Chemoresponsive liquid crystal (LC) sensors are promising platforms for the detection of vapor-phase analytes. Understanding the transport of analyte molecules within LC films could guide the design of LC sensors with improved selectivity. In this work, we use molecular dynamics simulations to quantify the partitioning and diffusion of nine small-molecule analytes, including four common atmospheric pollutants, in model systems representative of LC sensors. We first parameterize all-atom models for 4-cyano-4′-pentylbiphenyl (5CB), a mesogen typically used for LC sensors, and all analytes. We validate these models by reproducing experimentally determined 5CB structural parameters, 5CB diffusivity, and analyte Henry's law constants in 5CB. Using the all-atom models, we calculate analyte solvation free energies and diffusivities in bulk 5CB. These simulation-derived quantities are then used to parameterize an analytical mass-transport model to predict sensor activation times. These results demonstrate that differences in analyte–LC interactions can translate into distinct activation times to distinguish activation by different analytes. Finally, we quantify the effect of LC composition by calculating analyte solvation free energies in TL205, a proprietary LC mixture. These calculations indicate that varying the LC composition can modulate activation times to further improve sensor selectivity. These results thus provide a computational framework for guiding LC sensor design by using molecular simulations to predict analyte transport as a function of LC composition.

中文翻译：

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液晶传感器中分析物分配和扩散的分子模拟

化学响应液晶（LC）传感器是用于检测气相分析物的有前途的平台。了解LC膜内分析物分子的运输方式可以提高选择性，从而指导LC传感器的设计。在这项工作中，我们使用分子动力学模拟来量化代表LC传感器的模型系统中9种小分子分析物（包括4种常见大气污染物）的分配和扩散。我们首先为4-氰基-4'-戊基联苯（5CB）（通常用于LC传感器的液晶元）和所有分析物的所有原子模型参数化。我们通过再现实验确定的5CB结构参数，5CB扩散率和5CB中的分析物亨利定律常数来验证这些模型。使用全原子模型，我们计算了5CB块中的分析物溶剂化自由能和扩散率。然后，将这些源自仿真的数量用于参数化分析性传输模型，以预测传感器的激活时间。这些结果表明，分析物与LC相互作用的差异可以转化为不同的活化时间，以区分不同分析物的活化。最后，我们通过计算专用LC混合物TL205中的分析物溶剂化自由能来量化LC成分的影响。这些计算表明，改变LC成分可以调节激活时间，从而进一步提高传感器的选择性。因此，这些结果提供了一个计算框架，该指导框架通过使用分子模拟来预测作为LC组成函数的分析物迁移，从而指导LC传感器设计。