(729f) Multirefpredict: An Automated Workflow for Method Selection of First Principles Calculations on Transition Metal Chemistry

Liu, F., Stanford University
Duan, C., Massachusetts Institute of Technology
Kulik, H. J., Massachusetts Institute of Technology
Accurate prediction of electronic properties of open-shell transition metal complexes is essential for materials design and catalysis. However, transition metal complexes are notoriously difficult to study accurately with approximate Density Functional Theory (DFT). A crucial step to obtain accurate results for transition metal containing systems is to choose between single-reference and multi-reference based methods. Here we develop a python module, MultirefPredict, which is a high-level cross-platform workflow that calculates widely used multi-reference diagnostics for any given molecular system, without users handling the input or output of quantum chemistry packages. The backend quantum chemistry packages of MutlrefPredict supports several quantum chemistry packages based on both DFT and wavefunction based method, with calculation done on both CPUs and GPUs. We are working on incorporating this module into molSimplify, an automated, open source toolkit that enables seamless generation of candidate inorganic molecule structures, preparation and execution of electronic structure calculations developed in our group. The updated version of molSimplify will be able to recommend appropriate electronic structure methods for each automatically generated inorganic complex structure. This workflow is anticipated to make transition metal chemistry simulation more automated and transparent.