An embedding scheme for constraint-based orbital-optimized excitations in molecular and bulk environments†

IF 2.9 3区 化学 Q3 CHEMISTRY, PHYSICAL
Yannick Lemke, Jörg Kussmann and Christian Ochsenfeld
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引用次数: 0

Abstract

We recently presented a novel approach to variationally determine electronically excited states based on constrained density functional theory calculations. The constraint-based orbital-optimized excited state method (COOX) [Kussmann et al., J. Chem. Theory Comput., 2024, 20, 8461–8473] allows the evaluation of arbitrary electronic excitations and has several advantages compared to other methods like ΔSCF. In this work, we present an embedding scheme for COOX where the constraint potential is drawn from a sub-system calculation. This approach enables the accurate evaluation of specific excited states within complex environments that are difficult to obtain with conventional methods. The validity and range of applicability of the presented method are investigated for first exemplary calculations.

Abstract Image

Abstract Image

分子和体环境中基于约束的轨道优化激励嵌入方案
我们最近提出了一种基于约束密度泛函理论计算的变分确定电子激发态的新方法。基于约束的轨道优化激发态方法[Kussmann et al., J. Chem.]理论第一版。[j] .电子学报,2024,20,8461-8473]允许对任意电子激励进行评估,并且与ΔSCF等其他方法相比具有几个优点。在这项工作中,我们提出了一种COOX的嵌入方案,其中约束势是从子系统计算中提取的。这种方法能够准确地评估复杂环境中的特定激发态,这是传统方法难以获得的。通过首次算例研究了所提方法的有效性和适用范围。
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来源期刊
Physical Chemistry Chemical Physics
Physical Chemistry Chemical Physics 化学-物理:原子、分子和化学物理
CiteScore
5.50
自引率
9.10%
发文量
2675
审稿时长
2.0 months
期刊介绍: Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.
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