Results 201 to 210 of about 7,125 (291)

A Pressure Microsensor Made of Parylene‐C for Use as Medical Implant

open access: yesAdvanced Materials Technologies, EarlyView.
A monolithic parylene‐C pressure sensor with gold strain gauges provides 6.2 μV$\mu{\rm V}$·mmHg$\cdot{\rm mmHg}$−1$^{-1}$ sensitivity. The morphology of a sputtered thin film strain sensor is granular/columnar, which results in a high gauge factor of 7.5. Thermal bonding and parylene‐C coating create a hermetic cavity.
Ann‐Kathrin Klein   +2 more
wiley   +1 more source

The nonlinear trajectory of post-stroke aphasia recovery. [PDF]

open access: yesFront Hum Neurosci
Maraka JO   +6 more
europepmc   +1 more source

Tunable Extraordinary Optical Transmission in the Long‐Wavelength Infrared Range Using Electrostatic MEMS Actuation

open access: yesAdvanced Materials Technologies, EarlyView.
A MEMS‐integrated metamaterial filter enables continuous, low‐voltage spectral tuning in the long‐wavelength infrared (LWIR). The device employs extraordinary optical transmission in a dual suspended metasurface stack, where electrostatic actuation precisely controls the intermembrane air gap.
Oleg Bannik   +6 more
wiley   +1 more source

Reconnaissance Peptide Labeling Grain Boundary of Chemically Grown MoS2 Polycrystalline Monolayer

open access: yesAdvanced Materials Technologies, EarlyView.
Self‐assembled peptides on substrates, through adsorption and aggregation, offer an alternative way to label grain boundaries in chemically grown single‐layer polycrystalline MoS2. During an early nucleation step, peptides preferentially bind to grain boundaries.
Linhao Sun, Jinhua Hu
wiley   +1 more source

Bidirectional Process Prediction in the Laser‐Induced‐Graphene Production Using Blackbox Deep Learning

open access: yesAdvanced Materials Technologies, EarlyView.
This study shows that a lightweight blackbox neural network provides a practical, cost‐effective solution for bidirectional process prediction in laser‐induced graphene (LIG) fabrication. Achieving high predictive performance with minimal overhead, the approach democratizes machine learning (ML) for resource‐limited environments.
Maxim Polomoshnov   +3 more
wiley   +1 more source

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