Transition state search using a guided direct inversion in the iterative subspace method

Abstract

A transition state optimization method using a guided energy-represented direct inversion in the iterative subspace (gEn-DIIS) algorithm is introduced and compared with the quasi-Newton rational function optimization (RFO) method. A hybrid technique that employs a combination of RFO and guided DIIS methods at various stages of convergence is presented. A set of test molecules is optimized for comparison using the hybrid method with gEn-DIIS and the traditional RFO methods. The gEn-DIIS method presented here exhibits fast optimization and is shown to be advantageous for difficult optimizations where the reaction path is flat. © 2012 American Chemical Society.