Results 181 to 190 of about 686,503 (253)

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

Association Between Patient Behavior and Clinician Emotional Burden, Perceived Performance, and Decision-Making in Implant Dentistry: A Cross-Sectional Study Among Clinicians. [PDF]

Clin Exp Dent Res
Pachiou A, Humm VL, Naenni N, Kontonasaki E, Jung RE, Thoma DS.   +5 more
europepmc   +1 more source

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

Advanced 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, Hyo Jung Kim, Ji‐Sang Park, Wolfgang Tress, Yasemin Saygili, Hui‐Seon Kim   +5 more
wiley   +1 more source

A 10-Year Experience of Teledermatology in a Korean Correctional Facility: A Retrospective Observational Study. [PDF]

J Korean Med Sci
Jang SH, Ahn SW, Hong SM, Park SH, Jung SY, Seol JE, Kim H.   +6 more
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

Nasopharyngeal Lipoma Anterior to the Eustachian Tube Orifice: A Case Report. [PDF]

J Rhinol
Lee Y, Park SY, Jung HJ, Park SK.
europepmc   +1 more source

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

Advanced 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, Sanghyeok An, Wooteak Jung, Hyun Min Kwon, Seonghyeon Kang, Jaehyuk Lee, Sowon Kim, Changwoo Park, Damin Lee, Young Yong Kim, Sungjin Jo, Chang Yun Son, Sae Byeok Jo, Dae Sung Chung, Hyojung Cha   +14 more
wiley   +1 more source

Clinical and Preclinical Obesity in Korean Adults from 2014 to 2023 (Diabetes Metab J 2026;50:127-38). [PDF]

Diabetes Metab J
Jung HN, Jung CH.
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

A machine learning approach to identify perspectives of people living with pulmonary fibrosis. [PDF]

ERJ Open Res
Hofman DE, Zhang R, Oltmans R, Hendriks JM, Moor CC, Wijsenbeek-Lourens M, Jung J.   +6 more
europepmc   +1 more source