Abstract
In the research field of material science, quantum chemistry database plays an indispensable role in determining the structure and properties of new material molecules and in deep learning in this field. A new quantum chemistry database, the QM-sym, has been set up in our previous work. The QM-sym is an open-access database focusing on transition states, energy, and orbital symmetry. In this work, we put forward the QM-symex with 173-kilo molecules. Each organic molecular in the QM-symex combines with the C(n)h symmetry composite and contains the information of the first ten singlet and triplet transitions, including energy, wavelength, orbital symmetry, oscillator strength, and other quasi-molecular properties. QM-symex serves as a benchmark for quantum chemical machine learning models that can be effectively used to train new models of excited states in the quantum chemistry region as well as contribute to further development of the green energy revolution and materials discovery.