New Numerical Solutions for Density Functional Theory

密度泛函理论的新数值解

• 批准号: 7159465
• 负责人: JING KONG
• 金额: $ 32.75万
• 依托单位: Q-CHEM, INC.
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-03-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7159465
• 关键词: bacteriorhodopsins; bioenergetics; biophysics; computer simulation; data collection methodology /evaluation; density; mathematical model; model design /development; molecular dynamics; quantum chemistry; statistics /biometry

DESCRIPTION (provided by applicant): First principle (ab initio) quantum chemistry methods are widely used for computational studies in biology, chemistry and material science. Among the various quantum chemistry models, density functional theory (DFT) offers a good balance between computational cost and accuracy and accordingly is the most widely used method in many scientific fields, including biological research. However, despite the remarkable advances in DFT in the past decade, the application of DFT to treat large biological systems or molecular dynamics is still limited by computational cost. Accordingly, the goal of the research proposed here is to increase the efficiency of DFT calculations by several fold through the implementation of novel algorithms. There are two major time-consuming parts in a DFT calculation, namely computation of the Coulomb and the exchange-correlation (XC) contributions. In the Phase I of this project, we implemented the Fourier Transform Coulomb method for the evaluation of the Coulomb contribution, and developed a new algorithm called multiresolution XC (mrXC), for the evaluation of XC contribution to the DFT energy with local functionals. The results show that FTC accelerates Coulomb calculation by up to a factor of 4.5 over the most efficient Coulomb algorithms. The mrXC method speeds up the calculation of XC contribution by as much as a factor of 5. In the Phase II of the project, we will develop and implement FTC and mrXC for the most widely used components of DFT calculations, including energy and gradients with respect to nuclear motions for both ground and excited states. Efforts will also be made to further improve the efficiency. Formulism will also be developed at the level of general-gradient approximation, the mostly widely used type of DFT functional. In order to demonstrate the utility of DFT algorithms developed here, we will carry out a state-of-the-art computational study of the mechanism of light-induced structural change in bacteriorhodopsin. These improvements will significantly increase Q-Chem users? productivity and greatly extend the complexity of molecular systems that can be studied using DFT. Furthermore, it will bring DFT much closer to our goal of being able to replace the less accurate but computationally less demanding models currently used today in molecular dynamics or Monte Carlo simulations of proteins and other large molecular systems. This project aims to improve the efficiency of the density-functional theory (DFT) calculations. DFT is at the core of molecular modeling and is applied widely in biological research/development and in drug discovery. The improved DFT will significantly increase researchers' productivity and extend its application scope.

描述（由申请人提供）：第一原理（从头算）量子化学方法广泛用于生物学，化学和材料科学领域的计算研究。在各种量子化学模型中，密度功能理论（DFT）在计算成本和准确性之间提供了良好的平衡，因此，包括生物学研究在内的许多科学领域中最广泛使用的方法。但是，尽管在过去十年中DFT取得了显着进步，但DFT在处理大型生物系统或分子动力学方面的应用仍受到计算成本的限制。因此，这里提出的研究的目的是通过实施新算法来提高DFT计算的效率。 DFT计算中有两个主要耗时的部分，即库仑的计算和交换 - 相关（XC）贡献。在该项目的第一阶段，我们实施了傅立叶变换库仑方法来评估库仑的贡献，并开发了一种称为多解决XC（MRXC）的新算法，以评估XC使用本地功能对DFT贡献的XC贡献。结果表明，在最有效的库仑算法上，FTC可以加速库仑的计算4.5倍。 MRXC方法将XC贡献的计算加快了多达5倍。在项目的第二阶段，我们将开发和实施DFT计算的最广泛使用的组件，包括对于地面和激发状态的核运动，包括能量和梯度。还将努力进一步提高效率。配方主义还将在通用梯度近似的水平上开发，这是大多数广泛使用的DFT功能。为了证明此处开发的DFT算法的实用性，我们将对细菌紫红素的光诱导结构变化机理进行最新的计算研究。这些改进会大大增加Q Chem用户吗？生产力并大大扩展了可以使用DFT研究的分子系统的复杂性。此外，它将使DFT更接近我们的目标，即能够替代当今当今分子动力学或蒙特卡洛模拟蛋白质和其他大分子系统的准确但计算较少的模型。该项目旨在提高密度功能理论（DFT）计算的效率。 DFT是分子建模的核心，广泛应用于生物学研究/发育和药物发现。改进的DFT将显着提高研究人员的生产率并扩大其应用范围。