Abstract: The paper proposes two new efficient algorithms, implemented by a short program code in MS Excel, designed to identify and
characterize the sizes of nano- and micropowders of particles in the form of generalized gamma or lognormal distributions according
to experimental histograms. The proposed method is a new general approach to solving inverse problems of identifying the
parameters of differential distribution functions from experimental data based on minimizing the functional that is the coefficient of
The algorithm is implemented with formulas (less than 10) of the most common tools (MS Excel spreadsheets without the use of
macros), which allow researchers without the skills of professional programmers to easily check and reproduce the presented
material, as well as the ability to modify the code to solve a wider range of problems. The text of the article and comments on the
worksheets of screenshots represent ready-made instructions for solving problems of identification of distribution functions and
characterization of the sizes of nano- and micropowders.
Index terms: particles, powders, distribution function, generalized gamma distribution, lognormal distribution, moment of distribution function, identification of distribution function, characterization of particle sizes, spreadsheets, program code.