Results 191 to 200 of about 1,105,296 (333)

The Versatility of Layered Two‐Dimensional Heterostructures for Energy Storage: Bridging Scientific Insights and Practical Applications

open access: yesAdvanced Materials, EarlyView.
This review highlights the potential of 2D‐2D heterostructures (HRs) in advancing monovalent ion‐based energy storage. It examines their role in tailoring charge interactions mechanisms, optimizing interfacial properties, and overcoming the limitations of individual layered materials.
Neetu Bansal   +6 more
wiley   +1 more source

Unperceivable Designs of Wearable Electronics

open access: yesAdvanced Materials, EarlyView.
Unperceivable wearable technologies seamlessly integrate into everyone's daily life, for healthcare and Internet‐of‐Things applications. By remaining completely unnoticed both visually and tactilely, by the user and others, they ensure medical privacy and allow natural social interactions.
Yijun Liu   +2 more
wiley   +1 more source

Second language syntax acquisition

open access: yes, 2015
This paper explores the acquisition of syntactic properties in a second language. To understand how syntactic properties are acquired, a theoretical approach of Universal Grammar is presented, with an emphasis on the application of the Universal Grammar approach to second language acquisition.
openaire   +2 more sources

Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application

open access: yesAdvanced Materials, EarlyView.
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong   +12 more
wiley   +1 more source

AI‐Driven Defect Engineering for Advanced Thermoelectric Materials

open access: yesAdvanced Materials, EarlyView.
This review presents how AI accelerates the design of defect‐tuned thermoelectric materials. By integrating machine learning with high‐throughput data and physics‐informed representations, it enables efficient prediction of thermoelectric performance from complex defect landscapes.
Chu‐Liang Fu   +9 more
wiley   +1 more source

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