New Supported Catalytic Binary System for the Green and
Sustainable Production of Cyanogen Fumigant Optimization Using
Artificial Neural Network

J 2014

New Supported Catalytic Binary System for the Green and Sustainable Production of Cyanogen Fumigant Optimization Using Artificial Neural Network

ZELINKA, Karel; Jan ŠIMBERA; Richard ŠEVČÍK; Josef HAVEL; Pavel PAZDERA et al.

Základní údaje

Originální název

New Supported Catalytic Binary System for the Green and Sustainable Production of Cyanogen Fumigant Optimization Using Artificial Neural Network

Autoři

ZELINKA, Karel; Jan ŠIMBERA; Richard ŠEVČÍK; Josef HAVEL a Pavel PAZDERA

Vydání

Journal of Chemical Engineering and Chemistry Research (Chemistry ), 2014, 2333-9195

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10401 Organic chemistry

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Kód RIV

RIV/00216224:14310/14:00073302

Organizační jednotka

Přírodovědecká fakulta

Klíčová slova anglicky

Solid support catalysis; cation-exchanger resin; fumigants; cyanogens; artificial neural networks

Štítky

AKR, rivok

Změněno: 3. 12. 2014 09:08, doc. RNDr. Pavel Pazdera, CSc.

Anotace

V originále

We report a new binary Cu(n)/Fe(m) supported catalytic system for a green and sustainable oxidation of hydrogen cyanide to cyanogen by hydrogen peroxide action. The binary catalytic system Cu(n)/Fe(m), wherein n has the value of I or II, m is II or III, is supported on an acidic cation-exchanger resin. Oxidation process was carried out in a mixture of methanol-water as a solvent. We found that only two undesirable by-products, carbon dioxide and elementary nitrogen are formed during an oxidation of hydrogen cyanide. Furthermore, we observed that the relative content of the target cyanogen and undesirably CO2 depends on all input parameters, i.e. on a character and amount of an applied resin, quantity of both metal ions Fe and Cu supported on catalyst, presence and character of a potential ligand (acetyl acetone or 2,2´-bipyridyl for the stabilization of possible metal oxidation states), input rates of both reagents, and reaction temperature, respectively. Relationship among input and output parameters was studied by using of artificial neural networks (ANNs) and the model for the characterization of relationship within the synthetic process was found, described and used for the optimization. Predicted optimal synthetic input data were successfully verified in experiments. It was found that weakly acidic polyacrylate cation exchanger applied without presence of potential ligands is the most convenient resin for the supported catalytic system. Cyanogen is recently introduced for the protection of agricultural products as a “greener” fumigant to replace existing environmentally dangerous fumigants such as methyl bromide or sulfuryl difluoride.

Návaznosti

TA03010633, projekt VaV

Název: Progresivní udržitelné technologie pro syntézy chemických specialit z oblasti kyanové chemie (Akronym: Kyanchem LZD-MU-VUOS)

Investor: Technologická agentura ČR, Progresivní udržitelné technologie pro syntézy chemických specialit z oblasti kyanové chemie

Citovat

ZELINKA, Karel; Jan ŠIMBERA; Richard ŠEVČÍK; Josef HAVEL a Pavel PAZDERA. New Supported Catalytic Binary System for the Green and Sustainable Production of Cyanogen Fumigant Optimization Using Artificial Neural Network. Journal of Chemical Engineering and Chemistry Research (Chemistry ). 2014, roč. 1, č. 5, s. 302-313. ISSN 2333-9195.

@article{1211612,
   author = {Zelinka, Karel and Šimbera, Jan and Ševčík, Richard and Havel, Josef and Pazdera, Pavel},
   article_number = {5},
   keywords = {Solid support catalysis; cation-exchanger resin; fumigants; cyanogens; artificial neural networks},
   language = {eng},
   issn = {2333-9195},
   journal = {Journal of Chemical Engineering and Chemistry Research (Chemistry )},
   title = {New Supported Catalytic Binary System for the Green and Sustainable Production of Cyanogen Fumigant Optimization Using Artificial Neural Network},
   url = {http://www.ethanpublishing.com/index.php?m=content&c=index&a=show&catid=170&id=271},
   volume = {1},
   year = {2014}
}

TY  - JOUR
ID  - 1211612
AU  - Zelinka, Karel - Šimbera, Jan - Ševčík, Richard - Havel, Josef - Pazdera, Pavel
PY  - 2014
TI  - New Supported Catalytic Binary System for the Green and Sustainable Production of Cyanogen Fumigant Optimization Using Artificial Neural Network
JF  - Journal of Chemical Engineering and Chemistry Research (Chemistry )
VL  - 1
IS  - 5
SP  - 302-313
EP  - 302-313
SN  - 23339195
KW  - Solid support catalysis
KW  - cation-exchanger resin
KW  - fumigants
KW  - cyanogens
KW  - artificial neural networks
UR  - http://www.ethanpublishing.com/index.php?m=content&c=index&a=show&catid=170&id=271
L2  - http://www.ethanpublishing.com/index.php?m=content&c=index&a=show&catid=170&id=271
N2  - We report a new binary Cu(n)/Fe(m) supported catalytic system for a green and sustainable oxidation of hydrogen cyanide to cyanogen by hydrogen peroxide action. The binary catalytic system Cu(n)/Fe(m), wherein n has the value of I or II, m is II or III, is supported on an acidic cation-exchanger resin. Oxidation process was carried out in a mixture of methanol-water as a solvent. We found that only two undesirable by-products, carbon dioxide and elementary nitrogen are formed during an oxidation of hydrogen cyanide. Furthermore, we observed that the relative content of the target cyanogen and undesirably CO2 depends on all input parameters, i.e. on a character and amount of an applied resin, quantity of both metal ions Fe and Cu supported on catalyst, presence and character of a potential ligand (acetyl acetone or 2,2´-bipyridyl for the stabilization of possible metal oxidation states), input rates of both reagents, and reaction temperature, respectively. Relationship among input and output parameters was studied by using of artificial neural networks (ANNs) and the model for the characterization of relationship within the synthetic process was found, described and used for the optimization. Predicted optimal synthetic input data were successfully verified in experiments. It was found that weakly acidic polyacrylate cation exchanger applied without presence of potential ligands is the most convenient resin for the supported catalytic system. Cyanogen is recently introduced for the protection of agricultural products as a “greener” fumigant to replace existing environmentally dangerous fumigants such as methyl bromide or sulfuryl difluoride.
ER  -

ZELINKA, Karel; Jan ŠIMBERA; Richard ŠEVČÍK; Josef HAVEL a Pavel PAZDERA. New Supported Catalytic Binary System for the Green and Sustainable Production of Cyanogen Fumigant Optimization Using Artificial Neural Network. \textit{Journal of Chemical Engineering and Chemistry Research (Chemistry )}. 2014, roč.~1, č.~5, s.~302-313. ISSN~2333-9195.

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