Results 171 to 180 of about 133,855 (339)

Impact of distance measures in adaptive K-means clustering on load profiles and spatial patterns of distributed substations in Thailand. [PDF]

open access: yesSci Rep
Prompook T   +8 more
europepmc   +1 more source

Capillary‐Driven 3D Open Fluidic Networks for Versatile Continuous Flow Manipulation

open access: yesAdvanced Materials, EarlyView.
The capillary‐driven 3D open fluidic networks (OFNs), composed of connected polyhedral frames, enable precise, programmable, and versatile manipulation of unary, binary, and multiple continuous flows in both spatial and temporal dimensions. OFNs represent a significant leap beyond conventional microfluidics, unlocking new possibilities for selective ...
Shuangmei Wu   +4 more
wiley   +1 more source

Electrochemical Cell Designs for Efficient Carbon Dioxide Reduction and Water Electrolysis: Status and Perspectives

open access: yesAdvanced Materials, EarlyView.
This review discusses recent innovations in electrochemical CO2 reduction reactions (eCO2RR) and hydrogen evolution reaction cell designs. The latest advancements in in situ cells for operando characterization are also presented. Optimizations in flow patterns, membrane electrode assemblies, electrolyte engineering, and counter‐anodic reactions provide
Zhangsen Chen   +3 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

Home - About - Disclaimer - Privacy