A force field interpolation method for generating initial guesses for transition state optimizations is presented. The user supplies reactants and products as SMILES strings (or XYZ coordinates), after which automatically constructed force fields are interpolated to approximate the potential energy surface (PES) along the reaction coordinate. The transition state guess is obtained by sampling along this approximate PES. Reliance on force fields ensures the method is transparent in its workings and computationally inexpensive. The workflow is implemented in VeloxChem, enabling Jupyter notebook execution with a few lines of Python code. An interactive widget makes visualization and inspection of results easy and intuitive, and a flexible Python API facilitates integration into complex automated workflows. The method is demonstrated on ten chemically diverse systems, including a transition-metal catalytic cycle. Benchmarking across 121 reactions resulted in convergence for 115 transition states, with an average cost of 107 gradient evaluations per reaction-comparable to more demanding double-ended methods.
Hoorn et al. (Fri,) studied this question.
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