Hello, A yearly allocation for the LCRC cluster has been requested with the following updated information: Submitter/PI: Jens Niklas Project Name: Solar_EPR Division: CSE Project title: Solar energy conversion in organic photovoltaics Associated funding: DOE Division of Chemical Sciences, Geosciences, and Biosciences Other Systems: Dr. Mardis has three small linux clusters (12/24/48 nodes) which are housed at her home institution. Her research group is the sole users of these systems. Orca, pqs, gabedit, and gamess all can be run on these systems. Science: This work is focused on elucidating the electronic structures of electron donor and electron acceptor molecules which are the most promising solar conversion material for organic photovoltaic devices. A key process of the solar energy conversion in organic photovoltaics is the initial charge separation. Delocalization of the positive and negative polarons on the molecule minimizes wasteful charge recombination. The delocalization correlates with solar energy conversion efficiency and is determined by the electronic structures of the organic molecules. The first aim is to use Density Functional Theory (DFT) to evaluate the extent of polaron delocalization on these systems. The second aim is to explore the effect of solvent and conformation on the calculated magnetic resonance parameters in order to assess the feasibility of this approach for modeling the bulk systems. These results will facilitate interpretation of our multifrequency Electron Paramagnetic Resonance (EPR) data of polymer fullerene bulk heterojunction (BHJ) solar cells. This study will provide a rationale for design of efficient BHJ blends. Project description: We are evaluating the effect of modifying the electron donor part of BHJ solar cells to modify the delocalization of positive polaron, which correlates with solar energy conversion efficiency. Prior work studied delocalization in polymers, oligomers, and monomers of various molecular systems. We will extend our studies to new molecules of interest, which have been reported to provide high efficiencies in organic photovoltaic. This includes the study of electron donor molecules used in small molecule BHJ solar cells which was started in the end of the last FY. In addition, novel non-fullerene based electron acceptors have been recently reported and our collaborators are synthetizing these acceptors for us. DFT calculations will be performed to determine their electronic structure and magnetic resonance parameters. These results will then be compared with our experimental results on BHJ solar cells containing these novel acceptors. We intend to run a series of gas-phase model DFT optimizations to determine the low energy conformations of the various using standard ab initio optimization codes such as Gaussian09, GAMESS, or NWCHEM. This will also allow us to generate a set of conformers likely to be present in the experimental samples. The resultant conformations will be used to calculate EPR parameters (g-tensors and hyperfine coupling constants) using Orca 3.0.3. The initial structure building, monomer and dimer test calculations, and analysis of spin densities will be carried out on our lab computers. The optimization subroutines of NWCHEM, Gaussian09, and GAMESS are highly parallelized. Orca 3.0.3 is a highly accurate program for calculating EPR parameters. Benchmarks on fusion with Orca showed good scaling up to 16 processors for the EPR parameter subroutines. Prior optimization calculations on fusion for the largest oligomer we have calculated so far took about 250 (B3LYP; small basis set) to 425 (Long range functional; medium basis set) CPU hours for optimization. Frequency calculations required the bigmem queues and approximately 5000 CPU hours. The EPR parameter calculations (g-tensor) took 50-150 CPU hours with the largest oligomer requiring the bigmem queue. We anticipate also calculating the hyperfine coupling constants which in test calculations added about three times the computational cost per molecule so each EPR calculation will require 200-600 CPU hours with the longer ones requiring the bigmem queue. Thus, assuming three functionals for each of 10 oligom ers with 4-8 conformations for each requires 66,000 CPU hours for optimization with an additional (5000 CPU x 10 conformations x 3 functionals x 2 bigmem cost)300,000 CPU hours for frequency calculations on the lowest energy conformation for each molecule and functional. The EPR parameter (hyperfine and g-tensor) calculations will take 50,000 (an estimate with some on bigmem) CPU hours. This totals to 416,000 CPU hours. Since we anticipate some of the frequency calculations being possible on other computer systems, and some speed-up with the transition from fusion to blues, we are asking for slightly less (360,000 CPU hours). This is in good agreement with our prior usage of approximately 30K CPU hours/month over the past few months as we’ve moved from benchmarking and testing to production runs. Industry partnership: Project URL: Current FY Hours Used: undetermined amount New FY Requested allocation: 360000 Q1: 90000 Q2: 90000 Q3: 90000 Q4: 90000 Justification: Storage requirements: 1TB Thank You, The LCRC Accounts System