Home » Computing
Category Archives: Computing
The Nobel Prize in Chemistry 2007 awarded to Gerhard Ertl for his groundbreaking studies in surface chemistry highlighted the importance of heterogeneous catalysis not only for modern chemical industry but also for environmental protection.
Heterogeneous catalysis is seen as one of the key technologies which could solve the challenges associated with the increasing diversification of raw materials and energy sources. It is the decisive step in most chemical industry processes, a major method of reducing pollutant emissions from mobile sources and is present in fuel cells to produce electricity.
The increasing power of computers over the last decades has led to modeling and numerical simulation becoming valuable tools in heterogeneous catalysis. This book covers many aspects, from the state-of-the-art in modeling and simulations of heterogeneous catalytic reactions on a molecular level to heterogeneous catalytic reactions from an engineering perspective.
This first book on the topic conveys expert knowledge from surface science to both chemists and engineers interested in heterogeneous catalysis. The well-known and international authors comprehensively present many aspects of the wide bridge between surface science and catalytic technologies, including DFT calculations, reaction dynamics on surfaces, Monte Carlo simulations, heterogeneous reaction rates, reactions in porous media, electro-catalytic reactions, technical reactors, and perspectives of chemical and automobile industry on modeling heterogeneous catalysis. The result is a one-stop reference for theoretical and physical chemists, catalysis researchers, materials scientists, chemical engineers, and chemists in industry who would like to broaden their horizon and get a substantial overview on the different aspects of modeling and simulation of heterogeneous catalytic reactions.
This book synthesizes current research in the integration of computational intelligence and pattern analysis techniques, either individually or in a hybridized manner. The purpose is to analyze biological data and enable extraction of more meaningful information and insight from it. Biological data for analysis include sequence data, secondary and tertiary structure data, and microarray data. These data types are complex and advanced methods are required, including the use of domain-specific knowledge for reducing search space, dealing with uncertainty, partial truth and imprecision, efficient linear and/or sub-linear scalability, incremental approaches to knowledge discovery, and increased level and intelligence of interactivity with human experts and decision makers.
Using computers to solve problems and model physical problems has fast become an integral part of undergraduate and graduate education in physics. This 3rd year undergraduate and subsequent graduate course is a supplement to courses in theoretical physics and develops problem-solving techniques using the computer. It makes use of the newest version of Mathematica (3.0) while still remaining compatible with older versions The programs using Mathematica 3.0 and C are written for both PCs and workstations, and the problems, source files, and graphic routines help students gain experience from the very beginning.
Nowadays the computer is an important tool in physics. The acquisition and analysis of extensive experimental data and the control of complex experiments are hardly imaginable without the use of computers. In theoretical
physics the computer has turned from a mere calculator to a comprehensive tool. Graphical displays, numerical and algebraic solutions of equations, and extensive simulations of microscopic models have become important methods for the exploration of the laws of physics.
The computer, however, is not just a tool, it also offers new perspectives and opens new areas of research. Until recently physicists generally described nature with differential equations; nowadays discrete algorithms are also used.
For some apparently simple physical models there are only numerical answers so far. We know universal laws that any high school student can reproduce on a pocket calculator, for which there is, however, no analytical theory (yet?).
In addition to this, the computer opens up new fields to physics: neural networks, combinatorial optimization, biological evolution, formation of fractal structures, and self-organized criticality are just some of the topics from the growing field of complex systems.
Almost every advanced undergraduate or graduate physics student uses a computer at one time or another. Nonetheless, computer training and the use of computers in teaching are still by no means the expected norm, but rather the exception. The literature in this field is correspondingly sparse.
The goal of our textbook is to contribute to filling this gap.
This book evolved out of lectures at the University of Wiirzburg, Germany, for physics majors after their fourth semester – those having completed the introductory coursework in theoretical physics. It is conceived as a text book in computational physics but may also serve as a supplement to the traditional physics classes in which the possibilities of computer use have so far been underutilized. We would like to show the reader how to solve physics problems using the computer. Experience with computers and computer languages is helpful, but not necessary, for we want to present an introduction and explain the first steps with computers and algorithms. This book does not contain many details about numerical mathematics, it does not offer a course on programming languages, nor does it teach advanced methods of
computer-oriented theoretical physics. It does, however, introduce numerous physics problems, some of which are at the cutting edge of research, and tries to solve them with simple algorithms.
One goal is to encourage our readers to do their own programming. Although a CD-ROM with finished programs is enclosed with the book, they are not meant as user-friendly experimental environments. We hope that instead they can be taken as a starting-point, and we encourage our readers to modify them, or better yet to rewrite them more efficiently. Exercises accompany every section of this introductory book.
We have received suggestions from many colleagues and students, to whom we wish to express our thanks. We would like especially to mention M. Biehl, H. Dietz, A. Engel, A. Freking, Th. Hahn, W. Hanke, G. Hildebrand, A. Jung, A. Karch, U. Krey, B. Lopez, J. Nestler, M. Opper, M. Schreckenberg, and D. Stauffer. Special thanks go to the following three people: Martin Liiders developed the program package Xgraphics, Martin Schroder wrote the section on Unix, and Ursula Eitelwein typed the manuscript of this book in UTEX.
Finally we would like to thank Martin Clajus for valuable suggestions in the course of translating this textbook into English.