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 and 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, vol. 1, No 5, p. 302-313. ISSN 2333-9195.

Basic information

• Original name: New Supported Catalytic Binary System for the Green and Sustainable Production of Cyanogen Fumigant Optimization Using Artificial Neural Network
• Authors: ZELINKA, Karel (203 Czech Republic, belonging to the institution), Jan ŠIMBERA (203 Czech Republic, belonging to the institution), Richard ŠEVČÍK (203 Czech Republic, belonging to the institution), Josef HAVEL (203 Czech Republic, belonging to the institution) and Pavel PAZDERA (203 Czech Republic, guarantor, belonging to the institution).
• Edition: Journal of Chemical Engineering and Chemistry Research (Chemistry ), 2014, 2333-9195.

Other information

• Original language: English
• Type of outcome: Article in a journal
• Field of Study: 10401 Organic chemistry
• Country of publisher: United States of America
• Confidentiality degree: is not subject to a state or trade secret
• WWW: URL
• RIV identification code: RIV/00216224:14310/14:00073302
• Organization unit: Faculty of Science
• Keywords in English: Solid support catalysis; cation-exchanger resin; fumigants; cyanogens; artificial neural networks
• Tags: AKR, rivok

Abstract

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.

Links

• TA03010633, research and development project: Name: Progresivní udržitelné technologie pro syntézy chemických specialit z oblasti kyanové chemie (Acronym: Kyanchem LZD-MU-VUOS)

Investor: Technology Agency of the Czech Republic