Heil Christian M, Ma Yingzhen, Bharti Bhuvnesh, Jayaraman Arthi
Department of Chemical and Biomolecular Engineering, University of Delaware, 150 Academy St., Newark, Delaware 19716, United States.
Cain Department of Chemical Engineering, Louisiana State University, 3307 Patrick F. Taylor Hall, Baton Rouge, Louisiana 70803, United States.
JACS Au. 2023 Feb 20;3(3):889-904. doi: 10.1021/jacsau.2c00697. eCollection 2023 Mar 27.
In this paper, we present an open-source machine learning (ML)-accelerated computational method to analyze small-angle scattering profiles [() vs ] from concentrated macromolecular solutions to simultaneously obtain the form factor () (., dimensions of a micelle) and the structure factor () (., spatial arrangement of the micelles) without relying on analytical models. This method builds on our recent work on Computational Reverse-Engineering Analysis for Scattering Experiments (CREASE) that has either been applied to obtain () from dilute macromolecular solutions (where () ∼1) or to obtain () from concentrated particle solutions when () is known (., sphere form factor). This paper's newly developed CREASE that calculates () and (), termed as "() and () CREASE", is validated by taking as input () vs from structures of known polydisperse core(A)-shell(B) micelles in solutions at varying concentrations and micelle-micelle aggregation. We demonstrate how "() and () CREASE" performs if given two or three of the relevant scattering profiles- (), (), and ()-as inputs; this demonstration is meant to guide experimentalists who may choose to do small-angle X-ray scattering (for total scattering from the micelles) and/or small-angle neutron scattering with appropriate contrast matching to get scattering solely from one or the other component (A or B). After validation of "() and () CREASE" on structures, we present our results analyzing small-angle neutron scattering profiles from a solution of core-shell type surfactant-coated nanoparticles with varying extents of aggregation.
在本文中，我们提出了一种开源的机器学习加速计算方法，用于分析来自浓缩大分子溶液的小角散射曲线（[() 对 ]），以在不依赖解析模型的情况下同时获得形状因子（()，即胶束的尺寸）和结构因子（()，即胶束的空间排列）。该方法基于我们最近关于散射实验的计算逆向工程分析（CREASE）的工作，该工作要么已应用于从稀大分子溶液（其中 () ∼1）中获得 ()，要么在已知 () 时（即球形形状因子）从浓缩颗粒溶液中获得 ()。本文新开发的计算 () 和 () 的 CREASE，称为“() 和 () CREASE”，通过将不同浓度和胶束 - 胶束聚集状态下溶液中已知多分散核（A） - 壳（B）胶束的 () 对 作为输入进行验证。我们展示了如果将两个或三个相关散射曲线——()、() 和 ()——作为输入，“() 和 () CREASE”将如何执行；该展示旨在指导实验人员，他们可能会选择进行小角 X 射线散射（用于胶束的总散射）和/或具有适当对比度匹配的小角中子散射，以仅从一种或另一种组分（A 或 B）获得散射。在对 结构验证了“() 和 () CREASE”之后，我们展示了分析具有不同聚集程度的核壳型表面活性剂包覆纳米颗粒溶液的小角中子散射曲线的结果。
