Quantum Computing Based Design of Multivariate Porous Materials.

ABSTRACT: Multivariate (MTV) porous materials exhibit unique structural complexities based on their diverse spatial arrangements of multiple building block combinations. These materials possess potential synergistic functionalities that exceed the sum of their individual components. However, the exponentially increasing design complexity of these materials poses significant challenges for accurate ground-state configuration prediction and design. To address this, we propose a Hamiltonian model for quantum computing that integrates compositional, structural, and balance constraints directly into the Hamiltonian, enabling efficient optimization of the MTV configurations. The model employs a graph-based representation to encode linker types as qubits. Our framework enables quantum encoding of a vast li

SUBMITTER: Kang S 

PROVIDER: S-EPMC12550618 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature