Chemistry education computer simulations

Luyben, W. L. (1993). Dynamics and Control of Recycle Systems. I. Simple Open-Loop and Closed-Loop Systems. Industrial engineering chemistry research, 32(3), 466 75. Ghosh, (2004). Control Systems Theory And Applications.. Pearson Education. 628. Huang, B. K. (1994). Computer Simulation Analysis of Biological and Agricultural Systems. Taylor Francis. 880. 

The credit load for die computational chemistry laboratory course requires that the average student should be able to complete almost all of the work required for the course within die time constraint of one four-hour laboratory period per week. This constraint limits the material covered in the course. Four principal computational methods have been identified as being of primary importance in the practice of chemistry and thus in the education of chemistry students (1) Monte Carlo Methods, (2) Molecular Mechanics Methods, (3) Molecular Dynamics Simulations, and (4) Quantum Chemical Calculations. Clearly, other important topics could be added when time permits. These four methods are developed as separate units, in each case beginning with die fundamental principles including simple programming and visualization, and building to the sophisticated application of the technique to a chemical problem. 

Previous studies have reported that pre-laboratory exercises in Physics can improve student performance and improve student perceptions of the laboratory (Johnstone et al. 1998), however, the additional marking was seen as apotential disincentive (Reid and Shah, 2007). A number of studies have reported the use of computer based exercises to support the pre-laboratory work, particularly in Chemistry (e.g. McKelvey 2000) where it has been in use for over 10 years, and sophisticated online Dynamic Laboratory Manuals have been created incorporating video clips and interactive simulations (www.chemlabs.bris.ac.uk). There are also a number of uses of computer assisted pre-laboratory work in the biosciences (Adams 2009). One of these (Dantas and Kemm 2008) points out the importanee of including assessment, as simply making e-resources available will not itself motivate students. The use of online pre-laboratory work has not been reported in the engineering education literature. 

CC has developed into a very broad field, and it is impossible, especially at the undergraduate level, to educate and train the students in all of its aspects. Consequently, in this aiti-cle we will have to focus on the teaching of those subjects of CC which directly relate to computation, such as molecular mechanics (MM), quantum chemistry (QC), and molecular modeling, as well as molecular simulation (molecular dynamics (MD), Monte Carlo (MC)). Topics such as chemometrics. 

As part of the education for graduate students, ETH Zurich, like many other European universities, does not offer a graduate school , but advanced lectures in molecular dynamics and molecular simulation (W. F. van Gunsteren), and numerical quantum chemistry (T. K. Ha, H. P. LUthi) are offered. In these courses the modern methods in molecular dynamics and ab initio quantum chemistry are addressed and discussed based on examples from the current research literature. These lectures are also part of the ETH Computational Science and Engineering curriculum, a program which offers a degree based on an education with an interdisciplinary character (chemistry, physics, biology, mathematics, and computer science see http //www.inf.ethz.ch/departinent/WR/RW/). 

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