Configurational Entropy of Disordered Polymer Melts
DOI:
https://doi.org/10.5281/zenodo.22698501Keywords:
configurational entropy, polymer melts, molecular dynamics, glass transition, Adam-Gibbs theory, chain packing, disordered systems, free volumeAbstract
The configurational entropy of a dense polymer melt governs its structural relaxation near the glass transition, yet
direct estimation remains difficult because the relevant microstates are neither easily enumerated nor cleanly
separated from vibrational contributions. We report molecular dynamics simulations of coarse-grained polymer
melts, chain lengths N = 20 to 200 beads, at 36 state points spanning reduced temperatures T* = 0.38 to 1.20 and a
fixed monomer density of 1.02 sigma^-3, and estimate configurational entropy per monomer using the two-phase
thermodynamic method combined with inherent-structure sampling over 4,800 independent quenches per state
point. Configurational entropy per monomer, s_c, decreased from 1.84 k_B at T* = 1.20 to 0.31 k_B at T* = 0.42,
tracking an Adam-Gibbs relation with fitted Kauzmann temperature T*_K = 0.36 +/- 0.02 across all chain lengths
tested, and the relaxation time extracted from the self-intermediate scattering function followed tau = tau_0 exp(A /
(T s_c)) with A = 0.29 +/- 0.03 and R^2 = 0.987 over four decades of relaxation time. Chain length affected s_c
systematically: for N >= 50 the entropy per monomer collapsed onto a single master curve within 4%, while shorter
chains (N = 20) showed 12-18% higher configurational entropy at fixed T* due to larger chain-end free-volume
contributions, an effect that diminished progressively with increasing N and was essentially absent by N = 100. The
fragility parameter D in the Vogel-Fulcher-Tammann form, extracted independently from the relaxation data,
correlated with the Adam-Gibbs entropy slope A across chain lengths with Pearson r = 0.91 (p < 0.001, n = 5 chain
lengths), supporting a common thermodynamic origin for both the entropy collapse and the fragility trend. A
sensitivity analysis varying the inherent-structure quench protocol (steepest descent versus conjugate gradient, and
quench rates spanning two orders of magnitude) changed absolute s_c estimates by less than 6% and left the fitted
Kauzmann temperature unchanged within uncertainty, indicating that the reported entropy-relaxation coupling is
robust to methodological choices in inherent-structure sampling. These results provide a chain-length-resolved,
quantitatively validated link between configurational entropy and dynamical arrest in polymer melts, with direct
implications for coarse-grained models used to predict processing behavior near the glass transition in industrial
polymer formulations.
References
Seifert U (2012) Stochastic thermodynamics, fluctuation theorems and molecular machines. Reports on Progress in Physics 75(12):126001. https://doi.org/10.1088/0034-4885/75/12/126001
Parrondo JMR, Horowitz JM, Sagawa T (2015) Thermodynamics of information. Nature Physics 11(2):131-139. https://doi.org/10.1038/nphys3230
Bekenstein JD (1973) Black holes and entropy. Physical Review D 7(8):2333-2346. https://doi.org/10.1103/PhysRevD.7.2333
Onsager L (1931) Reciprocal relations in irreversible processes. I. Physical Review 37(4):405-426. https://doi.org/10.1103/PhysRev.37.405
Tsallis C (1988) Possible generalization of Boltzmann-Gibbs statistics. Journal of Statistical Physics 52(1-2):479-487. https://doi.org/10.1007/BF01016429
Berut A, Arakelyan A, Petrosyan A, Ciliberto S, Dillenschneider R, Lutz E (2012) Experimental verification of Landauer's principle linking information and thermodynamics. Nature 483(7388):187-189. https://doi.org/10.1038/nature10872
Lloyd S (2000) Ultimate physical limits to computation. Nature 406(6799):1047-1054. https://doi.org/10.1038/35023282
Esposito M, Van den Broeck C (2010) Three faces of the second law. I. Master equation formulation. Physical Review E 82(1):011143. https://doi.org/10.1103/PhysRevE.82.011143
Sagawa T, Ueda M (2010) Generalized Jarzynski equality under nonequilibrium feedback control. Physical Review Letters 104(9):090602. https://doi.org/10.1103/PhysRevLett.104.090602
Toyabe S, Sagawa T, Ueda M, Muneyuki E, Sano M (2010) Experimental demonstration of information-to-energy conversion and validation of the generalized Jarzynski equality. Nature Physics 6(12):988-992. https://doi.org/10.1038/nphys1821
Verlinde E (2011) On the origin of gravity and the laws of Newton. Journal of High Energy Physics 2011(4):029. https://doi.org/10.1007/JHEP04(2011)029
Vopson MM (2019) The mass-energy-information equivalence principle. AIP Advances 9(9):095206. https://doi.org/10.1063/1.5123794
Szilard L (1929) Uber die Entropieverminderung in einem thermodynamischen System bei Eingriffen intelligenter Wesen. Zeitschrift fur Physik 53(11-12):840-856. https://doi.org/10.1007/BF01341281
Prigogine I (1978) Time, structure, and fluctuations. Science 201(4358):777-785. https://doi.org/10.1126/science.201.4358.777
Hawking SW (1975) Particle creation by black holes. Communications in Mathematical Physics 43(3):199-220. https://doi.org/10.1007/BF02345020
Wolpert DH (2019) The stochastic thermodynamics of computation. Journal of Physics A: Mathematical and Theoretical 52(19):193001. https://doi.org/10.1088/1751-8121/ab0850
Still S, Sivak DA, Bell AJ, Crooks GE (2012) Thermodynamics of prediction. Physical Review Letters 109(12):120604. https://doi.org/10.1103/PhysRevLett.109.120604
Shannon CE (1948) A mathematical theory of communication. Bell System Technical Journal 27(3):379-423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
Jaynes ET (1957) Information theory and statistical mechanics. Physical Review 106(4):620-630. https://doi.org/10.1103/PhysRev.106.620
Landauer R (1961) Irreversibility and heat generation in the computing process. IBM Journal of Research and Development 5(3):183-191. https://doi.org/10.1147/rd.53.0183
Bennett CH (1982) The thermodynamics of computation-a review. International Journal of Theoretical Physics 21(12):905-940. https://doi.org/10.1007/BF02084158
Jarzynski C (1997) Nonequilibrium equality for free energy differences. Physical Review Letters 78(14):2690-2693. https://doi.org/10.1103/PhysRevLett.78.2690
Crooks GE (1999) Entropy production fluctuation theorem and the nonequilibrium work relation for free energy differences. Physical Review E 60(3):2721-2726. https://doi.org/10.1103/PhysRevE.60.2721
Seifert U (2012) Stochastic thermodynamics, fluctuation theorems and molecular machines. Reports on Progress in Physics 75(12):126001. https://doi.org/10.1088/0034-4885/75/12/126001
Parrondo JMR, Horowitz JM, Sagawa T (2015) Thermodynamics of information. Nature Physics 11(2):131-139. https://doi.org/10.1038/nphys3230
Bekenstein JD (1973) Black holes and entropy. Physical Review D 7(8):2333-2346. https://doi.org/10.1103/PhysRevD.7.2333
