Hello, A yearly allocation for the LCRC cluster has been requested with the following updated information: Submitter/PI: Rajeev Surendran Assary Project Name: Cat_Biomass Division: MSD Project title: Computational Studies of Biomass Catalysis Associated funding: EERE Other Systems: CNM Argonne, Blue Gene/P Argonne, NERSC Science: This computational project will be performed to gain fundamental understanding of the chemistry of biomass reactions and help to design catalysts that improve the efficiency of biomass conversion to transportation fuels or industrial chemicals. The project is an integral part of the computational modeling as part of the Computational Biomass Pyrolysis consortium funded by Energy Efficiency and Renewable Energy (EERE). Efficient chemical transformation of biomass is essential to produce sustainable energy and industrial chemicals. Conversion of biomass to useful chemicals include sequence of chemical transformation including, C-O bond cleavage and C-C bond formation. Project description: At present, the project is an integral part of the computational modeling as part of the Computational Biomass Pyrolysis consortium funded by Energy Efficiency and Renewable Energy (EERE). Main challenges facing the biomass conversion reactions are a plethora of undesired reactions and lack of efficient catalysts for various chemical reactions associated with biomass conversion process. Various reactions include dehydration, rehydration, isomerization, aldol/retro aldol reaction, ring opening/closing, carbon-carbon coupling, hydrogenation, and hydrodeoxygenation reactions. A detailed understanding of the chemistry of both desired and undesired reactions, together with the understanding of catalysis is essential for catalyst design for efficient biomass conversion. Our principle objective is identify guidelines to search for efficient C-O bond cleaving and C-C bond forming catalysts from first principles to assist experimentalists to discover efficient c atalysts. This project involves mainly application of existing computational modeling techniques to explore the chemistry and discovery of catalysts. The methods employed are state of the art and accurate to make in situ prediction possible. The computational chemistry approach is based on the accurate principles such as density functional theory and ab initio methods. Software packages such as Gaussian 09, Quantum Espresso, and CPMD were the main tools employed for this information. Following specific problems will be addressed using first principle-based simulations. 1. Catalytic Deactivation of HZSM5 zeolite: Activity: Develop a model for this process (molecular to mesoscale scale) to predict catalyst deactivation for selected model compounds. (b) Quantitative structure activity Relationships of bio-oil surrogates with HZSM5: dev Adsorption and Kinetics of aromatics and low molecular weight carbohydrates. (c) Develop models that enables to predict the adsorption and kinetics of bio-oil surrogates using QSAR type approach Verify this experimentally(d) Mechanistic understanding of acid catalyzed Levoglucosenone to Hydroxy Methyl Furfural; (LGO-HMF) conversion Industry partnership: Industry Partnership: Project URL: http://cpcbiomass.org/ Project URL: http://cpcbiomass.org/ Current FY Hours Used: undetermined amount New FY Requested allocation: 800000 Q1: 200000 Q2: 200000 Q3: 200000 Q4: 200000 Justification: Efficiency: Gaussian 09/VASP software is scalable up to 64 processes. Here main bottle neck is large number of calculations and long execution times than the parelliization. CPMD and CP2K are high performance software packages, scalable to 64 nodes. Storage requirements: Thank You, The LCRC Accounts System