A research team from the Department of Chemical and Biomolecular Engineering at KAIST, led by Professor Jihan Kim, has developed a new framework for designing multicomponent porous materials (MTVs) using quantum computers. The team addressed the challenge of designing complex MTV structures, where the number of possible combinations increases exponentially, making it difficult for conventional methods to predict properties. The research was published online in the Journal of the American Chemical Society (ACS Central Science).
The framework converts the complex porous structure into a network (graph) that can be expressed in terms of qubits, allowing a quantum computer to solve the problem of finding the most stable structure. The research team constructed a variational quantum circuit using a Two Local ansatz and executed it with a Sampling VQE algorithm. Experiments were conducted on four actual reported MTV structures, and the same ground state configurations were successfully reproduced in both simulations and on a real IBM 127-qubit quantum computer (ibm_kyiv). This confirmed the model’s viability and its ability to correctly identify the optimal values.
This study is positioned as the first instance of using quantum computing to resolve a bottleneck in the design of complex multicomponent porous materials. The achievement is expected to be applied as a customized material design technology in fields such as carbon capture and separation, selective catalytic reactions, and ion-conducting electrolytes. The researchers plan to expand this method into a platform that can be coupled with classical simulations or machine learning-based property prediction tools. The research was supported by the National Research Foundation of Korea (NRF) through the Ministry of Science and ICT‘s Mid-career Researcher Support Project and Heterogeneous Materials Support Project.
Read the full announcement from KAIST here and the paper in ACS Central Science here.
September 10, 2025
