Please post your graphical plot and the result including any expert advice and quality report.. If you have material outside the range of the analysis range then the z-average will be large. What is MNP?

well Alan as per i think MNP's are Mangnetic Nanoparticles.... well what dispersion medium are you using Namita ....and pls give some more details about ur sample prep if any other polymers are there for stabilising it.

Thanks for the answers, MNPs are magnetic nanoparticles, magnetite with maghemite. Their actual particle size from TEM is 6-8 nm. I have used milli Q water as dispersion medium. This is the question about blank MNPs although I have got the similar results for small organic molecules coated particles as well. I am attaching here a file for the size distribution, its 129.2 nm, z average is 4.6u and pdi is 3.6 for the same. Frequency distribution is 82% 134 nm and 18% 151 nm. How could the z average then be in microns and pdi so high? Then what value should I report and why? Thanks in advance.

The distribution and Z Ave are both results of analytical fits, and anything derrived from a fit is only reliable as long as the model is correct and the fit is of good quality (generally low residuals).

A distribution is typically calculated by inverting a range of fitted sizes to the correlation data, and as such only sizes in this analysis range will be fitted. Your result is the solution within that range that gave the lowest residual, but that does not mean that it is accurate.

Z Ave is not derived from a range of specified sizes but the model applied here assumes a monomodal dispersion. Typically PdI would be reported between 0 and 1, but the fact that you report a PdI of greater than 1 signifies that the fit was not reliable.

DLS data is only reliable if the recorded correlation data is reliable, and I suspect yours isn't for this sample.

Thank you, Mahesh. OK, magnetic nanoparticles.

@ Namita Please show your TEM result as, frankly, I do not believe it. The long range magnetic forces are much greater than short range van der Waals forces and will cause the particles to come together. As the material is dense (~ 5.5 g/cm3) then the agglomerated particles will sink. Hence MilliQ water is a completely unsuitable medium for their preparation and, in particular, their stabilization. Charge stabilization doesn't work in this case of magnetic materials. They need to be sterically stabilized with a polymer - typically 50 kDa PEI or PEG is used.

Have you confirmed the performance of the instrument with an appropriate standard?

BTW you talk of multiple peaks but your one Word document attachment shows a single narrow peak and no tabular information. Why can't you post the full report that comes from the instrument?

Thanks Alexander and Alan. Then my question to Alexander is, can I report the data as the different sized particles with their respective percentages?

@ Alan, I am not attaching the TEM image here but the particles are 6-8 nm. I have attached the data sheet of the instruments, highlighted the peak sizes and z average value. The distribution fit is giving one peak as in the attached word file but there are two peaks with different percentage.

The first thing to do is confirm you have good data before anything else. You are running before you can walk by trying to get different peaks de-convoluted. Please post the plot. My suspicion is that you have a collection of fused sub- and post-micron material. Did the material start as a solid powder?

Again, have you confirmed the performance of the instrument with an appropriate standard?

I have posted the data from the instrument and graph as well. This is not the deconvolution, only the data of the percentage of particles with different sizes in the sample, as provided by the instrument.

Instrument performance was not at the time checked but it was in the past.

The other measurements also gave the similar results.

I hope I could make my point clear. Thanks.

Hi Namita,

As mentioned there are two types of fit applied to DLS data, cumulants and distribution analysis, and it is not clear which of these the fitting data you shared represents.

Either way I produces a quick plot and you can clearly see that whilst the fit is reasonably good at lower delay times, it is poor towards the tail of the correlation function, and slower decays in the correlation function are not being captured.

Looking at the form of the correlation function, it does not present a clear decay and there is no resolved baseline (values around zero) so I would have my doubts about being able to infer anything of meaning using any fitting method.

Either correlation plot above indicates the presence of large material and certainly not material in the 6 - 8 nm range.

Thanks Alexander, the data I have shared is for distribution analysis.

Thanks Alan, the particles are large may be due to aggregation in aqueous media, as they are blank.

May I request for some advice related to good reading material for DLS analysis?

Try the attached.

Hello Namita,

most likely there is a peak beyond the normal display range of the software. Check case #3 in http://www.materials-talks.com/blog/2014/07/10/faq-peak-size-or-z-average-size-which-one-to-pick-in-dls/

If you are completely new to DLS you may also like http://www.materials-talks.com/blog/2015/10/22/new-users-of-dls-the-zetasizer-quick-guide-to-perfection/ with an introduction to the technique.

Your sample may look much "nicer" in TEM due to number versus intensity distribution, however these are just different representations of the same distribution in your sample http://www.materials-talks.com/blog/2017/01/23/intensity-volume-number-which-size-is-correct/

Hope this helps.

Frankly, with a PDI >3 and an order of magnitude difference in size via cumulants and the more advanced algorithm, I'd wouldn't bother trying to interpret the results except to very qualitatively suggest that there are very large particles/aggregates in the sample.

I think everyone would like to see part of a TEM. In my experience, it is a challenge to overcome user bias when choosing "representative" fields of view. It only takes one large aggregate to significantly skew the size distribution when comparing number- and intensity-weighted data. SEM is helpful here because you can get a good wide-field image.

I recommend Ulf's answer

Best Regards

The magnetic Nanoparticle dispersion shows high z average size and large pdi,

the large pdi means your sample is more polydispersed that increases the particle size distribution.

You said that you got only one peak,

sometimes if the sample have various sizes of Nanoparticles, but if the difference between the distribution is not much then resulting plot will give you only one peak and this happen when the NPs size is more than 100 nm higher sizes.

actually, At higher sizes with large pdi, you May observe only one peak.

Thanks Manik, yes there is only small difference between different size distributions, and that may be one reason for large pdi.