Patel Roshan A, Colmenares Sophia, Webb Michael A
Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey 08544, USA.
ACS Polym Au. 2023 Jun 5;3(3):284-294. doi: 10.1021/acspolymersau.3c00007. eCollection 2023 Jun 14.
Single-chain nanoparticles (SCNPs) are intriguing materials inspired by proteins that consist of a single precursor polymer chain that has collapsed into a stable structure. In many prospective applications, such as catalysis, the utility of a single-chain nanoparticle will intricately depend on the formation of a mostly specific structure or morphology. However, it is not generally well understood how to reliably control the morphology of single-chain nanoparticles. To address this knowledge gap, we simulate the formation of 7680 distinct single-chain nanoparticles from precursor chains that span a wide range of, in principle, tunable patterning characteristics of cross-linking moieties. Using a combination of molecular simulation and machine learning analyses, we show how the overall fraction of functionalization and blockiness of cross-linking moieties biases the formation of certain local and global morphological characteristics. Importantly, we illustrate and quantify the dispersity of morphologies that arise due to the stochastic nature of collapse from a well-defined sequence as well as from the ensemble of sequences that correspond to a given specification of precursor parameters. Moreover, we also examine the efficacy of precise sequence control in achieving morphological outcomes in different regimes of precursor parameters. Overall, this work critically assesses how precursor chains might be feasibly tailored to achieve given SCNP morphologies and provides a platform to pursue future sequence-based design.
单链纳米颗粒（SCNPs）是受蛋白质启发的有趣材料，由一条已折叠成稳定结构的单一前体聚合物链组成。在许多潜在应用中，如催化，单链纳米颗粒的效用将复杂地取决于形成大多特定的结构或形态。然而，如何可靠地控制单链纳米颗粒的形态，目前人们普遍还不太清楚。为了填补这一知识空白，我们模拟了由前体链形成的7680种不同的单链纳米颗粒，这些前体链涵盖了原则上可调节的交联部分的广泛图案化特征。通过结合分子模拟和机器学习分析，我们展示了功能化的总体比例和交联部分的嵌段性如何影响某些局部和全局形态特征的形成。重要的是，我们说明了并量化了由于从明确序列以及与给定前体参数规格相对应的序列集合中塌缩的随机性而产生的形态分散性。此外，我们还研究了精确序列控制在不同前体参数范围内实现形态结果的有效性。总体而言，这项工作批判性地评估了如何合理定制前体链以实现给定的SCNP形态，并提供了一个追求未来基于序列设计的平台。
