A user-friendly graphical user interface for dynamic light scattering data analysis

A user-friendly graphical user interface for dynamic light scattering data analysis
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用于动态光散射数据分析的用户友好的图形用户界面

DOI：
10.1039/d3sm00469d
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发表时间：
2023
期刊：
Soft Matter
影响因子：
3.4
通讯作者：
Srivastava, Samanvaya
Srivastava, Samanvaya
中科院分区：
化学2区
文献类型：
--
作者：
Salazar, Matthew;Srivastav, Harsh;Srivastava, Abhishek;Srivastava, Samanvaya

文献摘要

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动态光散射（DLS）是一种常用的分析工具，用于表征分散体或溶液中胶体的大小分布。通常，将入射激光束以固定角度照射样品时产生的散射强度记录为时间的函数，并将其转换为时间自相关数据，可将其反向估计胶体扩散率的分布，从而估计胶体尺寸分布。对于多分散样本，这种反演问题是第一类Fredholm积分方程，是病态的，通常使用累积展开或正则化方法来处理。本文介绍了一个用户友好的图形用户界面（GUI），用于使用累积展开法和正则化方法分析测量的散射强度时间自相关数据，正则化方法使用各种常用算法，包括NNLS， CONTIN， REPES和DYNALS。GUI允许用户调节任何和所有的拟合参数，提供极大的灵活性。此外，GUI还支持对各种算法生成的大小分布进行比较，并评估它们的性能。我们展示了从GUI中获得的模型单峰和双峰色散的拟合结果，以突出这些算法在分析DLS时间自相关数据时的优势、局限性和适用范围。
Dynamic light scattering (DLS) is a commonly used analytical tool for characterizing the size distribution of colloids in a dispersion or a solution. Typically, the intensity of a scattering produced from the sample at a fixed angle from an incident laser beam is recorded as a function of time and converted into time autocorrelation data, which can be inverted to estimate the distribution of colloid diffusivity to estimate the colloid size distribution. For polydisperse samples, this inversion problem, being a Fredholm integral equation of the first kind, is ill-posed and is typically handled using cumulant expansions or regularization methods. Here, we introduce a user-friendly graphical user interface (GUI) for analyzing the measured scattering intensity time autocorrelation data using both the cumulant expansion method and regularization methods, with the latter implemented using various commonly employed algorithms, including NNLS, CONTIN, REPES, and DYNALS. The GUI allows the user to modulate any and all of the fit parameters, offering extreme flexibility. Additionally, the GUI also enables a comparison of the size distributions generated by various algorithms and an evaluation of their performance. We present the fit results obtained from the GUI for model monomodal and bimodal dispersions to highlight the strengths, limitations, and scope of applicability of these algorithms for analyzing time autocorrelation data from DLS.