动态电子结构，与 MP2、耦合簇和其他后 Hartree-Fock 方法一致，（ b）使用这些方法计算势表面以促进动态量子动力学。要研究的化学问题包括：（i）研究质子化水簇的构象动力学和振动性质，以及（ii）确定反应路径的精确势面以及氧化途径中涉及的氢转移反应的量子波包动力学研究羟基异戊二烯，这是一种生物挥发性有机化合物。

项目成果

Embedded, graph‐theoretically defined many‐body approximations for wavefunction‐in‐DFT and DFT‐in‐DFT : Applications to gas‐ and condensed‐phase ab initio molecular dynamics, and potential surfaces for quantum nuclear effects

嵌入的图形——理论上定义了波函数的多体近似——DFT 和 DFT——DFT：在气体和凝聚相从头开始分子动力学中的应用，以及量子核的势表面

• DOI: 10.1002/qua.26244
• 发表时间: 2020-05
• 期刊: International Journal of Quantum Chemistry
• 影响因子: 2.2
• 作者: Ricard, Timothy C.;Kumar, Anup;Iyengar, Srinivasan S.
• 通讯作者: Iyengar, Srinivasan S.

Proton relays in anomalous carbocations dictate spectroscopy, stability, and mechanisms: case studies on C 2 H 5 + and C 3 H 3 +

异常碳阳离子中的质子中继决定了光谱、稳定性和机制：C 2 H 5 和 C 3 H 3 的案例研究

• DOI: 10.1039/c7cp05577c
• 发表时间: 2017-01
• 期刊: Phys. Chem. Chem. Phys.
• 作者: Sager, LeeAnn M.;Iyengar, Srinivasan S.
• 通讯作者: Iyengar, Srinivasan S.

Efficient and Accurate Approach To Estimate Hybrid Functional and Large Basis-Set Contributions to Condensed-Phase Systems and Molecule–Surface Interactions

估计混合函数和大基组对凝聚相系统和分子表面相互作用的贡献的高效和准确的方法

• DOI: 10.1021/acs.jctc.9b01089
• 发表时间: 2020-08
• 期刊: Journal of Chemical Theory and Computation
• 影响因子: 5.5
• 作者: Ricard, Timothy C.;Iyengar, Srinivasan S.
• 通讯作者: Iyengar, Srinivasan S.

Adaptive Dimensional Decoupling for Compression of Quantum Nuclear Wave Functions and Efficient Potential Energy Surface Representations through Tensor Network Decomposition

通过张量网络分解进行量子核波函数压缩和有效势能面表示的自适应维度解耦

• DOI: 10.1021/acs.jctc.8b01113
• 发表时间: 2019-04
• 期刊: Journal of Chemical Theory and Computation
• 影响因子: 5.5
• 作者: DeGregorio, Nicole;Iyengar, Srinivasan S.
• 通讯作者: Iyengar, Srinivasan S.

Weighted-Graph-Theoretic Methods for Many-Body Corrections within ONIOM: Smooth AIMD and the Role of High-Order Many-Body Terms

ONIOM 内多体校正的加权图论方法：平滑 AIMD 和高阶多体项的作用

• DOI: 10.1021/acs.jctc.0c01287
• 发表时间: 2021-05
• 期刊: Journal of Chemical Theory and Computation
• 影响因子: 5.5
• 作者: Zhang, Juncheng Harry;Ricard, Timothy C.;Haycraft, Cody;Iyengar, Srinivasan S.
• 通讯作者: Iyengar, Srinivasan S.