Traditional human emotion recognition is based on electroencephalogram (EEG) data collection technologies which rely on plenty of rigid electrodes and lack anti‐interference, wearing comfort, and portability. Moreover, a significant distribution difference in EEG data also results in low classification accuracy. Here, on‐skin biosensors with adhesive and hydrophobic bilayer hydrogel (AHBH) as interfaces for high accuracy emotion classification are proposed. The AHBH achieves remarkable adhesion (59.7 N m−1) by combining the adhesion mechanism of catechol groups and electrostatic attraction. Meanwhile, based on the synergistic effects of hydrophobic group rearrangements and surface energy reduction, the AHB‐hydrophobic layer exhibits 133.87° water contact angles through hydrophobic treatment of only 0.5 h. Hydrogen and electrostatic bonds are also introduced to form a seamless adhesive‐hydrophobic hydrogel interface and inhibit adhesion attenuation, respectively. With the AHBH as an ideal device/skin interface, the biosensor can reliably collect high‐quality electrophysiological signals even under vibration, sweating, and long‐lasting monitoring condition. Furthermore, the on‐skin electrodes, data processing, and wireless modules are integrated into a portable headband for EEG‐based emotion classification. A domain adaptive neural network based on the transfer learning technique is introduced to alleviate the effect of domain shift and achieve high classification accuracy.
Direct ink writing (DIW) holds enormous potential in fabricating multiscale and multi-functional architectures by virtue of its wide range of printable materials, simple operation, and ease of rapid prototyping. Although it is well known that ink rheology and processing parameters directly affect the resolution and morphology of the printed objects, the underlying mechanisms of these key factors on the printability and quality of DIW technique remain poorly understood. To tackle this issue, we systematically analyzed the printability and quality through extrusion mechanism modelling and experimental validating. Hybrid non-Newtonian fluid inks were first prepared, and their rheological properties were measured. Then, finite element analysis of the whole DIW process was conducted to reveal the flow dynamics of these inks. The obtained optimal process parameters (ink rheology, applied pressure, printing speed, etc.) were also validated by experiments where high-resolution (< 100 μm) patterns were fabricated rapidly (> 70 mm/s). Finally, as a proof of concept, we printed a series of microstructures and circuit systems with hybrid inks and silver inks, showing the suitability of the printable process parameters. This study offers powerful quantitative guidelines for the usage of DIW in fabricating high-resolution, multi-component, and complex geometries.
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