Results 141 to 150 of about 10,853 (264)

Data-driven EV charging infrastructure with uncertainty based on a spatial-temporal flow-driven (STFD) models considering batteries. [PDF]

Sci Rep
Alharbi T, Abdalrahman A, Mostafa MH.
europepmc   +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

Light‐Imprinted Chirality in Nanomaterials: From Principles to Applications

Advanced Science, EarlyView.
Light‐induced chirality represents a transformative paradigm for fabricating chiral nanostructures. This review provides a comprehensive framework encompassing light‐based strategies for imprinting and tuning chirality in nanomaterials, which guides researchers in harnessing light to create next‐generation functional materials.
Xinru Jin, Emiliano Cortés, Alexander O. Govorov, Tao Ding   +3 more
wiley   +1 more source

Impact of charging infrastructure construction on electric vehicle diffusion based on a multi-agent model. [PDF]

iScience
Zheng Y, Liu D, An F, Wang J, Gao X, Jia N.   +5 more
europepmc   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

Transfer learning for securing electric vehicle charging infrastructure from cyber-physical attacks. [PDF]

Sci Rep
Almadhor A, Alsubai S, Bouazzi I, Karovic V, Davidekova M, Al Hejaili A, Sampedro GA.   +6 more
europepmc   +1 more source

A Triple‐Nanoparticle System for Controlled Graphene Nanosheet Stacking: Enabling K/Na‐Ion Battery Anodes with Ultra‐Fast Charging Exceeding Petroleum Vehicle Refueling

Advanced Science, EarlyView.
ABSTRACT Large‐ion (K, Na) battery systems mitigate uneven global lithium distribution, while their ability to attain recharge time shorter than refueling would remove the final barrier for secondary batteries to replace petroleum vehicles. However, their large‐ion chemistry makes ultra‐fast charging an even significant challenge.
Shukai Ding, Le Zhang, Hang Li, Yang Zhang, Guoquan Suo, Bin Han, Dongfeng Sun, Wenqi Zhao, Gaohui Du, Qingmei Su, Bingshe Xu, Zhen Xu, Wei Wang   +12 more
wiley   +1 more source

Energy-efficient and reliable dual closed-loop DC control system for intelligent electric vehicle charging infrastructure. [PDF]

PLoS One
Li J, Chen W, Zhu X, Zang B, Zhang C, Hu H, Zhang M, Lei W.   +7 more
europepmc   +1 more source

Diverse Landscape of Tunable Magnetic, Topological, and Ferroelectric States in 2D Ti3Se3Te2

Advanced Science, EarlyView.
Ti3Se3Te2 emerges as a multifunctional 2D van der Waals platform. The monolayer is a dynamically stable ferromagnetic quantum anomalous Hall insulator. In bilayers, two stacking configurations yield distinct phases: AA‐stacking hosts an altermagnetic quantum spin Hall insulator, while AA′‐stacking exhibits three‐state in‐plane ferroelectricity ...
Jiangtao Yu, Jingbo Bai, Yali Yang, Shifeng Qian, Xiaotian Wang, Zhuhong Liu   +5 more
wiley   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source