Preface Free

It is with great honor that we take over editing the Specialist Periodical Reports on Chemical Modelling from Michael Springborg and Jan-Ole Joswig. They have successfully compiled a total of 11 volumes over the past 12 years, to which both of us have contributed with pleasure. The series has always aimed at bringing into the spotlight selected contributions on topics of current interest in the general field of chemical modeling. The contributions—reporting on the latest developments in the field while proposing comprehensive critical reviews and serving as an introduction to specific topics—should be appealing to veterans and non-experts alike. By successfully putting up with such hard constraints, our predecessors have left us with quite a challenge!

This book contains six chapters from what we consider emerging yet established leaders in their field. It spans a broad array of subjects in chemical modelling, ranging from method development to applications. Electronic structure theory plays a prominent role throughout this book, as we believe it remains the paramount challenge for accurate modelling of chemical processes. Different methods are discussed that aim at improving the scaling and accuracy of computational approaches with respect to system size and complexity. Other contributions discuss how to understand, rationalize, and visualize many-electron wave function data. Finally, the extension of electronic structure to treat dynamical processes on ultrafast and ultralong timescales are presented.

In the first chapter, Maren Podewitz discusses how to harness the power of available quantum chemistry tools to accurately predict reaction profiles in complex chemical reactions. After state-of-the-art methods in computational catalysis are reviewed in detail, several protocols for the inclusion of solvent effects are compared and the importance of conformer searches for reaction mechanisms involving transition metals is discussed. The strengths and weaknesses of existing approaches, as well as the remaining open questions are demonstrated for an explicit example on olefin metathesis.

The second chapter by Carolin König and co-workers proposes a fundamental review of quantum mechanical and classical embedding schemes. A common framework is used to derive effective operators for both subsystem density-based embedding schemes and perturbative classical polarizable embedding models. This allows a critical comparison between the two methodologies, while their latest extensions and recent applications to local absorption properties of complex molecular systems in the linear response regime are also presented, highlighting potential pitfalls in such simulations.

Going beyond linear response theory, Thibaud Etienne introduces in Chapter 3 the formal foundations for the application of the reduced density matrix and Green's function formalisms to the characterization of excited electronic states. A self-contained description of transition density and difference density operators is proposed in both first and second quantization, highlighting differences in both approaches to characterize many-body wave functions that are often overlooked.

Visualization of many-body wave functions plays a central role in the following chapter, albeit from a time-dependent perspective. Electrons out of equilibrium are involved in most chemical reactions, and electron dynamics allows to follow the evolution of the underlying charge transfer and energy transfer processes on their natural timescales. Annika Bande describes an array of modern simulation methods for electron dynamics in molecular and nanostructured materials. In this contribution, various visualization tools are adapted from static excited electronic state characterization while other approaches specific to transient electronic distributions are introduced. The author finally offers her perspectives on the future of many-electron dynamics, with the advent of quantum compute algorithm and the rise of machine learning applications.

Moving to ultrafast timescales, Anthony Ferté and Morgane Vacher discuss the advent of attochemistry in the fifth chapter. They report on the recent experimental and theoretical developments in electron dynamics that allow to investigate the coherent evolution and relaxation of electron-hole pairs upon ionization, and to characterize the electronic coherences themselves. The importance of nuclear dynamics even on these ultrashort timescales is highlighted, and state-of-the-art simulation techniques are presented to address the issue. Finally, the possible future of attochemistry – direct control of electron dynamics inside polyatomic molecules to induce chemical reactions – is critically discussed by the authors.

The last chapter of this Specialist Periodical Report by Philipp Marquetand and collaborators is dedicated to the study of long time dynamics during photochemical reactions on excited states. Despite the fact that nuclear dynamics plays a prominent role in such processes, the bottleneck in the simulations remains the characterization of their electronic structure. Marquetand and co-workers thoroughly review the most important developments in machine learning for molecular dynamics simulations involving excited states and their non-adiabatic coupling. Machine learning is a disruptive technology that recently entered the field of chemical modelling, and it holds the promise of bridging timescales that have remained unattainable for traditional atomistic modelling approaches up to now.

Hilke Bahmann and Jean Christophe Tremblay