FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2775771241> ?p ?o ?g. }

• W2775771241 endingPage "21" @default.
• W2775771241 startingPage "10" @default.
• W2775771241 abstract "CO2 hydrogenation was optimized by a combination of AANs (Artificial Neuron Networks) with RSM (Response Surface Methodology) in a microchannel reactor using a K-promoted iron-based catalyst. This robust and cost-effective methodology was reliable to extensively analyze the effect of operating conditions i.e. gas ratio, temperature, pressure, and space velocity on product distribution of selective CO2 hydrogenation. With experimental data as training data using ANNs and Box-Behnken design as design of experiment, the obtained model was able to present good results in a nonlinear noisy process with significant changes of critical operation parameters in an experimental design plan during CO2 hydrogenation using K-promoted iron-based catalyst in a microchannel reactor. The achieved quadratic model was flexible and effective in optimizing either single or multiple objections of product distribution for CO2 hydrogenation." @default.
• W2775771241 created "2017-12-22" @default.
• W2775771241 creator A5023986637 @default.
• W2775771241 creator A5027034980 @default.
• W2775771241 creator A5066956788 @default.
• W2775771241 creator A5076565491 @default.
• W2775771241 creator A5078326384 @default.
• W2775771241 date "2018-03-01" @default.
• W2775771241 modified "2023-10-17" @default.
• W2775771241 title "Artificial neural networks with response surface methodology for optimization of selective CO2 hydrogenation using K-promoted iron catalyst in a microchannel reactor" @default.
• W2775771241 cites W1264901066 @default.
• W2775771241 cites W1518731614 @default.
• W2775771241 cites W1898040326 @default.
• W2775771241 cites W1957276486 @default.
• W2775771241 cites W1967702774 @default.
• W2775771241 cites W1970339193 @default.
• W2775771241 cites W1988470894 @default.
• W2775771241 cites W2007605265 @default.
• W2775771241 cites W2018940436 @default.
• W2775771241 cites W2066257970 @default.
• W2775771241 cites W2082386135 @default.
• W2775771241 cites W2157432447 @default.
• W2775771241 cites W2175775681 @default.
• W2775771241 cites W2243351590 @default.
• W2775771241 cites W2251869852 @default.
• W2775771241 cites W2293745039 @default.
• W2775771241 cites W2296600430 @default.
• W2775771241 cites W2297608469 @default.
• W2775771241 cites W2315086621 @default.
• W2775771241 cites W2338427865 @default.
• W2775771241 cites W2415768042 @default.
• W2775771241 cites W2500621968 @default.
• W2775771241 cites W2512146647 @default.
• W2775771241 cites W2519102655 @default.
• W2775771241 cites W2520401090 @default.
• W2775771241 cites W2528014376 @default.
• W2775771241 cites W2538931867 @default.
• W2775771241 cites W2619053476 @default.
• W2775771241 cites W2620387123 @default.
• W2775771241 cites W2752661218 @default.
• W2775771241 cites W2766569887 @default.
• W2775771241 cites W962309817 @default.
• W2775771241 cites W973237564 @default.
• W2775771241 doi "https://doi.org/10.1016/j.jcou.2017.11.013" @default.
• W2775771241 hasPublicationYear "2018" @default.
• W2775771241 type Work @default.
• W2775771241 sameAs 2775771241 @default.
• W2775771241 citedByCount "52" @default.
• W2775771241 countsByYear W27757712412018 @default.
• W2775771241 countsByYear W27757712412019 @default.
• W2775771241 countsByYear W27757712412020 @default.
• W2775771241 countsByYear W27757712412021 @default.
• W2775771241 countsByYear W27757712412022 @default.
• W2775771241 countsByYear W27757712412023 @default.
• W2775771241 crossrefType "journal-article" @default.
• W2775771241 hasAuthorship W2775771241A5023986637 @default.
• W2775771241 hasAuthorship W2775771241A5027034980 @default.
• W2775771241 hasAuthorship W2775771241A5066956788 @default.
• W2775771241 hasAuthorship W2775771241A5076565491 @default.
• W2775771241 hasAuthorship W2775771241A5078326384 @default.
• W2775771241 hasConcept C105795698 @default.
• W2775771241 hasConcept C118792377 @default.
• W2775771241 hasConcept C119857082 @default.
• W2775771241 hasConcept C127413603 @default.
• W2775771241 hasConcept C147831808 @default.
• W2775771241 hasConcept C150077022 @default.
• W2775771241 hasConcept C154945302 @default.
• W2775771241 hasConcept C161790260 @default.
• W2775771241 hasConcept C17112743 @default.
• W2775771241 hasConcept C171250308 @default.
• W2775771241 hasConcept C178790620 @default.
• W2775771241 hasConcept C185592680 @default.
• W2775771241 hasConcept C186060115 @default.
• W2775771241 hasConcept C192562407 @default.
• W2775771241 hasConcept C21880701 @default.
• W2775771241 hasConcept C2776990819 @default.
• W2775771241 hasConcept C2983524802 @default.
• W2775771241 hasConcept C33923547 @default.
• W2775771241 hasConcept C34559072 @default.
• W2775771241 hasConcept C41008148 @default.
• W2775771241 hasConcept C42360764 @default.
• W2775771241 hasConcept C42922719 @default.
• W2775771241 hasConcept C50644808 @default.
• W2775771241 hasConcept C63662833 @default.
• W2775771241 hasConcept C86803240 @default.
• W2775771241 hasConceptScore W2775771241C105795698 @default.
• W2775771241 hasConceptScore W2775771241C118792377 @default.
• W2775771241 hasConceptScore W2775771241C119857082 @default.
• W2775771241 hasConceptScore W2775771241C127413603 @default.
• W2775771241 hasConceptScore W2775771241C147831808 @default.
• W2775771241 hasConceptScore W2775771241C150077022 @default.
• W2775771241 hasConceptScore W2775771241C154945302 @default.
• W2775771241 hasConceptScore W2775771241C161790260 @default.
• W2775771241 hasConceptScore W2775771241C17112743 @default.
• W2775771241 hasConceptScore W2775771241C171250308 @default.
• W2775771241 hasConceptScore W2775771241C178790620 @default.
• W2775771241 hasConceptScore W2775771241C185592680 @default.
• W2775771241 hasConceptScore W2775771241C186060115 @default.

• next