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Cited by 408

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Molecular Driving Forces: Statistical Thermodynamics in Biology, Chemistry, Physics, and Nanoscience

Dill, Ken A., Bromberg, Sarina, Stigter, Dirk·2010·Garland Science eBooks

Abstract

Molecular Driving Forces, Second Edition E-book is an introductory statistical thermodynamics text that describes the principles and forces that drive chemical and biological processes. It demonstrates how the complex behaviors of molecules can result from a few simple physical processes, and how simple models provide surprisingly accurate insights into the workings of the molecular world. Widely adopted in its First Edition, Molecular Driving Forces is regarded by teachers and students as an accessible textbook that illuminates underlying principles and concepts. The Second Edition includes two brand new chapters: (1) "Microscopic Dynamics" introduces single molecule experiments; and (2) "Molecular Machines" considers how nanoscale machines and engines work. "The Logic of Thermodynamics" has been expanded to its own chapter and now covers heat, work, processes, pathways, and cycles. New practical applications, examples, and end-of-chapter questions are integrated throughout the revised and updated text, exploring topics in biology, environmental and energy science, and nanotechnology. Written in a clear and reader-friendly style, the book provides an excellent introduction to the subject for novices while remaining a valuable resource for experts.

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Metadata

Authors
Dill, K. A., Bromberg, S., & Stigter, D.
Venue
Garland Science eBooks
Published
2010-10-21
OpenAlex
W1485352641
Cited by
408
References
0
FWCI
3.30
Type
book
Language
en
Open access
closed

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CoChat. (2026). Citation check: Molecular Driving Forces: Statistical Thermodynamics in Biology, Chemistry, Physics, and Nanoscience. https://app.cochat.ai/papers/10.4324/9780203809075
The paper
Dill, K. A., Bromberg, S., & Stigter, D. (2010). Molecular Driving Forces: Statistical Thermodynamics in Biology, Chemistry, Physics, and Nanoscience. Garland Science eBooks. https://doi.org/10.4324/9780203809075

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.