Currently I am synthesizing AgNPs from bacteria. I did the DLS analysis and zeta potential measurement. The most predominant size in my sample was 118 nm and the average around 60 nm. The Zeta potential was -19. Please see the attached photo.
Z-Average is the result of Cumulants analysis which gives hydrodynamic size from the measured autocorrelation function assuming that the sample is monodisperse.
Your size intensity data shows that there are two size populations present in your sample, so it would therefore not be relevant to quote the Z-average.
The intensity distribution shows the relative amount of scattering from different size populations within your sample. Given that light scattering is related to particle size (proportional to r^6), a small amount of a large component may dominate the signal.
The number distribution report uses the optical properties of the sample to present the relative number based of the size distribution from the intensity distribution data.
I hope this helps explain how to interpret your results and good luck with your measurements.
One important point to note is that your report states under 'Result Quality': "Refer to Quality Report"
What does the quality report say?
From ISO and ASTM, the most robust values coming from a DLS experiment are the z-average and PDI but this (as Alexander states) refers to a monodisperse situation. By volume or mass then the lower peak ( ~ 10 nm) will be the major one displayed. For this conversion you'll need the optical properties of the material. At this size then - 19 mV will not be stable - however, I assume you've diluted the sample. This needs to be carried out correctly with the mother liquor to avoid possible agglomeration issues on dilution.
I have diluted and sonicated my sample and I got almost the same result. The quality report stated that the particles are too polydispersed with poor quality. The zeta potential is the same also
The quality report checks for a range of different influences on the data and then summarizes the result with a list of potential causes for the not-so-ideal data quality. One outcome that may look worse than it should is the statement
"Sample too polydisperse for cumulant analysis - suggest rely on distribution analysis"
If that is the case for your data, then the size distribution should be the result for you. If the above line does not appear, then the best procedure is to repeat measurements several times and overlay the results to see how repeatable the obtained distribution actually is.
When comparing the distribution to other techniques, keep in mind that volume/mass or number may be what the other technique is probing.