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Zero-Emission Vehicles Aid in Decarbonization, Solar Cells Efficiency Improvements, AI Innovations in Wind Energy

Zero-Emission Vehicles Aid in Decarbonization, Solar Cells Efficiency Improvements, AI Innovations in Wind Energy

Released Wednesday, 15th November 2023
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Zero-Emission Vehicles Aid in Decarbonization, Solar Cells Efficiency Improvements, AI Innovations in Wind Energy

Zero-Emission Vehicles Aid in Decarbonization, Solar Cells Efficiency Improvements, AI Innovations in Wind Energy

Zero-Emission Vehicles Aid in Decarbonization, Solar Cells Efficiency Improvements, AI Innovations in Wind Energy

Zero-Emission Vehicles Aid in Decarbonization, Solar Cells Efficiency Improvements, AI Innovations in Wind Energy

Wednesday, 15th November 2023
Good episode? Give it some love!
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Hosts Kerrin Jeromin and Taylor Mankle discuss recent stories from NREL:  

  • The rapid adoption of zero-emission electric vehicles, alongside a transition to a clean electric grid and measures to manage travel demand growth, could lead to an 80% or more drop in transportation greenhouse gas emissions in the United States by 2050, according to researchers from the U.S. Department of Energy’s NREL. Their study, published in the journal Nature Communications, involved over 2,000 simulations and identified the dynamic variable in reducing emissions as measures supporting the transition to zero-emission vehicles, emphasizing the importance of a multifaceted approach involving technology advancements, policy changes, and behavioral shifts. 
  • Researchers at the U.S. Department of Energy’s NREL achieved a record-breaking efficiency of 27% for a gallium arsenide (GaAs) heterojunction solar cell, using dynamic hydride vapor phase epitaxy (D-HVPE). By optimizing the doping and bandgap of the emitter layer, the study provides a roadmap for enhancing the performance of solar cells, with potential applications beyond III-V materials, such as silicon, cadmium telluride, or perovskites. 
  • NREL researchers are utilizing artificial intelligence, specifically invertible neural network (INN) tools, to accelerate airfoil design for wind turbine blades, demonstrating a hundredfold speedup over current methods and achieving performance characteristics satisfaction, offering a potential breakthrough in optimizing airfoil shapes and streamlining the design process. The INN, by learning an invertible relationship between airfoil shapes and their properties, enables rapid exploration of design spaces, providing higher-fidelity insights into aerodynamics and structural properties without compromising tight design timelines. 

This episode was hosted by Kerrin Jeromin and Taylor Mankle, written and produced by Allison Montroy and Kaitlyn Stottler, and edited by Joe DelNero and Brittany Falch. Graphics are by Brittnee Gayet. Our title music is written and performed by Ted Vaca and episode music by Chuck Kurnik, Jim Riley, and Mark Sanseverino of Drift BC. Transforming Energy: The NREL Podcast is created by the U.S. Department of Energy’s National Renewable Energy Laboratory in Golden, Colorado. We express our gratitude and acknowledge that the land we are on is the traditional and ancestral homelands of the Arapaho, Cheyenne, and Ute peoples. Email us at [email protected]. Follow NREL on Twitter, Instagram, LinkedIn, YouTube, and Facebook.

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