Results 131 to 140 of about 114,028 (261)

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

open access: yesAdvanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen   +4 more
wiley   +1 more source

Lattice Coherency‐Driven (111)‐Oriented Wide Bandgap Perovskite Films

open access: yesAdvanced Energy Materials, EarlyView.
Methylammonium lead chloride (MAPbCl3)‐derived seed templates regulate wide‐bandgap perovskite crystallization through coupled thermodynamic and kinetic effects. Lattice‐coherent templating lowers the energy cost for (111) epilayer growth, while growth retardation controls crystallization kinetics, ultimately producing highly crystalline face‐up (111 ...
Yu‐Na Lee   +5 more
wiley   +1 more source

Sunburn-induced bark damage facilitates <i>Eutypella decipiens</i> infection of <i>Carpinus betulus</i> in Serbian urban landscapes. [PDF]

open access: yesFront Plant Sci
Jovanović D   +7 more
europepmc   +1 more source

Amorphous π‐Conjugated Passivator Facilitates Widening Process Window for Reliable Perovskite Solar Modules

open access: yesAdvanced Energy Materials, EarlyView.
A wide process window is essential for the commercialization of perovskite photovoltaics. Here, we demonstrate an amorphous π‐conjugated passivator having an asymmetric mono‐iodine substituent on a carbazole moiety imparts a high dipole moment, desirable molecular energy levels, and high thickness tolerance, thereby enabling a wide process window in ...
Hyun Seo Kim   +17 more
wiley   +1 more source

Dual Impact of Long‐Lived Localized Carriers Induced by Restricted Hole Transfer in Organic Photovoltaics and Photocatalytic Hydrogen Evolution

open access: yesAdvanced Energy Materials, EarlyView.
This work clarifies why organic semiconductors perform differently in photovoltaic devices and photocatalytic nanoparticles. By examining D18:Y5 and PM6:Y6 systems, we show how aggregation, exciton lifetime, and interfacial charge transfer behavior govern energy‐conversion pathways.
Gayoung Ham   +14 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

open access: yesAdvanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park   +19 more
wiley   +1 more source

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