These are the succeeding volumes of a series of books on thermodynamic properties of engineering materials prepared under the auspices of the State Service of Standard Reference data of the Soviet Union. Each volume is set up in the same way: Part I deals with a study of all necessary aspects of experimental data interpretation and analysis; Part II then presents the fundamental constants, symbols with units, and data tables. Researchers and engineers in the fields of process design, equipment development, custody transfer and safety will find these book valuable and reliable reference sources for their respective tasks.

Although the study of dynamical systems is mainly concerned with single trans formations and one-parameter flows (i. e. with actions of Z, N, JR, or JR+), er godic theory inherits from statistical mechanics not only its name, but also an obligation to analyze spatially extended systems with multi-dimensional sym metry groups. However, the wealth of concrete and natural examples, which has contributed so much to the appeal and development of classical dynamics, is noticeably absent in this more general theory. A remarkable exception is provided by a class of geometric actions of (discrete subgroups of) semi-simple Lie groups, which have led to the discovery of one of the most striking new phenomena in multi-dimensional ergodic theory: under suitable circumstances orbit equivalence of such actions implies not only measurable conjugacy, but the conjugating map itself has to be extremely well behaved. Some of these rigidity properties are inherited by certain abelian subgroups of these groups, but the very special nature of the actions involved does not allow any general conjectures about actions of multi-dimensional abelian groups. Beyond commuting group rotations, commuting toral automorphisms and certain other algebraic examples (cf. [39]) it is quite difficult to find non-trivial smooth Zd-actions on finite-dimensional manifolds. In addition to scarcity, these examples give rise to actions with zero entropy, since smooth Zd-actions with positive entropy cannot exist on finite-dimensional, connected manifolds. Cellular automata (i. e.

Despite scientific evidence that business-as-usual is unsustainable, there is a huge and widespread inertia to 'greening' the planet. Warming to Ecocide considers climate change from a thermodynamic perspective and asks whether market-driven organisations have carried us to the point of no return through the flawed economics of endless growth. Warming to Ecocide begins by exploring the thermodynamic origins of climate change. It demonstrates that equilibrium thermodynamics can provide full explanations for the basic processes of life such as photosynthesis and metabolism, and that non-equilibrium thermodynamics is close to providing an explanation for how life started. Armed with a solid appreciation of the power of thermodynamics, the second half of Warming to Ecocide discusses whether multinational corporations have convinced the public that climate change is insignificant and thereby neutered any all attempts by governments to espouse environmentally-friendly policies. It then goes on to offer strategies whereby mankind may avoid propelling the global average temperature above the pre-industrial level by more than 2 DegreesC, which scientists view as a threshold presaging catastrophic run-away processes.

Combined for researchers and graduate students the articles from the Sitges Summer School together form an excellent survey of the applications of neural-network theory to statistical mechanics and computer-science biophysics. Various mathematical models are presented together with their interpretation, especially those to do with collective behaviour, learning and storage capacity, and dynamical stability.

This volume contains a series of six lecture courses presented by some of the leading exponents in the field of low-temperature physics. Special emphasis is given to theoretical and experimental advances in our understanding of 3He, heavy fermion systems and high-Tc superconductivity. The book provide an ideal basis for graduate courses in low-temperature physics.

This textbook takes an interdisciplinary approach to the subject of thermodynamics and is therefore suitable for undergraduates in chemistry, physics and engineering courses. The book is an introduction to phenomenological thermodynamics and its applications to phase transitions and chemical reactions, with some references to statistical mechanics. It strikes the balance between the rigorousness of the Callen text and phenomenological approach of the Atkins text. The book is divided in three parts. The first introduces the postulates and laws of thermodynamics and complements these initial explanations with practical examples. The second part is devoted to applications of thermodynamics to phase transitions in pure substances and mixtures. The third part covers thermodynamic systems in which chemical reactions take place. There are some sections on more advanced topics such as thermodynamic potentials, natural variables, non-ideal mixtures and electrochemical reactions, which make this book of suitable also to post-graduate students.

This book explains the minimum error entropy (MEE) concept applied to data classification machines. Theoretical results on the inner workings of the MEE concept, in its application to solving a variety of classification problems, are presented in the wider realm of risk functionals. Researchers and practitioners also find in the book a detailed presentation of practical data classifiers using MEE. These include multi-layer perceptrons, recurrent neural networks, complexvalued neural networks, modular neural networks, and decision trees. A clustering algorithm using a MEE-like concept is also presented. Examples, tests, evaluation experiments and comparison with similar machines using classic approaches, complement the descriptions.

Materials sciences relate the macroscopic properties of materials to their microscopic structure and postulate the need for holistic multiscale research. The investigation of shape memory alloys is a prime example in this regard. This particular class of materials exhibits strong coupling of temperature, strain and stress, determined by solid state phase transformations of their metallic lattices. The present book presents a collection of simulation studies of this behaviour. Employing conceptually simple but comprehensive models, the fundamental material properties of shape memory alloys are qualitatively explained from first principles. Using contemporary methods of molecular dynamics simulation experiments, it is shown how microscale dynamics may produce characteristic macroscopic material properties. The work is rooted in the materials sciences of shape memory alloys and covers thermodynamical, micro-mechanical and crystallographical aspects. It addresses scientists in these research fields and their students.

This volume presents five different methods recently developed to tackle the large scale behavior of highly correlated random systems, such as spin glasses, random polymers, local times and loop soups and random matrices. These methods, presented in a series of lectures delivered within the Jean-Morlet initiative (Spring 2013), play a fundamental role in the current development of probability theory and statistical mechanics. The lectures were: Random Polymers by E. Bolthausen, Spontaneous Replica Symmetry Breaking and Interpolation Methods by F. Guerra, Derrida's Random Energy Models by N. Kistler, Isomorphism Theorems by J. Rosen and Spectral Properties of Wigner Matrices by B. Schlein. This book is the first in a co-edition between the Jean-Morlet Chair at CIRM and the Springer Lecture Notes in Mathematics which aims to collect together courses and lectures on cutting-edge subjects given during the term of the Jean-Morlet Chair, as well as new material produced in its wake. It is targeted at researchers, in particular PhD students and postdocs, working in probability theory and statistical physics.

Stability conditions for functional differential equations can be obtained using Lyapunov functionals. Lyapunov Functionals and Stability of Stochastic Functional Differential Equations describes the general method of construction of Lyapunov functionals to investigate the stability of differential equations with delays. This work continues and complements the author's previous book Lyapunov Functionals and Stability of Stochastic Difference Equations, where this method is described for difference equations with discrete and continuous time. The text begins with both a description and a delineation of the peculiarities of deterministic and stochastic functional differential equations. There follows basic definitions for stability theory of stochastic hereditary systems, and the formal procedure of Lyapunov functionals construction is presented. Stability investigation is conducted for stochastic linear and nonlinear differential equations with constant and distributed delays. The proposed method is used for stability investigation of different mathematical models such as: * inverted controlled pendulum; * Nicholson's blowflies equation; * predator-prey relationships; * epidemic development; and * mathematical models that describe human behaviours related to addictions and obesity. Lyapunov Functionals and Stability of Stochastic Functional Differential Equations is primarily addressed to experts in stability theory but will also be of interest to professionals and students in pure and computational mathematics, physics, engineering, medicine, and biology.

Entransy in Phase-Change Systems summarizes recent developments in the area of entransy, especially on phase-change processes. This book covers new developments in the area including the great potential for energy saving for process industries, decreasing carbon dioxide emissions, reducing energy bills and improving overall efficiency of systems. This concise volume is an ideal book for engineers and scientists in energy-related industries.

Large-scale winds and currents tend to balance Coriolis and pressure gradient forces. The time evolution of these winds and currents is the subject of the quasi-geostrophic theory. Chapter 1 presents concepts and equations of classical inertial fluid mechanics. Chapter 2 deals with the equations of thermodynamics that close the governing equations of the fluids. Then, the motion is reformulated in a uniformly rotating reference frame. Chapter 3 deals with the shallow-water model and the homogeneous model of wind-driven circulation. The chapter also describes a classical application of the Ekman layer to the atmosphere. Chapter 4 considers the two-layer model, as an introduction to baroclinic flows, together with the concept of available potential energy. Chapter 5 takes into account continuously stratified flows in the ocean and in the atmosphere.

This book provides a comprehensive yet short description of the basic concepts of Complex Network theory. In contrast to other books the authors present these concepts through real case studies. The application topics span from Foodwebs, to the Internet, the World Wide Web and the Social Networks, passing through the International Trade Web and Financial time series. The final part is devoted to definition and implementation of the most important network models. The text provides information on the structure of the data and on the quality of available datasets. Furthermore it provides a series of codes to allow immediate implementation of what is theoretically described in the book. Readers already used to the concepts introduced in this book can learn the art of coding in Python by using the online material. To this purpose the authors have set up a dedicated web site where readers can download and test the codes. The whole project is aimed as a learning tool for scientists and practitioners, enabling them to begin working instantly in the field of Complex Networks.

The domain of non-extensive thermostatistics has been subject to intensive research over the past twenty years and has matured significantly. Generalised Thermostatistics cuts through the traditionalism of many statistical physics texts by offering a fresh perspective and seeking to remove elements of doubt and confusion surrounding the area. The book is divided into two parts - the first covering topics from conventional statistical physics, whilst adopting the perspective that statistical physics is statistics applied to physics. The second developing the formalism of non-extensive thermostatistics, of which the central role is played by the notion of a deformed exponential family of probability distributions. Presented in a clear, consistent, and deductive manner, the book focuses on theory, part of which is developed by the author himself, but also provides a number of references towards application-based texts. Written by a leading contributor in the field, this book will provide a useful tool for learning about recent developments in generalized versions of statistical mechanics and thermodynamics, especially with respect to self-study. Written for researchers in theoretical physics, mathematics and statistical mechanics, as well as graduates of physics, mathematics or engineering. A prerequisite knowledge of elementary notions of statistical physics and a substantial mathematical background are required.

The study of thermodynamics is often limited to classical thermodynamics where minimal laws and concepts lead to a wealth of equations and applications. The resultant equations best describe systems at equilibrium with no temporal or s- tial parameters. The equations do, however, often provide accurate descriptions for systems close to equilibrium. . Statistical thermodynamics produces the same equilibrium information starting with the microscopic properties of the atoms or molecules in the system that correlates with the results from macroscopic classical thermodynamics. Because both these disciplines develop a wealth of information from a few starting postulates, e. g. , the laws of thermodyamics, they are often introduced as independent disciplines. However, the concepts and techniques dev- oped for these disciplines are extremely useful in many other disciplines. This book is intended to provide an introduction to these disciplines while revealing the connections between them. Chemical kinetics uses the statistics and probabilities developed for statistical thermodynamics to explain the evolution of a system to equilibrium. Irreversible thermodynamics, which is developed from the equations of classical thermodyn- ics, centers on distance-dependent forces, and time-dependent ?uxes. The force ?ux equations of irreversible thermodynamics lead are generated from the intensive and extensive variables of classical thermodynamics. These force ?ux equations lead, in turn, to transport equations such as Fick's ?rst law of diffusion and the Nernst Planck equation for electrochemical transport. The book illustrates the concepts using some simple examples.

This collection of lectures covers a wide range of present day research in thermodynamics and the theory of phase transitions far from equilibrium. The contributions are written in a pedagogical style and present an extensive bibliography to help graduates organize their further studies in this area. The reader will find lectures on principles of pattern formation in physics, chemistry and biology, phase instabilities and phase transitions, spatial and temporal structures in optical systems, transition to chaos, critical phenomena and fluctuations in reaction-diffusion systems, and much more.

Hydrogen in Intermetallics I is the first of two volumes aiming to provide atutorial introduction to the general topic of hydrogen in intermetallic compounds and alloys. In the present volume, a series of chapters, each written by two experts in the field, gives a comprehensive review of thefollowing areas: -preparation of intermetallics and their hydrides on a laboratory and industrial scale; - thermodynamic properties; -crystal and magnetic structure; - electronic properties; - heat of formation models; - magnetism and superconductivity.

More than to any other single individual, thermodynamics owes its creation to Nicolas-Leonard-Sadi ' Carnot. Sadi, the son of the "great Carnot" Lazare, was he- ily in uencedby his father. Not onlywas LazareMinister of War duringNapoleon's consulate, he was a respected mathematician and engineer in his own right. Ma- ematically, Lazare can lay claim to the de nition of the cross ratio, a projective invariant of four points. Lazare was also interested in how machines operated, - phasizing the roles of work and "vis viva," or living force, which was later to be associated with the kinetic energy. He arrived at a dynamical theory that machines in order to operate at maximum ef ciency should avoid "any impact or sudden change. " This was the heritage he left to his son Sadi. The mechanics of Newton, in his Principia, was more than a century old. It dealt with the mechanics of conservative systems in which there was no room for p- cesses involving heat and friction. Such processes would ruin the time reversibility of mechanical laws, which could no longer be derived by minimizing the difference between kinetic and potential energies. When Sadi wrote his only scienti c work in 1824, there were no laws governing the mechanical effects of heat. In fact, caloric theory was still in vogue, which treated heat as an imponderable uid that was c- served.

In this comprehensive text a systematic numerical and analytical treatment of the procedures for reducing complicated systems to a simplified reaction mechanism is presented. The results of applying the reduced reaction mechanism to a one-dimensional laminar flame are discussed. A set of premixed and non-premixed methane-air flames with simplified transport and skeletal chemistry are employed as test problems that are used later on to evaluate the results and assumptions in reduced reaction networks. The first four chapters form a short tutorial on the procedures used in formulating the test problems and in reducing reaction mechanisms by applying steady-state and partial-equilibrium approximations. The final six chapters discuss various aspects of the reduced chemistry problem for premixed and nonpremixed combustion.

In this volume the author gives a detailed presentation of his theory of multiphase mixtures with structure. The book also addresses students, and in addition encourages further research. Based on the concept of averaging the field equations, conservation and balance equations are developed. A material deformation postulate leads to structured mixtures. The resulting model is compared with those in use elsewhere. The final chapters are devoted to constitutive theory and constitutive equations. In particular, two-phase mixtures are treated in some detail.

This thesis presents a novel coarse-grained model of DNA, in which bases are represented as rigid nucleotides. The model is shown to quantitatively reproduce many phenomena, including elastic properties of the double-stranded state, hairpin formation in single strands and hybridization of pairs of strands to form duplexes, the first time such a wide range of properties has been captured by a coarse-grained model. The scope and potential of the model is demonstrated by simulating DNA tweezers, an iconic nanodevice, and a two-footed DNA walker - the first time that coarse-grained modelling has been applied to dynamic DNA nanotechnology.

This book reviews the basic ideas of the Law of Large Numbers with its consequences to the deterministic world and the issue of ergodicity. Applications of Large Deviations and their outcomes to Physics are surveyed. The book covers topics encompassing ergodicity and its breaking and the modern applications of Large deviations to equilibrium and non-equilibrium statistical physics, disordered and chaotic systems, and turbulence.

There are many examples of cooperation in Nature: cells cooperate to form tissues, organs cooperate to form living organisms, and individuals cooperate to raise their offspring or to hunt. However, why cooperation emerges and survives in hostile environments, when defecting would be a much more profitable short-term strategy, is a question that still remains open. During the past few years, several explanations have been proposed, including kin and group selection, punishment and reputation mechanisms, or network reciprocity. This last one will be the center of the present study. The thesis explores the interface between the underlying structure of a given population and the outcome of the cooperative dynamics taking place on top of it, (namely, the Prisoner's Dilemma Game). The first part of this work analyzes the case of a static system, where the pattern of connections is fixed, so it does not evolve over time. The second part develops two models for growing topologies, where the growth and the dynamics are entangled.

What are the principles that keep our society together? This question is even more difficult to answer than the long-standing question, what are the forces that keep our world together. However, the social challenges of humanity in the 21st century ranging from the financial crises to the impacts of globalization, require us to make fast progress in our understanding of how society works, and how our future can be managed in a resilient and sustainable way. This book can present only a few very first steps towards this ambitious goal. However, based on simple models of social interactions, one can already gain some surprising insights into the social, ``macro-level'' outcomes and dynamics that is implied by individual, ``micro-level'' interactions. Depending on the nature of these interactions, they may imply the spontaneous formation of social conventions or the birth of social cooperation, but also their sudden breakdown. This can end in deadly crowd disasters or tragedies of the commons (such as financial crises or environmental destruction). Furthermore, we demonstrate that classical modeling approaches (such as representative agent models) do not provide a sufficient understanding of the self-organization in social systems resulting from individual interactions. The consideration of randomness, spatial or network interdependencies, and nonlinear feedback effects turns out to be crucial to get fundamental insights into how social patterns and dynamics emerge. Given the explanation of sometimes counter-intuitive phenomena resulting from these features and their combination, our evolutionary modeling approach appears to be powerful and insightful. The chapters of this book range from a discussion of the modeling strategy for socio-economic systems over experimental issues up the right way of doing agent-based modeling. We furthermore discuss applications ranging from pedestrian and crowd dynamics over opinion formation, coordination, and cooperation up to conflict, and also address the response to information, issues of systemic risks in society and economics, and new approaches to manage complexity in socio-economic systems. Selected parts of this book had been previously published in peer reviewed journals.