Analytical excited state gradients for time-dependent density functional theory plus tight binding (TDDFT + TB)

Author:

Havenridge Shana1ORCID,Rüger Robert2ORCID,Aikens Christine M.1ORCID

Affiliation:

1. Department of Chemistry, Kansas State University 1 , Manhattan, Kansas 66502, USA

2. Software for Chemistry & Materials BV 2 , De Boelelaan 1083, 1081 HV Amsterdam, The Netherlands

Abstract

Understanding photoluminescent mechanisms has become essential for photocatalytic, biological, and electronic applications. Unfortunately, analyzing excited state potential energy surfaces (PESs) in large systems is computationally expensive, and hence limited with electronic structure methods such as time-dependent density functional theory (TDDFT). Inspired by the sTDDFT and sTDA methods, time-dependent density functional theory plus tight binding (TDDFT + TB) has been shown to reproduce linear response TDDFT results much faster than TDDFT, particularly in large nanoparticles. For photochemical processes, however, methods must go beyond the calculation of excitation energies. Herein, this work outlines an analytical approach to obtain the derivative of the vertical excitation energy in TDDFT + TB for more efficient excited state PES exploration. The gradient derivation is based on the Z vector method, which utilizes an auxiliary Lagrangian to characterize the excitation energy. The gradient is obtained when the derivatives of the Fock matrix, the coupling matrix, and the overlap matrix are all plugged into the auxiliary Lagrangian, and the Lagrange multipliers are solved. This article outlines the derivation of the analytical gradient, discusses the implementation in Amsterdam Modeling Suite, and provides proof of concept by analyzing the emission energy and optimized excited state geometry calculated by TDDFT and TDDFT + TB for small organic molecules and noble metal nanoclusters.

Funder

National Science Foundation

Publisher

AIP Publishing

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

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