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Abstract
In the large inversion range, the wavelet-regularization inversion method (WRIM) is an effective method for improving the inversion accuracy of dynamic light scattering (DLS) data. However, the initial decomposition scale (IDS) of this method has a great effect on the inversion accuracy. The particle size distribution (PSD) obtained from inappropriate IDS is not optimal. We analyze the effect of the different IDS on the inversion result in this paper. The results show that IDS of the smallest relative error should be chosen as the optimal IDS. However, because the true PSD is unknown in the practical measurements, this optimal IDS criterion is infeasible. Therefore, we propose an application criterion determining the optimal IDS. Based on this criterion, an improved WRIM with the optimal IDS is established. By the improved WRIM, high accuracy inversion PSD is obtained from DLS data. The simulated and experimental data demonstrate the effectiveness of this algorithm. Besides, we also further study the effect of the data noise on the optimal IDS. These studies indicate that the optimal IDS usually shows a downward trend with an increase of noise level.
Highlights
dynamic light scattering (DLS) is a widely used technique for measuring the particle size distribution (PSD) of ultrafine particles in suspension [1,2,3,4].The principle of DLS is based on the Brownian motion of particles in suspension, which leads to the fluctuation of scattered light
PSDs recovered by the improved wavelet-regularization inversion method (WRIM), constrained regularization method (CONTIN), and the traditional regularization method (IDS 1)
When WRIM is used to invert DLS data, initial decomposition scale (IDS) of WRIM has a great effect on the inversion is used to invert
Summary
DLS is a widely used technique for measuring the PSD of ultrafine particles in suspension [1,2,3,4]. Each of these algorithms has its own advantages and limitations These approaches solve the problem in a single-scale space and a fixed inversion range. In many cases, the manual method is not feasible, for example, polymeric materials study and biological analysis [30,31] The former inversion results have been no longer applicable for the latter inversion. WRIM is an effective method for obtaining the optimal PSD in preselecting a large inversion range. Considering the application, an improved WRIM with the optimal IDS is proposed in this paper. The high-accuracy inversion PSD is obtained from DLS data. This study has a very important role for improving the measurement accuracy of DLS data
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