QM/MM Methods

· ACS In Focus Ibhuku elingu-1 · American Chemical Society
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Izilinganiso nezibuyekezo aziqinisekisiwe  Funda Kabanzi

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Many chemical, physical, and biological processes occur in complex environments and span multiple scales in space and time. Combined (hybrid or integrated) quantum-mechanics/molecular-mechanics (QM/MM) is one family of multiscale algorithms for computer modeling these processes. First introduced in 1976, along with critical developments over the following decades, QM/MM is now a popular and powerful tool that helps scientists simultaneously capture the fundamental atomistic details and the overall big picture of these processes.

 

Instead of providing a comprehensive survey of the QM/MM algorithms and their applications, QM/MM Methods focuses on explaining the key concepts in QM/MM methodology and how to interpret the results in applications. The author frequently uses small “toy” model systems to illustrate the fundamental principles, which can be easily generalized to large model systems. Unavoidably, formal proofs and many technical details are left out, for which readers are referred to the relevant literature.

 

QM/MM Methods helps researchers enter the field with a good starting position, empowering them to ask the right questions in their QM/MM applications and select suitable algorithms to address them.

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Hai Lin is a Professor in the Department of Chemistry at the University of Colorado Denver. He received his B.E. in Computer Science in 1993, M.S. in Physics in 1995, and Ph.D. in Chemistry in 1998, all from the University of Science and Technology of China. He was an Alexander von Humboldt Fellow in Universität-Wuppertal, a Max-Planck Postdoctoral Fellow at Max-Planck-Institut für Kohlenforschung, and a Minnesota Supercomputing Institute Scholar at the University of Minnesota. He became an Assistant Professor at the University of Colorado Denver in 2005. He received an NSF CAREER Award, was named a Cottrell Scholar, and was honored with a Henry Dreyfus Teacher-Scholar Award.


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