scholarly journals An Advanced Sensor for Particles in Gases Using Dynamic Light Scattering in Air as Solvent

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5115
Author(s):  
Dan Chicea ◽  
Cristian Leca ◽  
Sorin Olaru ◽  
Liana Maria Chicea

Dynamic Light Scattering is a technique currently used to assess the particle size and size distribution by processing the scattered light intensity. Typically, the particles to be investigated are suspended in a liquid solvent. An analysis of the particular conditions required to perform a light scattering experiment on particles in air is presented in detail, together with a simple experimental setup and the data processing procedure. The results reveal that such an experiment is possible and using the setup and the procedure, both simplified to extreme, enables the design of an advanced sensor for particles and fumes that can output the average size of the particles in air.

Author(s):  
Алена Игорьевна Маркова ◽  
Александр Викторович Соколов ◽  
Светлана Дмитриевна Хижняк ◽  
Павел Михайлович Пахомов

Предложен метод оптической спектроскопии для оценки качества растворителя, на примере вазелинового масла (ВМ), используемого при гель-формованиии сверхвысокомолекулярного полиэтилена (СВМПЭ). Метод основан на анализе упруго рассеянного света от частиц загрязнителя в ВМ. С помощью этого метода удалось определить средний размер рассеивающих частиц и их распределение по размерам. Методы динамического светорассеяния (ДСР) и оптической микроскопии подтвердили данные о среднем размере частиц загрязнителя в ВМ и их распределении по размерам, полученные методом оптической спектроскопии. A method of optical spectroscopy for evaluating the quality of a solvent is proposed, using the example of vaseline oil (VM) used in gel molding of ultra-high molecular weight polyethylene (UHMWPE). The method is based on the analysis of elastically scattered light from pollutant particles in a VM. Using this method, it was possible to determine the average size of scattering particles and their size distribution. The methods of dynamic light scattering (DLS) and optical microscopy have confirmed the data on the average size of pollutant particles in VM and their size distribution obtained by optical spectroscopy.


Author(s):  
Lin Jin ◽  
Curtis W Jarand ◽  
Mark L Brader ◽  
Wayne F Reed

Abstract Dynamic light scattering (DLS) is widely used for analyzing biological polymers and colloids. Its application to nanoparticles in medicine is becoming increasingly important with the recent emergence of prominent lipid nanoparticle-(LNP)based products, such as the SARS-CoV-2 vaccines from Pfizer, Inc.-BioNTech (BNT162b2) and Moderna, Inc. (mRNA-1273). DLS plays an important role in the characterization and quality control of nanoparticle-based therapeutics and vaccines. However, most DLS instruments have a single detection angle ,and the amplitude of the scattering vector, q, varies among them according to the relationship q=(n/sin(/2) where 0 is the laser wavelength. Results for identical, polydisperse samples among instruments of varying q yield different hydrodynamic diameters, because, as particles become larger they scatter less light at higher angles, so that higher-q instruments will under-sample large particles in polydisperse populations, and report higher z-average diffusion coefficients, and hence smaller effective hydrodynamic diameters than lower-q instruments. As particle size reaches the Mie regime the scattering envelope manifests angular maxima and minima, and the monotonic decrease of average size versus q is lost. This work examines results for different q-value instruments, using mixtures of monodisperse latex sphere standards, for which experimental measurements agree well with computations, and also polydisperse solutions of LNP, for which results follow expected trends. Mie effects on broad unimodal populations are also considered. There is no way to predict results between two instruments with different q for samples of unknown particle size distributions.


2021 ◽  
Vol 343 ◽  
pp. 10010
Author(s):  
Dan Chicea ◽  
Cristian Leca ◽  
Sorin Olaru

Several types of sensors capable of detecting fumes are commercially available. A well-established procedure for sizing particles suspended in liquid solvent is called Dynamic Light Scattering (DLS) and is based on assessing the diffusion coefficient of the particles from the fluctuations of the scattered light recorded in the scattered light intensity time series. This work highlights the difficulties encountered in an attempt to use DLS for sizing particles suspended in air and the particular, narrow experimental conditions chosen in designing and setting such a DLS experiment. The experimental setup was tested on combustion gases and the results of the preliminary experiment are presented in detail. The results stand as a proof of concept for using DLS in sizing particle in gases and in designing a sensor for fumes detection that can indicate the average size of the particles over an extended range.


Materials ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 5683
Author(s):  
Mengjie Wang ◽  
Jin Shen ◽  
John C. Thomas ◽  
Tongtong Mu ◽  
Wei Liu ◽  
...  

Dynamic light scattering (DLS) is a popular method of particle size measurement, but at ultra-low particle concentrations, the occurrence of number concentration fluctuations limits the use of the technique. Number fluctuations add a non-Gaussian term to the scattered light intensity autocorrelation function (ACF). This leads to an inaccurate particle size distribution (PSD) being recovered if the normal DLS analysis model is used. We propose two methods for inverting the DLS data and recovering the PSDs when number fluctuations are apparent. One is to directly establish the relationship between the non-Gaussian ACF and the PSD by the kernel function reconstruction (KFR) method while including the non-Gaussian term to recover the PSD. The other is to remove the effect of the non-Gaussian term in the ACF by the baseline reset (BR) method. By including the number fluctuation term, the ideal recovered PSD can be obtained from the simulated data, but this will not happen in the experimental measurement data. This is because the measured intensity ACF contains more noise than the simulated ACF at ultra-low concentration. In particular, the baseline noise at the tail of long delay time of ACF overwhelms the number fluctuation term, making it difficult to recover reliable PSD data. Resetting the baseline can effectively remove the digital fluctuation term in ACF, which is also a feasible method to improve PSD recovery under ultra-low concentration. However, increasing noise at ultra-low concentrations can lead to errors in determining an effective baseline. This greatly reduces the accuracy of inversion results. Results from simulated and measured ACF data show that, for both methods, noise on the ACF limits reliable PSD recovery.


Materials ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2094
Author(s):  
Seok-Ki Jung ◽  
Dae Woon Kim ◽  
Jeongyol Lee ◽  
Selvaponpriya Ramasamy ◽  
Hyun Sik Kim ◽  
...  

The aim of this study was to present a control method for modulating the translucency of lithium disilicate ceramics through thermal refinement. Identical lithium disilicate blocks were thermally refined using four different heat treatment schedules, and the microstructure, translucency, and flexural strength of the ceramics were investigated in detail by SEM, spectroscopy, and a piston-on-three-ball test. The results showed that ceramics treated under higher heat had larger grains, with an average size between 240 and 1080 nm. In addition, a higher transmittance of all wavelengths was observed in ceramics treated under lower heat, and the transmittance in the 550 nm wavelength ranged from 27 to 34%. The results suggest that the translucency of ceramics can be modified through thermal refinement under two conditions: (1) the particle size of the ceramic is small enough to achieve minimal grain-boundary light scattering, and (2) the percentage of particles allowing visible light transmission is altered by the heat treatment.


2018 ◽  
Vol 8 (9) ◽  
pp. 1674
Author(s):  
Wengang Chen ◽  
Wenzheng Xiu ◽  
Jin Shen ◽  
Wenwen Zhang ◽  
Min Xu ◽  
...  

By using different weights to deal with the autocorrelation function data of every delay time period, the information utilization of dynamic light scattering can be obviously enhanced in the information-weighted constrained regularization inversion, but the denoising ability and the peak resolution under noise conditions for information-weighted inversion algorithm are still insufficient. On the basis of information weighting, we added a penalty term with the function of flatness constraints to the objective function of the regularization inversion, and performed the inversion of multiangle dynamic light scattering data, including the simulated data of bimodal distribution particles (466/915 nm, 316/470 nm) and trimodal distribution particles (324/601/871 nm), and the measured data of bimodal distribution particles (306/974 nm, 300/502 nm). The results of the inversion show that multiple-penalty-weighted regularization inversion can not only improve the utilization of the particle size information, but also effectively eliminate the false peaks and burrs in the inversed particle size distributions, and further improve the resolution of peaks in the noise conditions, and then improve the weighting effects of the information-weighted inversion.


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