Acta Optica Sinica, Volume. 43, Issue 9, 0929002(2023)

Machine Learning-Based Inversion Algorithm for Particle Size Distribution of Non-Spherical Particle System

Jiaxing Xu, Min Xia, Kecheng Yang, Yinan Wu, and Wei Li*
Author Affiliations
  • School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, Hubei , China
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    References(43)

    [1] Phillips D L. A technique for the numerical solution of certain integral equations of the first kind[J]. Journal of the ACM, 9, 84-97(1962).

    [2] Tikhonov A N. On the solution of ill-posed problems and the method of regularization[J]. Doklady Akademii Nauk SSSR, 151, 501-504(1963).

    [3] Tikhonov A N, Arsenin V[J]. Solution of ill-posed problems(1977).

    [4] Kirsch A[M]. An introduction to the mathematical theory of inverse problems(1996).

    [5] Gugliotta L M, Stegmayer G S, Clementi L A et al. A neural network model for estimating the particle size distribution of dilute latex from multiangle dynamic light scattering measurements[J]. Particle & Particle Systems Characterization, 26, 41-52(2009).

    [6] Provencher S W. A constrained regularization method for inverting data represented by linear algebraic or integral equations[J]. Computer Physics Communications, 27, 213-227(1982).

    [7] Arias M L, Frontini G L. Particle size distribution retrieval from elastic light scattering measurements by a modified regularization method[J]. Particle & Particle Systems Characterization, 23, 374-380(2006).

    [8] Roig A R, Alessandrini J L. Particle size distributions from static light scattering with regularized non-negative least squares constraints[J]. Particle & Particle Systems Characterization, 23, 431-437(2006).

    [9] Liu W, Wang Y J, Chen W G et al. Influence of regularization matrix on inversion of bimodal dynamic light scattering data[J]. Chinese Journal of Lasers, 42, 0908003(2015).

    [10] Wang Y J, Dou Z, Shen J et al. Multi-scale inversion combining TSVD-Tikhonov regularization for dynamic light scattering[J]. Chinese Journal of Lasers, 44, 0104003(2017).

    [11] Li L, Yang K, Li W et al. A recursive regularization algorithm for estimating the particle size distribution from multiangle dynamic light scattering measurements[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 178, 244-254(2016).

    [12] Liu L, Chen M, Qiu J et al. Weighted Bayesian inversion method in multi-angle dynamic light scattering measurements[J]. Chinese Journal of Computational Physics, 36, 673-681(2019).

    [13] Austin J, Minelli C, Hamilton D et al. Nanoparticle number concentration measurements by multi-angle dynamic light scattering[J]. Journal of Nanoparticle Research, 22, 108(2020).

    [14] Liu X Y, Shen J, Zhu X J et al. Angular dependence of dynamic light scattering[J]. Acta Optica Sinica, 32, 0629002(2012).

    [15] Linak W P, Miller C A, Wendt J O L. Comparison of particle size distributions and elemental partitioning from the combustion of pulverized coal and residual fuel oil[J]. Journal of the Air & Waste Management Association, 50, 1532-1544(2000).

    [16] Chang Q, Yang F M, Li X H et al. Characteristics of mass and chemical species size distributions of particulate matter during haze pollution in the winter in Beijing[J]. Acta Scientiae Circumstantiae, 35, 363-370(2015).

    [17] Gong Y J, Li H J, Zhang H et al. Design method of particle size distribution of low density cement slurry filling reinforcement material[J]. Journal of Oil and Gas Technology, 32, 288-290(2010).

    [18] Shu X M, Fang J, Shao Q et al. Fire smoke particle size measurement based on the multiwavelength and multiangle light scattering method[J]. Chinese Physics Letters, 23, 385-387(2006).

    [19] Sato T, Tojo H, Watanabe Y. Highly sensitive detection of red blood cell aggregation with ultrasonic peak frequency[J]. Japanese Journal of Applied Physics, 52, 07HF18(2013).

    [20] Mauer J, Peltomäki M, Poblete S et al. Static and dynamic light scattering by red blood cells: a numerical study[J]. PLoS One, 12, e0176799(2017).

    [21] Wang Y W, Han G C, Liu Y et al. Light scattering virtual simulation of red blood cell under double curve symmetrical model[J]. Chinese Journal of Lasers, 34, 1676-1681(2007).

    [22] Bu M, Hu S S, Tao Z H et al. Scattering characteristics of leukocytes on polarized light and relationship between scattering characteristics and cell structure[J]. Chinese Journal of Lasers, 44, 1007001(2017).

    [23] Felker G M, Allen L A, Pocock S J et al. Red cell distribution width as a novel prognostic marker in heart failure: data from the CHARM program and the Duke databank[J]. Journal of the American College of Cardiology, 50, 40-47(2007).

    [24] Yilmaz M B, Beton O, Yucel H et al. Red cell distribution width predicts length of stay in patients with acutely decompensated heart failure[J]. European Journal of Health Sciences, 1, 1-8(2015).

    [25] Albayrak S, Zengin K, Tanik S et al. Red cell distribution width as a predictor of prostate cancer progression[J]. Asian Pacific Journal of Cancer Prevention, 15, 7781-7784(2014).

    [26] Podhorecka M, Halicka D, Szymczyk A et al. Assessment of red blood cell distribution width as a prognostic marker in chronic lymphocytic leukemia[J]. Oncotarget, 7, 32846-32853(2016).

    [27] Jiao L C, Yang S Y, Liu F et al. Seventy years beyond neural networks: retrospect and prospect[J]. Chinese Journal of Computers, 39, 1697-1716(2016).

    [28] Liu J W, Liu Y, Luo X L. Research and development on deep learning[J]. Application Research of Computers, 31, 1921-1930, 1942(2014).

    [29] Ishimaru A, Marks Ii R J, Tsang L et al. Particle-size distribution determination using optical sensing and neural networks[J]. Optics Letters, 15, 1221-1223(1990).

    [30] Nascimento C A O, Guardani R, Giulietti M. Use of neural networks in the analysis of particle size distributions by laser diffraction[J]. Powder Technology, 90, 89-94(1997).

    [31] Song X Y. Research and application in particle size soft-sensor of radial basis function neural network[D](2009).

    [32] Ren Y L, Mao J D, Zhao H et al. Prediction of aerosol particle size distribution based on neural network[J]. Advances in Meteorology, 2020, 5074192(2020).

    [33] Li Y M, Xie D L, Xu Z P et al. Measurement of particle size distribution in suspension based on artificial neural network[C], 911-916(2019).

    [34] Wu J, Zhou Z, Qi J et al. Size detection and attribute recognition of particles by multi-angle light scattering[J]. Acta Optica Sinica, 37, 0929002(2017).

    [35] Mo Z S, Bu L B, Wang Q et al. Estimation of particulate matter mass concentration based on generalized regression neural network model combining aerosol extinction coefficient and meteorological elements[J]. Chinese Journal of Lasers, 49, 1710001(2022).

    [36] Zhang X Y, Zhou W, Jiang Y X et al. Particle size and position measurement of defocused particle based on convolutional neural network[J]. Acta Optica Sinica, 42, 1912006(2022).

    [37] Yang Y, Dong H, Wang S et al. Surface enhanced Raman scattering detection of four foodborne pathogens using positively charged silver nanoparticles and convolutional neural networks[J]. Chinese Journal of Lasers, 49, 1507405(2022).

    [38] Specht D F. The general regression neural network-rediscovered[J]. Neural Networks, 6, 1033-1034(1993).

    [39] Vega J R, Gugliotta L M, Gonzalez V D et al. Latex particle size distribution by dynamic light scattering: novel data processing for multiangle measurements[J]. Journal of Colloid and Interface Science, 261, 74-81(2003).

    [40] Koppel D E. Analysis of macromolecular polydispersity in intensity correlation spectroscopy: the method of cumulants[J]. The Journal of Chemical Physics, 57, 4814-4820(1972).

    [41] Streekstra G J, Hoekstra A G, Nijhof E J et al. Light scattering by red blood cells in ektacytometry: Fraunhofer versus anomalous diffraction[J]. Applied Optics, 32, 2266-2272(1993).

    [42] Streekstra G J, Hoekstra A G, Heethaar R M. Anomalous diffraction by arbitrarily oriented ellipsoids: applications in ektacytometry[J]. Applied Optics, 33, 7288-7296(1994).

    [43] Tuchin V V, Xu X Q, Wang R K. Dynamic optical coherence tomography in studies of optical clearing, sedimentation, and aggregation of immersed blood[J]. Applied Optics, 41, 258-271(2002).

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    Jiaxing Xu, Min Xia, Kecheng Yang, Yinan Wu, Wei Li. Machine Learning-Based Inversion Algorithm for Particle Size Distribution of Non-Spherical Particle System[J]. Acta Optica Sinica, 2023, 43(9): 0929002

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    Paper Information

    Category: Scattering

    Received: Oct. 31, 2022

    Accepted: Dec. 12, 2022

    Published Online: May. 9, 2023

    The Author Email: Li Wei (weili@hust.edu.cn)

    DOI:10.3788/AOS221901

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