Large-scale computational design and selection of polymers for solar cells
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  • In terms of overall capacity globally: ocean << geothermal < solar PV < solar heating < wind < hydropower6MW << 11GW < 40 < 185 < 198 < 1010
  • TCO – transparent conducting oxidePEDOT - Poly(3,4-ethylenedioxythiophene)PCBM – Phenyl-C61-butyric acid methyl ester
  • Efficiency = ratio of maximum power (FF.i(sc).V(oc)) to incident radiant power
  • 132 monomers
  • 132 monomers
  • 132 monomers
  • Within 1.0

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  • 1. Large-scale computational design and selection of polymers for solar cells Dr Noel O’Boyle & Dr Geoffrey Hutchison ABCRF Department of Chemistry University College Cork University of PittsburghSmart Surfaces 2012: Solar & BioSensor Applications Dublin 6-9 March 2012 [This version edited for web]
  • 2. Ren 21, 2011. Renewables 2011 Global Status Report.Solar photovoltaics is the world’s fastest growing power-generation technology. - In the EU, 2010 was the first year that more PV than wind capacity was added.Majority of capacity is silicon-based solar cells - Costly to produce, materials difficult to source (on large scale)Alternatives such as polymer solar cells hold promise of cheaper electricity.
  • 3. Conductive Polymers• 2000 Nobel Prize in Chemistry “for the discovery and development of conductive polymers” – Alan J. Heeger, Alan G. MacDiarmid and Hideki Shirakawa• Applications in LEDs and polymer solar cells – Low cost, availability of materials, better processability – But not yet efficient enough...
  • 4. Efficiency improvements over time VOC I SC FF Pin McGehee et al. Mater. Today, 2007, 10, 28
  • 5. “Design Rules for Donors in Bulk-Heterojunction Solar Cells” VOC I SC FF Pin VOC (1 / e)( E Donor HOMO E PCBM LUMO ) 0.3V Scharber, Heeger et al, Adv. Mater. 2006, 18, 789
  • 6. “Design Rules for Donors in Bulk-Heterojunction Solar Cells” Max is 11.1% Band Gap 1.4eV LUMO -4.0eV (HOMO -5.4eV) Scharber, Heeger et al, Adv. Mater. 2006, 18, 789
  • 7. Now we know the design rules......but how do we find polymers that match them? Large-scale computational design and selection of polymers for solar cells
  • 8. Computer-Aided Drug Design Library of in-house compoundsLibrary of commercially-available compounds Virtual librarySubstructure filterSimilarity search Docking Priority list of compounds for experimental testing as drug candidates
  • 9. Computer-Aided Screening for Highly- Drug Design Efficient Polymers Library of in-house compoundsLibrary of commercially-available compounds Library of all possible polymers? Virtual librarySubstructure filter Calculate HOMO,Similarity search LUMO Docking % Efficiency Priority list of compounds for Priority list of compounds for experimental testing as drug experimental testing in solar cells candidates
  • 10. 132 monomers Screening for Highly- Cl Cl Br Br NC CN O2N NO2 H3C CH3 S n S n S n S n S n Efficient Polymers 26 27 28 29 30MeO OMe MeO NH2 MeO CN MeO CF3 H2N NO2 S S S S S n n n n n 31 32 33 34 35NC CF3 HO O OH H3C HS OH Library of all possible polymers? S S S S S n n n n n 36 37 38 39 40 O O HN NH S S Se Se O768 million tetramers! S S S S59k synthetically-accessible 41 n 42 n 43 n 44 n S 45 n HN F3CN S Se Calculate HOMO, S S S S n n n S n n LUMO 46 47 48 49 50 % Efficiency Priority list of compounds for experimental testing in solar cells
  • 11. Open Babel1,2 Open Babel MMFF94 Gaussian PM6 cclib3 Gaussian% Efficiency ZINDO/S Slower calculations such as charge mobility Electronic transitions Predicted Efficient [1] OBoyle, Banck, James, Morley, Vandermeersch, Hutchison. J. Polymers Cheminf. 2011, 3, 33. [2] OBoyle, Morley, Hutchison. Chem. Cent. J. 2008, 2, 5. [3] OBoyle, Tenderholt, Langner. J. Comp. Chem. 2008, 29, 839-845.
  • 12. Excited state (eV) Excited state (eV) Counts Counts
  • 13. Excited state (eV) Counts • Number of accessible octamers: 200k − Calculations proportionally slower Excited state (eV) → Brute force method no longer feasible • Solution: use a Genetic Algorithm to Counts search for efficient octamers • Find good solutions while only searching a fraction of the octamers • 7k octamers calculated (of the 200k)
  • 14. Excited state (eV) Excited state (eV) Counts Counts
  • 15. 524 > 9%, 79 > 10%, 1 > 11%
  • 16. 524 > 9%, 79 > 10%, 1 > 11%• Filter predictions using slower calculations• Eliminate polymers with poor charge mobility • Reorganisation energy (λ) is a barrier to charge transport • Here, internal reorganisation energy is the main barrier • λint = (neutral@cation - neutral) + (cation@neutral - cation)
  • 17. O’Boyle, Campbell, Hutchison.J. Phys. Chem. C. 2011, 115, 16200.First large-scale computationalscreen for solar cell materialsA tool to efficiently generate synthetictargets with specific electronicproperties (not a quantitative predictivemodel for efficiencies)...this is just the first step
  • 18. Large-scale computational design and selection of polymers for solar cellsFunding n.oboyle@ucc.ieHealth Research Board Career http://baoilleach.blogspot.comDevelopment FellowshipIrish Centre for High-EndComputingUniversity of PittsburghDr. Geoff HutchisonCasey Campbell Image: Tintin44 (Flickr)Open Source projectsOpen Babel (http://openbabel.org)cclib (http://cclib.sf.net)
  • 19. Accuracy of PM6/ZINDO/S calculationsTest set of 60 oligomers from Hutchison et al, J Phys Chem A, 2002, 106, 10596
  • 20. Searching polymer space using a Genetic Algorithm • An initial population of 64 chromosomes was generated randomly – Each chromosome represents an oligomer formed by a particular base dimer joined together multiple times • Pairs of high-scoring chromosomes (“parents”) are repeatedly selected to generate “children” – New oligomers were formed by crossover of base dimers of parents – E.g. A-B and C-D were combined to give A-D and C-B • Children are mutated – For each monomer of a base dimer, there was a 75% chance of replacing it with a monomer of similar electronic properties • Survival of the fittest to produce the next generation – The highest scoring of the new oligomers are combined with the highest scoring of the original oligomers to make the next generation • Repeat for 100 generations