密度泛函理论
缩放比例
晶体结构预测
统计物理学
色散(光学)
晶体结构
标杆管理
近似误差
结晶学
Crystal(编程语言)
化学
分布(数学)
计算化学
物理
数学
计算机科学
算法
量子力学
数学分析
业务
营销
程序设计语言
几何学
作者
Yuriy A. Abramov,Bochen Li,Chao Chang,Qun Zeng,Geng Sun,Gianpaolo Gobbo
标识
DOI:10.1021/acs.cgd.1c00527
摘要
The modern crystal structure prediction (CSP) technologies have proven to be accurate enough to provide a valuable support for a stable form selection in the pharmaceutical industry. We demonstrate that successful applications of the CSP predictions, in part, may be accounted for by favorable uncertainty distribution with the smallest absolute errors in the low relative crystal energy region. Such behavior is dictated by the lowest contribution of the systematic scaling error of dispersion-corrected density functional theory (DFT-D) approaches in this region. These considerations are validated by benchmarking studies of selected popular DFT-D approaches relative to post-Hartree–Fock (post-HF) calculations for representative molecular dimeric configurations in the virtual crystalline states of four pharmaceutical compounds. In addition, discussed are uncertainty distributions of DFT-D predictions of relative energies of eight ROY and five oxalyl dihydrazide (ODH) polymorphs relative to MP2D/HMBI and CCSD(T)/HMBI predictions, respectively.
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