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Novel Next-Generation Multijunction Quantum Dot Solar Panel Designs Using Monte Carlo-Based Modeling. Valerie Ding. Introduction. Problem. The Idea. Model. Results. Conclusion. Overview. Introduction The Problem The Idea The Model Data and Analysis Conclusion. Introduction.

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## Novel Next-Generation Multijunction Quantum Dot Solar Panel Designs Using Monte Carlo-Based Modeling

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**Novel Next-Generation Multijunction Quantum Dot Solar Panel**DesignsUsing Monte Carlo-Based Modeling Valerie Ding**Introduction**• Problem • The Idea • Model • Results • Conclusion Overview • Introduction • The Problem • The Idea • The Model • Data and Analysis • Conclusion**Introduction**• Our Sun is incredibly powerful • We can harness its energy Just 45 minutes of sunlight on Earthprovides complete global energy needs for 1 year Sun to Earth: 1.74 X 1017 Watts**The Problem**• 30+ billion tons of CO2 emissions EACH YEAR • 100 times the weight of the entire human race • Solar energy is a perfect solution: clean and infinite • Yet, solar is < 1% of world energy supply; current solar is not competitive**The Culprit: Cost**Solar energy cost, in dollars, per watt**The Key Limiter of Cost: Efficiency**• Conventional solar cells have average 15% and demonstrated maximum 21% efficiency. • Conventional solar cell efficiency is limited by Shockley-Queisser: theoretical maximum efficiency is 33.7%. • Spectral losses are the biggest mode of loss. More than half of solar irradiance (at right, in blue) is currently unused in electricity generation.**High-Efficiency Multijunction AND Low-Cost Quantum Dots**High efficiency: Multijunction solar cells boost efficiency by tuning each layer for a specific spectral portion. e- e- e- e- e- Low cost:Quantum dots enable bandgap tuning without changing material. e- e- e- e-**Challenges Facing Multijunction Quantum Dot Solar Cells**• Multijunction quantum dot solar cells (MJQDSCs) offer huge potential for solar energy. • Very little experimental data is available, as it is difficult to conduct experiments without a good understanding of complex photon-quantum dot interactions. • This work focuses on modeling and investigating interactions in order to address the most important issue: designing multijunction quantum dot solar cells to minimize intrinsic spectral losses.**My Integrated Methodology**• NanoHUB • Cloud computing • Bulk PbS properties • NREL: • Solar spectrum on earth • Monte Carlo simulation for each MJQD SC stack • Compare Spectral Loss and Efficiency • QD Absorption Spectrum for each • Best • MJ • QDSC • Schrodinger equation solutions • Gaussian • distribution to account for QD diameter spread • Colloidal PbS quantum dot diameters • JAVA program, 10 million photons**Schrodinger’s equation (3-D time-independent)**• h is Planck’s constant • mis particle’s mass • Ψ is particle’s wavefunction • Laplace operator (2nd-order differential eq.) Photon Absorptionby QDs • Absorption coefficient (can be quantum mechanically computed) • frepresents the Fermi-Dirac distribution • δ function is a step function = 1 when EC– EV– E = 0, otherwise 0 where**A sample of states: 5nm QD diameter, states 1, 5, 17, 30,**85, and 100**Flux and 10 Million Photons**Intensity I at photon energy E is fluxF (# photons striking surface) times E Flux will change as photons travel through solar cells. For one photon in one layer, change in flux can be expressed as a ceiling function: r = random # generator p = absorption probability For a multijunction solar cell with 10 million incoming photons assumed, change in flux can be expressed as: at energy E The distribution of 10 million photons across the solar spectrum is described at right, which assumes a Gaussian distribution of photon energies due to quantum dot diameter distribution.**Intrinsic and Carnot Efficiency**The total incoming solar power is P0: Usable power by N stacks total: Intrinsic efficiency, absorbed/incoming Thermodynamic loss is common to all solar cells. The intrinsic efficiency is multiplied by the Carnot thermal efficiency η(right) to find the theoretical maximum.**The Designs**Using this grid size, the best order and size choices identified with Monte Carlo modeling**Analysis**• As predicted, increasing the number of stacks leads to higher intrinsic efficiency. • The model accounted for normalization by holding the total thickness of QD layers at 18 microns. • Because the simulation involved 10 million photons, variation from run to run was small. Results were stable to three significant figures. • The model accounts for fundamental spectral loss. Additional losses such as inefficient capture and transport need to be minimized to truly reap full benefits and achieve maximum efficiency.**Feedback from Experts**“Very impressive” Univ of Toronto Prof. Ted Sargent: world record holder, quantum dot solar efficiency “Big success” Stanford Prof. Stacey Bent: Director, TomKat Center on Sustainable Energy “Key to future success” Univ of Notre Dame Prof. Prashant Kamat: leading expert on nanoparticles and energy**Conclusion**• Using Monte Carlo simulation from theoretical calculations and factoring in the Carnot principle, this model predicts 2,3,5, 9 junction PbS quantum dot solar cells to have maximum 50.0%, 57.5%, 66.1% and 75.0% efficiency respectively. • A model using photon-electron interaction has been demonstrated and can be used to rapidly design and optimize MJQDSC. • This model can be calibrated using future experimental data to achieve accuracy and be used to improve MJQDSC for various materials.**Acknowledgements**• Dr. Veronica Ledoux • Dr. Bjoern Seipel, SolarWorld USA • Mr. Andrew Merrill • Mr. Bob Sauer • Prof. Stacey Bent & Group, Stanford • Prof. Ted Sargent & Group, Toronto • Prof. Prashant Kamat & Group, Notre Dame • Dr. Christophe Ballif& Team, EPFL • Ms. Bonnie Raskin & Caroline D. Bradley Scholarship • Oregon JSHS and Judges**Thank You!**Questions?**Ivanpah, Mojave Desert: World’s largest solar plant @ 392**MW, opened Feb 13, 2014 Efficiency: 18%, Cost: $2.2B, Technology: Boiler from focused sunlight

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