Hussain Rubaiya, Alican Noyan Mehmet, Woyessa Getinet, Retamal Marín Rodrigo R, Antonio Martinez Pedro, Mahdi Faiz M, Finazzi Vittoria, Hazlehurst Thomas A, Hunter Timothy N, Coll Tomeu, Stintz Michael, Muller Frans, Chalkias Georgios, Pruneri Valerio
1ICFO- Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, 08860 Castelldefels (Barcelona), Spain.
Ipsumio B.V., High Tech Campus, 5656 AE Eindhoven, Netherlands.
Light Sci Appl. 2020 Feb 12;9:21. doi: 10.1038/s41377-020-0255-6. eCollection 2020.
Light scattering is a fundamental property that can be exploited to create essential devices such as particle analysers. The most common particle size analyser relies on measuring the angle-dependent diffracted light from a sample illuminated by a laser beam. Compared to other non-light-based counterparts, such a laser diffraction scheme offers precision, but it does so at the expense of size, complexity and cost. In this paper, we introduce the concept of a new particle size analyser in a collimated beam configuration using a consumer electronic camera and machine learning. The key novelty is a small form factor angular spatial filter that allows for the collection of light scattered by the particles up to predefined discrete angles. The filter is combined with a light-emitting diode and a complementary metal-oxide-semiconductor image sensor array to acquire angularly resolved scattering images. From these images, a machine learning model predicts the volume median diameter of the particles. To validate the proposed device, glass beads with diameters ranging from 13 to 125 µm were measured in suspension at several concentrations. We were able to correct for multiple scattering effects and predict the particle size with mean absolute percentage errors of 5.09% and 2.5% for the cases without and with concentration as an input parameter, respectively. When only spherical particles were analysed, the former error was significantly reduced (0.72%). Given that it is compact (on the order of ten cm) and built with low-cost consumer electronics, the newly designed particle size analyser has significant potential for use outside a standard laboratory, for example, in online and in-line industrial process monitoring.
光散射是一种基本特性，可用于制造诸如颗粒分析仪等重要设备。最常见的粒度分析仪依靠测量来自激光束照射样品的角度相关衍射光。与其他非基于光的同类设备相比，这种激光衍射方案具有精度，但代价是尺寸、复杂性和成本。在本文中，我们介绍了一种使用消费级电子相机和机器学习的准直光束配置新型粒度分析仪的概念。关键的新颖之处在于一种小尺寸角空间滤波器，它允许收集颗粒散射至预定义离散角度的光。该滤波器与发光二极管和互补金属氧化物半导体图像传感器阵列相结合，以获取角度分辨散射图像。从这些图像中，机器学习模型预测颗粒的体积中值直径。为了验证所提出的设备，对直径范围为13至125μm的玻璃珠在几种浓度下的悬浮液进行了测量。对于不将浓度作为输入参数和将浓度作为输入参数的情况，我们能够校正多重散射效应并预测颗粒尺寸，平均绝对百分比误差分别为5.09%和2.5%。当仅分析球形颗粒时，前一个误差显著降低（0.72%）。鉴于新设计的粒度分析仪体积紧凑（约十厘米）且由低成本消费电子产品制成，它在标准实验室之外具有显著的应用潜力，例如在线和在线工业过程监测。
