Microchip gas chromatography column using magnetic beads coated with polydimethylsiloxane and metal organic frameworks.

Micro gas chromatography (µGC) using microfabricated silicon columns has been developed in response to the requirement for portable on-site gas analysis. Although different stationary phases have been developed, repeatable and reliable surface coatings in these rather small microcolumns remains a challenge. Herein, a new stationary phase coating strategy using magnetic beads (MBs) as carriers for micro column is presented. MBs modified with organopolysiloxane (MBs@OV-1) and a metal organic framework (MBs@HKUST-1) are deposited in on-chip microcolumns assisted with a magnetic field with an optimized modification process. MBs@OV-1 column showed a minimum HETP of 0.074 cm (1351 plates/m) of 62 cm/s. Mixtures of volatile organic compounds are successfully separated using MBs carried stationary phase which demonstrates that this technique has good chromatographic column efficiency. This method not only provides a novel coating process, washing and characterization of the stationary phases but also establishes a straightforward strategy for testing new absorbent materials for µGC systems.

On-Chip Monolithic Integrated Multimode Carbon Nanotube Sensor for a Gas Chromatography Detector.

Carbon nanotube (CNT)-based chemiresistors are promising gas detectors for gas chromatography (GC) due to their intrinsic nanoscale porosity and excellent electrical conductivity. However, fabrication reproducibility, long desorption time, limited sensitivity, and low dynamic range limit their usage in real applications. This paper reports a novel on-chip monolithic integrated multimode CNT sensor, where a micro-electro-mechanical system-based bulk acoustic wave (BAW) resonator is embedded underneath a CNT chemiresistor. The device fabrication repeatability was improved by on-site monitoring of CNT deposition using BAW. We found that the acoustic stimulation can accelerate the gas desorption rate from the CNT surface, which solves the slow desorption issue. Due to the different sensing mechanisms, the multimode CNT sensor provides complementary responses to targets with improved sensitivity and dynamic range compared to a single mode detector. A prototype of a chromatographic system using the multimode CNT sensor was prepared by dedicated design of the connection between the device and the separation column. Such a GC system is used for the quantitative identification of a gas mixture at different GC conditions, which proves the feasibility of the multimode CNT detector for chromatographic analysis. The as-developed CMOS compatible multimode CNT sensor offers high sensing performance, miniaturized size, and low power consumption, which are critical for developing portable GC.

Multifunctional Soft Robotic Finger Based on a Nanoscale Flexible Temperature-Pressure Tactile Sensor for Material Recognition.

Robotic hands with tactile perception can perform more advanced and safer operations, such as material recognition. Nanowires with high sensitivity, fast response, and low power consumption are suitable for multifunctional flexible tactile sensors to provide the tactile perception of robotic hands. In this work, we designed a multifunctional soft robotic finger with a built-in nanoscale temperature-pressure tactile sensor for material recognition. The flexible multifunctional tactile sensor integrates a nanowire-based temperature sensor and a conductive sponge pressure sensor to measure the temperature change rate and contact pressure simultaneously. The developed nanoscale temperature and conductive sponge pressure sensor can reach a high sensitivity of 1.196%/°C and 13.29%/kPa, respectively. With this multifunctional tactile sensor, the soft finger can quickly recognize four metals within three contact pressure ranges and 13 materials within a high contact pressure range. By combining tactile information and artificial neural networks, the soft finger can recognize the materials precisely with a high recognition accuracy of 92.7 and 95.9%, respectively. This work proves the application potential of the multifunctional soft robot finger in material recognition.