FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2036544080> ?p ?o ?g. }

• W2036544080 endingPage "611" @default.
• W2036544080 startingPage "605" @default.
• W2036544080 abstract "Transition metal catalysts play a crucial role in many industrial applications, including the manufacture of lubricants, smoke suppressants, corrosion inhibitors and pigments. The development of novel catalysts is commonly performed using a trial-and-error approach which is costly and time-consuming. The application of computer-aided molecular design (CAMD) to this problem has the potential to greatly decrease the time and effort required to improve current catalytic materials in terms of their efficacy and biological effects. This work applies an optimization approach to redesign environmentally-benign homogeneous catalysts, specifically those which contain transition metal centers, to improve certain physical properties. Two main tasks must be achieved in order to perform the molecular design of a novel catalyst: biological and chemical properties must be estimated directly from the molecular structure, and the resulting optimization problem must be solved in a reasonable time. In this work, connectivity indices are used for the first time to predict the physical properties of a homogeneous catalyst. The existence of multiple oxidation states for transition metals requires a reformulation of the original equations for these indices. Once connectivity index descriptors have been defined for transition metal catalysts, structure–property correlations are then developed based on regression analysis using literature data for various properties of interest, including toxicity and electronegativity. These structure–property correlations are then used within an optimization framework to design novel homogeneous catalyst structures for use in a given application. The use of connectivity indices which define the topology of the molecule within the formulation guarantees that a complete molecular structure is obtained when the global optimum is found. In this work, second-order connectivity indices are used to obtain more information about steric features of the catalyst molecules, and non-linear correlations are employed to improve the accuracy of the property prediction equations. The structure–property correlations are then combined with linear structural feasibility constraints to form a mixed-integer non-linear program (MINLP), which when solved to optimality results in a catalyst molecule which most closely matches given property targets. To solve the resulting optimization problem, two methods are applied: Tabu search (a stochastic method), and outer approximation, a deterministic approach. For the outer approximation solution, a data structure is used which permits all equations except for the property prediction expressions to be written in linear forms. The computational efficiency of Tabu search is not strongly dependent on the existence of non-linear constraints, so for solution using this method, a non-linear form for the second-order connectivity index was chosen, which decreases the number of binary variables required. The solution methods are compared using three examples involving the design of environmentally-benign homogeneous catalysts containing molybdenum centers. Results show the efficacy of the formulation, and provide evidence that the Tabu search algorithm is more suitable for this type of molecular design algorithm than the commercially available deterministic approach." @default.
• W2036544080 created "2016-06-24" @default.
• W2036544080 creator A5003948950 @default.
• W2036544080 creator A5061592458 @default.
• W2036544080 creator A5062315245 @default.
• W2036544080 creator A5066191241 @default.
• W2036544080 date "2004-05-01" @default.
• W2036544080 modified "2023-09-23" @default.
• W2036544080 title "Environmentally-benign transition metal catalyst design using optimization techniques" @default.
• W2036544080 cites W1964959815 @default.
• W2036544080 cites W1972776843 @default.
• W2036544080 cites W1980202436 @default.
• W2036544080 cites W1981097545 @default.
• W2036544080 cites W2005712405 @default.
• W2036544080 cites W2037361138 @default.
• W2036544080 cites W2045056637 @default.
• W2036544080 cites W2068110511 @default.
• W2036544080 cites W2071334094 @default.
• W2036544080 cites W2081750791 @default.
• W2036544080 cites W2084792706 @default.
• W2036544080 cites W2088515272 @default.
• W2036544080 cites W2095112175 @default.
• W2036544080 cites W2149714238 @default.
• W2036544080 cites W4212899374 @default.
• W2036544080 doi "https://doi.org/10.1016/j.compchemeng.2004.02.005" @default.
• W2036544080 hasPublicationYear "2004" @default.
• W2036544080 type Work @default.
• W2036544080 sameAs 2036544080 @default.
• W2036544080 citedByCount "38" @default.
• W2036544080 countsByYear W20365440802012 @default.
• W2036544080 countsByYear W20365440802013 @default.
• W2036544080 countsByYear W20365440802015 @default.
• W2036544080 countsByYear W20365440802016 @default.
• W2036544080 countsByYear W20365440802017 @default.
• W2036544080 countsByYear W20365440802018 @default.
• W2036544080 countsByYear W20365440802019 @default.
• W2036544080 countsByYear W20365440802021 @default.
• W2036544080 countsByYear W20365440802022 @default.
• W2036544080 crossrefType "journal-article" @default.
• W2036544080 hasAuthorship W2036544080A5003948950 @default.
• W2036544080 hasAuthorship W2036544080A5061592458 @default.
• W2036544080 hasAuthorship W2036544080A5062315245 @default.
• W2036544080 hasAuthorship W2036544080A5066191241 @default.
• W2036544080 hasConcept C106773901 @default.
• W2036544080 hasConcept C11413529 @default.
• W2036544080 hasConcept C127413603 @default.
• W2036544080 hasConcept C137836250 @default.
• W2036544080 hasConcept C161790260 @default.
• W2036544080 hasConcept C177293861 @default.
• W2036544080 hasConcept C178790620 @default.
• W2036544080 hasConcept C183696295 @default.
• W2036544080 hasConcept C185592680 @default.
• W2036544080 hasConcept C18762648 @default.
• W2036544080 hasConcept C192562407 @default.
• W2036544080 hasConcept C21880701 @default.
• W2036544080 hasConcept C41008148 @default.
• W2036544080 hasConcept C78519656 @default.
• W2036544080 hasConceptScore W2036544080C106773901 @default.
• W2036544080 hasConceptScore W2036544080C11413529 @default.
• W2036544080 hasConceptScore W2036544080C127413603 @default.
• W2036544080 hasConceptScore W2036544080C137836250 @default.
• W2036544080 hasConceptScore W2036544080C161790260 @default.
• W2036544080 hasConceptScore W2036544080C177293861 @default.
• W2036544080 hasConceptScore W2036544080C178790620 @default.
• W2036544080 hasConceptScore W2036544080C183696295 @default.
• W2036544080 hasConceptScore W2036544080C185592680 @default.
• W2036544080 hasConceptScore W2036544080C18762648 @default.
• W2036544080 hasConceptScore W2036544080C192562407 @default.
• W2036544080 hasConceptScore W2036544080C21880701 @default.
• W2036544080 hasConceptScore W2036544080C41008148 @default.
• W2036544080 hasConceptScore W2036544080C78519656 @default.
• W2036544080 hasIssue "5" @default.
• W2036544080 hasLocation W20365440801 @default.
• W2036544080 hasOpenAccess W2036544080 @default.
• W2036544080 hasPrimaryLocation W20365440801 @default.
• W2036544080 hasRelatedWork W1979227820 @default.
• W2036544080 hasRelatedWork W1980545080 @default.
• W2036544080 hasRelatedWork W1983644133 @default.
• W2036544080 hasRelatedWork W2094754776 @default.
• W2036544080 hasRelatedWork W211624929 @default.
• W2036544080 hasRelatedWork W2364749328 @default.
• W2036544080 hasRelatedWork W2748952813 @default.
• W2036544080 hasRelatedWork W2899084033 @default.
• W2036544080 hasRelatedWork W3024798676 @default.
• W2036544080 hasRelatedWork W4246591301 @default.
• W2036544080 hasVolume "28" @default.
• W2036544080 isParatext "false" @default.
• W2036544080 isRetracted "false" @default.
• W2036544080 magId "2036544080" @default.
• W2036544080 workType "article" @default.