Polymers and Perovskites for Hybrid Tandem Photovoltaics

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1 Polymers and Perovskites for Hybrid Tandem Photovoltaics Michael D. McGehee Stanford University 1.2 V 1.2 V 0.6 V 0.6 V

2 Tandem Photovoltaics 2 Goal: Inexpensive cells with efficiency 25% Efficiency Cost Organic 12% efficient $30/m 2 Hybrid 25% efficient $100/m 2 Epitaxial crystalline 45 % efficient $40,000/m 2 Heliatek s oligomer tandem Low Cost Defect-Tolerant Technology: Perovskite, Organic, Nanowires or II-VI E g ~ 1.9 ev Established Technology: Silicon or CIGS E g ~ 1.1 ev Fraunhofer s wafer bonded tandem

3 Hybrid Tandem Architectures 3 Glass Transparent Electrode Top Cell Transparent Electrode Transparent Electrode Bottom Cell Rear Contact 4 Terminal Easier prototyping No current matching required No tunnel junction or recombination layer required Transparent Electrode Top Cell Tunnel Junction/ Recombination Layer Bottom Cell Rear Contact 2 Terminal Fewer layers that parasitically absorb Module fabrication easier

4 4 How the Morphology of Polymer Bulk Heterojunction Solar Cells Determines the Charge Separation Efficiency Jon Bartelt, Tim Burke, Jason Bloking, Sean Sweetnam, William Mateker, Alberto Salleo, Michael Toney and Mike McGehee (Stanford University) Jessica Douglas, Jean chet (UC Berkeley) Ken Graham, Clement Cabanetos, Abdulrahman El Labban, Aram Amassian, Pierre Beaujuge (KAUST) Chad Risko, Jean Luc Bredas (Georgia Tech) Thomasso Giovanno, Alan Sellinger (Colorado School of Mines) Brain Collins, Harald Ade (NC State)

5 3-Phase Morphology with Energetic Offsets Local Energy Landscape Donor Mixed Region Acceptor EVac Electron Affinity Ionization Potential Energy - Donor Polymer + Fullerene Acceptor Bartelt, et al. Adv. En. Mat Skompska et al. Electrochimia Acta Kim et al. Nature Materials Durrant et al. Chemical Science 3. (2012) 5

6 Kinetic Monte Carlo Simulations Hopping rates calculated from a mobility model + - ~ E Recombination rate inferred from experiment An event is picked at random and the process repeats Kinetic Monte Carlo allows for simulation of processes where all rates are known 6

7 7 Our Modeling Assumptions r ec hop Width + ~ E - Donor Mixed Region Acceptor hop Incorporates Observations 1. Includes the mixed region 2. Nearest neighbor initial conditions 3. Experimental lifetimes and mobility 4. Low electric field (10 3 V/cm) Trilayer Simulation

8 8 Low Mobility Regime 3.2 nm mixed region: τ = 5 ns and μ = 4 * 10-4 cm 2 /Vs Energetic Offset Geminate Separation Probability 0 < 0.1% 200 mev < 0.1%

9 9 Medium Mobility Regime 3.2 nm mixed region: τ = 5 ns and μ = 4 * 10-2 cm 2 /Vs Energetic Offset Geminate Separation Probability 0 0.9% 200 mev 25%

10 10 High Mobility Regime 3.2 nm mixed region: τ = 5 ns and μ = 4 cm 2 /Vs Energetic Offset Geminate Separation Probability 0 41% 200 mev 96%

11 11 Simulated Separation vs Time μ = 10 cm 2 /Vs and τ = 1 ns, IQE = 50% Split After 1.75 ns Split After 0.75 ns Recomb. After 0.85 ns

12 What is the local mobility in OPV? Previous Monte Carlo Studies Group Year Local Mobility * Janssen et al x 10-5 cm 2 /Vs Groves et al x 10-3 cm 2 /Vs Deibel et al x 10-5 cm 2 /Vs Tachiya et al x 10-3 cm 2 /Vs Groves x 10-4 cm 2 /Vs * Values corrected for comparison across mobility models Terahertz Spectroscopy System Φ*(μ e +μ h ) P3HT/PCBM cm 2 /Vs P3HT/PCBM cm 2 /Vs P3HT/PCBM cm 2 /Vs APFO-3/PCBM 4 1 cm 2 /Vs APFO-3/PCBM cm 2 /Vs ZNPC/C cm 2 /Vs TQ1/PCBM cm 2 /Vs References /jp065212i /PhysRevB /jp711827g /jp710184r /jz301013u / /ja301757y /j.chemphys / /PhysRevLett / /c3ee24455e

13 13 What makes BHJs work well Donor Mixed Region Acceptor - + Polymer Fullerene Local μ ( cm 2 /Vs) τ ct (1-10 ns) >90% IQE 3 Phase Morphology

14 Center for Advanced Molecular Photovoltaics Stanford Michael McGehee (MSE) Reiner Dauskardt (MSE) Zhenan Bao (Chemical Engineering) Stacey Bent (Chemical Engineering) Mark Brongersma (MSE) Shanhui Fan (EE) Alberto Salleo (MSE) Michael Toney (SSRL) Outside Stanford Jean-Luc Brédas (Georgia Tech) Brad Chmelka (UCSB) Michael Grätzel (EPFL Switzerland) Mark Thompson (USC) Jean Fréchet (UC Berkeley and KAUST) KAUST Collaborators Aram Amassian Pierre Beaujuge

15 Device Efficiency (%) 15 Perovskite Solar Cells are Soaring Jul 2013 Grätzel 15% Sept 2013 Snaith 15.4% Snaith et al., Nature 2013 Grätzel et al., Nature Year

16 Perovskites 16 Generic formula: ABX 3, where X = oxygen or halide A cation 12-fold, B-cation 6-fold co-ordinated with X anion Pb I CH 3 NH 3 CH 3 NH 3 PbI 3 Methylammonium-lead-iodide

17 Grätzel et al., Nature Record Mesostructured Perovskite Cell

18 Record Planar Perovskite Cell 18 Jsc = 21.5 ma/cm 2 Voc = 1.07 V FF = 0.68 η = 15.4% Snaith et al., Nature 2013

19 19 Low voltage losses in perovskite solar cells Material Bandgap (ev) q Voc (ev) Energy loss (ev) GaAs CIGS ~ Silicon Perovskite (CH 3 NH 3 PbI 3 ) CdTe a-silicon Perovskites out perform CdTe, a-si and continue to improve! M. Green et al. Solar cell efficiency tables (version 42) July 2013

20 New GCEP Project Colin Bailie, Becky Belisle, Andrea Bowring, Rongrong Cheacharoen, Greyson Christoforo, Eric Hoke, Eva Unger and Michael McGehee Emma Dohner, Ian Smith, Hema Karunadasa 20

21 Goals for the GCEP Project 21 Figure out what makes PbMAI 3 so special. Fully optimize it. Raise the band gap and obtain V OC > 1.3 V. Develop lead-free perovskite solar cells. Study degradation and make stable cells. Make >25 % efficient hybrid tandems on silicon.

22 22 Our Semitransparent Perovskite Cells We expect huge improvements since Graetzel has made cells with 15 % efficiency and the records are soaring with perovskites.

23 Increasing the Band Gap 23 We need perovskite cells with band gaps of ev for current matching The band gap can be increased by substituting some bromine for the iodine creating MAPbI 3-x Br x E g of 1.8 ev: CH 3 NH 3 Pb(Br 0.5 I 0.5 ) 3