已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整的填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

GFN2-xTB—An Accurate and Broadly Parametrized Self-Consistent Tight-Binding Quantum Chemical Method with Multipole Electrostatics and Density-Dependent Dispersion Contributions

多极展开 紧密结合 偶极子 统计物理学 静电学 物理 各向异性 计算物理学 化学 计算化学 分子物理学 电子结构 量子力学
作者
Christoph Bannwarth,Sebastian Ehlert,Stefan Grimme
出处
期刊:Journal of Chemical Theory and Computation [American Chemical Society]
卷期号:15 (3): 1652-1671 被引量:2762
标识
DOI:10.1021/acs.jctc.8b01176
摘要

An extended semiempirical tight-binding model is presented, which is primarily designed for the fast calculation of structures and noncovalent interaction energies for molecular systems with roughly 1000 atoms. The essential novelty in this so-called GFN2-xTB method is the inclusion of anisotropic second order density fluctuation effects via short-range damped interactions of cumulative atomic multipole moments. Without noticeable increase in the computational demands, this results in a less empirical and overall more physically sound method, which does not require any classical halogen or hydrogen bonding corrections and which relies solely on global and element-specific parameters (available up to radon, Z = 86). Moreover, the atomic partial charge dependent D4 London dispersion model is incorporated self-consistently, which can be naturally obtained in a tight-binding picture from second order density fluctuations. Fully analytical and numerically precise gradients (nuclear forces) are implemented. The accuracy of the method is benchmarked for a wide variety of systems and compared with other semiempirical methods. Along with excellent performance for the "target" properties, we also find lower errors for "off-target" properties such as barrier heights and molecular dipole moments. High computational efficiency along with the improved physics compared to its precursor GFN-xTB makes this method well-suited to explore the conformational space of molecular systems. Significant improvements are furthermore observed for various benchmark sets, which are prototypical for biomolecular systems in aqueous solution.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
fuyoushengwu完成签到,获得积分10
1秒前
拾柒发布了新的文献求助10
1秒前
白白发布了新的文献求助10
2秒前
4秒前
4秒前
4秒前
6秒前
大男发布了新的文献求助10
7秒前
小牙签哈哈哈完成签到,获得积分10
7秒前
疯尤金给疯尤金的求助进行了留言
7秒前
英姑应助小付采纳,获得10
7秒前
科研通AI5应助longtengfei采纳,获得10
7秒前
干破天完成签到 ,获得积分10
8秒前
Wmhuahuaood完成签到,获得积分20
8秒前
cq220发布了新的文献求助10
10秒前
fuyoushengwu发布了新的文献求助10
10秒前
10秒前
彭于晏应助阿芙乐尔采纳,获得10
11秒前
14秒前
科研通AI2S应助研友_Z6Qrbn采纳,获得10
16秒前
16秒前
YMkaiye发布了新的文献求助10
18秒前
19秒前
激动的猫咪完成签到,获得积分10
20秒前
20秒前
大气建辉完成签到 ,获得积分10
21秒前
打打应助pp采纳,获得10
21秒前
博ge完成签到 ,获得积分10
21秒前
狼与麦芽糖色完成签到,获得积分20
21秒前
21秒前
小付发布了新的文献求助10
22秒前
Wmhuahuaood发布了新的文献求助10
22秒前
在水一方应助拾柒采纳,获得10
23秒前
23秒前
CSY应助SherlockLiu采纳,获得10
24秒前
轻松的冥王星完成签到,获得积分10
26秒前
wkwkkwk发布了新的文献求助10
30秒前
30秒前
坚强的雁蓉完成签到,获得积分10
31秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Kelsen’s Legacy: Legal Normativity, International Law and Democracy 1000
Interest Rate Modeling. Volume 3: Products and Risk Management 600
Interest Rate Modeling. Volume 2: Term Structure Models 600
Dynamika przenośników łańcuchowych 600
The King's Magnates: A Study of the Highest Officials of the Neo-Assyrian Empire 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3538747
求助须知:如何正确求助?哪些是违规求助? 3116472
关于积分的说明 9325379
捐赠科研通 2814343
什么是DOI,文献DOI怎么找? 1546605
邀请新用户注册赠送积分活动 720644
科研通“疑难数据库(出版商)”最低求助积分说明 712109