Results 101 to 110 of about 4,242,048 (285)

Synergistic Spin‐Polarization and Single‐Atom Engineering in Magnetic Heterojunctions for Efficient Solar Water Splitting

Advanced Science, EarlyView.
High‐throughput screening led to the identification of 67 Z‐scheme heterojunctions (comprising 2D magnetic transition metal halides and non‐magnetic transition metal chalcogenides). For CrI3/MoTe2 and CrI3/WTe2, electronic structure analysis demonstrated that synergistic crystallographic point group and built‐in electric field effects generate a ...
Hongyang Ren, Zhenzhou Guo, Huirong Wu, Peilin Huang, Jie Yang, Jie Zhang, Guangqian Ding, Hongkuan Yuan, Biao Wang   +8 more
wiley   +1 more source

A Ship Energy Consumption Prediction Method Based on TGMA Model and Feature Selection

Journal of Marine Science and Engineering
Optimizing ship energy efficiency is a crucial measure for reducing fuel use and emissions in the shipping industry. Accurate prediction models of ship energy consumption are essential for achieving this optimization.
Yuhang Liu, Kai Wang, Yong Lu, Yongfeng Zhang, Zhongwei Li, Ranqi Ma, Lianzhong Huang   +6 more
doaj   +1 more source

Field Measurement and Calibration of HDM-4 Fuel Consumption Model on Interstate Highway in Florida

International Journal of Transportation Science and Technology, 2015
Fuel consumptions are measured by operating passenger car and tractor-trailer on two interstate roadway sites in Florida. Each site contains flexible pavement and rigid pavement with similar pavement, traffic and environmental condition.
Xin Jiao, Michael Bienvenu
doaj   +1 more source

Analysis of uncertainties in the prediction of ships’ fuel consumption – from early design to operation conditions [PDF]

, 2018
This investigation presents an approach that contributes to a better understanding of achievable accuracy of fuel consumption predictions of ships and provides an example of how a thorough uncertainty analysis of prediction models can be performed.
Wengang Mao, Mao, Wengang,, Jonas W. Ringsberg, Bengt Ramne, Fabian Tillig, Tillig, Fabian,, Ringsberg, Jonas,, Ringsberg, Jonas, Mao, Wengang, Ramne, Bengt,, Tillig, Fabian, Ramne, Bengt   +11 more
core   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Toward Realistic Ship Fuel Consumption Prediction Under Chronological Validation

Journal of Marine Science and Engineering
Accurate prediction of ship propulsion fuel consumption from operational data is important for performance assessment and energy efficiency management.
Aleksandar Vorkapić
doaj   +1 more source

The Taxation of Fuel Economy [PDF]

Policy-makers have instituted a variety of fuel economy tax policies -- polices that tax or subsidize new vehicle purchases on the basis of fuel economy performance -- in the hopes of improving fleet fuel economy and reducing gasoline consumption.
James Sallee
core  

Fuel Consumption and Collision Avoidance Strategy in Multi-static Orbit Formations [PDF]

, 2011
This paper analysesthe fuel consumption of interferometric rader missions employing small satellite formations like, e.g., Cross-track pendulum, Cartwheel, CarPe, or Trinodal Pendulum.
H. Fiedler, E.F. Jochim, Fiedler, Hauke, G. Krieger, Krieger, Gerhard, Jochim, Fritz   +5 more
core   +1 more source

Smart Nanotechnologies for Multimodal Neuromodulation and Brain Interfacing

Advanced Science, EarlyView.
Recent advances in smart nanotechnologies are expanding the toolbox for brain interfacing, from wireless neuromodulation and high‐resolution sensing to targeted delivery within the central nervous system. By combining responsive nanomaterials with bioinspired design, these platforms enable multimodal interactions with neurons and glia, while also ...
Tommaso Curiale, Marie Celine Lefevre, Alessio Carmignani, Maria Cristina Ceccarelli, Matteo Battaglini, Attilio Marino, Gianni Ciofani   +6 more
wiley   +1 more source

Integrating Machine Learning With Constant‐Potential Simulation to Unravel Charge‐Transfer Mechanisms in Electrochemical Nitrogen Fixation

Advanced Science, EarlyView.
Integrating interpretable machine learning with the fixed‐potential method reveals a novel mechanism: the catalytic activity of the electrochemical nitrogen reduction reaction is governed by partial charge transfer, induced by variations in the intermediate potential of zero charge under constant potential.
Yufei Xue, Dushuo Feng, Yuefei Zhang, Yang Zhang, Yalong Jiao, Aijun Du, Guoping Gao   +6 more
wiley   +1 more source