Results 171 to 180 of about 2,754,875 (281)

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

Advanced 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, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Performance augmentation of spherical solar distiller using dual-axis sun tracking system with corrugated absorber and phase change material. [PDF]

Sci Rep
Ibrahim M, Younes MM, Omara ZM, Essa FA.
europepmc   +1 more source

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

Advanced 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, Young Yun Kim, Hyejin Na, You‐Hyun Seo, Sung Jae Na, Seulyi Lee, Mingi Kang, Jinuk Jang, Daehyeok Kim, Yeonkyeong Ju, So‐Min Yoo, Jae Yong Park, Bong Joo Kang, Geun Ho Gu, Tae Joo Shin, Jaemin Lee, Nam Joong Jeon, Eui Hyuk Jung   +17 more
wiley   +1 more source

The Behaviour of the EUV Corona Before Flares in Regions with High Free Magnetic Energy. [PDF]

Sol Phys
Harra L, Kusano K, Zhu Y, Barczynski K, De-Sassi A, Stiefel MZ, Kontogiannis I, West MJ, Brooks DH.   +8 more
europepmc   +1 more source

4th Solar Polarization Workshop

, 2006
Maps of magnetic field topologies for rapidly rotating, solar-type stars have been produced for the past decade, and offer a unique insight into the operation of the stellar dynamo. The creation of these maps uses the combined techniques of Least-Squares
Mengel, M. W., Donati, J.-F., Semel, M., Marsden, S. C., Petit, P., Carter, B. D.   +5 more
core  

Multiscale Perspectives on Perovskite Instability: From Atomistic Deformation to Device Degradation in Perovskite Solar Cells

Advanced Energy Materials, EarlyView.
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, Donghyeon Lee, Seoyoon Lee, Jin‐Wook Lee, Mansoo Choi, Min‐cheol Kim, Namyoung Ahn   +6 more
wiley   +1 more source

Potential Solar Precursors to Magnetic Switchbacks. [PDF]

Space Sci Rev
Tripathi D, Madjarska MS, Karpen J, Velli M, Froment C, Pariat E, Patsourakos S, Raouafi NE, Rouillard AP, Sterling AC, Tziotziou K, Wyper PF.   +11 more
europepmc   +1 more source

High‐Performance Noble‐Metal‐Free Perovskite Solar Cells Enabled by MoOX/Cr/Al Multilayer Electrodes

Advanced Energy Materials, EarlyView.
Cost‐effective perovskite solar cells (PSCs) are developed using a noble‐metal‐free MoOX/Cr/Al multilayer electrode. The devices achieve a power conversion efficiency (PCE) of 25.6%, competitive with that of Au‐based devices (26.3%), and a 25.5 cm2 mini‐module shows 21.3% PCE.
Wooyeon Kim, Soyeon Kim, In Choi, Seoyeong Lee, Subin Yu, Young Yun Kim, Bonkee Koo, Min Jae Ko   +7 more
wiley   +1 more source

The Sun as a driver of the inner heliosphere: Modern investigations of fundamental plasma processes. [PDF]

Nat Commun
Ervin T, Nakhleh AJ, Bharati Das S.
europepmc   +1 more source

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

Advanced 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, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source