Prediction of the By-products Formation in the Adiabatic Industrial Benzene Nitration Process

Side reactions are undesirable in most industrial processes, as they decrease process yield and selectivity. For this reason, mononitrobenzene’s manufacturers set nitrophenols minimization as a critical goal, along with the MNB production targets. The mechanism of these side reactions in benzene nit...

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Main Authors: A. Nogueira, D. Silva, M. Reis, C. Baptista
Format: Article
Language:English
Published: AIDIC Servizi S.r.l. 2013-06-01
Series:Chemical Engineering Transactions
Online Access:https://www.cetjournal.it/index.php/cet/article/view/6603
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spelling doaj-0d9a4456e2264f3f8f542fe16d685f252021-02-21T21:13:18ZengAIDIC Servizi S.r.l.Chemical Engineering Transactions2283-92162013-06-013210.3303/CET1332209Prediction of the By-products Formation in the Adiabatic Industrial Benzene Nitration ProcessA. NogueiraD. SilvaM. ReisC. BaptistaSide reactions are undesirable in most industrial processes, as they decrease process yield and selectivity. For this reason, mononitrobenzene’s manufacturers set nitrophenols minimization as a critical goal, along with the MNB production targets. The mechanism of these side reactions in benzene nitration is still under debate and, so far, none of the alternatives has achieved general consensus in the scientific community. As an alternative, industrial data may provide valuable information on the contribution of inlet process variables and operating conditions upon the formation of nitrophenolic compounds in the adiabatic nitration process. In this work, Partial Least Squares regression was applied to data collected from a mononitrobenzene industrial production plant. This methodology allowed concluding that nitration temperature and mixed acid volumetric flow rate as the most influential variables in nitrophenols formation. The models developed enable proper estimates of DNP and TNP concentrations in the industrial process, although their explanation power is lower than those previously obtained by Quadros et al. (2005), in a pilot plant, and by Portugal et al. (2009) in their extended models.https://www.cetjournal.it/index.php/cet/article/view/6603
collection DOAJ
language English
format Article
sources DOAJ
author A. Nogueira
D. Silva
M. Reis
C. Baptista
spellingShingle A. Nogueira
D. Silva
M. Reis
C. Baptista
Prediction of the By-products Formation in the Adiabatic Industrial Benzene Nitration Process
Chemical Engineering Transactions
author_facet A. Nogueira
D. Silva
M. Reis
C. Baptista
author_sort A. Nogueira
title Prediction of the By-products Formation in the Adiabatic Industrial Benzene Nitration Process
title_short Prediction of the By-products Formation in the Adiabatic Industrial Benzene Nitration Process
title_full Prediction of the By-products Formation in the Adiabatic Industrial Benzene Nitration Process
title_fullStr Prediction of the By-products Formation in the Adiabatic Industrial Benzene Nitration Process
title_full_unstemmed Prediction of the By-products Formation in the Adiabatic Industrial Benzene Nitration Process
title_sort prediction of the by-products formation in the adiabatic industrial benzene nitration process
publisher AIDIC Servizi S.r.l.
series Chemical Engineering Transactions
issn 2283-9216
publishDate 2013-06-01
description Side reactions are undesirable in most industrial processes, as they decrease process yield and selectivity. For this reason, mononitrobenzene’s manufacturers set nitrophenols minimization as a critical goal, along with the MNB production targets. The mechanism of these side reactions in benzene nitration is still under debate and, so far, none of the alternatives has achieved general consensus in the scientific community. As an alternative, industrial data may provide valuable information on the contribution of inlet process variables and operating conditions upon the formation of nitrophenolic compounds in the adiabatic nitration process. In this work, Partial Least Squares regression was applied to data collected from a mononitrobenzene industrial production plant. This methodology allowed concluding that nitration temperature and mixed acid volumetric flow rate as the most influential variables in nitrophenols formation. The models developed enable proper estimates of DNP and TNP concentrations in the industrial process, although their explanation power is lower than those previously obtained by Quadros et al. (2005), in a pilot plant, and by Portugal et al. (2009) in their extended models.
url https://www.cetjournal.it/index.php/cet/article/view/6603
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AT cbaptista predictionofthebyproductsformationintheadiabaticindustrialbenzenenitrationprocess
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