Quantum-Classical Computational Molecular Design of Deuterated High-Efficiency OLED Emitters

This paper describes a hybrid quantum-classical computational approach to designing synthesizable deuterated tris(8-hydroxyquinolinato) aluminum (Alq3) emitters with desirable emission quantum efficiency (QE). This multi-pronged approach first uses classical quantum chemistry to create a machine learning dataset, which is then used to construct an Ising Hamiltonian by a factorization-machine-based model to predict the QEs of Alq3 emitters. Finally, the Ising Hamiltonian is applied to perform simulations using the variational quantum eigensolver (VQE) and quantum approximate optimization algorithm (QAOA) on a quantum device to discover molecules with optimal QE. Moreover, to improve the simulations on the noisy quantum device, we developed the recursive probabilistic variable elimination method, which recursively eliminates qubits depending on the probability that each qubit has a binary value. We demonstrated that the accuracy of VQE and QAOA optimized for a noisy device can be improved from a probability of 0.075 to 0.97.