Polymer Physics
Abstract
This is a polymer physics textbook for upper level undergraduates and first year graduate students. Any student with a working knowledge of calculus, physics and chemistry should be able to read this book. The essential tools of the polymer physical chemist or engineer are derived in this book without skipping any steps. The book is a self-contained treatise that could also serve as a useful reference for scientists and engineers working with polymers. While no prior knowledge of polymers is assumed, the book goes far beyond introductory polymer texts in the scope of what is covered. The fundamental concepts required to fully understand polymer melts, solutions and gels in terms of both static structure and dynamics are explained in detail. Problems at the end of each Chapter provide the reader with the opportunity to apply what has been learned to practice. The book is divided into four parts. After an introduction in Chapter 1, where the necessary concepts from a first course on polymers are summarized, the conformations of single polymer chains are treated in Part 1. Part 2 deals with the thermodynamics of polymer solutions and melts, including the conformations of chains in those states. Part 3 applies the concepts of Part 2 to the formation and properties of polymer networks. Finally, Part 4 explains the essential aspects of how polymers move in both melt and solution states. In all cases, attention is restricted to concepts that are firmly entrenched in the field.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The chosen model chains were shorter than real bimodal materials, but the short chains were sufficiently long to form entanglements and the long chains were significantly longer than the short chains to mimic the bimodal character of practical systems.
“Due to computational limits, the chosen model chains were shorter than the chains of the real bimodal materials, but the short chains were sufficiently long to form entanglements [41] and the long chains were significantly longer than the short chains to mimic the bimodal character of 'practical' systems.”
From Molecular dynamics simulation of linear polyethylene blends: Effect of molar mass bimodality on topological characteristics and mechanical behavior (2019) · cites this paper as [41]
Cited by
Sorted by citations
Valence and patterning of aromatic residues determine the phase behavior of prion-like domains
Martin, E. W., Holehouse, A. S., Peran, I., Farag, M., Incicco, J. J., Bremer, A., Grace, C. R., Soranno, A., Pappu, R. V., & Mittag, T. (2020) · Science · doi:10.1126/science.aaw8653 · Cited by 1,147 · see citing works
Exploring the three-dimensional organization of genomes: Interpreting chromatin interaction data
Dekker, J., Marti-Renom, M. A., & Mirny, L. A. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3454 · Cited by 1,068 · see citing works
Fracture and adhesion of soft materials: a review
Creton, C., & Ciccotti, M. (2016) · Reports on Progress in Physics · doi:10.1088/0034-4885/79/4/046601 · Cited by 915 · see citing works
Harmon, T. S., Holehouse, A. S., Rosen, M. K., & Pappu, R. V. (2017) · eLife · doi:10.7554/elife.30294 · Cited by 713 · see citing works
Heterochromatin drives compartmentalization of inverted and conventional nuclei
Falk, M., Feodorova, Y., Naumova, N., Imakaev, M., Lajoie, B. R., Leonhardt, H., Joffe, B., Dekker, J., Fudenberg, G., Solovei, I., et al. (2019) · Nature · doi:10.1038/s41586-019-1275-3 · Cited by 646 · see citing works
Expanding plastics recycling technologies: chemical aspects, technology status and challenges
Li, H., Aguirre-Villegas, H. A., Allen, R. D., Bai, X., Benson, C. H., Beckham, G. T., Bradshaw, S. L., Brown, J. L., Brown, R. C., Cecon, V. S., et al. (2022) · Green Chemistry · doi:10.1039/d2gc02588d · Cited by 616 · see citing works
Quantifying the impact of molecular defects on polymer network elasticity
Zhong, M., Wang, R., Kawamoto, K., Olsen, B. D., & Johnson, J. A. (2016) · Science · doi:10.1126/science.aag0184 · Cited by 528 · see citing works
50th Anniversary Perspective: Networks and Gels: Soft but Dynamic and Tough
Creton, C. (2017) · Macromolecules · doi:10.1021/acs.macromol.7b01698 · Cited by 463 · see citing works
Polymer Networks: From Plastics and Gels to Porous Frameworks
Gu, Y., Zhao, J., & Johnson, J. A. (2020) · Angewandte Chemie International Edition · doi:10.1002/anie.201902900 · Cited by 388 · see citing works
Photoswitching topology in polymer networks with metal–organic cages as crosslinks
Gu, Y., Alt, E. A., Wang, H., Li, X., Willard, A. P., & Johnson, J. A. (2018) · Nature · doi:10.1038/s41586-018-0339-0 · Cited by 371 · see citing works
Hoy, R. S., Foteinopoulou, K., & Kröger, M. (2009) · Physical Review E · doi:10.1103/physreve.80.031803 · Cited by 335 · see citing works
Molecular-level driving forces in lignocellulosic biomass deconstruction for bioenergy
Petridis, L., & Smith, J. C. (2018) · Nature Reviews Chemistry · doi:10.1038/s41570-018-0050-6 · Cited by 228 · see citing works
Instant Thermal Switching from Soft Hydrogel to Rigid Plastics Inspired by Thermophile Proteins
Nonoyama, T., Lee, Y. W., Ota, K., Fujioka, K., Hong, W., & Gong, J. P. (2020) · Advanced Materials · doi:10.1002/adma.201905878 · Cited by 208 · see citing works
Progress of shape memory polymers and their composites in aerospace applications
Li, F., Liu, Y., & Leng, J. (2019) · Smart Materials and Structures · doi:10.1088/1361-665x/ab3d5f · Cited by 180 · see citing works
Combined one-way and two-way shape memory in a glass-forming nematic network
Qin, H., & Mather, P. T. (2009) · Macromolecules · doi:10.1021/ma8022926 · Cited by 179 · see citing works
Describing sequence–ensemble relationships for intrinsically disordered proteins
Mao, A. H., Lyle, N., & Pappu, R. V. (2013) · Biochemical Journal · doi:10.1042/bj20121346 · Cited by 135 · see citing works
Raquez, J., Vanderstappen, S., Meyer, F., Verge, P., Alexandre, M., Thomassin, J., Jérôme, C., & Dubois, P. (2011) · Chemistry – A European Journal · doi:10.1002/chem.201100496 · Cited by 133 · see citing works
Stochastic motion and transcriptional dynamics of pairs of distal DNA loci on a compacted chromosome
Brückner, D. B., Chen, H., Barinov, L., Zoller, B., & Gregor, T. (2023) · Science · doi:10.1126/science.adf5568 · Cited by 112 · see citing works
Cooperative Unfolding of Compact Conformations of the Intrinsically Disordered Protein Osteopontin
Kurzbach, D., Platzer, G., Schwarz, T. C., Henen, M. A., Konrat, R., & Hinderberger, D. (2013) · Biochemistry · doi:10.1021/bi400502c · Cited by 105 · see citing works
Lubrication by Polyelectrolyte Brushes
Zhulina, E. B., & Rubinstein, M. (2014) · Macromolecules · doi:10.1021/ma500772a · Cited by 100 · see citing works
Self-citationMoyassari, A., Gkourmpis, T., Hedenqvist, M. S., & Gedde, U. W. (2019) · Polymer · doi:10.1016/j.polymer.2018.12.012 · Cited by 82 · see citing works
Sliozberg, Y. R., Yeh, I.-C., Kröger, M., Masser, K. A., Lenhart, J. L., & Andzelm, J. W. (2018) · Macromolecules · doi:10.1021/acs.macromol.8b01538 · Cited by 79 · see citing works
Engineering the Dynamic Properties of Protein Networks through Sequence Variation
Dooling, L. J., & Tirrell, D. A. (2016) · ACS Central Science · doi:10.1021/acscentsci.6b00205 · Cited by 63 · see citing works
Advancing reversible shape memory by tuning the polymer network architecture
Li, Q., Zhou, J., Vatankhah-Varnoosfaderani, M., Nykypanchuk, D., Gang, O., & Sheiko, S. S. (2016) · Macromolecules · doi:10.1021/acs.macromol.5b02740 · Cited by 61 · see citing works
Entanglements and dynamics of polymer melts near a SWCNT
Karatrantos, A., Composto, R. J., Winey, K. I., Kröger, M., & Clarke, N. (2012) · Macromolecules · doi:10.1021/ma3007637 · Cited by 53 · see citing works
Wittmer, J. P., Cavallo, A., Xu, H., Zabel, J. E., Polińska, P., Schulmann, N., Meyer, H., Farago, J., Johner, A., Obukhov, S. P., et al. (2011) · Journal of Statistical Physics · doi:10.1007/s10955-011-0354-0 · Cited by 38 · see citing works
A new coarse grained particle-to-mesh scheme for modeling soft matter
Zhang, G., Daoulas, K. C., & Kremer, K. (2013) · Macromolecular Chemistry and Physics · doi:10.1002/macp.201200520 · Cited by 32 · see citing works
Chemically defined, ultrasoft PDMS elastomers with selectable elasticity for mechanobiology
Heinrichs, V., Dieluweit, S., Stellbrink, J., Pyckhout-Hintzen, W., Hersch, N., Richter, D., & Merkel, R. (2018) · PLOS ONE · doi:10.1371/journal.pone.0195180 · Cited by 30 · see citing works
Lin, M.-C., Chen, H.-L., Lin, W.-F., Huang, P.-S., & Tsai, J.-C. (2012) · The Journal of Physical Chemistry B · doi:10.1021/jp306410j · Cited by 27 · see citing works
Palacios, J. K., Mugica, A., Zubitur, M., Iturrospe, A., Arbe, A., Liu, G., Wang, D., Zhao, J., Hadjichristidis, N., & Müller, A. J. (2016) · RSC Advances · doi:10.1039/c5ra25812j · Cited by 22 · see citing works
Mikes, P., Horakova, J., Saman, A., Vejsadova, L., Topham, P., Punyodom, W., Dumklang, M., & Jencova, V. (2021) · Journal of Industrial Textiles · doi:10.1177/1528083719848155 · Cited by 22 · see citing works
Palacios, J. K., Liu, G., Wang, D., Hadjichristidis, N., & Müller, A. J. (2019) · Macromolecular Chemistry and Physics · doi:10.1002/macp.201900292 · Cited by 15 · see citing works
ToPolyAgent: AI agents for coarse-grained bead-spring topological polymer simulations
Ding, L., Carrillo, J.-M., & Do, C. (2026) · Digital Discovery · doi:10.1039/d5dd00471c · Cited by 11 · see citing works
Role of Intrinsically Disordered Regions in Acceleration of Protein–Protein Association
Misiura, M. M., & Kolomeisky, A. B. (2020) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.9b08793 · Cited by 10 · see citing works
- Authors
- Rubinstein, M., & Colby, R. H.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Publisher
- Oxford University PressOxford
- Published
- 2003-06-26
- OpenAlex
- W4388376074
- Cited by
- 5,686
- References
- 0
- Citations by year
- 2026: 414 · 2025: 457 · 2024: 417 · 2023: 358 · 2022: 398 · 2021: 375 · 2020: 387 · 2019: 388 · 2018: 349 · 2017: 285 · 2016: 301 · 2015: 267 · 2014: 222 · 2013: 165 · 2012: 155
- FWCI
- 18.44
- Type
- book
- Language
- en
- Open access
- closed
- Topics
- Physical Sciences › Chemical Engineering › Fluid Flow and Transfer Processes › Rheology and Fluid Dynamics Studies
- Physical Sciences › Chemistry › Physical and Theoretical Chemistry › Advanced Physical and Chemical Molecular Interactions
- Physical Sciences › Materials Science › Materials Chemistry › Material Dynamics and Properties
- Keywords
- polymer physics, chain conformation, polymer melts, polymer solutions, polymer gels, polymer networks, polymer thermodynamics, polymer dynamics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review