LITMIR.BIZ

PREFACE

This book series seeks to aid researchers in selecting and applying new computational chemistry methods to their own research problems. This aim is achieved through tutorial‐style chapters that provide solid starting points and advice for novices as well as critical literature reviews highlighting advanced applications to illustrate current state of the art. Volume 32 continues this longstanding tradition. While each chapter has a unique focus, two themes connect the chapters in this volume. The first theme centers on methods that can be broadly applied to a variety of systems in Chapters 1 and 2, and the second theme emphasizes special considerations required when modeling very specific system types in Chapters 3 and 4.

Chapter 1 highlights the vast space of local minimum energy structures of complex molecules to illustrate the importance of non‐deterministic global optimization (NDGO) approaches. Such approaches avoid visiting every region of search space, thus inevitably allowing for the possibility that the global minimum has not been found (otherwise the method would be deterministic!). Because NDGO methods lack a true convergence criterion, it is essential to use them properly to ensure meaningful results are obtained. Thus, the subsection titled “NDGO Tips for Absolute Beginners” should be bookmarked and reviewed regularly by new computational chemists applying NDGO methods to any problem. Bernd Hartke illustrates the humorous practice of naming NDGO algorithms after natural processes that have no parallels to the NDGO problem, but then breaks down the fundamental algorithm ideas into simple ingredients to identify similarities and differences between such algorithms. Important guidance on the use of NDGO methods include use of a two‐level strategy with combining exhaustive global search using inexpensive methods to calculate energies followed by local post‐optimization of selected results at high levels of theory as well avoiding single runs when using nondeterministic algorithms. This latter advice is one that would be well‐taken in many areas of computational chemistry and a piece of advice one of the book editors personally gives her students regularly! Chapter 1 closes with a set of recent highlights such as the applicability of NDGO to a variety of optimization targets ranging from force‐field parameters to reaction networks.

      Chapter 2 focuses on the excited‐state dynamics calculations required to calculate electronic absorption spectra or to investigate electron dynamics of chemical systems irradiated by laser light. In particular, real‐time time‐dependent (RT‐TD) and non‐adiabatic dynamics calculations using the density functional tight binding (DFTB) formalism are explored. Stepwise tutorials on the molecule naphthalene, are given to provide researchers with practice applying these techniques to probe and understand the chemical dynamics exhibited in a simple system to prepare them for work on larger systems. Silver nanoparticles and nanoparticle chains illustrate applications of the method to large systems. After thoroughly exploring the electron dynamics of adiabatic systems in external electric fields using a single potential energy surface (PES), the theory and methods used to allow nonadiabatic evolution of nuclear position on different PESs are considered. Nonadiabatic evolution is essential for accurate modeling of photochemical and photovoltaic processes that involve transitions between PESs. Computational efficiency of DFTB has advanced to the point that applications in emerging areas of excited‐state chemical dynamics in large, complex systems are now within reach.

      Chapter 3 transitions from a focus on methodology to applications of methodologies to investigate a specialized type of chemical system, namely chemical systems that form microphases with periodic morphologies such as lamellae and cylinders. Microphases can form in diverse systems, ranging from aggregated colloidal particles to diblock copolymers. Charbonneau and Khang focus on the phenomenological field‐theory description of

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