Results 181 to 190 of about 164,385 (278)

Recent Advances in Nano‐Microstructured Catalysts for Electrochemical Seawater Electrocatalysis

Advanced Energy Materials, EarlyView.
This review highlights advances in nano‐ and microstructured catalysts for electrochemical seawater conversion. It elucidates design principles, mechanistic understanding, and machine‐learning‐assisted discovery, and outlines key challenges and future opportunities toward efficient, selective, and durable seawater electrocatalysis.
Xiaodong Shao, Mengfang Liang, Xiaotong Han, Xu Yu, Huan Pang, Ho Seok Park   +5 more
wiley   +1 more source

Research on time series prediction of microclimate in agrivoltaic systems based on the long short-term memory and attention mechanism. [PDF]

Front Plant Sci
Zhang L, Gong J, Wu C, Murchie EH, Gibbs AJ, Liu B, Yang C, Xu G, Zhang J, Guo J, Xiao M, Bao E.   +11 more
europepmc   +1 more source

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

Exploring the potential role of multi-source remote sensing data during different growth stages in crop yield prediction. [PDF]

PeerJ
Gu X, Xu E, Chi Y, Zhou L, Liang Q.
europepmc   +1 more source

Engineering Trace‐Amount Electrolyte Additives for Aqueous Zinc Batteries

Advanced Energy Materials, EarlyView.
Large‐amount additives primarily modify the bulk electrolyte by coordinating with Zn2+ or reshaping the hydrogen‐bond network, thereby altering the overall solution chemistry. In contrast, trace‐amount additives mainly operate at the electrode–electrolyte interface, regulating Zn deposition through electric double‐layer modulation, interfacial ...
Zhaoxin Li, Jinhua Guo, Longjun Chang, Zhenyu Jiang, Shuchang Liu, Chao Wang, Qi Liu, Baohua Li, Zhiqiang Niu, Qing Li   +9 more
wiley   +1 more source

Energy-Aware Duty Cycle Management for Solar-Powered IoT Devices. [PDF]

Sensors (Basel)
Gerndt M, Ispir M, Nunez I, Benedict S.
europepmc   +1 more source

Beyond Descriptor‐Based AI Design: Sp2‐Hybridized Branched Side Chains Enable Pre‐Aggregation–Driven Seeding Effects in Green‐Solvent‐Processed Organic Solar Cells

Advanced Energy Materials, EarlyView.
sp2‐hybridized branched side chains are introduced as a new molecular design for NFAs, YBOV, inducing strong solution‐state pre‐aggregation. This pre‐aggregation enables universal seeding motifs, highly ordered film growth, and overcoming the intrinsic current–voltage trade‐off, achieving 19.67% efficiency via green‐solvent processing beyond descriptor‐
Seokhwan Jeong, Donghoo Won, Zhe Sun, Chihyung Lee, Jaewook Kim, Seunglok Lee, Sangjin Yang, Jieun Kim, Keonho Yoon, Dong Young Kim, Yongjoon Cho, Seung‐Jae Shin, Hee‐Seung Lee, Doo‐Hyun Ko, Changduk Yang   +14 more
wiley   +1 more source

Temporal and spatial dynamics of Net Primary Productivity and prediction of wetland carbon sequestration potential on the Tibetan Plateau. [PDF]

PeerJ
Cao L, Dong S, Wang Y, Li X, Zhao Y, Ma D, Pubu Z, Ma H, Li W, Cao P.   +9 more
europepmc   +1 more source

Molecular Design and Interfacial Functions of Self‐Assembled Monolayers for Perovskite and Tandem Solar Cells

Advanced Energy Materials, EarlyView.
We identify two decisive levers for SAM interfaces: molecular design (carboxylic acid‐based, phosphonic acid, other anchoring chemistries, and polymeric SAMs) and mixing routes (co‐assembly, in situ assembly, pre‐ and post‐treatment). Coordinated tuning of headgroups and assembly pathways optimises energy alignment and film formation, suppresses ...
Jiaxu Zhang, Bochun Kang, Feng Yan
wiley   +1 more source

Modeling freshwater yield: deep learning applications in seawater greenhouses in Iran. [PDF]

Sci Rep
Barzigar A, Allahyari S, Fathi M, Mujumdar AS, Hosseinalipour SM.   +4 more
europepmc   +1 more source