RUI: Equilibrium Studies of Solution-Phase Self-Assembly

在这个由化学系高分子、超分子和纳米化学计划以及计算和数据支持的科学与工程计划资助的项目中，卡尔文学院的道格拉斯·范德·格里德将研究导致超分子结构溶液相自组装的逐步热力学过程。为了描述这种分子系综的特征，平衡限制因子分析(ERFA)，一种强大的数学反卷积技术，被用于复合数据。具体地说，可以对来自UV-VIS分光光度滴定的原始吸光度数据进行建模，以确定1)溶液中不同化学物种的数量，2)每个化学物种的光谱特征，以及3)它们之间反应的平衡常数。总而言之，将使用该技术研究三个超分子体系。在不需要化学隔离任何组件的情况下获得关于系统的如此详细的信息将解锁各种类型协同分子组织的关键设计元素。更广泛的影响包括培训本科生，与世界各地的合作者和其他研究人员建立网络，分享各种形式的因子分析知识，以及通过互联网提供ERFA的软件程序Sivvu？无论它是在我们体内，作为纳米机器的一部分，还是作为有效的化学传感器，分子作为集合完成了一些最好的工作；然而，表征各种类型的分子基团以及它们如何相互协作并不是一项简单的任务。有时可以分离和研究每个组件，但通常这种方法无助于确定组件之间的交互方式。这一研究项目寻求解决这一挑战，方法是收集整个系统的数据，然后使用强大的数学技术根据精确的化学定律对不同的分子进行建模。具体的重点是探索生物分子如何在溶液中重新排列，以及更小的分子如何结合在一起来包裹目标分子。这项研究应该有助于科学家了解分子如何在更大的群体中具体相互作用，并可能导致设计系统以执行有用的技术功能的方法。

In this project funded by the Macromolecular, Supramolecular and Nanochemistry Program of the Chemistry Division and the Computational and Data-Enabled Science and Engineering Program, Douglas Vander Griend of Calvin College will study the step-by-step thermodynamic processes that lead to solution-phase self-assembly of supramolecular structures. To characterize such ensembles of molecules, equilibrium-restricted factor analysis (ERFA), a powerful mathematical deconvolution technique, is used on composite data. Specifically, raw absorbance data from a UV-Vis spectrophotometric titration can be modeled in order to ascertain 1) the number of distinct chemical species in solution, 2) the spectroscopic signature of each, and 3) the equilibrium constants for the reactions between them. In all, three supramolecular systems will be studied using this technique. Obtaining such detailed information about a system without having to chemically isolate any of the components will unlock the key design elements for various types of synergistic molecular organization. The broader impacts involve training undergraduate students, networking with collaborators and other researchers around the world to share knowledge about various forms of factor analysis, and making Sivvu?, the software program for ERFA, available through the internet.Whether it is inside our bodies, as part of nanoscale machines, or as effective chemical sensors, molecules do some of their best work as ensembles; however, characterizing groups of various types of molecules and how they cooperate with each other is no straightforward task. Sometimes each component can be isolated and studied, but usually this method is unhelpful for sorting out how the components interact. This research project seeks to address this challenge by collecting data on a system as a whole, and then using powerful mathematical techniques to model the different molecules according to precise chemical laws. The specific focus is to probe how biomolecules rearrange themselves in solution and how smaller molecules join together to encapsulate target molecules. This research should help scientists understand how molecules specifically interact with each other in larger groups, and could lead to ways to design systems to perform useful technological functions.