Molecularly imprinted polymer based on MWCNTs-QDs as fluorescent biomimetic sensor for specific recognition of target protein

A novel molecularly imprinted optosensing material based on multi-walled carbon nanotube-quantum dots (MWCNT-QDs) has been designed and synthesized for its high selectivity, sensitivity and specificity in the recognition of a target protein bovine serum albumin (BSA). Molecularly imprinted polymer coated MWCNT-QDs using BSA as the template (BMIP-coated MWCNT-QDs) exhibits a fast mass-transfer speed with a response time of 25 min. It is found that the BSA as a target protein can significantly quench the luminescence of BMIP-coated MWCNT-QDs in a concentration-dependent manner that is best described by a Stem-Volmer equation. The K-SV for BSA is much higher than bovine hemoglobin and lysozyme, implying a highly selective recognition of the BMIP-coated MWCNT-QDs to BSA. Under optimal conditions, the relative fluorescence intensity of BMIP-coated MWCNT-QDs decreases linearly with the increasing target protein BSA in the concentration range of 5.0 x 10(-7)-35.0 x 10(-7) M with a detection limit of 80 nM

Magnetoelectric coupling of a magnetoelectric flux gate sensor in vibration noise circumstance

A magnetoelectric (ME) flux gate sensor (MEFGS) consisting of piezoelectric PMN-PT single crystals and ferromagnetic amorphous alloy ribbon in a self-differential configuration is featured with the ability of weak magnetic anomaly detection. Here, we further investigated its ME coupling and magnetic field detection performance in vibration noise circumstance, including constant frequency, impact, and random vibration noise. Experimental results show that the ME coupling coefficient of MEFGS is as high as 5700 V/cm*Oe at resonant frequency, which is several orders magnitude higher than previously reported differential ME sensors. It was also found that under constant and impact vibration noise circumstance, the noise reduction and attenuation factor of MEFGS are over 17 and 85.7%, respectively. This work is important for practical application of MEFGS in real environment

Improved Linear Quadratic Regulator Lateral Path Tracking Approach Based on a Real-Time Updated Algorithm with Fuzzy Control and Cosine Similarity for Autonomous Vehicles

Path tracking plays a crucial role in autonomous driving. In order to ensure the real-time performance of the controller and at the same time improve the stability and adaptability of the path tracking controller, a lateral path control strategy based on the improved LQR algorithm is proposed in this paper. To begin with, a discrete LQR controller with feedforward and feedback components is designed based on the error model of vehicle lateral dynamics constructed by the natural coordinate system. Then, a fuzzy control method is applied to adjust the weight coefficients of the LQR in real time according to the state of the vehicle. Furthermore, an update mechanism based on cosine similarity is designed to reduce the computational effort of the controller. The improved LQR controller is tested on a joint Simulink–Carsim simulation platform for a two-lane shift maneuver. The results show that the control algorithm improves tracking accuracy, steering stability and computational efficiency

Improved Linear Quadratic Regulator Lateral Path Tracking Approach Based on a Real-Time Updated Algorithm with Fuzzy Control and Cosine Similarity for Autonomous Vehicles

Path tracking plays a crucial role in autonomous driving. In order to ensure the real-time performance of the controller and at the same time improve the stability and adaptability of the path tracking controller, a lateral path control strategy based on the improved LQR algorithm is proposed in this paper. To begin with, a discrete LQR controller with feedforward and feedback components is designed based on the error model of vehicle lateral dynamics constructed by the natural coordinate system. Then, a fuzzy control method is applied to adjust the weight coefficients of the LQR in real time according to the state of the vehicle. Furthermore, an update mechanism based on cosine similarity is designed to reduce the computational effort of the controller. The improved LQR controller is tested on a joint Simulink–Carsim simulation platform for a two-lane shift maneuver. The results show that the control algorithm improves tracking accuracy, steering stability and computational efficiency

A Piezoelectric and Electromagnetic Dual Mechanism Multimodal Linear Actuator for Generating Macro- and Nanomotion

Fast actuation with nanoprecision over a large range has been a challenge in advanced intelligent manufacturing like lithography mask aligner. Traditional stacked stage method works effectively only in a local, limited range, and vibration coupling is also challenging. Here, we design a dual mechanism multimodal linear actuator (DMMLA) consisted of piezoelectric and electromagnetic costator and coslider for producing macro-, micro-, and nanomotion, respectively. A DMMLA prototype is fabricated, and each working mode is validated separately, confirming its fast motion (0~50 mm/s) in macromotion mode, micromotion (0~135 μm/s) and nanomotion (minimum step: 0~2 nm) in piezoelectric step and servomotion modes. The proposed dual mechanism design and multimodal motion method pave the way for next generation high-precision actuator development