Results 231 to 240 of about 972,067 (310)

Roadmap for High‐Throughput Ceramic Materials Synthesis and Discovery for Batteries

open access: yesAdvanced Energy Materials, EarlyView.
This work examines ceramic synthesis through the lens of high‐throughput synthesis and optimization, identifying opportunities for faster, adaptable routes. It emphasizes flexible liquid precursor–to–solid film methods over slower solid‐state approaches and highlights computer‐aided decision making to optimize both material properties and device ...
Jesse J. Hinricher   +10 more
wiley   +1 more source

Hybrid artificial intelligence architectures for automatic text correction in the Kazakh language. [PDF]

open access: yesFront Artif Intell
Baitenova L   +4 more
europepmc   +1 more source

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

Localized Heterogeneous Nucleation for Vapor‐Assisted Sequential Deposition of Metal Halide Perovskites

open access: yesAdvanced Energy Materials, EarlyView.
A compact, nonporous, and highly crystalline layered inorganic precursor formed by thermal evaporation inherently restricts its conversion into the halide perovskite phase during vapor‐assisted hybrid two‐step deposition. Introducing localized heterogeneous nucleation sites during vapor deposition enables deliberate modulation of the inorganic layer's ...
Sung‐Eun Kim   +10 more
wiley   +1 more source

Achieving Phonon‐Glass Electron‐Crystal Behavior in Fully Organic Flexible Thermoelectrics

open access: yesAdvanced Energy Materials, EarlyView.
Phonon‐glass Electron‐crystal (PGEC) behavior is demonstrated in fully organic composites consisting of conductive polymers (PEDOT:PSS) and soft polymeric fillers (PVA). The optimized PEDOT:PSS–PVA composite concurrently reveals delocalized transport and thermal conductivity close to its theoretical minimum, yielding a superior thermoelectric figure of
Jeong Han Song   +5 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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