搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

具有不同扩散系数的活性手征粒子分离

李晨璞 吴魏霞 张礼刚 胡金江 谢革英 郑志刚

引用本文:
Citation:

具有不同扩散系数的活性手征粒子分离

李晨璞, 吴魏霞, 张礼刚, 胡金江, 谢革英, 郑志刚

Separation of active chiral particles with different diffusion coefficients

Li Chen-Pu, Wu Wei-Xia, Zhang Li-Gang, Hu Jin-Jiang, Xie Ge-Ying, Zheng Zhi-Gang
PDF
HTML
导出引用
  • 近几年对活性粒子的研究已成为很多领域研究者关注的重要课题之一, 其中关于活性手征粒子的相分离问题具有重要的理论和实际意义. 本文通过朗之万动力学研究了具有不同扩散系数的活性手征粒子组成的二元混合系统中粒子的相分离. 较小的相对扩散系数有利于“冷”粒子形成大的团簇而分离, 较大的相对扩散系数则会减弱分离效果. 由于粒子特征(自驱动速度、自转角速度)和相对扩散系数对粒子间碰撞作用的影响, 系统要使“冷”“热”粒子达到相分离, 自驱动速度和自转角速度的增大(或减小)不能同步, 自驱动速度的相对变化率要小于自转角速度的相对变化率. 通过分析“冷”粒子有效扩散系数的变化, 系统相分离现象得到了很好的解释. 有效扩散系数较小意味着“冷”粒子会聚集形成较大的团簇, 系统可出现相分离现象, 而当有效扩散系数较大时“冷”粒子的扩散较强, 不会形成大的团簇产生相分离. 另外, 随着粒子填充率的增大“冷”粒子最大团簇粒子数占比曲线进行先增大后减小的非单调变化, 每条曲线存在一段最优粒子填充率宽度. 相对扩散系数和自驱动速度的增大, 会使曲线的最优填充率宽度变窄并向右偏移.
    In recent years, the study of active particles has become one of the important topics concerned by researchers in many fields, among which the phase separation of active chiral particles has important theoretical and practical significance. In this paper, the phase separation of binary mixed systems composed of active chiral particles with different diffusion coefficients is studied by Langevin dynamics. A smaller relative diffusion coefficient is conducive to the formation of large clusters and the separation of “cold” particles, while a larger relative diffusion coefficient will weaken the separation effect. Due to the influence of particle characteristics (self-driven velocity, self-rotational angular velocity) and relative diffusion coefficient on the collision between particles, if one wants the “cold” and “hot” particles to reach phase separation, increasing (or reducing) the self-driven velocity and self-rotational angular velocity cannot be synchronous, and the relative rate of change of self-driven velocity is smaller than that of the self-rotational angular velocity. By analyzing the changes of the effective diffusion coefficient of “cold” particles, the phenomenon of phase separation in the system can be better explained. A smaller effective diffusion coefficient means that the “cold” particles will aggregate into larger clusters, and the system may exhibit phase separation. However, when the effective diffusion coefficient is larger, the diffusion of “cold” particles is stronger and the “cold” particles will not form large clusters, which means that the system cannot aggregate into phase separation. In addition, with the filling rate of particle increasing, the proportion curve of the number of cold particles in maximum cold particle cluster undergoes a non-monotonic change, specifically, it first increases and then decreases. Each curve has an optimal filling rate but its width is different .With the increase of the relative diffusion coefficient and self-driven velocity, the width of the optimal filling rate of the proportion curve will become narrower and shift toward the right.
      通信作者: 郑志刚, zgzheng@hau.edu.cn
    • 基金项目: 国家自然科学基金(批准号: 12375031, 11875135)资助的课题.
      Corresponding author: Zheng Zhi-Gang, zgzheng@hau.edu.cn
    • Funds: Project partially supported by the National Natural Science Foundation of China (Grant Nos. 12375031, 11875135).
    [1]

    Ramaswamy S 2010 Ann. Rev. Condens. Matt. Phys. 1 323Google Scholar

    [2]

    Howse J S, Ebbens S J 2010 Soft Matter 6 726Google Scholar

    [3]

    Lobaskin V, Romenskyy M 2013 Phys. Rev. E 87 052135Google Scholar

    [4]

    Edwards A M, Phillips R A, Watkins N W, Freeman M P, Murphy E J, Afanasyev V, Buldyrev S V, da Luz M G, Raposo E P, Stanley H E, Viswanathan G M 2007 Nature 449 1044Google Scholar

    [5]

    Brambilla M, Ferrante E, Birattari M, Dorigo M 2013 Swarm Intelligence 7 1Google Scholar

    [6]

    Helbing D 2001 Rev. Mod. Phys. 73 1067Google Scholar

    [7]

    Marchetti M C, Joanny J F, Ramaswamy S, Liverpool T B, Prost J, Rao M, Simha R A 2013 Rev. Mod. Phys. 85 1143Google Scholar

    [8]

    Wang J, Gao W 2012 ACS Nano 6 5745Google Scholar

    [9]

    Chen C, Liu S, Shi X Q, Chaté H, Wu Y 2017 Nature 542 210Google Scholar

    [10]

    Berg H C 2003 Biochem 72 19

    [11]

    Berg H C 2004 Ecoli in Motion (New York: Springer Press) pp39–47

    [12]

    Nishiguchi D, Sano M 2015 Phys. Rev. E 92 052309

    [13]

    Ma X, Hahn K, Sanchez S 2015 J. Am. Chem. Soc. 137 4976Google Scholar

    [14]

    Li J, Singh V V, Sattayasamitsathit S, Orozco J, Kaufmann K, Dong R, Gao W, Jurado-Sanchez B, Fedorak Y, Wang J 2014 ACS Nano 8 11118Google Scholar

    [15]

    Abdelmohsen L K, Peng F, Tu Y, Wilson D A 2014 J. Mater. Chem. B 2 2395Google Scholar

    [16]

    Vlope G, Gigan S, Volpe G 2014 Am. J. Phys. 82 659Google Scholar

    [17]

    Bechinger C, Di Leonardo R, Löwen H, Reichhardt C, Volpe G, Volpe G 2016 Rev. Mod. Phys. 88 045006Google Scholar

    [18]

    Ai B Q, Shao Z G, Zhong W R 2018 soft matter 14 4388Google Scholar

    [19]

    张何朋, 施夏清, 杨明成 2022 物理 51 217Google Scholar

    Zhang H P, Shi X Q, Yang M C 2022 Physics 51 217Google Scholar

    [20]

    Cates M E, Tailleur J 2015 Annu. Rev. Condens. Matter Phys. 6 219Google Scholar

    [21]

    Fily Y, Marchetti M C 2012 Phys. Rev. Lett. 108 235702Google Scholar

    [22]

    Redner G S, Hagan M F, Baskaran A 2013 Biophys. J. 104 640aGoogle Scholar

    [23]

    Speck T, Bialké J, Menzel A M, Löwen H 2014 Phys. Rev. Lett. 112 218304Google Scholar

    [24]

    夏益祺, 谌庄琳, 郭永坤 2019 物理学报 68 161101Google Scholar

    Xia Y Q, Shen Z L, Guo Y K 2019 Acta Phys. Sin. 68 161101Google Scholar

    [25]

    Kaiser A, Popowa K, Wensink H H, Lowen H 2013 Phys. Rev. E 88 022311Google Scholar

    [26]

    Wan M B, Reichhardt C O, Nussinov Z, Reichhardt C 2008 Phys. Rev. Lett. 101 018102Google Scholar

    [27]

    Ahuja S 2011 Chiral Separation Methods for Pharmaceutical and Biotechnological Products (Hoboken: John Wiley and Sons Press) p131

    [28]

    Wu J C, Dong T W, Jiang G W, An M, Ai B Q 2020 J. Chem. Phys. 152 034901Google Scholar

    [29]

    廖晶晶, 蔺福军 2020 物理学报 69 220501Google Scholar

    Liao J J, Lin F J 2020 Acta Phys. Sin. 69 220501Google Scholar

    [30]

    Kümmel F P, Shabestari P, Lozano C, Volpe G, Bechinger C 2015 Soft Matter 11 6187Google Scholar

    [31]

    Zhu W J, Li T C, Zhong W R, Ai B Q 2020 J. Chem. Phys. 152 1849031

    [32]

    Weber S N, Weber C A, Frey E 2016 Phys. Rev. Lett. 116 058301Google Scholar

    [33]

    Kumari S, Nunes A S, Araújo N A, Telo da Gama M M 2017 J. Chem. Phys. 147 174702Google Scholar

    [34]

    Ai B Q 2017 Phys. Rev. E 96 012131Google Scholar

  • 图 1  三种不同系统中粒子的相分离(Ncold = Nhot = N/2 = 150, D = DTL/DTH = 0.001) (a)被动粒子系统(v0 = 0, ω = 0); (b)自驱动粒子系统(v0 = 0.1, ω = 0); (c)自驱动粒子系统(v0 = 1, ω = 0); (d)活性手征粒子系统(v0 = 1, ω = 10)

    Fig. 1.  Phase separation of particles in three different systems (Ncold = Nhot = N/2 = 150, D = DTL/DTH = 0.001): (a) The system of passive particles (v0 = 0, ω = 0); (b) the system of self-driven particles (v0 = 0.1, ω = 0); (c) the system of self-driven particles (v0 = 1, ω = 0); (d) the system of active chiral particles (v0 = 1, ω = 10).

    图 2  不同的v0ω时“冷”粒子最大团簇粒子数占比P随相对扩散系数D的变化曲线

    Fig. 2.  The proportion P of “cold” particle in the largest cluster as a function of the relative diffusion coefficient D for different values of v0 and ω.

    图 3  不同的v0ω时“冷”粒子的有效扩散系数DeffL随相对扩散系数D的变化曲线

    Fig. 3.  The effective diffusion coefficient DeffL of “cold” particle as a function of the relative diffusion coefficient D for different values of v0 and ω.

    图 4  不同ωD时“冷”粒子的最大团簇粒子数占比P随自驱动速度的v0变化

    Fig. 4.  The proportion P of “cold” particle in the largest cluster as a function of the self-driven velocity v0 for different values of ω and D .

    图 5  不同ωD时“冷”粒子的有效扩散系数DeffL随自驱动速度的v0变化

    Fig. 5.  The effective diffusion coefficient DeffL of “cold” particle as a function of the self-driven velocity v0 for different value of ω and D .

    图 6  不同v0时“冷”粒子的最大团簇粒子数占比P随自转角速度ω的变化(D = 0.001)

    Fig. 6.  The proportion P of “cold” particle in the largest cluster as a function of the self-rotational angular velocity ω for different values of v0 with D = 0.001.

    图 7  不同v0时“冷”粒子的有效扩散系数DeffL随自旋角频率ω的变化(D = 0.001)

    Fig. 7.  The effective diffusion coefficient DeffL of “cold” particle as a function of the self-rotational angular velocity ω for different values of v0 with D = 0.001.

    图 8  不同D时“冷”粒子的最大团簇粒子数占比P随自转角速度ω的变化(v0 = 0.5)

    Fig. 8.  The proportion P of “cold” particle in the largest cluster as a function of the self-rotational angular velocity ω for different values of D with v0 = 0.5.

    图 9  不同D时“冷”粒子的有效扩散系数DeffL随自旋角频率ω的变化(v0 = 0.5)

    Fig. 9.  The effective diffusion coefficient DeffL of “cold” particle as a function of the self-rotational angular velocity ω for different values of D with v0 = 0.5.

    图 10  不同v0, ωD时“冷”粒子的最大团簇粒子数占比P随粒子填充率Φ变化曲线

    Fig. 10.  The proportion P of “cold” particle in the largest cluster as a function of the filling rate of particle for different values of v0, ω and D.

    图 11  不同v0, ωD时“冷”粒子的有效扩散系数DeffL随粒子填充率Φ变化曲线

    Fig. 11.  The effective diffusion coefficient DeffL of “cold” particle as a function of the filling rate of particle for different values of v0, ω and D.

  • [1]

    Ramaswamy S 2010 Ann. Rev. Condens. Matt. Phys. 1 323Google Scholar

    [2]

    Howse J S, Ebbens S J 2010 Soft Matter 6 726Google Scholar

    [3]

    Lobaskin V, Romenskyy M 2013 Phys. Rev. E 87 052135Google Scholar

    [4]

    Edwards A M, Phillips R A, Watkins N W, Freeman M P, Murphy E J, Afanasyev V, Buldyrev S V, da Luz M G, Raposo E P, Stanley H E, Viswanathan G M 2007 Nature 449 1044Google Scholar

    [5]

    Brambilla M, Ferrante E, Birattari M, Dorigo M 2013 Swarm Intelligence 7 1Google Scholar

    [6]

    Helbing D 2001 Rev. Mod. Phys. 73 1067Google Scholar

    [7]

    Marchetti M C, Joanny J F, Ramaswamy S, Liverpool T B, Prost J, Rao M, Simha R A 2013 Rev. Mod. Phys. 85 1143Google Scholar

    [8]

    Wang J, Gao W 2012 ACS Nano 6 5745Google Scholar

    [9]

    Chen C, Liu S, Shi X Q, Chaté H, Wu Y 2017 Nature 542 210Google Scholar

    [10]

    Berg H C 2003 Biochem 72 19

    [11]

    Berg H C 2004 Ecoli in Motion (New York: Springer Press) pp39–47

    [12]

    Nishiguchi D, Sano M 2015 Phys. Rev. E 92 052309

    [13]

    Ma X, Hahn K, Sanchez S 2015 J. Am. Chem. Soc. 137 4976Google Scholar

    [14]

    Li J, Singh V V, Sattayasamitsathit S, Orozco J, Kaufmann K, Dong R, Gao W, Jurado-Sanchez B, Fedorak Y, Wang J 2014 ACS Nano 8 11118Google Scholar

    [15]

    Abdelmohsen L K, Peng F, Tu Y, Wilson D A 2014 J. Mater. Chem. B 2 2395Google Scholar

    [16]

    Vlope G, Gigan S, Volpe G 2014 Am. J. Phys. 82 659Google Scholar

    [17]

    Bechinger C, Di Leonardo R, Löwen H, Reichhardt C, Volpe G, Volpe G 2016 Rev. Mod. Phys. 88 045006Google Scholar

    [18]

    Ai B Q, Shao Z G, Zhong W R 2018 soft matter 14 4388Google Scholar

    [19]

    张何朋, 施夏清, 杨明成 2022 物理 51 217Google Scholar

    Zhang H P, Shi X Q, Yang M C 2022 Physics 51 217Google Scholar

    [20]

    Cates M E, Tailleur J 2015 Annu. Rev. Condens. Matter Phys. 6 219Google Scholar

    [21]

    Fily Y, Marchetti M C 2012 Phys. Rev. Lett. 108 235702Google Scholar

    [22]

    Redner G S, Hagan M F, Baskaran A 2013 Biophys. J. 104 640aGoogle Scholar

    [23]

    Speck T, Bialké J, Menzel A M, Löwen H 2014 Phys. Rev. Lett. 112 218304Google Scholar

    [24]

    夏益祺, 谌庄琳, 郭永坤 2019 物理学报 68 161101Google Scholar

    Xia Y Q, Shen Z L, Guo Y K 2019 Acta Phys. Sin. 68 161101Google Scholar

    [25]

    Kaiser A, Popowa K, Wensink H H, Lowen H 2013 Phys. Rev. E 88 022311Google Scholar

    [26]

    Wan M B, Reichhardt C O, Nussinov Z, Reichhardt C 2008 Phys. Rev. Lett. 101 018102Google Scholar

    [27]

    Ahuja S 2011 Chiral Separation Methods for Pharmaceutical and Biotechnological Products (Hoboken: John Wiley and Sons Press) p131

    [28]

    Wu J C, Dong T W, Jiang G W, An M, Ai B Q 2020 J. Chem. Phys. 152 034901Google Scholar

    [29]

    廖晶晶, 蔺福军 2020 物理学报 69 220501Google Scholar

    Liao J J, Lin F J 2020 Acta Phys. Sin. 69 220501Google Scholar

    [30]

    Kümmel F P, Shabestari P, Lozano C, Volpe G, Bechinger C 2015 Soft Matter 11 6187Google Scholar

    [31]

    Zhu W J, Li T C, Zhong W R, Ai B Q 2020 J. Chem. Phys. 152 1849031

    [32]

    Weber S N, Weber C A, Frey E 2016 Phys. Rev. Lett. 116 058301Google Scholar

    [33]

    Kumari S, Nunes A S, Araújo N A, Telo da Gama M M 2017 J. Chem. Phys. 147 174702Google Scholar

    [34]

    Ai B Q 2017 Phys. Rev. E 96 012131Google Scholar

  • [1] 周雄峰, 陈彬, 刘坤. 大气压交流氩气放电等离子体射流特性研究:电压、气体流速、外磁场的综合影响. 物理学报, 2024, 73(21): . doi: 10.7498/aps.73.20241166
    [2] 刘坤, 项红甫, 周雄峰, 夏昊天, 李华. 固定功率下大气压交流氩气等离子体射流的光谱特性. 物理学报, 2023, 72(11): 115201. doi: 10.7498/aps.72.20230307
    [3] 李德彰, 卢智伟, 赵宇军, 杨小宝. 自旋半经典朗之万方程一般形式的探讨. 物理学报, 2023, 72(14): 140501. doi: 10.7498/aps.72.20230106
    [4] 赵立芬, 哈静, 王非凡, 李庆, 何寿杰. 氧气空心阴极放电模拟. 物理学报, 2022, 71(2): 025201. doi: 10.7498/aps.71.20211150
    [5] 马奥杰, 陈颂佳, 李玉秀, 陈颖. 纳米颗粒布朗扩散边界条件的分子动力学模拟. 物理学报, 2021, 70(14): 148201. doi: 10.7498/aps.70.20202240
    [6] 刘妮, 王建芬, 梁九卿. 双光腔耦合下机械振子的基态冷却. 物理学报, 2020, 69(6): 064202. doi: 10.7498/aps.69.20191541
    [7] 廖晶晶, 蔺福军. 混合手征活性粒子在时间延迟反馈下的扩散和分离. 物理学报, 2020, 69(22): 220501. doi: 10.7498/aps.69.20200505
    [8] 楚硕, 郭春文, 王志军, 李俊杰, 王锦程. 浓度相关的扩散系数对定向凝固枝晶生长的影响. 物理学报, 2019, 68(16): 166401. doi: 10.7498/aps.68.20190603
    [9] 李阳, 宋永顺, 黎明, 周昕. 碳纳米管中水孤立子扩散现象的模拟研究. 物理学报, 2016, 65(14): 140202. doi: 10.7498/aps.65.140202
    [10] 杨彪, 王丽阁, 易勇, 王恩泽, 彭丽霞. C, N, O原子在金属V中扩散行为的第一性原理计算. 物理学报, 2015, 64(2): 026602. doi: 10.7498/aps.64.026602
    [11] 孟伟东, 孙丽存, 翟影, 杨瑞芬, 普小云. 用液芯柱透镜快速测量液相扩散系数-折射率空间分布瞬态测量法. 物理学报, 2015, 64(11): 114205. doi: 10.7498/aps.64.114205
    [12] 李晨璞, 韩英荣, 展永, 谢革英, 胡金江, 张礼刚, 贾利云. 基于三磷酸腺苷调节的分子马达单向能量跃迁模型. 物理学报, 2013, 62(19): 190501. doi: 10.7498/aps.62.190501
    [13] 张首誉, 包尚联, 亢孝俭, 高嵩. 描述人体内水分子扩散各向异性特征的新方法. 物理学报, 2013, 62(20): 208703. doi: 10.7498/aps.62.208703
    [14] 李强, 普小云. 用毛细管成像法测量液相扩散系数——等折射率薄层测量方法. 物理学报, 2013, 62(9): 094206. doi: 10.7498/aps.62.094206
    [15] 李晨璞, 韩英荣, 展永, 胡金江, 张礼刚, 曲蛟. 肌球蛋白Ⅵ分子马达周期势场下的弹性扩散模型. 物理学报, 2013, 62(23): 230501. doi: 10.7498/aps.62.230501
    [16] 蒋泽南, 房超, 孙立风. 朗之万方程及其在蛋白质折叠动力学中的应用. 物理学报, 2011, 60(6): 060502. doi: 10.7498/aps.60.060502
    [17] 王振中, 王楠, 姚文静. 低扩散系数对Pd77Cu6Si17合金易非晶化的影响. 物理学报, 2010, 59(10): 7431-7436. doi: 10.7498/aps.59.7431
    [18] 樊华, 李理, 袁坚, 山秀明. 互联网流量控制的朗之万模型及相变分析. 物理学报, 2009, 58(11): 7507-7513. doi: 10.7498/aps.58.7507
    [19] 李万万, 孙 康. Cd0.9Zn0.1Te晶体的Cd气氛扩散热处理研究. 物理学报, 2007, 56(11): 6514-6520. doi: 10.7498/aps.56.6514
    [20] 李万万, 孙 康. Cd1-xZnxTe晶体的In气氛扩散热处理研究. 物理学报, 2006, 55(4): 1921-1929. doi: 10.7498/aps.55.1921
计量
  • 文章访问数:  589
  • PDF下载量:  42
  • 被引次数: 0
出版历程
  • 收稿日期:  2024-05-14
  • 修回日期:  2024-07-16
  • 上网日期:  2024-09-13
  • 刊出日期:  2024-10-20

/

返回文章
返回