Results 161 to 170 of about 1,367,918 (252)

Physical Origin of Temperature Induced Activation Energy Switching in Electrically Conductive Cement

open access: yesAdvanced Science, EarlyView.
The temperature‐induced Arrhenius activation energy switching phenomenon of electrical conduction in electrically conductive cement originates from structural degradation within the biphasic ionic‐electronic conduction architecture and shows percolation‐governed characteristics: pore network opening dominates the low‐percolation regime with downward ...
Jiacheng Zhang   +7 more
wiley   +1 more source

Site and Capacity Planning of Electric Vehicle Charging Stations Based on Road–Grid Coupling

open access: yes
To address the rapidly growing demand for charging stations (CSs) and the associated challenges posed by the expansion of electric vehicles (EVs), this study proposes a collaborative planning method integrates user demand considerations with operational ...
Yuelong Ma   +3 more
core   +1 more source

Recent Advances in Laser‐Induced Graphene‐Based Gas Sensors: From Sensing Mechanisms to Biomedical Applications

open access: yesAdvanced Science, EarlyView.
Laser‐induced graphene (LIG) provides a scalable, laser‐direct‐written route to porous graphene architecture with tunable chemistry and defect density. Through heterojunction engineering, catalytic functionalization, and intrinsic self‐heating, LIG achieves highly sensitive and selective detection of NOX, NH3, H2, and humidity, supporting next ...
Md Abu Sayeed Biswas   +6 more
wiley   +1 more source

The model of wireless charging infrastructure for electric transport of open-pit mining enterprises

open access: yesЗаписки Горного института
The prospects for implementing battery-powered dump trucks at open-pit mining enterprises are considered. Main attention is on the problem of charging infrastructure for adopting the unmanned production concept. The suggestion is to use wireless charging
Irina Yu. Semykina   +3 more
doaj  

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

open access: yesAdvanced 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   +8 more
wiley   +1 more source

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

open access: yesAdvanced 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   +12 more
wiley   +1 more source

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

open access: yesAdvanced 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   +5 more
wiley   +1 more source

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

open access: yesAdvanced 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   +2 more
wiley   +1 more source

Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review

open access: yesAdvanced Science, EarlyView.
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh   +8 more
wiley   +1 more source

Machine Learning‐Assisted KCl‐CaCl2‐LiCl Electrolyte Design for Low‐Temperature, High‐Performance Calcium‐Based Liquid Metal Batteries

open access: yesAdvanced Science, EarlyView.
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou   +3 more
wiley   +1 more source

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