Flexible sensing devices provide a convenient and effective solution for real-time human motion monitoring, but achieving efficient and low-cost assembly of pressure sensors with high performance remains a considerable challenge. Herein, a highly compressible and sensitive flexible foam-shaped piezoresistive pressure sensor was prepared by sequential fixing multiwalled carbon nanotubes and ${\mathrm{Ti}}_3{\mathrm{C}}_2{\mathrm{T}}_{\mathrm{x}}$ MXene on the skeleton of melamine foam. Due to the porous skeleton of the melamine foam and the extraordinary electrical properties of the conductive fillers, the obtained MWCNTs/${\mathrm{Ti}}_3{\mathrm{C}}_2{\mathrm{T}}_{\mathrm{x}}$ MXene @ melamine foam device features high sensitivity of 0.339 kPa${}^{-1}$, a wide working range up to 180 kPa, a desirable response time and excellent cyclic stability. The sensing mechanism of the composite foam device is attributed to the change in the conductive pathways between adjacent porous skeletons. The proposed sensor can be used successfully to monitor human gestures in real-time, such as finger bending and tilting, scrolling the mouse and stretching fingers. By combining with the decision tree algorithm, the sensor can unambiguously classify different Arabic numeral gestures with an average recognition accuracy of 98.9%. Therefore, our fabricated foam-shaped sensor may have great potential as next-generation wearable electronics to accurately acquire and recognize human gesture signals in various practical applications.

Flexible pressure sensors have been studied as wearable voice-recognition devices to be utilized in human-machine interaction. However, the development of highly sensitive, skin-attachable, and comfortable sensing devices to achieve clear voice detection remains a considerable challenge. Herein, we present a wearable and flexible pressure and temperature sensor with a sensitive response to vibration, which can accurately recognize the human voice by combing with the artificial neural network. The device consists of a polyethylene terephthalate (PET) printed with a silver electrode, a filament-microstructured polydimethylsiloxane (PDMS) film embedded with single-walled carbon nanotubes and a polyimide (PI) film sputtered with a patterned Ti/Pt thermistor strip. The developed pressure sensor exhibited a pressure sensitivity of 0.398 kPa${}^{-1}$ in the low-pressure regime, and the fabricated temperature sensor shows a desirable temperature coefficient of resistance of 0.13% ${}^{\circ }$C in the range of 25 ${}^{\circ }$C to 105 ${}^{\circ }$C. Through training and testing the neural network model with the waveform data of the sensor obtained from human pronunciation, the vocal fold vibrations of different words can be successfully recognized, and the total recognition accuracy rate can reach 93.4%. Our results suggest that the fabricated sensor has substantial potential for application in the human-computer interface fields, such as voice control, vocal healthcare monitoring, and voice authentication.

Wearable and flexible pressure sensors have sparked great interest due to their unique capacity to conformally attach to the surface of the skin and quantify human activities into recordable electric signals. As a result, more and more research efforts are being devoted to developing high-sensitivity and cost-effective flexible sensors for monitoring an individual’s state of activity. Herein, a high-performance flexible piezoresistive sensor was designed and fabricated by combing 2D transition metal carbides, nitrides, and carbonitrides (MXene) with a honeycomb-like structure formed by femtosecond filamentating pulses. The sensing mechanism is attributed to the change of the connecting conductive paths between the top interdigital electrodes and the bottom microstructured films coated with MXene. The obtained sensing device demonstrates high sensitivity of 0.61 kPa⁻¹, relatively short response time, and excellent reliability and stability. Benefiting from the aforementioned extraordinary sensing performance, the sensor can be used with success to monitor tiny physiological signals, detect large deformations during human movement, and distinguish finger gestures, thus demonstrating its broad prospects in physiological analysis systems, health monitoring systems, and human–machine interaction.

In recent years, silver sintering has gained increasing attention in high-power density electronic packaging due to its characteristics such as a high melting point and excellent thermal and electrical conductivity. Micron-sized silver sintering offers a lower cost, but requires a longer processing time and additional pressure, which constrains its application. This paper presents a low-cost sintering process using infrared radiation (IR) as a heat source. By leveraging the unique properties of IR, the process achieves selective heating. The thermal energy can be mainly absorbed by the specific areas requiring sintering. This innovative approach eliminates the need for external pressure during the sintering process. This feature not only simplifies the overall process but also reduces the processing time required for sintering. The silver joints obtained from IR sintering process for 45 min achieved an average chip shear strength of 38 MPa at a temperature of 225 °C, which is higher than the strength of silver joints obtained from a traditional sintering process for 2 h. Additionally, the IR-sintered silver joints have a resistivity of 9.83 × 10⁻⁵ Ω·cm and scanning electron microscope (SEM) images of the joints reveal that the sintered joints obtained through the IR sintering process exhibit less porosity compared to joints obtained through a traditional sintering process. The porosity of the IR silver joints at 225 °C is 6.4% and does not change even after 3000 cycles of thermal shock testing, showing outstanding reliability. A GaN power device using IR silver joint also performed better in thermal and electrical performance testing, showing promising potential for the application of micro-silver paste in power electronic devices.

Flexible pressure sensor can acquire important information during contact with the human body and the external environment, thus shining in various fields such as rehabilitative monitoring, artificial intelligence and touch-on displays. With the development of the fifth generation (5 G) mobile communication technology and the Internet of Things, flexible sensing devices need to be used more in ultra-precision fields, such as biopressure and tiny force detection, which require devices to have higher sensitivity. In this work, an ultra-sensitive flexible piezoresistive pressure sensor is created by embedding multi-walled carbon nanotubes onto a polydimethylsiloxane layer with tilted micropillar array microstructures on its surface. Based on the sensing mechanism of microstructure bending deformation rather than compression deformation, the fabricated device exhibits fascinating properties in terms of ultrahigh sensitivity (1.74 kPa⁻¹), fast response time (<100 ms), low detection limit (5.8 Pa) and excellent cyclic stability. Furthermore, the prepared sensors can meet the sensing needs in a variety of dynamic environments, including real-time artery pulse, airflow, acoustic vibrations, and finger bending, indicating that the sensing devices have enormous potential in human health assessment and diagnosis, and robotic tactile perception. This work provides an innovative approach for the development of highly sensitive sensors required in practical applications.

Herein, we present a novel method for junction temperature monitoring of GaN HEMT devices to achieve real-time temperature perception at different locations on the device surface. Through sputtering patterned Ti/Pt thermistor strips on the surface of a GaN HEMT device to construct an on-chip array junction temperature monitoring unit, the thermal distribution of the device during operation is fully reflected. The developed temperature monitoring unit exhibited a desirable temperature coefficient of resistance of 0.183%/°C in the range of 25 °C to 205 °C. Comparison with the thermal imager shows that the integrated temperature monitoring unit can accurately reflect the real-time temperature with a monitoring accuracy of more than 95%, which helps to improve the long-term reliability of GaN power devices under actual application conditions of high frequency and high power density.