Karsai Andras, Cassidy Grace J, Rajanala Aradhya P, Yang Lixinhao, Kerimoglu Deniz, Gumbart James C, Kim Harold D, Goldman Daniel I
School of Physics, Georgia Institute of Technology, Atlanta, GA, United States.
School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, United States.
Front Phys. 2023;11. doi: 10.3389/fphy.2023.1142004. Epub 2023 Jun 29.
Recent studies in polymer physics have created macro-scale analogs to solute microscopic polymer chains like DNA by inducing diffusive motion on a chain of beads. These bead chains have persistence lengths of O(10) links and undergo diffusive motion under random fluctuations like vibration. We present a bead chain model within a new stochastic forcing system: an air fluidizing bed of granular media. A chain of spherical 6 mm resin beads crimped onto silk thread are buffeted randomly by the multiphase flow of grains and low density rising air "bubbles". We "thermalize" bead chains of various lengths at different fluidizing airflow rates, while X-ray imaging captures a projection of the chains' dynamics within the media. With modern 3D printing techniques, we can better represent complex polymers by geometrically varying bead connections and their relative strength, e.g., mimicking the variable stiffness between adjacent nucleotide pairs of DNA. We also develop Discrete Element Method (DEM) simulations to study the 3D motion of the bead chain, where the bead chain is represented by simulated spherical particles connected by linear and angular spring-like bonds. In experiment, we find that the velocity distributions of the beads follow exponential distributions rather than the Gaussian distributions expected from polymers in solution. Through use of the DEM simulation, we find that this difference can likely be attributed to the distributions of the forces imparted onto the chain from the fluidized bed environment. We anticipate expanding this study in the future to explore a wide range of chain composition and confinement geometry, which will provide insights into the physics of large biopolymers.
聚合物物理学领域的近期研究通过在一串珠子上诱导扩散运动,创造出了与溶质微观聚合物链(如DNA)类似的宏观模型。这些珠子链的持续长度为O(10)个链节,并在诸如振动等随机涨落下进行扩散运动。我们在一个新的随机强迫系统——颗粒介质的空气流化床中提出了一个珠子链模型。一串压接到丝线上的6毫米球形树脂珠子受到颗粒多相流和低密度上升空气“气泡”的随机冲击。我们在不同的流化气流速率下使各种长度的珠子链达到“热平衡”,同时X射线成像捕捉介质中珠子链动态的投影。借助现代3D打印技术,我们可以通过几何方式改变珠子连接及其相对强度,更好地表示复杂聚合物,例如模仿DNA相邻核苷酸对之间的可变刚度。我们还开发了离散单元法(DEM)模拟来研究珠子链的三维运动,其中珠子链由通过线性和角向弹簧状键连接的模拟球形颗粒表示。在实验中,我们发现珠子的速度分布遵循指数分布,而非溶液中聚合物预期的高斯分布。通过使用DEM模拟,我们发现这种差异可能归因于流化床环境施加在链上的力的分布。我们预计未来会扩展这项研究,以探索广泛的链组成和受限几何结构,这将为大型生物聚合物的物理学提供见解。