Dynals has proved itself as the fast, reliable and user-friendly software for Particle Size Distribution analysis in Photon Correlation Spectroscopy also known as (Quasi Elastic or Dynamic Light Scattering). Dynals uses proprietary, NTSVD algorithm for solving the associated ill-posed mathematical problem.

Dynals includes the old as well as new computational methods:

  • Particle Size Distribution analysis with reliable automatic or visually assisted choice of regularization level
  • Distribution Peak Analysis gives full information about individual peaks in the computed distribution
  • Robust, GLSA based multi-exponential analysis (up to four components) with automatic choice of initial conditions
  • Cumulant Analysis with variable number of cumulants

Dynals includes many other new features that make in unique software for data analysis:

  • Simultaneous plot of experimental data, residuals, computed particle size distribution and its peak analysis as well as graphical representation of multi-exponential and cumulant analysis
  • Simultaneous analysis and overlapping presentation of results for several experimental data sets greatly simplifies comparison without using any external software
  • Simultaneous analysis and results presentation of experimental data by different processing methods provides additional confidence in the results
  • Export of results in text format or in one of popular image formats
  • Export of result into file or clipboard for easy import into documents, presentations and image handling software
  • External control interface allows running and controlling Dynals from other applications

Dynals support several types of input data formats:

  • Simple data format (*.dat)
  • Tagged Data Format (*.tdf)
  • Photocor data format

Dynals screenshot examples

Distribution Analysis with optimal resolution Distribution Analysis for multiple selection
Distribution Analysis with high resolution Discrete Components Analysis for multiple selection
Multiple Analysis of one data file Multiple Analysis for multi-selection

You may get more information by Viewing Dynals white paper