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Articles de revues sur le sujet « Random polymers »

Auteur : Grafiati

Publié le 9 mars 2023

Mis à jour le 31 juillet 2025

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1

Hollander, F. "Random polymers." Statistica Neerlandica 50, no. 1 (1996): 136–45. http://dx.doi.org/10.1111/j.1467-9574.1996.tb01484.x.

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2

DURHUUS, BERGFINNUR, and THORDUR JONSSON. "A POLYMER GAS ON A RANDOM SURFACE." Modern Physics Letters A 13, no. 02 (1998): 153–57. http://dx.doi.org/10.1142/s021773239800019x.

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Using the observation that configurations of N polymers with hard core interactions on a closed random surface correspond to random surfaces with N boundary components, we calculate the free energy of a gas of polymers interacting with fully quantized two-dimensioanal gravity. We derive the equation of state for the polymer gas and find that all the virial coefficients beyond the second one vanish identically.

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3

Buffet, E., and J. V. Pul�. "Polymers and random graphs." Journal of Statistical Physics 64, no. 1-2 (1991): 87–110. http://dx.doi.org/10.1007/bf01057869.

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4

Tobita, Hidetaka. "Random Degradation of Branched Polymers. 1. Star Polymers." Macromolecules 29, no. 8 (1996): 3000–3009. http://dx.doi.org/10.1021/ma950971c.

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5

Hu, Liuyong, Wenqiang Qiao, Jinfeng Han, et al. "Naphthalene diimide–diketopyrrolopyrrole copolymers as non-fullerene acceptors for use in bulk-heterojunction all-polymer UV–NIR photodetectors." Polymer Chemistry 8, no. 3 (2017): 528–36. http://dx.doi.org/10.1039/c6py01828a.

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6

Stepanow, S. "Polymers in a random environment." Journal of Physics A: Mathematical and General 25, no. 23 (1992): 6187–92. http://dx.doi.org/10.1088/0305-4470/25/23/016.

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7

Kantor, Y., and M. Kardar. "Polymers with Random Self-Interactions." Europhysics Letters (EPL) 14, no. 5 (1991): 421–26. http://dx.doi.org/10.1209/0295-5075/14/5/006.

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8

FRANZ, SILVIO, MARC MÉZARD, and GIORGIO PARISI. "ON THE MEAN FIELD THEORY OF RANDOM HETEROPOLYMERS." International Journal of Neural Systems 03, supp01 (1992): 195–200. http://dx.doi.org/10.1142/s0129065792000528.

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We discuss some of the problems appearing in the Mean Field Theory of Random Heteropolymers. We show how an hypothesis of replica symmetry maps this problem onto a directed polymer in a random potential, and explain how this hypothesis can be checked through numerical simulations on directed polymers. The approach of Shaknovitch and Gutin is also reviewed in light of these findings.

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9

Lin, Yan-Cheng, Kosuke Terayama, Keita Yoshida, et al. "Strain-insensitive naphthalene-diimide-based conjugated polymers through sequential regularity control." Materials Chemistry Frontiers 6, no. 7 (2022): 891–900. http://dx.doi.org/10.1039/d1qm01521d.

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Sequential regularity control on the n-type conjugated polymers was investigated in this work. The sequentially random polymer produced a near-amorphous structure and a strain-insensitive charge transport performance.

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10

Yang, Wen Jun, Guo Zhu Liu, Ji Min Wang, and Du Ling Xia. "Synthesis of Zero-Birefringence Polymers Based on Positive and Negative Birefringence Polymer." Key Engineering Materials 428-429 (January 2010): 111–16. http://dx.doi.org/10.4028/www.scientific.net/kem.428-429.111.

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Birefringence of a polymer is caused by polymer chain orientation during an injection-molding, extrusion processing or heat drawing. Birefringence of polymers degrades the performance of optical devices that require focusing by lenses or maintaining the polarization state of incident light. Optical polymers which exhibit no birefringence with any orientation of polymer chains are desirable to realize high performance optical devices that handle polarized light. In this study we demonstrate the random copolymerization method for synthesizing the zero-birefringence polymers in which positive and

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11

Li, Hongze, Yingwu Luo, and Xiang Gao. "Core–shell nano-latex blending method to prepare multi-shape memory polymers." Soft Matter 13, no. 31 (2017): 5324–31. http://dx.doi.org/10.1039/c7sm00899f.

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12

Pei, Yi Wen, Jadranka Travas-Sejdic, and David E. Williams. "Synthesis and Characterization of Polysulfobetaines and their Random Copolymers." Materials Science Forum 700 (September 2011): 219–22. http://dx.doi.org/10.4028/www.scientific.net/msf.700.219.

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[3-(Methacryloylamino) propyl) dimethyl (3-sulfopropyl) ammonium hydroxide] polymer, known as poly (MPDSAH), and the random copolymers based on methyl methacrylate (MMA), methacryloxyethyltrimethylammonium (METAC) and 3-sulfopropyl methacrylate potassium (SPMA) were synthesized via Reversible Addition-Fragmentation Chain Transfer (RAFT) polymerization technique. Solution properties of these (co) polymers in response to temperature and ionic strength have been studied using dynamic light scattering (DLS). For poly (MPDSAH), polymer size decreased from 500 nm to 10 nm (in diameter) when the poly

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13

Hoffman, Allan S. "Bioconjugates of Intelligent Polymers and Recognition Proteins for Use in Diagnostics and Affinity Separations." Clinical Chemistry 46, no. 9 (2000): 1478–86. http://dx.doi.org/10.1093/clinchem/46.9.1478.

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Abstract Polymers that respond to small changes in environmental stimuli with large, sometimes discontinuous changes in their physical state or properties are often called “intelligent” or “smart” polymers. We have conjugated these polymers to different recognition proteins, including antibodies, protein A, streptavidin, and enzymes. These bioconjugates have been prepared by random polymer conjugation to lysine amino groups on the protein surface, and also by site-specific conjugation of the polymer to specific amino acid sites, such as cysteine sulfhydryl groups, that are genetically engineer

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14

Comets, Francis, Gregorio Moreno, and Alejandro F. Ramí rez. "Random polymers on the complete graph." Bernoulli 25, no. 1 (2019): 683–711. http://dx.doi.org/10.3150/17-bej1002.

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15

Gorokhov, D. A., and G. Blatter. "Marginal pinning of quenched random polymers." Physical Review B 62, no. 21 (2000): 14032–39. http://dx.doi.org/10.1103/physrevb.62.14032.

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16

Jögi, Per, and Didier Sornette. "Self-organized critical random directed polymers." Physical Review E 57, no. 6 (1998): 6936–43. http://dx.doi.org/10.1103/physreve.57.6936.

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17

AFONSO, M. MARTINS, and D. VINCENZI. "Nonlinear elastic polymers in random flow." Journal of Fluid Mechanics 540, no. -1 (2005): 99. http://dx.doi.org/10.1017/s0022112005005951.

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18

Staggs, J. E. J. "Modelling random scission of linear polymers." Polymer Degradation and Stability 76, no. 1 (2002): 37–44. http://dx.doi.org/10.1016/s0141-3910(01)00263-4.

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19

Wolf, M., and K. Fesser. "Random interchain coupling of conjugated polymers." Synthetic Metals 43, no. 1-2 (1991): 3403. http://dx.doi.org/10.1016/0379-6779(91)91314-z.

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20

Comets, Francis, and Nobuo Yoshida. "Brownian Directed Polymers in Random Environment." Communications in Mathematical Physics 254, no. 2 (2004): 257–87. http://dx.doi.org/10.1007/s00220-004-1203-7.

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21

Dua, Arti, and Thomas A. Vilgis. "Semiflexible polymers in a random environment." Journal of Chemical Physics 121, no. 11 (2004): 5505–13. http://dx.doi.org/10.1063/1.1783272.

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22

Zygouras, N. "Strong disorder in semidirected random polymers." Annales de l'Institut Henri Poincaré, Probabilités et Statistiques 49, no. 3 (2013): 753–80. http://dx.doi.org/10.1214/12-aihp483.

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23

Wolf, M., and K. Fesser. "Random interchain coupling of conjugated polymers." Journal of Physics: Condensed Matter 3, no. 29 (1991): 5489–98. http://dx.doi.org/10.1088/0953-8984/3/29/004.

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24

Klein, D. J., T. P. Zivković та N. Trinajstić. "Resonance in random π-network polymers". Journal of Mathematical Chemistry 1, № 3 (1987): 309–34. http://dx.doi.org/10.1007/bf01179796.

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25

Derrida, B. "Directed polymers in a random medium." Physica A: Statistical Mechanics and its Applications 163, no. 1 (1990): 71–84. http://dx.doi.org/10.1016/0378-4371(90)90316-k.

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26

Hossain, MA, Morium, M. Elias, et al. "Multi-phenyl structured aromatic hydrocarbon polymer." Bangladesh Journal of Scientific and Industrial Research 55, no. 2 (2020): 139–46. http://dx.doi.org/10.3329/bjsir.v55i2.47634.

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Multi-phenyl structured random polymer was synthesized via condensation polymerization reaction by applying different monomer ratios and characterized by various spectroscopic methods (FT-IR, 1H NMR). The prepared polymers showed good thermooxidative stability up to 400 ºC. The surface morphology was studied by FESEM that showed the good linkage among the polymer chains. The EDS data of poly(fluorenylene ether ketone), PFEK; demonstrated that all the monomers participated in the copolymerization reaction. Inherent viscosity values of the polymers were obtained in the range of 0.76∼1.12 dL g-1.

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27

Tashkinov, M. A., A. D. Dobrydneva, V. P. Matveenko, and V. V. Silberschmidt. "Modeling the Effective Conductive Properties of Polymer Nanocomposites with a Random Arrangement of Graphene Oxide Particles." PNRPU Mechanics Bulletin, no. 2 (December 15, 2021): 167–80. http://dx.doi.org/10.15593/perm.mech/2021.2.15.

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Сomposite materials are widely used in various industrial sectors, for example, in the aviation, marine and automotive industries, civil engineering and others. Methods based on measuring the electrical conductivity of a composite material have been actively developed to detect internal damage in polymer composite materials, such as matrix cracking, delamination, and other types of defects, which make it possible to monitor a composite’s state during its entire service life. Polymers are often used as matrices in composite materials. However, almost always pure polymers are dielectrics. The ad

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28

Raccosta, Samuele, Fabio Librizzi, Alistair M. Jagger, et al. "Scaling Concepts in Serpin Polymer Physics." Materials 14, no. 10 (2021): 2577. http://dx.doi.org/10.3390/ma14102577.

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α1-Antitrypsin is a protease inhibitor belonging to the serpin family. Serpin polymerisation is at the core of a class of genetic conformational diseases called serpinopathies. These polymers are known to be unbranched, flexible, and heterogeneous in size with a beads-on-a-string appearance viewed by negative stain electron microscopy. Here, we use atomic force microscopy and time-lapse dynamic light scattering to measure polymer size and shape for wild-type (M) and Glu342→Lys (Z) α1-antitrypsin, the most common variant that leads to severe pathological deficiency. Our data for small polymers

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29

Zygouras, Nikolaos. "Semidirected random polymers: Strong disorder and localization." Actes des rencontres du CIRM 2, no. 1 (2010): 47–48. http://dx.doi.org/10.5802/acirm.25.

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30

Jurjiu, A., R. Dockhorn, O. Mironova, and J. U. Sommer. "Two universality classes for random hyperbranched polymers." Soft Matter 10, no. 27 (2014): 4935. http://dx.doi.org/10.1039/c4sm00711e.

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31

Kardar, Mehran, and Yi-Cheng Zhang. "Scaling of Directed Polymers in Random Media." Physical Review Letters 58, no. 20 (1987): 2087–90. http://dx.doi.org/10.1103/physrevlett.58.2087.

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32

Sebastian, K. L., and K. Sumithra. "Adsorption of polymers on a random surface." Physical Review E 47, no. 1 (1993): R32—R35. http://dx.doi.org/10.1103/physreve.47.r32.

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33

Høye, Johan Skule, George Stell, and Chi-Lun Lee. "Ornstein−Zernike Random-Walk Approach for Polymers†." Journal of Physical Chemistry B 108, no. 51 (2004): 19809–17. http://dx.doi.org/10.1021/jp0404302.

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34

Sznitko, Lech, Jaroslaw Mysliwiec, and Andrzej Miniewicz. "The role of polymers in random lasing." Journal of Polymer Science Part B: Polymer Physics 53, no. 14 (2015): 951–74. http://dx.doi.org/10.1002/polb.23731.

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35

Zhang, Zhi-Yong, Shi-Jie Xiong, and S. N. Evangelou. "Electronic transport in random-side-chain polymers." Journal of Physics: Condensed Matter 10, no. 36 (1998): 8049–57. http://dx.doi.org/10.1088/0953-8984/10/36/014.

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36

Chakrabarti, Bikas K., Amit K. Chattopadhyay, and Amit Dutta. "Dynamics of linear polymers in random media." Physica A: Statistical Mechanics and its Applications 333 (February 2004): 34–40. http://dx.doi.org/10.1016/j.physa.2003.10.047.

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37

Hansen, Alex, Einar L. Hinrichsen, and St�phane Roux. "Non-directed polymers in a random medium." Journal de Physique I 3, no. 7 (1993): 1569–84. http://dx.doi.org/10.1051/jp1:1993201.

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38

Semenov, A. N. "Dynamics of associating polymers with random structure." Europhysics Letters (EPL) 76, no. 6 (2006): 1116–22. http://dx.doi.org/10.1209/epl/i2006-10396-9.

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39

Halpin-Healy, Timothy. "Directed polymers in random media: Probability distributions." Physical Review A 44, no. 6 (1991): R3415—R3418. http://dx.doi.org/10.1103/physreva.44.r3415.

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40

Berger, Quentin, and Niccolò Torri. "Directed polymers in heavy-tail random environment." Annals of Probability 47, no. 6 (2019): 4024–76. http://dx.doi.org/10.1214/19-aop1353.

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41

Trovato, A., J. van Mourik, and A. Maritan. "Swollen-collapsed transition in random hetero-polymers." European Physical Journal B 6, no. 1 (1998): 63–73. http://dx.doi.org/10.1007/s100510050527.

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42

Borodin, Alexei, Alexey Bufetov, and Ivan Corwin. "Directed random polymers via nested contour integrals." Annals of Physics 368 (May 2016): 191–247. http://dx.doi.org/10.1016/j.aop.2016.02.001.

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43

Scott, Kenneth W. "Criteria for random degradation of linear polymers." Journal of Polymer Science: Polymer Symposia 46, no. 1 (2009): 321–34. http://dx.doi.org/10.1002/polc.5070460124.

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44

Romm, Freddy A., and Oleg L. Figovsky. "Statistical polymer method: Modeling of macromolecules and aggregates with branching and crosslinking, formed in random processes." Discrete Dynamics in Nature and Society 2, no. 3 (1998): 203–8. http://dx.doi.org/10.1155/s1026022698000181.

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The statistical polymer method is based on the consideration of averaged structures of all possible macromolecules of the same weight. One has derived equations allowing evaluation of all additive parameters of macromolecules and their systems. The statistical polymer method allows modeling of branched crosslinked macromolecules and their systems in equilibrium or non-equilibrium. The fractal consideration of statistical polymer allows modeling of all kinds of random fractal and other objects studied by fractal theory. The statistical polymer method is applicable not only to polymers but also

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45

Howard, Jenna B., and Barry C. Thompson. "Design of Random and Semi-Random Conjugated Polymers for Organic Solar Cells." Macromolecular Chemistry and Physics 218, no. 21 (2017): 1700255. http://dx.doi.org/10.1002/macp.201700255.

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46

Michieletto, Davide, Marco Baiesi, Enzo Orlandini, and Matthew S. Turner. "Rings in random environments: sensing disorder through topology." Soft Matter 11, no. 6 (2015): 1100–1106. http://dx.doi.org/10.1039/c4sm02324b.

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We study the mobility of ring and linear polymers driven through a random environment by an external field. Changes in the surrounding structure are captured by measuring the mobility of the rings, while linear polymers are insensitive. This encourages novel non-invasive ways of exploiting topology to sense microscopic disorder.

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47

Meng, Xianghe. "Efficient Prediction of Polymer Glass Transition Temperatures through Machine Learning Methods." Advances in Engineering Technology Research 9, no. 1 (2024): 544. http://dx.doi.org/10.56028/aetr.9.1.544.2024.

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The glass transition temperature (Tg) plays a crucial role in defining polymer properties. Despite the widespread use of machine learning for material design and property prediction, there are still challenges concerning the interpretability and model performance when predicting Tg. In this study, Simplified Molecular Input Line Entry System strings are utilised to encode the polymer structure, which are then transformed into molecular descriptors for analytical training and prediction of Tg using Artificial Neural Network and Random Forest models. Meticulous hyperparameter tuning of the Rando

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48

Benito, Javier, Nikos Karayiannis, and Manuel Laso. "Confined Polymers as Self-Avoiding Random Walks on Restricted Lattices." Polymers 10, no. 12 (2018): 1394. http://dx.doi.org/10.3390/polym10121394.

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Polymers in highly confined geometries can display complex morphologies including ordered phases. A basic component of a theoretical analysis of their phase behavior in confined geometries is the knowledge of the number of possible single-chain conformations compatible with the geometrical restrictions and the established crystalline morphology. While the statistical properties of unrestricted self-avoiding random walks (SAWs) both on and off-lattice are very well known, the same is not true for SAWs in confined geometries. The purpose of this contribution is (a) to enumerate the number of SAW

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49

Le Doussal, Pierre. "Diffusion in layered random flows, polymers, electrons in random potentials, and spin depolarization in random fields." Journal of Statistical Physics 69, no. 5-6 (1992): 917–54. http://dx.doi.org/10.1007/bf01058756.

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50

Chen, Congyi. "Heat diffusion coefficient study of polymers based on interpretable machine learning." Theoretical and Natural Science 42, no. 1 (2024): 125–30. http://dx.doi.org/10.54254/2753-8818/42/20240674.

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Abstract. Polymers hold significant application value across various fields of modern society, with different application scenarios requiring specific thermal diffusivity coefficients. Finding polymer materials with targeted thermal diffusivities is crucial. However, due to the vast variety and complex structures of polymers, constructing a unified structured dataset for machine learning modeling is challenging. Although machine learning has shown great potential in materials science, it has rarely been applied to predict the heat diffusion coefficient of polymers. This paper constructs a data

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