Suppr超能文献

开壳层有机分子和过渡金属分子的相似性变换运动方程(STEOM)评估

Assessment of the similarity-transformed equation of motion (STEOM) for open-shell organic and transition metal molecules.

作者信息

Casanova-Páez Marcos, Neese Frank

机构信息

Max-Planck-Institut für Kohlenforschung, Kaiser-Wilhelm-Platz 1, 45470 Mülheim an der Ruhr, Germany.

出版信息

J Chem Phys. 2024 Oct 14;161(14). doi: 10.1063/5.0234225.

Abstract

This study benchmarks the newly re-implemented single-reference excited-state methods, IP-EOM-CCSD, EA-EOM-CCSD, and STEOM-CCSD, in ORCA6.0, with a focus on open-shell systems. We compare STEOM against EOM-CCSD, CC3, and CCSDT across a range of systems, including small organic radicals, hydrated transition metal (TM) ions, and TM diatomic systems with both closed and open-shell configurations. For organic radicals, STEOM and EOM-CCSD show comparable performance, aligning closely with CC3 and CCSDT results. In the case of hydrated TM ions, IP-EOM closely matches DLPNO-CCSD results, while deviations from DLPNO-CCSD(T) are consistent. For open-shell TM systems, IP-EOM exhibits a blueshift relative to both the DLPNO-CCSD methods, while EA-EOM-CCSD shows better agreement. When comparing STEOM and CC3 to CCSDT, STEOM shows slightly larger deviations in closed-shell systems but shows excellent agreement in open-shell systems. Computational efficiency is also assessed, revealing a significant speedup in ORCA 6.0 compared to ORCA 5.0, with optimizations improving computation times. This study provides valuable insights into the performance and efficiency of STEOM in various chemical environments, highlighting its strengths and limitations.

摘要

本研究对ORCA6.0中新重新实现的单参考激发态方法IP-EOM-CCSD、EA-EOM-CCSD和STEOM-CCSD进行了基准测试,重点关注开壳层体系。我们在一系列体系中比较了STEOM与EOM-CCSD、CC3和CCSDT,这些体系包括小有机自由基、水合过渡金属(TM)离子以及具有闭壳层和开壳层构型的TM双原子体系。对于有机自由基,STEOM和EOM-CCSD表现出可比的性能,与CC3和CCSDT的结果紧密吻合。对于水合TM离子,IP-EOM与DLPNO-CCSD的结果非常匹配,而与DLPNO-CCSD(T)的偏差是一致的。对于开壳层TM体系,IP-EOM相对于DLPNO-CCSD方法均表现出蓝移,而EA-EOM-CCSD显示出更好的一致性。在将STEOM和CC3与CCSDT进行比较时,STEOM在闭壳层体系中显示出稍大的偏差,但在开壳层体系中显示出极佳的一致性。还评估了计算效率,结果表明与ORCA 5.0相比,ORCA 6.0有显著加速,优化提高了计算时间。本研究为STEOM在各种化学环境中的性能和效率提供了有价值的见解,突出了其优势和局限性。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验