利用快速多极法提高静电嵌入效率

IF 3.4 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY
Pauline Colinet, Frank Neese, Benjamin Helmich-Paris
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引用次数: 0

摘要

本文报道了快速多极子方法对ORCA中嵌入簇模型(ECM)计算效率的提高。我们的实现是基于最先进的算法,并重新审视某些方面,如有效和准确地处理原子轨道壳对的范围。这使我们能够以我们认为简单有效的方式分解近场和远场项。这项工作的主要结果是使静电势积分的计算速度加快了至少一个数量级,最多两个数量级,同时保持了优异的精度(总是优于1千卡/摩尔的化学精度)。此外,该实现具有足够的通用性,可以通过QM/MM方法用于分子系统。这些代码已经完全并行化,可以在ORCA 6.0中使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Improving the Efficiency of Electrostatic Embedding Using the Fast Multipole Method

Improving the Efficiency of Electrostatic Embedding Using the Fast Multipole Method

Improving the Efficiency of Electrostatic Embedding Using the Fast Multipole Method

This paper reports the improvement in the efficiency of embedded-cluster model (ECM) calculations in ORCA thanks to the implementation of the fast multipole method. Our implementation is based on state-of-the-art algorithms and revisits certain aspects, such as efficiently and accurately handling the extent of atomic orbital shell pairs. This enables us to decompose near-field and far-field terms in what we believe is a simple and effective manner. The main result of this work is an acceleration of the evaluation of electrostatic potential integrals by at least one order of magnitude, and up to two orders of magnitude, while maintaining excellent accuracy (always better than the chemical accuracy of 1 kcal/mol). Moreover, the implementation is versatile enough to be used with molecular systems through QM/MM approaches. The code has been fully parallelized and is available in ORCA 6.0.

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来源期刊
CiteScore
6.60
自引率
3.30%
发文量
247
审稿时长
1.7 months
期刊介绍: This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.
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