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High throughput experimentation has met great success in drug design but it has, so far, been scarcely used in the field ofcatalysis. We present in this book the outcome of a NATO ASI meeting that was held in Vilamoura, Portugal, between July 15 and 28, 2001, with the objective of delineating and consolidating the principles and methods underpinning accelerated catalyst design, evaluation, and development. There is a need to make the underlying principles of this new methodology more widely understood and to make it available in a coherent and integrated format. The latter objective is particularly important to the young scientists who will constitute the new catalysis researchers generation. Indeed, this field which is at the frontier offundamental science and may be a renaissance for catalysis, is one which is much more complex than classical catalysis itself. It implies a close collaboration between scientists from many disciplines (chemistry, physics, chemical and mechanical engineering, automation, robotics, and scientific computing in general). In addition, this emerging area of science is also of paramount industrial importance, as progress in this area would collapse the time necessary to discover new catalysts or improve existing ones.
Written by a team of internationally recognized experts, this book addresses the most important types of catalytic reactions and catalysts as used in industrial practice. Both applied aspects and the essential scientific principles are described. The main topics can be summarized as follows: heterogeneous, homogeneous and biocatalysis, catalyst preparation and characterization, catalytic reaction engineering and kinetics, catalyst deactivation and industrial perspective.
The book provides a comprehensive treatment of combinatorial development of heterogeneous catalysts. In particular, two computer-aided approaches that have played a key role in combinatorial catalysis and high-throughput experimentation during the last decade — evolutionary optimization and artificial neural networks — are described. The book is unique in that it describes evolutionary optimization in a broader context of methods of searching for optimal catalytic materials, including statistical design of experiments, as well as presents neural networks in a broader context of data analysis. It is the first book that demystifies the attractiveness of artificial neural networks, explaining its rational fundamental — their universal approximation capability. At the same time, it shows the limitations of that capability and describes two methods for how it can be improved. The book is also the first that presents two other important topics pertaining to evolutionary optimization and artificial neural networks: automatic generating of problem-tailored genetic algorithms, and tuning evolutionary algorithms with neural networks. Both are not only theoretically explained, but also well illustrated through detailed case studies./a
In this first book to present every important aspect of this fascinating and developing field, the three editors A. Hagemeyer, P. Strasser and A. F. Volpe Jr. from Symyx Technologies have chosen a perfect mixture of distinguished, international authors from both academia and industry. Each chapter is devoted to a major topic - high-throughput experimentation methodologies, integrated combinatorial synthesis and screening workflow, and applications to chemical catalysts with an emphasis on heterogeneous catalysis, olefin polymerization and electrocatalysis for fuel cells. An indispensable source for everyone working in the field.
This practical book combines recent progress with a discussion of the general aspects of catalyst preparation. The first part deals with the basic principles of solid catalyst preparation, explaining the main aspects of sol-gel chemistry and interfacial chemistry, followed by such techniques as co-precipitation and immobilization. New tools for catalyst preparation research, including microspectroscopy and high-throughput experimentation, are also taken into account. The second part heightens the practical relevance by providing six case studies on such topics as the preparation of zeolites, hydrotreating catalysts, methanol catalysts and gold catalysts
Covering all aspects of transport phenomena on the nano- and micro-scale, this encyclopedia features over 750 entries in three alphabetically-arranged volumes including the most up-to-date research, insights, and applied techniques across all areas. Coverage includes electrical double-layers, optofluidics, DNC lab-on-a-chip, nanosensors, and more.
2.1 Text Summarization “Text summarization is the process of distilling the most important information from a source (or sources) to produce an abridged version for a particular user (or users) and task (or tasks)” [3]. Basic and classical articles in text summarization appear in “Advances in automatic text summarization” [3]. A literature survey on information extraction and text summarization is given by Zechner [7]. In general, the process of automatic text summarization is divided into three stages: (1) analysis of the given text, (2) summarization of the text, (3) presentation of the summary in a suitable output form. Titles, abstracts and keywords are the most common summaries in Academic papers. Usually, the title, the abstract and the keywords are the first, second, and third parts of an Academic paper, respectively. The title usually describes the main issue discussed in the study and the abstract presents the reader a short description of the background, the study and its results. A keyword is either a single word (unigram), e.g.: ‘learning', or a collocation, which means a group of two or more words, representing an important concept, e.g.: ‘machine learning', ‘natural language processing'. Retrieving collocations from text was examined by Smadja [5] and automatic extraction of collocations was examined by Kita et al. [1].
Data mining continues to be an emerging interdisciplinary field that offers the ability to extract information from an existing data set and translate that knowledge for end-users into an understandable way. Data Mining: Concepts, Methodologies, Tools, and Applications is a comprehensive collection of research on the latest advancements and developments of data mining and how it fits into the current technological world.