Results 281 to 290 of about 1,872,988 (376)

Stiffening Liquid Crystal Elastomers with Liquid Crystal Inclusions

open access: yesAdvanced Materials, EarlyView.
Incorporation of low molecular weight liquid crystals (LC) into liquid crystal elastomers (LCE) leads to a significant increase in their stiffness and output work density. Such remarkable stiffening is attributed to nanoscale phase‐separation and the formation of induced‐smectic domains in polydomain and monodomain LC‐LCEs, respectively.
Sahad Vasanji   +7 more
wiley   +1 more source

Additive Manufacturing of Neuromorphic Systems

open access: yesAdvanced Materials, EarlyView.
The crossover of additive Manufacturing (AM) and neuromorphic engineering promises a new paradigm in the fabrication of intelligent hardware—one that is sustainable, scalable, cost‐efficient, and customizable. The AM‐printed neuromorphic hardware (electronics and mechanical systems) is examined, and we discussed the technological integration.
Jiongyi Yan   +3 more
wiley   +1 more source

Practical Considerations in the Design and Use of Non‐Crystalline Metal–Organic Frameworks

open access: yesAdvanced Materials, EarlyView.
This review explores the emerging field of non‐crystalline MOFs ‐ amorphous, liquid, and glassy forms ‐ highlighting how they differ from traditional crystalline MOFs. It discusses their unique synthesis strategies, fundamental principles, and diverse applications.
Hamidreza Mahdavi   +8 more
wiley   +1 more source

Thermionics in Topological Materials

open access: yesAdvanced Materials, EarlyView.
Thermionics is one of the fundamental energy conversion mechanisms in solid state systems. Recent development in topological materials opens new avenues in developing thermionic systems and devices. Due to the linear energy dispersion and topological protection of charge transport, these new materials are promising candidates for high efficiency ...
Sunchao Huang   +8 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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