Estimating reaction parameters in mechanism‐enabled population balance models of nanoparticle size distributions: A Bayesian inverse problem approach

2021 ◽  
Author(s):  
Danny K. Long ◽  
Wolfgang Bangerth ◽  
Derek R. Handwerk ◽  
Christopher B. Whitehead ◽  
Patrick D. Shipman ◽  
...  
Keyword(s):  
Inverse Problem ◽  
Population Balance ◽  
Nanoparticle Size ◽  
Size Distributions ◽  
Reaction Parameters ◽  
Bayesian Inverse Problem

Fractal analysis as a complimentary technique for characterizing nanoparticle size distributions

2012 ◽  
Vol 226 ◽  
pp. 189-198 ◽  
Author(s):  
Vinod Kanniah ◽  
Peng Wu ◽  
Natalia Mandzy ◽  
Eric A. Grulke
Keyword(s):  
Fractal Analysis ◽  
Nanoparticle Size ◽  
Size Distributions

Solving the inverse problem for aggregation in activated sludge flocculation using a population balance framework

2007 ◽  
Vol 56 (6) ◽  
pp. 95-103 ◽  
Author(s):  
I. Nopens ◽  
N. Nere ◽  
P.A. Vanrolleghem ◽  
D. Ramkrishna
Keyword(s):  
Experimental Data ◽  
Inverse Problem ◽  
Particle Size ◽  
Activated Sludge ◽  
Predictive Power ◽  
Population Balance ◽  
Model Structure ◽  
Forward Simulation ◽  
Floc Size

Many systems contain populations of individuals. Often, they are regarded as a lumped phase, which might, for some applications, lead to inadequate model predictive power. An alternative framework, Population Balance Models, has been used here to describe such a system, activated sludge flocculation in which particle size is the property one wants to model. An important problem to solve in population balance modelling is to determine the model structure that adequately describes experimentally obtained data on for instance, the time evolution of the floc size distribution. In this contribution, an alternative method based on solving the inverse problem is used to recover the model structure from the data. In this respect, the presence of similarity in the data simplifies the problem significantly. Similarity was found and the inverse problem could be solved. A forward simulation then confirmed the quality of the model structure to describe the experimental data.

Particle Size Distributions via Mechanism-Enabled Population Balance Modeling

2020 ◽  
Vol 124 (8) ◽  
pp. 4852-4880 ◽  
Author(s):  
Derek R. Handwerk ◽  
Patrick D. Shipman ◽  
Christopher B. Whitehead ◽  
Saim Özkar ◽  
Richard G. Finke
Keyword(s):  
Particle Size ◽  
Population Balance ◽  
Size Distributions ◽  
Particle Size Distributions ◽  
Population Balance Modeling

Modelling polydisperse nanoparticle size distributions as produced via flame spray pyrolysis

2020 ◽  
Vol 370 ◽  
pp. 116-128 ◽  
Author(s):  
Pedro Bianchi Neto ◽  
Florian Meierhofer ◽  
Henry França Meier ◽  
Udo Fritsching ◽  
Dirceu Noriler
Keyword(s):  
Spray Pyrolysis ◽  
Nanoparticle Size ◽  
Flame Spray Pyrolysis ◽  
Flame Spray ◽  
Size Distributions

scholarly journals Determining magnetic nanoparticle size distributions from thermomagnetic measurements

2010 ◽  
Vol 96 (22) ◽  
pp. 222506 ◽  
Author(s):  
R. S. DiPietro ◽  
H. G. Johnson ◽  
S. P. Bennett ◽  
T. J. Nummy ◽  
L. H. Lewis ◽  
...  
Keyword(s):  
Magnetic Nanoparticle ◽  
Nanoparticle Size ◽  
Size Distributions
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