Preface

Over the past decade, great strides have been taken in developing quantum mechanical (QM) electronic structure methodologies, notably those using density functional theory (DFT) and its parameterized version DF tight binding (DFTB), molecular mechanical (MM) force fields for molecular dynamics (MD), sometimes including polarization effects (MMpol), various hybrid schemes (QM/MM) and embedding models to treat the dynamics of more and more complex nano- and nano–bio systems embedded in complex environments with good accuracy. Most recently, some of these methods have benefitted from extraordinary acceleration afforded by incorporating the latest advances in machine learning (ML). This book aims to summarize this progress, with only enough historical background to situate the various studies but focusing on key methodological breakthroughs that have allowed the field to prosper. The authors have been asked to provide sufficient technical details of the new methods to provide a meaningful learning experience for the next generation of method developers and coders and to provide their perspective on potential future developments over the next five to ten years. A few key applications are described, but the focus is on the methodologies.

Leading experts have contributed in the following subfields:

• 1) DFT/MM-MD

  In Chapter 1, Andreas Köster from Cinvestav, Mexico City has coordinated the writing of co-authors from the deMon2k community to provide an in-depth account of the theory for QM/MM implementation in deMon2k within the framework of auxiliary density functional theory (ADFT). Working equations are given, and a practical tool for input preparation is presented. QM/MM magnetic shielding and excited state calculations are emphasized.

  Chapter 2 from the Calabria group (Nino Russo et al.) illustrates the state of the art of computational enzymology with several examples of the performance of cluster models and QM/MM methods along with MD, tracing the free energy through the many steps of enzymatically-catalyzed reactions. Enzymatic promiscuity and covalent inhibition are highlighted.

• 2) DFT/MMpol-MD

  Sergei Noskov and his University of Calgary co-authors set the question for Chapter 3, “Is explicit inclusion of polarization on the horizon?”. They examine the performance of stand-alone MMpol, and QM/MM, highlighting particular challenges for the parametrization of polarizable force fields, the treatment of QM/MM boundaries and free energy sampling. Reference is made to recent ML techniques that could be helpful going forward. Two case studies, the CIC transporter and carbonic anhydrase, illustrate the state of the art.

  Chapter 4 takes us on a deep dive into the world of atto science; electron dynamics in the context of polarizable surroundings. Aurélien de la Lande (Orsay) and co-workers guide us through “methodologies to simulate the dynamics of large molecular systems after perturbation of their electron clouds by an external stimulus.” They couple QMPol with real-time, time-dependent DFT (RT-TDDFT) implemented in deMon2k and, most recently, include Ehrenfest nuclear dynamics. Spectra and collisions with high-energy particles are now amenable to study for systems of unprecedented complexity.

• 3) DFTB/MM-MD

  Moving to even larger, more complex systems, beyond the purview of DFT, Mathias Rapacioli, Fernand Spiegelman and Nathalie Tarrat (Toulouse) (Chapter 5) situate DFTB in the context of traditional tight binding techniques, on the one hand, and DFT, on the other, and review various hybrid schemes involving higher- and lower-level methods. The dynamics and thermodynamics of metal nanoparticles are highlighted, extending to complex environments found in solution and at surfaces.

  In Chapter 6, Samuele Giannini (Jochen Blumberger group at University College, London) and co-workers explore charge transport in nanoscale materials with a mixed quantum/classical non-adiabatic molecular dynamics method termed fragment orbital-based surface hopping (FOB-SH). Concerns such as trivial crossing detection and the removal of spurious charge transfer due to decoherence corrections are addressed. The transport mechanisms across high-mobility planes of molecular crystals are elucidated.

  Mechanistic insight into nano-catalyzed reactions in complex environments is the goal espoused in Chapter 7 by Tingyu Lei, Xingchen Liu and Xiaodong Wen (Taiyuan and Beijing). They reach it with two different methodologies DFTB/MM-MD and DFTB nanoreactor-MD, shedding light on important reactions for the upgrading of oil sands, the synthesis of graphene by the detonation of carbonaceous material and Fischer–Tropsch synthesis with Fe nanoparticles.

• 4) Solvation/Embedding models

  Chapter 8, by Tomasz Wesolowski (Geneva) “concerns Frozen Density Embedding Theory (FDET), in which the optimal embedded wavefunction is obtained from constrained minimization of the Hohenberg–Kohn energy functional.” A comprehensive and detailed overview of the formalism with working equations is given for variational and non-variational approaches, going far beyond the original embedding of DFT, with extensions for excited states and underlying pragmatic approximations.

  The powerful integral equation formulation of molecular solvation represented by the 3D-RISM-KH theory is exposed in Chapter 9 by Dipankar Roy and Andriy Kovalenko (Edmonton), including innovations such as multiple-time-step MD and dissipative particle dynamics. State-of-the-art multiscale simulations for bio- and nano-systems include mapping binding sites on protein surfaces, water molecules in protein active sites and the electric double layer in nano-porous materials.

• 5) Atomistic MD in complex environments

  Choosing reaction coordinates (RC) to study the dynamics of complex nano–bio systems remains a central challenge. Xiao-Qing Guan and Dong-Qing Wei (Shanghai) address this challenge in Chapter 10 in the framework of multi-RC umbrella sampling, proposing a new weighted least squares analysis method (WELSAM). Success for the study of transmembrane ion permeation mechanisms is highlighted.

• 6) Machine learning approaches

  ML is now pervasive in science. We close the book with two chapters that should provide entries into the rapidly-growing ML literature.

  In Chapter 11 Jutta Rogel (Berlin) and Mark Tuckerman (New York and Shanghai) provide “a framework for combining ML for local structure classification with the definition of a global classifier space as a basis for enhanced sampling of structural transformations in condensed-phase systems.” Path collective variables are defined, yielding insight into mechanisms for such complex phenomena as solid–solid phase transitions in transition metals.

  Finally, in Chapter 12, Abbas Khan, Byu-Ri Sim and Dong-Qing Wei (Shanghai) show how an array of ML tools can be fruitfully applied to the analysis of MD trajectories. An extensive table compares the advantages of the most prominent techniques. Applications to drug–target interactions, infrared spectra and ligand binding energies are highlighted.

In the original proposal for this book, we expressed our main motivation as promoting cross-talk among the various subfields by gathering chapters from leading experts in a single volume. Our second, co-equal, motivation was to provide newcomers with a comprehensive menu of multiscale modeling options so that they can better chart their course in the nano/bio world. The extent to which our motivations have been satisfied will be judged by you, the reader. We are grateful to all of the authors who took up the challenge and produced such outstanding chapters. Any shortcomings of the volume are ours alone.

The dimensional stretch of systems treated in the book ranges from attoseconds to microseconds and beyond, from picometers to micrometers and beyond. Of course, not all of the techniques are fully integrated, but the knowledge gained from multiscale, multi-methodological approaches does, we think, define the state of the art for studying the dynamics of nano- and nano–bio systems in complex environments. Extensions of such methods, and entirely new approaches, will undoubtedly carry us to even larger and longer scales in years to come. We look forward to this!

We are grateful to the Royal Society of Chemistry's Helen Armes, Connor Sheppard, Lewis Pearce and Amina Headley for their friendly and professional support as the book went through the various steps from conception to production. Thanks also to Kumudha and her team for producing exemplary page proofs.

Dennis R. Salahub, University of Calgary, Canada

Dong-Qing Wei, Shanghai Jiao Tong University, China