RUI: Equilibrium Studies of Solution-Phase Self-Assembly

在这个由化学学部的大分子、超分子和纳米化学项目以及计算和数据支持科学与工程项目资助的项目中，加尔文学院的Douglas Vander Griend将研究导致超分子结构在溶液阶段自组装的逐步热力学过程。为了描述这样的分子集合，平衡限制因子分析（ERFA），一种强大的数学反褶积技术，被用于复合数据。具体来说，紫外可见分光光度滴定的原始吸光度数据可以建模，以确定1)溶液中不同化学物质的数量，2)每种化学物质的光谱特征，以及3)它们之间反应的平衡常数。总之，三种超分子体系将使用这种技术进行研究。在不需要化学分离任何成分的情况下获得系统的详细信息，将解开各种类型的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联系，分享各种形式的因素分析知识，并使Sivvu？是ERFA的软件程序，可在互联网上获得。无论是在我们体内，作为纳米级机器的一部分，还是作为有效的化学传感器，分子作为整体都能完成一些最好的工作；然而，描述不同类型的分子群以及它们如何相互合作并不是一项简单的任务。有时每个组件都可以被分离和研究，但通常这种方法无助于理清组件如何相互作用。该研究项目旨在通过收集系统整体的数据，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，从而解决这一挑战。具体的重点是探索生物分子如何在溶液中重新排列自己，以及更小的分子如何连接在一起来封装目标分子。这项研究将帮助科学家了解分子在更大的群体中是如何相互作用的，并可能导致设计系统来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.