ABSTRACT
Printed 2D materials, derived from solution-processed inks, offer scalable and cost-effective routes to mechanically flexible optoelectronics. With micrometer-scale control and broad processing latitude, aerosol-jet printing (AJP) is of particular interest for all-printed circuits and systems. Here, AJP is utilized to achieve ultrahigh-responsivity photodetectors consisting of well-aligned, percolating networks of semiconducting MoS2 nanosheets and graphene electrodes on flexible polyimide substrates. Ultrathin (≈1.2 nm thick) and high-aspect-ratio (≈1 µm lateral size) MoS2 nanosheets are obtained by electrochemical intercalation followed by megasonic atomization during AJP, which not only aerosolizes the inks but also further exfoliates the nanosheets. The incorporation of the high-boiling-point solvent terpineol into the MoS2 ink is critical for achieving a highly aligned and flat thin-film morphology following AJP as confirmed by grazing-incidence wide-angle X-ray scattering and atomic force microscopy. Following AJP, curing is achieved with photonic annealing, which yields quasi-ohmic contacts and photoactive channels with responsivities exceeding 103 A W-1 that outperform previously reported all-printed visible-light photodetectors by over three orders of magnitude. Megasonic exfoliation coupled with properly designed AJP ink formulations enables the superlative optoelectronic properties of ultrathin MoS2 nanosheets to be preserved and exploited for the scalable additive manufacturing of mechanically flexible optoelectronics.
ABSTRACT
This work presents a fall detection system that is worn on the head, where the acceleration and posture are stable such that everyday movement can be identified without disturbing the wearer. Falling movements are recognized by comparing the acceleration and orientation of a wearer's head using prespecified thresholds. The proposed system consists of a triaxial accelerometer, gyroscope, and magnetometer; as such, a Madgwick's filter is adopted to improve the accuracy of the estimation of orientation. Moreover, with its integrated Wi-Fi module, the proposed system can notify an emergency contact in a timely manner to provide help for the falling person. Based on experimental results concerning falling movements and activities of daily living, the proposed system achieved a sensitivity of 96.67% in fall detection, with a specificity of 98.27%, and, therefore, is suitable for detecting falling movements in daily life.
