AI-Guided Design and Property Prediction for Zeolites and Nanoporous Materials

9 Data-Driven Approach for Rational Synthesis of Zeolites and Other Nanoporous Materials

Watcharop Chaikittisilp

Research and Services Division of Materials Data and Integrated System (MaDIS), National Institute for Materials Science (NIMS), Tsukuba, Japan

9.1 Introduction

Zeolites, metal–organic frameworks, and mesoporous solids are representative nanoporous materials that have found their central place in several industrial applications [1–5]. Their applications range from traditional uses, such as adsorption, separation, and catalysis, to emerging areas, including sensing, electronics, and biomedicine. In the past few decades, progress in nanoporous materials has been accelerated by advances in experimental, analytical, and computational methods, thereby bringing the materials to practical applications. However, to bring the materials from laboratory to commercialization, in principle, it starts from materials searching, through optimization of materials properties and performance, for example, by tuning structures and compositions, to large-scale production. This process generally takes more than 10–15 years. To accelerate the development of materials, computational calculations and advanced characterization techniques have been employed to understand the synthesis–structure–property relationships. However, these relationships are sometime very complex and complicated.

As our society is changing at a rapid pace, with increasing demand for materials that can sustain us on ...