Size distribution of submicron particles by dynamic light scattering measurements: analyses considering normalization errors

Errors in the experimental baseline used to normalize dynamic light scattering data can seriously affect the size distribution resulting from the data analysis. A revised method, which incorporates the characteristics of this error into the size distribution algorithm CONTIN (Ruf 1989), is tested with experimental data of high statistical accuracy obtained from a sample of phospholipid vesicles. It is shown that the various commonly used ways of accumulating and normalizing dynamic light scattering data are associated with rather different normalization errors. As a consequence a variety of solutions differing in modality, as well as in width, are obtained on carrying out data analysis in the common way. It is demonstrated that a single monomodal solution is retrieved from all these data sets when the new method is applied, which in addition provides the corresponding baseline errors quantitatively. Furthermore, stable solutions are obtainable with data of lower statistical accuracy which results from measurements of shorter duration. The use of an additional parameter in data inversion reduces the occurrence of spurious peaks. This stabilizing effect is accompanied by larger uncertainties in the width of the size distribution. It is demonstrated that these uncertainties are reduced by nearly a factor of two on using the normalization error function instead of the ‘dust term’ option for the analysis of noisy data sets.

[1]  E Jakeman,et al.  Statistical accuracy in the digital autocorrelation of photon counting fluctuations , 1970 .

[2]  A. J. Hughes,et al.  Photon-correlation spectroscopy: dependence of linewidth error on normalization, clip level, detector area, sample time and count rate , 1973 .

[3]  Light scattering and intensity fluctuation spectroscopy , 1975 .

[4]  M. F. Cardoso,et al.  The effect of channel correlation on the accuracy of photon counting digital autocorrelators (photon counting spectroscopy) , 1973 .

[5]  G. Zampighi,et al.  Phospholipid vesicle formation and transmembrane protein incorporation using octyl glucoside. , 1981, Biochemistry.

[6]  H. Ruf,et al.  Determination of internal volume and volume distribution of lipid vesicles from dynamic light scattering data , 1989 .

[7]  I. D. Morrison,et al.  Improved techniques for particle size determination by quasi-elastic light scattering , 1985 .

[8]  S. Provencher,et al.  Direct determination of molecular weight distributions of polystyrene in cyclohexane with photon correlation spectroscopy , 1978 .

[9]  C. Oliver Recent Developments in Photon Correlation and Spectrum Analysis Techniques: I. Instrumentation for Photodetection Spectroscopy , 1981 .

[10]  B. Chu Correlation Function Profile Analysis in Laser Light Scattering I. General Review on Methods of Data Analysis , 1983 .

[11]  W. Ray,et al.  Interpretation of photon correlation spectroscopy data: A comparison of analysis methods , 1985 .

[12]  K. Schätzel,et al.  Photon Correlation Measurements at Large Lag Times: Improving Statistical Accuracy , 1988 .

[13]  H. Ruf Effects of normalization errors on size distributions obtained from dynamic light scattering data. , 1989, Biophysical Journal.

[14]  S. Provencher CONTIN: A general purpose constrained regularization program for inverting noisy linear algebraic and integral equations , 1984 .

[15]  Z. Kojro Influence of statistical errors on size distributions obtained from dynamic light scattering data. Experimental limitations in size distribution determination , 1990 .

[16]  Klaus Schatzel,et al.  Noise on photon correlation data. I. Autocorrelation functions , 1990 .

[17]  E. Grell,et al.  Dynamic laser light scattering to determine size distributions of vesicles. , 1989, Methods in enzymology.

[18]  David L. Phillips,et al.  A Technique for the Numerical Solution of Certain Integral Equations of the First Kind , 1962, JACM.

[19]  G. Parry Photon Correlation and Light Beating Spectroscopy , 1975 .

[20]  S. Aragon,et al.  Theory of dynamic light scattering from polydisperse systems , 1976 .

[21]  V. Degiorgio,et al.  Intensity-Correlation Spectroscopy , 1971 .

[22]  S. Provencher,et al.  Inverse problems in polymer characterization: Direct analysis of polydispersity with photon correlation spectroscopy , 1979 .

[23]  E. Stelzer,et al.  Analysis and Resolution of Polydisperse Systems , 1983 .

[24]  K. Schätzel,et al.  Correlation techniques in dynamic light scattering , 1987 .

[25]  R. Pecora,et al.  Dynamic light scattering study of micelles in a high ionic strength solution , 1984 .

[26]  R. Pecora,et al.  Theory of light scattering from hollow spheres. , 1974, Chemistry and physics of lipids.

[27]  F. Hallett,et al.  Vesicle sizing: Number distributions by dynamic light scattering. , 1991, Biophysical journal.

[28]  Dennis E. Koppel,et al.  Analysis of Macromolecular Polydispersity in Intensity Correlation Spectroscopy: The Method of Cumulants , 1972 .

[29]  S. Provencher A constrained regularization method for inverting data represented by linear algebraic or integral equations , 1982 .