Results 161 to 170 of about 1,750,632 (381)

An Efficient and Unified Modeling Framework for Trickle Bed Reactors: A Modular Approach

open access: yesChemie Ingenieur Technik, EarlyView.
This review gives an insight in modeling and designing techniques for multiphase catalytic reactors and their associated limitations and potential improvements. To enhance the predictive capabilities and capture events that take place on different scales, a modular approach is proposed.
Vasileios K. Mappas   +4 more
wiley   +1 more source

Local sensitivity analysis of a supercritical extraction model

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Abstract This study investigates the process of chamomile oil extraction from chamomile flowers. A parameter‐distributed model, consisting of a set of partial differential equations, was used to describe the governing mass transfer phenomena between solid and fluid phases under supercritical conditions using carbon dioxide as the solvent.
Oliwer Sliczniuk, Pekka Oinas
wiley   +1 more source

Estimating strongly wetting to non‐wetting contact angles for pure and mixed liquids on solids by considering film pressure

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Abstract In solid–liquid–vapour systems, the effect of film pressure (πe$$ {\pi}_e $$) by vapour adsorbate molecules becomes significant when the solid surface energy is similar to or larger than that of the liquid. We extend Young equation applicability to estimate contact angles of pure and mixed liquids on smooth solids by including πe$$ {\pi}_e $$,
Aliakbar Roosta, Nima Rezaei
wiley   +1 more source

On algebraic Lie algebras. [PDF]

open access: yesJournal of the Mathematical Society of Japan, 1948
openaire   +3 more sources

Learning hydrocracking reaction dynamics via neural ODEs: A data‐driven, gradient‐interpretable lumped modelling framework

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
This work demonstrates the application of neural ordinary differential equations (neural ODEs) for learning hydrocracking reaction kinetics directly from data, achieving robust predictions under noise and sparsity while preserving mechanistic interpretability through gradient‐based analysis of temperature‐ and concentration‐dependent reaction rates ...
Souvik Ta   +2 more
wiley   +1 more source

College Algebra with Applications.

open access: green, 1917
D. N. Lehmer   +2 more
openalex   +2 more sources

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