### Abstract

A method is proposed using the non-negative least-squares (NNLS) algorithm of Lawson and Hanson to analyze dynamic light scattering (DLS) data for the size distribution of particles in a colloidal dispersion. The NNLS algorithm gives sparse solutions, which are sensitive to the domains used for reconstructing the solutions. The method uses the algorithm to construct an optimal solution from a set of sparse solutions of different domains but of the same dimension. The sparse solutions are superimposed to give a general solution with its dimension being treated as a regularization parameter. An optimal solution is specified by a suitable value for the dimension, which is determined by either Morozov's criterion or the L-curve method. Simulated DLS data are generated from a unimodal and a bimodal distribution for evaluating the performance of the method, which is then applied to analyze experimental DLS data from the ocular lenses of a fetal calf and a Rhesus monkey to obtain optimal size distributions of the α-crystallins and crystallin aggregates in the ocular lenses.

Original language | English |
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Pages (from-to) | 459-477 |

Number of pages | 19 |

Journal | Chinese Journal of Physics |

Volume | 50 |

Issue number | 3 |

Publication status | Published - 2012 Jun |

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### All Science Journal Classification (ASJC) codes

- Physics and Astronomy(all)

### Cite this

*Chinese Journal of Physics*,

*50*(3), 459-477.

}

*Chinese Journal of Physics*, vol. 50, no. 3, pp. 459-477.

**Submicron particle size distributions by dynamic light scattering with non-negative least-squares algorithm.** / Ansari, Rafat R.; Nyeo, Su-Long.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Submicron particle size distributions by dynamic light scattering with non-negative least-squares algorithm

AU - Ansari, Rafat R.

AU - Nyeo, Su-Long

PY - 2012/6

Y1 - 2012/6

N2 - A method is proposed using the non-negative least-squares (NNLS) algorithm of Lawson and Hanson to analyze dynamic light scattering (DLS) data for the size distribution of particles in a colloidal dispersion. The NNLS algorithm gives sparse solutions, which are sensitive to the domains used for reconstructing the solutions. The method uses the algorithm to construct an optimal solution from a set of sparse solutions of different domains but of the same dimension. The sparse solutions are superimposed to give a general solution with its dimension being treated as a regularization parameter. An optimal solution is specified by a suitable value for the dimension, which is determined by either Morozov's criterion or the L-curve method. Simulated DLS data are generated from a unimodal and a bimodal distribution for evaluating the performance of the method, which is then applied to analyze experimental DLS data from the ocular lenses of a fetal calf and a Rhesus monkey to obtain optimal size distributions of the α-crystallins and crystallin aggregates in the ocular lenses.

AB - A method is proposed using the non-negative least-squares (NNLS) algorithm of Lawson and Hanson to analyze dynamic light scattering (DLS) data for the size distribution of particles in a colloidal dispersion. The NNLS algorithm gives sparse solutions, which are sensitive to the domains used for reconstructing the solutions. The method uses the algorithm to construct an optimal solution from a set of sparse solutions of different domains but of the same dimension. The sparse solutions are superimposed to give a general solution with its dimension being treated as a regularization parameter. An optimal solution is specified by a suitable value for the dimension, which is determined by either Morozov's criterion or the L-curve method. Simulated DLS data are generated from a unimodal and a bimodal distribution for evaluating the performance of the method, which is then applied to analyze experimental DLS data from the ocular lenses of a fetal calf and a Rhesus monkey to obtain optimal size distributions of the α-crystallins and crystallin aggregates in the ocular lenses.

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M3 - Article

VL - 50

SP - 459

EP - 477

JO - Chinese Journal of Physics

JF - Chinese Journal of Physics

SN - 0577-9073

IS - 3

ER -