Inverse Design Method with Enhanced Sampling for Complex Open Crystals: Application to Novel Zeolite Self-assembly

Abstract

Optimizing the design and synthesis of complex crystal structures presents pivotal opportunities and challenges in materials design. While recent computational advances in inverse design have proven effective for simpler crystals, their extension to intricate structures such as zeolites remains challenging. In this work, we introduce an efficient and robust inverse design workflow specifically tailored for the predictive design of a broad range of complex phases. By integrating an evolutionary parameter optimization strategy with enhanced sampling molecular dynamics simulations, this approach effectively surmounts the high energy barriers that typically hinder self-assembly in these complex structures. We apply this inverse design workflow to facilitate the efficient self-assembly of target zeolite frameworks in an efficient coarse-grained model of a tetrahedral network-forming component and a structure-directing agent. Using this method, we not only successfully reproduce the self-assembly of known structures like the Z1 and SGT zeolites and Type-I clathrates but also uncover previously unknown optimal design parameters for SOD and CFI zeolites. Remarkably, our approach also leads to the discovery of an uncatalogued framework, which we designate as Z5. Our methodology not only enables the screening and optimization of self-assembly protocols but also expands the possibilities for discovering hypothetical structures, driving innovation in materials design and offering a robust tool for advancing crystal engineering in complex systems.