Bridge the gap between thermodynamic theory and engineering practice with this essential textbook Thermodynamics is a discipline which straddles the fields of chemistry, physics, and engineering, and has long been a mainstay of undergraduate and graduate curricula. Conventional thermodynamics courses, however, often ignore modern developments in statistical mechanics, such as molecular simulation methods, cooperative phenomena, phase transitions, universality, as well as liquid-state and polymer theories, despite their close relevance to both fundamental research and engineering practice. Fundamentals and Practice in Statistical Thermodynamics fills this gap with an essential book that applies up-to-date statistical-mechanical techniques to address the most crucial thermodynamics problems found in chemical and materials systems. It is ideally suited to introduce a new generation of researchers and molecular engineers to modern thermodynamic topics with numerous cutting-edge applications. From Fundamentals and Practice in Statistical Thermodynamics readers will also find: An introduction to statistical-mechanical methods including molecular dynamics simulation, Monte Carlo simulation, as well as the molecular theories of phase transitions, classical fluids, electrolyte solutions, polymeric materials, and more Illustrative examples and exercise problems with solutions to facilitate student understanding Supplementary online materials covering the basics of quantum mechanics, density functional theory, variational principles of classical mechanics, intermolecular interactions, and many more subjects Fundamentals and Practice in Statistical Thermodynamics is ideal for graduate and advanced undergraduate students in chemical engineering, biomolecular engineering, environmental engineering, materials science and engineering, and all related scientific subfields of physics and chemistry.

This is a solutions manual to accompany Fundamentals and Practice in Statistical Thermodynamics This textbook supplements, modernizes, and updates thermodynamics courses for both advanced undergraduates and graduate students by introducing the contemporary topics of statistical mechanics such as molecular simulation and liquid-state methods with a variety of realistic examples from the emerging areas of chemical and materials engineering. Current curriculum does not provide the necessary preparations required for a comprehensive understanding of these powerful tools for engineering applications. This text presents not only the fundamental ideas but also theoretical developments in molecular simulation and analytical methods to engineering students by illustrating why these topics are of pressing interest in modern high-tech applications.

This textbook introduces chemistry and chemical engineering students to molecular descriptions of thermodynamics, chemical systems, and biomolecules. Equips students with the ability to apply the method to their own systems, as today's research is microscopic and molecular and articles are written in that language Provides ample illustrations and tables to describe rather difficult concepts Makes use of plots (charts) to help students understand the mathematics necessary for the contents Includes practice problems and answers

The 1952 Nobel physics laureate Felix Bloch (1905-83) was one of the titans of twentieth-century physics. He laid the fundamentals for the theory of solids and has been called the ?father of solid-state physics.? His numerous, valuable contributions include the theory of magnetism, measurement of the magnetic moment of the neutron, nuclear magnetic resonance, and the infrared problem in quantum electrodynamics.Statistical mechanics is a crucial subject which explores the understanding of the physical behaviour of many-body systems that create the world around us. Bloch's first-year graduate course at Stanford University was the highlight for several generations of students. Upon his retirement, he worked on a book based on the course. Unfortunately, at the time of his death, the writing was incomplete.This book has been prepared by Professor John Dirk Walecka from Bloch's unfinished masterpiece. It also includes three sets of Bloch's handwritten lecture notes (dating from 1949, 1969 and 1976), and details of lecture notes taken in 1976 by Brian Serot, who gave an invaluable opinion of the course from a student's perspective. All of Bloch's problem sets, some dating back to 1933, have been included.The book is accessible to anyone in the physical sciences at the advanced undergraduate level or the first-year graduate level.

This text presents the two complementary aspects of thermal physics as an integrated theory of the properties of matter. Conceptual understanding is promoted by thorough development of basic concepts. In contrast to many texts, statistical mechanics, including discussion of the required probability theory, is presented first. This provides a statistical foundation for the concept of entropy, which is central to thermal physics. A unique feature of the book is the development of entropy based on Boltzmann's 1877 definition; this avoids contradictions or ad hoc corrections found in other texts. Detailed fundamentals provide a natural grounding for advanced topics, such as black-body radiation and quantum gases. An extensive set of problems (solutions are available for lecturers through the OUP website), many including explicit computations, advance the core content by probing essential concepts. The text is designed for a two-semester undergraduate course but can be adapted for one-semester courses emphasizing either aspect of thermal physics. It is also suitable for graduate study.

In keeping with the tradition of previous summer schools on fundamental problems in statistical mechanics, this book contains in depth treatemnts of topics of current interest in statistical mechanics and closely related fields. The topics covered include: dynamical impurity problems, quantum phase transitions, vortex liquids and glasses, quasicrystals and related aperiodic structures, pattern formation, turbulence, exactly solvable models, polymers, phase transitions in colloids, interfaces and two-dimensional gravity.

This book was planned and written with one central goal in mind: to demonstrate that statistical thermodynamics can be used successfully by a broad group of scientists, ranging from chemists through biochemists to biologists, who are not and do not intend to become specialists in statistical thermodynamics. The book is addressed mainly to gradu ate students and research scientists interested in designing experiments the results of which may be interpreted at the molecular level, or in interpreting such experimental results. It is not addressed to those who intend to practice statistical thermodynamics per se. With this goal in mind, I have expended a great deal of effort to make the book clear, readable, and, I hope, enjoyable. This does not necessarily mean that the book as a whole is easy to read. The first four chapters are very detailed. The last four become progressively more difficult to read, for several reasons. First, presuming that the reader has already acquired familiarity with the methods and arguments presented in the first part, I felt that similar arguments could be skipped later on, leaving the details to be filled in by the reader. Second, the systems themselves become progressively more com plicated as we proceed toward the last chapter.

This 1966 account of thermodynamics was written premaritally for theoretical physicists and for experimental physicists and physical chemists wishing to enter more deeply into the fundamental principles of the subject. Although it covers elementary and advanced topics, the elementary ideas are treated from an advanced standpoint.

This textbook concerns thermal properties of bulk matter and is aimed at advanced undergraduate or first-year graduate students in a range of programs in science or engineering. It provides an intermediate level presentation of statistical thermodynamics for students in the physical sciences (chemistry, nanosciences, physics) or related areas of applied science/engineering (chemical engineering, materials science, nanotechnology engineering), as they are areas in which statistical mechanical concepts play important roles. The book enables students to utilize microscopic concepts to achieve a better understanding of macroscopic phenomena and to be able to apply these concepts to the types of sub-macroscopic systems encountered in areas of nanoscience and nanotechnology.

This book introduces the concept of “bespoke learning”, a new mechanistic approach that makes it possible to generate values of an output variable at each designated value of an associated input variable. Here the output variable generally provides information about the system’s behaviour/structure, and the aim is to learn the input-output relationship, even though little to no information on the output is available, as in multiple real-world problems. Once the output values have been bespoke-learnt, the originally-absent training set of input-output pairs becomes available, so that (supervised) learning of the sought inter-variable relation is then possible. Three ways of undertaking such bespoke learning are offered: by tapping into system dynamics in generic dynamical systems, to learn the function that causes the system’s evolution; by comparing realisations of a random graph variable, given multivariate time series datasets of disparate temporal coverage; and by designing maximally information-availing likelihoods in static systems. These methodologies are applied to four different real-world problems: forecasting daily COVID-19 infection numbers; learning the gravitational mass density in a real galaxy; learning a sub-surface material density function; and predicting the risk of onset of a disease following bone marrow transplants. Primarily aimed at graduate and postgraduate students studying a field which includes facets of statistical learning, the book will also benefit experts working in a wide range of applications. The prerequisites are undergraduate level probability and stochastic processes, and preliminary ideas on Bayesian statistics.