Insight engineering concepts

The primary purpose of this book is to convey insight into why semiconductors are the way they are, either because of how their atoms bond with one another, because of mistakes in their structure, or because of how they are produced or processed. The approach is to explore both the science of how atoms interact and to connect the results to real materials properties, and to show the engineering concepts that can be used to produce or improve a semiconductor by design. Along with this I hope to show some applications for the topics under discussion so that one may see how the concepts are applied in the laboratory. 

The movement from the deterministic design criteria as described by equation 4.1 to the probability based one described by equation 4.2 has far reaching effects on design (Haugen, 1980). The particular change which marks the development of modern engineering reliability is the insight that probability, a mathematical theory, can be utilized to quantify the qualitative concept of reliability (Ben-Haim, 1994). 

In the electronics industry, a large number of relatively small firms play a key role in generating new process concepts and equipment. These firms face important research problems in fundamental science and engineering that would benefit markedly from the insights of academic chemical engineering researchers. Academic researchers should seek out and forge links to these small firms that stand at the crucial step between laboratory research and production processes. Potential mechanisms for accomplishing this are described in Chapter 10. 

Chemical kinetics deals with quantitative studies of the rates at which chemical processes occur, the factors on which these rates depend, and the molecular acts involved in reaction processes. A description of a reaction in terms of its constituent molecular acts is known as the mechanism of the reaction. Physical and organic chemists are primarily interested in chemical kinetics for the light that it sheds on molecular properties. From interpretations of macroscopic. kinetic data in terms of molecular mechanisms, they can gain insight into the nature of reacting systems, the processes by which chemical bonds are made and broken, and the structure of the resultant product. Although chemical engineers find the concept of a reaction mechanism useful in the correlation, interpolation, and extrapolation of rate data, they are more concerned with applications... 

Finally, we want to point out that the concept of the endoreversible engine is a simplification that leads to a quick and clear insight into the role and thermodynamic cost of transfer processes in reducing the Carnot efficiency into smaller and more realistic values. But for finding the real optimum conditions, the concept of endoreversibility has to be sacrificed. This will complicate the matter to some extent but will allow for including all contributions to the lost work ... 

Jim Downs (1992) of Eastman Chemical Company has insightfully pointed out the importance of looking at the chemical component balances around the entire plant and checking to see that the control structure handles these component balances effectively. The concepts of overall component balances go back to our first course in chemical engineering, where we learned how to apply mass and energy balances to any system, microscopic or macroscopic. We did these balances for individual unit operations, for sections of a plant, and for entire processes. 

This Study Guide and Solutions Manual accompanies the textbook Chemical Principles The Quest for Insight, Fourth Edition, by Peter Atkins and Loretta Jones — an authoritative and thorough introduction to chemistry for students anticipating careers in science or engineering disciplines. We have followed the order of topics in the textbook chapter for chapter. The parallel between the symbols, concepts, and style of this supplement and the textbook enables the reader to easily move back and forth between the two. 

Due to the large number of domain concepts, ever-changing application areas, newly arising insights, and the continuous update of technological capabilities for model representation, the development of product data models for a complex domain is deemed to be an evolutionary process. Since the early nineties, several product data models have been developed by the authors and their former colleagues, which model various aspects of the chemical engineering domain. The results are VeDa [10, 55], CLiP [14, 19], and OntoCAPE [325, 326], the second version of which has been released lately. 

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