Neural network based model of the kinetics of catalytic hydrogenation reactions

Eugeniusz Molga , K. Roel Westerterp

Abstract

Application of artificial neural networks (ANN) for modelling of the kinetics of a catalytic hydrogenation reaction in a gas-liquid-solid system has been studied and discussed. The kinetics of the hydrogenation of 2,4-DNT over a palladium on alumina catalyst has been described with feedforward neural networks of different architectures. A simple experimental procedure to supply learning data has been proposed. The accuracy and flexibility of the hybrid first principles-neural network model have been tested and compared with those of the classical model. © 1997 Elsevier Science B.V. All rights reserved.

Author Eugeniusz Molga (FCPE / DPKT)
Eugeniusz Molga,,
- Department of Process Kinetics and Thermodynamics
, K. Roel Westerterp - [University of Twente (UT)
Administrator unit: 'COP'
]
K. Roel Westerterp,,
-
- Universiteit Twente
Pages379-388
Book Studies in Surface Science and Catalysis, Studies in Surface Science and Catalysis, 1997, 379-388 p.
ASJC Classification2505 Materials Chemistry; 2508 Surfaces, Coatings and Films; 1606 Physical and Theoretical Chemistry; 3104 Condensed Matter Physics; 1503 Catalysis
Languageen angielski
Score (nominal)3
Publication indicators Scopus Citations = 13; WoS Citations = 8; GS Citations = 10.0; Scopus SNIP (Source Normalised Impact per Paper): 1999 = 0.676
Citation count*10 (2014-12-22)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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