Data from University of Southern California (USC) Provide New　Insights into Mach ine Learning (Compression Eliminates Charge　Traps By Stabilizing Perovskite Grai n Boundary Structures: an Ab　Initio Analysis With Machine Learning Force Field)

Robotics & Machine Learning Daily News2024，Issue(Apr.10) ：26-27.

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Data from University of Southern California (USC) Provide New　Insights into Mach ine Learning (Compression Eliminates Charge　Traps By Stabilizing Perovskite Grai n Boundary Structures: an Ab　Initio Analysis With Machine Learning Force Field)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on Machine Learning have been presented. According to news reportingoriginating in Los Angeles, Califor nia, by NewsRx journalists, research stated, “Grain boundaries (GBs)play an imp ortant role in determining the optoelectronic properties of perovskites, requiri ng an atomisticunderstanding of the underlying mechanisms. Strain engineering h as recently been employed in perovskitesolar cells, providing a novel perspecti ve on the role of perovskite GBs.”

Key words

Los Angeles/California/United States/North and Central　America/Cyborgs/Emerging Technologies/Machine Learning/Uni versity of Southern California (USC)

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2024

Robotics & Machine Learning Daily News

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Data from University of Southern California (USC) Provide New Insights into Mach ine Learning (Compression Eliminates Charge Traps By Stabilizing Perovskite Grai n Boundary Structures: an Ab Initio Analysis With Machine Learning Force Field)

Data from University of Southern California (USC) Provide New Insights into Mach ine Learning (Compression Eliminates Charge Traps By Stabilizing Perovskite Grai n Boundary Structures: an Ab Initio Analysis With Machine Learning Force Field)

Abstract

Key words

引用本文复制引用

出版年

Robotics & Machine Learning Daily News

Data from University of Southern California (USC) Provide New　Insights into Mach ine Learning (Compression Eliminates Charge　Traps By Stabilizing Perovskite Grai n Boundary Structures: an Ab　Initio Analysis With Machine Learning Force Field)

Data from University of Southern California (USC) Provide New　Insights into Mach ine Learning (Compression Eliminates Charge　Traps By Stabilizing Perovskite Grai n Boundary Structures: an Ab　Initio Analysis With Machine Learning Force Field)