A regularization algorithm of dynamic light scattering for estimating the particle size distribution of dual-substance mixture in water--颗粒学报PARTICUOLOGY

Wang, Y., Meng, Z., Zhang, Z., Xia, M., Xia, L., & Li, W. (2024). A regularization algorithm of dynamic light scattering for estimating the particle size distribution of dual-substance mixture in water. Particuology, 89, 246-257. https://doi.org/10.1016/j.partic.2023.11.007

A regularization algorithm of dynamic light scattering for estimating the particle size distribution of dual-substance mixture in water

Yanghong Wang¹, Ziqiang Meng¹, Zipei Zhang, Min Xia, Li Xia, Wei Li^*

School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China

10.1016/j.partic.2023.11.007

Volume 89, June 2024, Pages 246-257

Received 9 May 2023, Revised 11 September 2023, Accepted 2 November 2023, Available online 18 November 2023, Version of Record 15 December 2023.

E-mail: weili@hust.edu.cn

Highlights

• A Tikhnonov regularization method based on refractive index differences is designed.

• Algorithm can analyze the particle size of a multi-substance suspension.

• Simulation experiment of two-substance suspension verifies the accuracy.

• Group of 30° scattering angles and second-order difference matrix is excellent.

• Relative errors of inversion were both less than 5% in the experiment.

Abstract

Dynamic light scattering (DLS) is a nondestructive, well-established technique for the size characterization of proteins, nanoparticles, polymers, and colloidal dispersions. However, current DLS techniques are only applied to particle groups of single composition due to the limitation of their inversion algorithm. In this study, we propose a particle size distribution inversion algorithm based on the Tikhnonov regularization method that can be applied to the dual-substance particle mixture. The algorithm retrieves the particle size distributions of two substances, respectively, by taking advantage of their refractive index differences. The simulation results reveal that the algorithm has excellent accuracy and stability when the scattering angle is 30°. Instead of the original identity matrix, the first-order difference matrix and second-order difference matrix are used as the regular matrix when utilizing the Tikhnonov algorithm, which obviously improves the anti-interference, accuracy, and stability of the algorithm. Furthermore, the inversion of particle size distribution is carried out at a 0.01%–1% noise level, which shows that the algorithm has an available antinoise ability. Finally, experimental particle size measurements for a mixture of polystyrene beads and toner particles demonstrate that the proposed algorithm is superior to the traditional Tikhnonov algorithm in applicability and accuracy.

Graphical abstract

Keywords

Dynamic light scattering; Dual-substance mixture; Particle size distribution; Tikhnonov regularization

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