How to determine the particle size from DLS ASCII sheet?

Hi Suseel,

If you were to plot this data, you would see a peak representing abundance of particles as a function of particle size.

The modal size according to your data is 220 nm as this has the highest percentage, however you could perform a fit to this data for a peak distribution, to determine a mean size.

I would expect most commercial DLS instruments would do this analysis for you. Do you mind me asking how you came by this data and what you wish to learn from your data?

Alan F Rawle

I have several issues relating to this question. First, one can’t determine a particle size from a sheet in Excel. The latter is simply a collection of numbers telling you nothing about the material, experiment, or application. Someone will have prepared or supplied a material to the analyst who may have prepared it, dispersed, and diluted it for the DLS experiment and collected the data and then used an algorithm or algorithms plus appropriate constants and constraints to calculate various parameters based on the assumptions in the algorithms and the correctness of the constants. A basic set of answers will be provided usually with a graphical plot of the derived result(s). Then certain processes can be enabled such as export to Excel of the data. So, taking a step back:

· There should be a fundamental report sheet or electronic saving of the data

· The above report sheet should contain the most robust DLS properties of z-average and polydispersion index (PDI) derived from the cumulants analysis (see ISI22412:2017 and ASTME2490-09(15)). It is these latter values that are best quoted along with any plot of a derived distribution

· The above report should provide details of the material and the form in which it was measured

DLS is a low-resolution technique so the quoting of so many size classes is ludicrous – indeed if you are incorrectly equating size classes with resolution then that’s another issue to deal with. It may be useful to have these to construct a plot but this does not imply that there’s any value in such high numbers of (apparent) size classes. So, it’s important to understand the basics of the DLS technique and the form of data that is originally generated (the correlogram).

Further, I have issues with the quoted number of decimal places. The diameter of a hydrogen atom is around 74 pm (or 0.07 nm). Thus, the quotation of 4 decimal places after the decimal point (0.0001 nm) implies that the experiment can split the hydrogen atom 700 times or so.

As John explains there are a number of means that can be quoted for such a spreadsheet. Alexander quotes one ‘average’ here – the mode. Both are correct. It’s a simple math or statistics exercise to find out about these averages and the conversion of a histogram to averages. Be aware that the number and spacing of the classes will have a major effect on derived average or points in the distribution. Note that the size classes are not linearly spaced (but logarithmic) and that the assumed mid-point of the size classes is not the arithmetic average of the size bands. Indeed, the only assumption of a histogram bar is that somewhere within this the continuous frequency cure should reside (could be anywhere within this).

Finally, it’s 9 months to Christmas Day. Happy Holidays!

John Francis Miller

@Suseel,

A distribution can have multiple averages that are calculated in different ways. I suggest you read this document that gives a good explanation of the different averages: https://www.horiba.com/fileadmin/uploads/Scientific/Documents/PSA/PSA_Guidebook.pdf

John.

Postscript: if you want some description of the averages as John has indicated you can also try the attached and webinar:

February 16th, 2017 Basic Principles of Particle Size Analysis

http://tinyurl.com/zo6mfgz

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