Results 191 to 200 of about 2,368,406 (271)

Technology options for multimedia in distance learning [PDF]

open access: yes, 1991
Sherwood-Roberts, P., Vervest, P.
core  

Exploring the Potential of Zero‐Dimensional Carbon Nanomaterials in Photoluminescent, Electrochemiluminescent and Electrochemical Sensors

open access: yesAdvanced Materials Interfaces, EarlyView.
Zero‐dimensional carbon nanomaterials are presented as multifunctional platforms linking structure, property, and sensing performance. Surface engineering and heteroatom doping modulate electron‐transfer and luminescent behavior, enabling electrochemical, photoluminescent, and electrochemiluminescent detection. Fundamental design principles, analytical
Gustavo Martins   +8 more
wiley   +1 more source

From the Discovery of the Giant Magnetocaloric Effect to the Development of High‐Power‐Density Systems

open access: yesAdvanced Materials Technologies, EarlyView.
The article overviews past and current efforts on caloric materials and systems, highlighting the contributions of Ames National Laboratory to the field. Solid‐state caloric heat pumping is an innovative method that can be implemented in a wide range of cooling and heating applications.
Agata Czernuszewicz   +5 more
wiley   +1 more source

Neck pain and distance learning: A pain in the neck for university students during COVID-19. [PDF]

open access: yesF1000Res
Musaad Mohamed A   +5 more
europepmc   +1 more source

Hydrogel‐Based 3D‐Printable Stretchable Pressure Sensor

open access: yesAdvanced Materials Technologies, EarlyView.
We present a carbon‐black‐functionalized double‐network granular hydrogel (DNGH) pressure sensor capable of detecting pressures from 200 Pa, equivalent to a light finger touch, up to 500 kPa. The sensor exhibits signal drifts below 3.5% after 800 cycles and response times around 80 ms. Leveraging this broad sensing range, we 3D print this material into
Tianyu Yuan   +4 more
wiley   +1 more source

Advanced Design for Weakly Coupled Resonators by Automatic Active Optimization

open access: yesAdvanced Materials Technologies, EarlyView.
An Automatic Active Optimization (AAO) strategy integrates machine learning predictors and genetic algorithms in a closed‐loop workflow. By iteratively expanding its dataset with new discoveries, AAO overcomes the limits of conventional methods. This approach finds superior microstructural designs beyond the initial sample space. We demonstrate this on
Wei Yue   +8 more
wiley   +1 more source

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