Role of Stochasticity in Helical Self-Organization during Precipitation

Role of Stochasticity in Helical Self-Organization during Precipitation
复制标题

DOI:
10.1021/acs.langmuir.2c02441
复制
发表时间:
2022-12-21
期刊:
影响因子:
3.9
通讯作者:
Nabika,Hideki
Nabika,Hideki
中科院分区:
化学2区
文献类型:
--
作者:
Tsushima,Kotori;Itatani,Masaki;Nabika,Hideki

文献摘要

相似文献

自发图案的形成具有明确的周期性,在自然界中普遍存在。李色冈现象就是这种自发图案形成的化学模型。在这项研究中,我们用实验分析和基于反应扩散方程的数值模拟的方法研究了反应扩散沉淀过程中的随机性在反应扩散沉淀过程中的作用,证明了CuCrO4析出物在Liesegang花样中自发对称性破缺和螺旋形成的温度依赖性。在高温下,除了李塞冈现象的离散平行带特征外,还出现了无分支、单分支和双分支的螺旋。当图案形成过程中的实验温度超过20℃时,螺旋形成的几率急剧增加,并且在高温下,定量表示所获得图案的周期性的间距系数增加。通过数值模拟研究了螺旋形成几率和间距系数对温度的依赖关系。初始化学反应的随机性会引发随后的成核和晶体生长,这严重影响了螺旋形成的概率和间距系数。通过考虑初始化学反应步骤的随机性程度,在成核前模型的框架内解释了这些特征。
Spontaneous pattern formation with a well-defined periodicity is ubiquitous in nature. The Liesegang phenomenon is a chemical model of such a spontaneous pattern formation. In this study, we investigated the role of stochasticity in reaction–diffusion precipitation processes by demonstrating the temperature dependence of spontaneous symmetry breaking and helix formation in the Liesegang pattern with CuCrO4precipitates; experimental analysis and numerical simulations based on reaction–diffusion equations were used. At high temperatures, helices with no, single, and double branches appeared in addition to the discrete parallel band characteristic of the Liesegang phenomenon. The probability of helix formation increased drastically when the experimental temperature during the pattern formation exceeded 20 °C. Moreover, the spacing coefficient, quantitatively representing the periodicity of obtained patterns, increased at high temperatures. Numerical simulations were performed to investigate the temperature dependence of the probability of helix formation and spacing coefficients. The stochasticity of the initial chemical reaction, which can trigger consequent nucleation and crystal growth, critically affected the probability of helix formation and the spacing coefficient. These features were explained in the framework of the prenucleation model by considering the degree of stochasticity in the initial chemical reaction step.