Results 161 to 170 of about 11,393 (262)
Advancing Energy Materials by In Situ Atomic Scale Methods
Progress in in situ atomic scale methods leads to an improved understanding of new and advanced energy materials, where a local understanding of complex, inhomogeneous systems or interfaces down to the atomic scale and quantum level is required. Topics from photovoltaics, dissipation losses, phase transitions, and chemical energy conversion are ...
Christian Jooss +21 more
wiley +1 more source
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
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
Design and Performance Analysis of Foldable Solar Panel for Agrivoltaics System [PDF]
Ramesh Kumar Lama, Heon Jeong
openalex +1 more source
Dust settles, we don’t: The electrodynamic screen—A self-cleaning technology for concentrated solar power mirrors and photovoltaic panels [PDF]
Annie Bernard +3 more
openalex +1 more source
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
Multiscale perspectives on how excess charges in soft lead halide perovskites induce operational instability in photovoltaic devices are presented. Localized carriers formed under thermodynamic non‐equilibrium states modify atomistic interactions and drive lattice distortions, accelerating device degradation.
Joo‐Hong Lee +6 more
wiley +1 more source
PHOTOVOLTAIC STATION "HALF-PYRAMID" WITH DOUBLE-SIDED SOLAR PANELS
Наталя Савченко +1 more
openalex +2 more sources
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

