Mechanism of charge transport in organic solids has been an issue of intensive interests and debates for over 50 years, not only because of the applications in printing electronics, but also because of the great challenges in understanding the electronic processes in complex systems. With the fast developments of both electronic structure theory and the computational technology, the dream of predicting the charge mobility is now gradually becoming a reality. This volume describes recent progresses in Prof. Shuai’s group in developing computational tools to assess the intrinsic carrier mobility for organic and carbon materials at the first-principles level. According to the electron-phonon coupling strength, the charge transport mechanism is classified into three different categories, namely, the localized hopping model, the extended band model, and the polaron model. For each of them, a corresponding theoretical approach is developed and implemented into typical examples.
Density Matrix Renormalization Group (DMRG)-based Approaches in Computational Chemistry outlines important theories and algorithms of DMRG-based approaches and explores their use in computational chemistry. Beginning with an introduction to DMRG and DMRG-based approaches, the book goes on to discuss the key theories and applications of DMRG, from DMRG for semi-empirical and ab-initio quantum chemistry, to DMRG in embedded environments, frequency spaces and quantum dynamics. Drawing on the experience of its expert authors, sections detail recent ideas and key developments, providing an up-to-date view of current developments in the field for students and researchers in quantum chemistry. Provides an expertly-curated, consolidated overview of research in the field Includes exercises that support learning and link theory to practice Outlines key theories and algorithms for computational chemistry applications
Nanocarbon-Inorganic Hybrids is dedicated exclusively to the new family of functional materials, covering a multidisciplinary research field that combines materials science, chemistry and physics with nanotechnology and applied energy science. It provides a concise introduction into fundamental principles of nanocarbons, defines hybrids and composites, explains the physics behind sustainability, and illustrates requirements for successful implementation in energy applications. It further reviews the current research on developing concepts for designing nanocarbon hybrids, unravels mechanistic details of interfacial electron transfer processes and highlights future challenges and perspectives associated with exploiting these exciting new materials in commercial energy applications and beyond. This comprehensively written book is indispensable for Master and PhD students seeking to become familiar with a modern fi eld of knowledge-driven material science as well as for senior researchers and industrial staff scientists who explore the frontiers of knowledge.
Density Matrix Renormalization Group (DMRG)-based Approaches in Computational Chemistry outlines important theories and algorithms of DMRG-based approaches and explores their use in computational chemistry. Beginning with an introduction to DMRG and DMRG-based approaches, the book goes on to discuss the key theories and applications of DMRG, from DMRG for semi-empirical and ab-initio quantum chemistry, to DMRG in embedded environments, frequency spaces and quantum dynamics. Drawing on the experience of its expert authors, sections detail recent ideas and key developments, providing an up-to-date view of current developments in the field for students and researchers in quantum chemistry. Provides an expertly-curated, consolidated overview of research in the field Includes exercises that support learning and link theory to practice Outlines key theories and algorithms for computational chemistry applications
Mechanism of charge transport in organic solids has been an issue of intensive interests and debates for over 50 years, not only because of the applications in printing electronics, but also because of the great challenges in understanding the electronic processes in complex systems. With the fast developments of both electronic structure theory and the computational technology, the dream of predicting the charge mobility is now gradually becoming a reality. This volume describes recent progresses in Prof. Shuai’s group in developing computational tools to assess the intrinsic carrier mobility for organic and carbon materials at the first-principles level. According to the electron-phonon coupling strength, the charge transport mechanism is classified into three different categories, namely, the localized hopping model, the extended band model, and the polaron model. For each of them, a corresponding theoretical approach is developed and implemented into typical examples.
With the increasing penetration of renewable energy and distributed energy resources, smart grid is facing great challenges, which could be divided into two categories. On the one hand, the endogenous uncertainties of renewable energy and electricity load lead to great difficulties in smart grid forecast. On the other hand, massive electric devices as well as their complex constraint relationships bring about significant difficulties in smart grid dispatch. Owe to the rapid development of artificial intelligence in recent years, several artificial intelligence enabled computational methods have been successfully applied in the smart grid and achieved good performances. Therefore, this book is concerned with the research on the key issues of artificial intelligence enabled computational methods for smart grid forecast and dispatch, which consist of three main parts. (1) Introduction for smart grid forecast and dispatch, in inclusion of reviewing previous contribution of various research methods as well as their drawbacks to analyze characteristics of smart grid forecast and dispatch. (2) Artificial intelligence enabled computational methods for smart grid forecast problems, which are devoted to present the recent approaches of deep learning and machine learning as well as their successful applications in smart grid forecast. (3) Artificial intelligence enabled computational methods for smart grid dispatch problems, consisting of edge-cutting intelligent decision-making approaches, which help determine the optimal solution of smart grid dispatch. The book is useful for university researchers, engineers, and graduate students in electrical engineering and computer science who wish to learn the core principles, methods, algorithms, and applications of artificial intelligence enabled computational methods.
This book provides an introduction to nanofluidics in a simple manner and can be easily followed by senior undergraduate students, graduate students, and other researchers who have some background in fluid mechanics. The book covers the main topics about the fundamentals of nanofluidics and how it differs from classic fluid mechanics. It also describes the methodologies of nanofluidics, including numerical approaches, e.g., molecular dynamics simulation and experimental techniques. Fundamental physics and new phenomena in nanofluidics are the major concerns of this book. The author goes on to discuss nanocofinements and the parameters that affect the fluid dynamics at the nanoscale and make flow analysis complex. These parameters accommodate rich, new flow phenomena that may not be observed at the macro- and microscale. Although not all of the new phenomena will find widespread applications, the physics underlying these new phenomena may offer insights for other fields. This is one of the reasons why this book emphasizes the mechanisms of various flow fashions. Explores the unique characteristics of nanoscale flows and related properties Reviews the latest research of nanoscale ion transport and its applications Discusses the fluid flows in nanoconfinements in a unique manner based on the author's original research Incorporates important applications of nanofluidics throughout.
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