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用于复杂开放晶体的增强采样逆设计方法:在新型沸石自组装中的应用

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

作者信息

Wang Chaohong, Pérez de Alba Ortíz Alberto, Dijkstra Marjolein

机构信息

Soft Condensed Matter & Biophysics, Debye Institute for Nanomaterials Science, Utrecht University, Princetonplein 1, 3584 CC Utrecht, the Netherlands.

Computational Soft Matter, van't Hoff Institute for Molecular Sciences and Informatics Institute, University of Amsterdam, Science Park 904, Amsterdam 1098 XH, the Netherlands.

出版信息

ACS Nano. 2025 May 13;19(18):17423-17437. doi: 10.1021/acsnano.4c17597. Epub 2025 May 1.

DOI:10.1021/acsnano.4c17597
PMID:40309966
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12080377/
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.

摘要

优化复杂晶体结构的设计与合成在材料设计中既带来了关键机遇,也带来了挑战。虽然最近逆设计方面的计算进展已证明对较简单的晶体有效,但将其扩展到诸如沸石等复杂结构仍具有挑战性。在这项工作中,我们引入了一种高效且稳健的逆设计工作流程,该流程专门针对广泛复杂相的预测设计进行了定制。通过将进化参数优化策略与增强采样分子动力学模拟相结合,这种方法有效地克服了通常阻碍这些复杂结构中自组装的高能垒。我们将此逆设计工作流程应用于在四面体网络形成组分和结构导向剂的高效粗粒度模型中促进目标沸石骨架的高效自组装。使用这种方法,我们不仅成功再现了Z1和SGT沸石以及I型笼形包合物等已知结构的自组装,还发现了SOD和CFI沸石以前未知的最佳设计参数。值得注意的是,我们的方法还导致发现了一种未编目的骨架,我们将其命名为Z5。我们的方法不仅能够筛选和优化自组装方案,还扩展了发现假设结构的可能性,推动材料设计创新,并为推进复杂系统中的晶体工程提供了一个强大的工具。

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本文引用的文献

1
Interzeolite Transformation through Cross-Nucleation: A Molecular Mechanism for Seed-Assisted Synthesis.通过交叉成核实现的沸石间转化:种子辅助合成的分子机制
J Am Chem Soc. 2024 Dec 4;146(48):33204-33213. doi: 10.1021/jacs.4c12863. Epub 2024 Nov 19.
2
Inverse design of crystals and quasicrystals in a non-additive binary mixture of hard disks.硬盘非加和二元混合物中晶体和准晶体的逆设计
J Chem Phys. 2024 Jun 28;160(24). doi: 10.1063/5.0210034.
3
Variational umbrella seeding for calculating nucleation barriers.用于计算成核势垒的变分伞形抽样法
J Chem Phys. 2024 May 7;160(17). doi: 10.1063/5.0204540.
4
Deep-learning-based inverse design of three-dimensional architected cellular materials with the target porosity and stiffness using voxelized Voronoi lattices.基于深度学习的具有目标孔隙率和刚度的三维结构多孔材料的逆向设计,采用体素化的Voronoi晶格。
Sci Technol Adv Mater. 2023 Jan 4;24(1):2157682. doi: 10.1080/14686996.2022.2157682. eCollection 2023.
5
What Is the Smallest Zeolite That Could Be Synthesized?能够合成的最小沸石是什么?
Angew Chem Int Ed Engl. 2022 Jul 18;61(29):e202205095. doi: 10.1002/anie.202205095. Epub 2022 May 19.
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Inverse design of soft materials via a deep learning-based evolutionary strategy.基于深度学习的进化策略实现软材料的逆向设计。
Sci Adv. 2022 Jan 21;8(3):eabj6731. doi: 10.1126/sciadv.abj6731. Epub 2022 Jan 19.
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Biomedical applications of zeolite-based materials: A review.基于沸石材料的生物医学应用:综述
Mater Sci Eng C Mater Biol Appl. 2020 Nov;116:111225. doi: 10.1016/j.msec.2020.111225. Epub 2020 Jun 20.
8
Inverse design of porous materials using artificial neural networks.基于人工神经网络的多孔材料逆向设计
Sci Adv. 2020 Jan 3;6(1):eaax9324. doi: 10.1126/sciadv.aax9324. eCollection 2020 Jan.
9
Assembly of clathrates from tetrahedral patchy colloids with narrow patches.四面体镶嵌胶体自组装形成具有狭窄镶嵌的笼形物。
J Chem Phys. 2019 Sep 7;151(9):094502. doi: 10.1063/1.5109382.
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Calculation of phase diagrams in the multithermal-multibaric ensemble.多热-多压系综中相图的计算。
J Chem Phys. 2019 Jun 28;150(24):244119. doi: 10.1063/1.5102104.