Browsing by Subject "Rule-based generation"

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    Construction, analysis, and modeling of complex reaction networks with RING
    (2013-08) Rangarajan, Srinivas
    Complex reaction networks are found in a variety of engineered and natural chemical systems ranging from petroleum processing to atmospheric chemistry and including biomass conversion, materials synthesis, metabolism, and biological degradation of chemicals. These systems comprise of several thousands of reactions and species inter-related through a highly interconnected network. This thesis presents methods, computational tools, and applications that demonstrate that: (a) any complex network can be constructed automatically from a small set of initial reactants and chemical transformation rules, and (b) a given network can be analyzed in terms of identifying topological information such as reaction pathways, determining thermodynamically feasible routes, evaluating the spectrum of plausible and synthetically feasible compounds, exploring dominant routes to form experimentally observed products, and formulating and solving a rigorous kinetic model. A new computational tool called Rule Input Network Generator, or RING, has been developed to construct and analyze complex reaction networks. Given initial reactants of a reaction system (e.g. the components of the feed to a reactor) and reaction rules that describe the possible chemical transformations that can occur, RING first constructs an exhaustive network of reactions and species consistent with the inputs. Inputs into RING are in the form an English-like domain specific language with syntax involving common chemistry parlance. The language compiler further catches erroneous chemistry rules, such as incorrect charge balance in a reaction rule, and heuristically optimizes user-specified instructions to improve the speed of execution. RING, further, accepts "post-processing" instructions that allow for: (i) lumping, or grouping together isomers to reduce the size of the reaction network, (ii) "querying" the network to extract information such as reaction pathways and mechanisms that describe how an initial reactant is transformed into a specific product, (iii) calculating thermochemical properties of species and reactions to evaluate thermochemical feasibility of reaction steps, and (iv) formulating and solving rigorous microkinetic models of complex reaction networks. RING, thus, provides a rule-based" framework to assemble and explore a complex reaction network. RING implements several algorithms, methods, and techniques from computer science, cheminformatics, and graph theory. The language has been developed using SILVER, a meta-language for specifying attribute grammars, and COPPER, a parser generator. The language is extensible in that independent additions can be incorporated to the original language to perform additional analysis without syntactical and semantic conflicts with the existing grammar. Algorithms from chemical graph theory and cheminformatics are adopted to (i) represent molecules as strings externally and as graphs internally, (ii) store reaction rules as graph transformation rules, (iii) identify fragments in molecules that can serve as reaction centers through pattern matching, (iv) determine molecular characteristics such as shape (linear, branched, cyclic, etc.) and aromaticity, and (v) identify isomeric lumps through a new molecular hashing technique. Graph traversal algorithms are further employed by the post-processing modules to identify pathways and mechanisms. This thesis presents several case studies of application of RING in elucidating complex networks of reactions. First, when chemistry alone is known about the system, RING can be used to identify plausible mechanisms for product formation consistent with experimental observations; it can further be used to postulate possible experiments to discriminate between the alternative mechanisms. This has been demonstrated with a case study of glycerol and acetone conversion on solid Bronsted acid catalysts. Second, if molecular properties can be evaluated quickly using semi-empirical methods for a large number of species and compounds, RING can be used to identify species in the network that have desired physical properties and thermochemically favorable synthesis routes to form them. A case study on identifying fatty alcohols, in a spectrum of more than 60,000 compounds, that can potentially be used to make nonionic surfactants with desirable properties and their synthesis routes from biomass-derived oxygenates presents an application of this method. It was found that lauryl alcohol, a fatty alcohol currently used to make surfactants, can be synthesized from biomass-oxygenates using a combination of metal, basic, and acid catalysts. It was also found that some of the intermediate synthesis steps could potentially be coupled to drive the overall reaction forward, or could benefit from using biphasic systems for immediate separation of products from reactants. Third, if activation barriers of each step in the reaction can be reliably predicted using semi-empirical methods, RING can be used to identify dominant reaction mechanisms for converting reactants to experimentally observed products. This was demonstrated by analyzing the energetically favorable mechanisms for glycerol conversion to syn gas or 1,2-propane diol on transition metal catalysts such as Platinum, Palladium, Rhodium, and Ruthenium. It was found that glycerol would decompose to syn gas on Platinum and Palladium, while a significant selectivity to the diol can be obtained on Rhodium and Ruthenium, thus offering insights for designing catalysts for complex biomass conversion systems. Finally, if kinetic parameters and thermochemistry can be estimated apriori, RING can be used to formulate and solve rigorous microkinetic models to get quantitative information such as yield and selectivity. This feature is demonstrated through a model developed for methanol conversion to hydrocarbons (MTH) on Bronsted acid catalyst HZSM-5. RING is generic in terms of chemistries it can handle and flexible in terms of the type of analysis that can be performed. This thesis posits that it can be used in conjunction with experimental and computational chemistry data to elucidate systems with complex reaction networks, especially in hydrocarbon processing and biomass conversion.