Statistical energy minimization theory for systems of drop-carrier particles
Statistical energy minimization theory for systems of drop-carrier particles
复制标题
液滴载体粒子系统的统计能量最小化理论
DOI：
10.1103/physreve.104.015109
复制
发表时间：
2021
影响因子：
2.4
通讯作者：
Di Carlo, Dino
中科院分区：
文献类型：
--
作者：
Du, Ryan Shijie;Liu, Lily;Ng, Simon;Sambandam, Sneha;Hernandez Adame, Bernardo;Perez, Hansell;Ha, Kyung;Falcon, Claudia;de Rutte, Joseph;Di Carlo, Dino
液滴载体颗粒（DCP）是固体微粒，其被设计成捕获目标溶液的均匀微尺度液滴，而不使用昂贵的微流体设备和技术。DCP可用于自动化和高通量生物测定和反应，以及单细胞分析。表面能最小化提供了一个理论预测的体积分布在成对的液滴分裂，显示出良好的协议与宏观实验。我们开发了一个概率成对相互作用模型，这样的DCP交换流体体积，以尽量减少表面能的系统。这导致了一个理论的数量成对相互作用的DCP需要达到一个统一的体积分布。具有不同尺寸颗粒的DCP的非均质混合物需要较少的相互作用以达到系统的最小能量分布。我们优化了DCP的几何形状，以获得最小的目标溶液和液滴体积的均匀性。
Drop-carrier particles (DCPs) are solid microparticles designed to capture uniform microscale drops of a target solution without using costly microfluidic equipment and techniques. DCPs are useful for automated and high-throughput biological assays and reactions, as well as single-cell analyses. Surface energy minimization provides a theoretical prediction for the volume distribution in pairwise droplet splitting, showing good agreement with macroscale experiments. We develop a probabilistic pairwise interaction model for a system of such DCPs exchanging fluid volume to minimize surface energy. This leads to a theory for the number of pairwise interactions of DCPs needed to reach a uniform volume distribution. Heterogeneous mixtures of DCPs with different sized particles require fewer interactions to reach a minimum energy distribution for the system. We optimize the DCP geometry for minimal required target solution and uniformity in droplet volume.