Results 221 to 230 of about 50,070 (293)

Deciphering Intricacies in Directional CO2 Conversion From Electrolysis to CO2 Batteries

Advanced Energy Materials, EarlyView.
This review will delve into the inherent connections and distinctions of CO2‐directed conversion in ECO2RR and CO2 batteries, in terms of product types, catalyst selection, catalytic mechanisms, and electrochemical performances, while proposing a benchmarking framework for the evaluation of CO2 batteries and innovative CO2 battery configurations for ...
Changfan Xu, Huaping Zhao, Lizhuang Chen, Weidong Shi, Guosheng Shao, Yong Lei   +5 more
wiley   +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

Identifying the contributions of progenitor Malus species to cultivated apple (M. domestica) using 20K SNP array data. [PDF]

BMC Genomics
Howard NP, Vanderzande S, Khan G, Luby JJ, Volk GM, Albach DC, Peace C.   +6 more
europepmc   +1 more source

Organic Photoelectrochemical Cells Beyond Performance: Interface and Catalyst Engineering for Durability

Advanced Energy Materials, EarlyView.
Organic photoelectrochemical cells based on π‐conjugated semiconductors offer a versatile platform for solar fuel generation. This review outlines operating principles, device architectures, and key metrics, and highlights advances in p‐ and n‐type photoelectrodes, interfacial engineering, and catalyst integration.
Jaehyeong Kim, Jung Min Ha, Yeonjeong Lee, Seung Won Oh, Wangyeon Lee, Munsu Kwon, Soonyong Lee, Jin Young Kim, Han Young Woo   +8 more
wiley   +1 more source

Reduced Genetic Load and Inbreeding in Reintroduced African Wild Dogs Reflect the Benefits of Admixture. [PDF]

Mol Ecol
Tensen L, Wang X, Watermeyer J, du Plessis C.   +3 more
europepmc   +1 more source

Strain‐Directed Ru Redistribution to Form RuO2/Pt Mosaic Heterointerfaces for Acid‐Stable Water Oxidation

Advanced Energy Materials, EarlyView.
Strain‐driven Ru inward migration creates confined RuO2/Pt mosaic heterointerfaces within a PtNi multiframe. These interfaces enable redox‐asymmetric Pt–Ru coupling that stabilizes Ru4+, suppresses lattice oxygen participation, and promotes highly durable acidic oxygen evolution.
Yeji Park, Doyeop Kim, Jungho Kim, Ho Yeon Jang, Minseon Cha, Subeen Lee, Tae Kyung Lee, Taekyung Kim, Hionsuck Baik, Jinwon Choi, Taehyun Kwon, Seoin Back, Sung Jong Yoo, Kwangyeol Lee   +13 more
wiley   +1 more source

Genetic Ancestry and Population Structure Across Ecuador. [PDF]

Genes (Basel)
González-Andrade F.
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

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source

Inference of admixture in dogs from whole genome sequences. [PDF]

GigaByte
Kislik G, Moore G, Rubbi L, Supara VN, Chen G, Pellegrini M.   +5 more
europepmc   +1 more source