Results 151 to 160 of about 2,299 (249)

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

A Digital Approach to Denture Marking. [PDF]

Cureus
Ghosh M, Gupta R, Mishra PN, Mishra A, Bhardwaj S, Gill S, Phogat M.   +6 more
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

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

Ensuring Safe Newborn Delivery Through Standards: A Scoping Review of Technologies Aligned with Healthcare Accreditation and Regulatory Frameworks. [PDF]

Healthcare (Basel)
Alsuhaimi A, Alkhurayji KS.
europepmc   +1 more source

Tracking Dynamic Sulfur Electrochemistry by Operando Techniques in Alkali Metal‐Sulfur Batteries

Advanced Energy Materials, EarlyView.
Dynamic sulfur electrochemistry in alkali metal‐sulfur batteries is tracked through operando spectroscopy, scattering, imaging, and modelling. This Review connects sulfur reaction pathways, polysulfide transport, electrolyte/interphase evolution, anode chemistry, and quantitative mechanistic analysis across Li‐S, Na‐S, and K‐S batteries, providing ...
Fangli Zhang, Meixuan Niu, Junya Huang, Dawei Su   +3 more
wiley   +1 more source

CommRad RF: A dataset of communication radio signals for detection, identification and classification. [PDF]

Data Brief
Zahid MU, Akram MU, Nisar MD, Maqsood F, Ali SU, Montaha M.   +5 more
europepmc   +1 more source

SOC Mismatch–Driven Inter‐Particle Synchronization via Internal Li‐Ion Transfer: An Unrecognized Electrode‐Emergent Degradation Pathway in Ni‐Rich Composite Cathodes

Advanced Energy Materials, EarlyView.
Composite cathode degradation is not merely the sum of its particles. Kinetically mismatched populations develop state‐of‐charge differences that drive spontaneous internal Li‐ion transfer; the accompanying transient currents accelerate surface degradation.
Seheon Oh, Suyoung Kim, Inho Kim, Kangwoo Ahn, Min Wook Pin, Minkyu Kim   +5 more
wiley   +1 more source

<i>J</i>-Resolved Molecular Fingerprinting by Parahydrogen Hyperpolarized Low-Field NMR. [PDF]

J Am Chem Soc
Zhang Z, Savukov I, Hilty C.
europepmc   +1 more source

Structure and Spectroscopic Characterisation of Phenanthroline‐Based Iodobismuthate(III) Complexes Utilised for Raw Acoustic Signal Classification

Advanced Intelligent Discovery, EarlyView.
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz, Gisya Abdi, Andrzej Sławek, Marlena Gryl, Konrad Szaciłowski   +4 more
wiley   +1 more source