Preface

This book brings together two rapidly developing fields, those of porous materials and computational modelling. Porous materials have been used by mankind for millennia, with their use on an industrial scale arising in the last hundred years, as humans have increasingly been able to tailor material structure and properties to suit the application demands. This book focuses on microporous materials, which have pore dimensions similar to the size of small molecules, leading to applications as sorbents, in molecular separations, (photo)catalysis, optoelectronics and more, with increasing examples of multifunctionality. Zeolites have a long and industrious record, particularly in the area of ion exchange agents and catalysis, and there is intense research effort in the development of a wide range of functional porous materials, including metal–organic frameworks (MOFs), polymers and porous molecules. Each materials class can have unique advantages and disadvantages, from ease and cost of synthesis and processing, their chemical and physical stability, to the ability to finely tailor and control structure, and to tune properties.

In the last few decades, computational modelling has played an increasing role in the field of porous materials, providing rationalisation of properties that could not be garnered from experimental studies alone, as well as moving towards the prediction of structure, synthesis method and properties a priori, before any experiment begins in the laboratory. There is currently a significant opportunity in the field of porous materials, as an increasing number of researchers, including those focused on experimental work, have a very high degree of computer literacy, with software coding and data visualisation as components of undergraduate degrees. More than ever before, software and data are open-source, opening new doors to accelerating discovery. There is also considerable excitement and interest in the application of artificial intelligence techniques, in particular machine learning, in all areas of science, and researchers in the porous materials community are no exception to this and are looking to accelerate high-throughput experimental screening, computational property screening or experimental design through data-driven methods.

This book is timely in providing a foundation for understanding the key areas where computational modelling can and is going to impact the broad field of porous materials. This includes structure prediction of the full range of (micro)porous material classes, the calculation of sorption and diffusion in porous materials, the challenging task of predicting catalytic and optical performance, and the simulation of mechanical properties as well as more exotic behaviour such as negative thermal expansion. Finally, the book closes with a focus on the future opportunities for porous materials modelling, including in particular the application of machine learning for the rapid prediction of properties and data-driven targeting of optimal synthesis procedures.

Readers of this book will be placed at the cutting edge of the field of porous materials, able to apply transformative methods in their own area of interest, and to identify opportunities where computational modelling can transform how they research and discover new porous materials.

Kim E. Jelfs

London, UK