Publications

Peer-reviewed articles, most recent first. Every link goes to the DOI.

Most of it follows the same through-line as the code on this site: what a droplet does between leaving a nozzle and arriving somewhere — how it forms, how fast it evaporates, where the air takes it, and what finally deposits. The rest is particle processing and, in one case, a much earlier detour.

2026

Evaporation rate of droplets of aqueous solutions containing agricultural adjuvants
C. A. Renaudo, M. S. Herrera, D. E. Bertin
Chemical Engineering Science 334 · 10.1016/j.ces.2026.124344

2024

Droplet deposition of agrochemical spraying: comparison of results from a random-walk model and CFD simulations
C. A. Renaudo, V. Bucalá, D. E. Bertin
Canadian Journal of Chemical Engineering 102(8), 2682–2694 · 10.1002/cjce.25198

2023

A hybrid Lagrangian-dispersion model for spray drift prediction applied to horizontal boom sprayers
C. A. Renaudo, D. E. Bertin, V. Bucalá
Journal of Aerosol Science 173 · 10.1016/j.jaerosci.2023.106210

2022

A coupled atomization-spray drift model as online support tool for boom spray applications
C. A. Renaudo, D. E. Bertin, V. Bucalá
Precision Agriculture 23(6), 2345–2371 · 10.1007/s11119-022-09923-1

Prediction of droplet size distributions from a pre-orifice nozzle using the Maximum Entropy Principle
C. A. Renaudo, A. Yommi, G. Slaboch, V. Bucalá, D. E. Bertin
Chemical Engineering Research and Design 185, 198–209 · 10.1016/j.cherd.2022.07.010

Influence of microbubbles on the production of spray-dried inhalable particles
L. Gallo, M. A. Serain, C. Renaudo, E. López, V. Bucalá
Drying Technology 40(9), 1819–1831 · 10.1080/07373937.2021.1881791

2019

Design impact on airflow patterns in fluidization units
C. A. Renaudo, D. E. Bertin, V. Bucalá
Chemical Engineering and Technology 42(11), 2365–2375 · 10.1002/ceat.201800580

2014

The use of artificial neural network modeling to represent the process of concentration by molecular distillation of omega-3 from squid oil
P. Rossi, M. F. Gayol, C. Renaudo, M. C. Pramparo, V. Nepote, N. R. Grosso
Grasas y Aceites 65(4) · 10.3989/gya.0231141

Worth reading the date on that one. Using an artificial neural network as the process model for a separation unit is unremarkable now; in 2014 it was not a tool you reached for in chemical engineering, and the case for it had to be made rather than assumed.