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

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.

复杂晶体结构的设计与合成优化，在材料设计领域兼具关键机遇与挑战。近年来，逆向设计（inverse design）领域的计算技术进展虽已在简单晶体的设计中展现出良好成效，但将其拓展至沸石这类复杂结构仍存在不小挑战。本研究提出了一套高效且稳健的逆向设计工作流，专为多种复杂相的预测性设计量身打造。该方法将进化参数优化策略与增强采样分子动力学（enhanced sampling molecular dynamics）模拟相结合，有效突破了通常阻碍这类复杂结构自组装的高能垒瓶颈。我们将这套逆向设计工作流应用于四面体网络形成组分与结构导向剂（structure-directing agent）的高效粗粒度模型（coarse-grained model）中，以实现目标沸石骨架的高效自组装。借助该方法，我们不仅成功复现了Z1、SGT沸石以及I型笼形包合物（Type-I clathrates）等已知结构的自组装过程，还挖掘出了SOD与CFI沸石此前未被探明的最优设计参数。尤为值得一提的是，本方法还促成了一种未被收录的骨架结构的发现，我们将其命名为Z5。本研究提出的方法论不仅能够实现自组装流程的筛选与优化，还拓展了假想结构（hypothetical structures）的发现边界，推动了材料设计领域的创新，并为复杂体系中的晶体工程发展提供了一款稳健的实用工具。