The development of high-performance sensors for doxycycline (DOX) detection is necessary because its residue accumulation will cause serious harm to human health and the environment. Here, a novel tri-emission ratiometric fluorescence sensor was proposed by using "post-mixing" strategy of different emissions fluorescence molecularly imprinted polymers with salicylamide as dummy template (DMIPs). BSA was chosen as assistant functional monomer, and also acted as sensitizers for the aggregation-induced emission (AIE) effect of DOX. The blue-emitting carbon dots and the red-emitting CdTe quantum dots were separately introduced into DMIPs as the response signals. Upon DOX recognition within 2 min, blue and red fluorescence of the tri-emission DMIPs sensor were quenched while green fluorescence of DOX was enhanced, resulting in a wide range of color variations observed over bluish violet-rosered-light pink-orange-yellow-green with a detection limit of 0.061 µM. The sensor possessed highly selective recognition and was successfully applied to detect DOX in complicated real samples. Moreover, with the fluorescent color collection and data processing, the smartphone-assisted visual detection of the sensors showed satisfied sensitivity with low detection limit. This work provides great potential applications for rapid and visual detection of antibiotics in complex substrates.
Anti-Bacterial Agents , Cadmium Compounds , Doxycycline , Molecular Imprinting , Quantum Dots , Spectrometry, Fluorescence , Tellurium , Doxycycline/analysis , Doxycycline/chemistry , Quantum Dots/chemistry , Tellurium/chemistry , Anti-Bacterial Agents/analysis , Cadmium Compounds/chemistry , Limit of Detection , Fluorescence , Carbon/chemistry , Fluorescent Dyes/chemistry , Molecularly Imprinted Polymers/chemistry , Smartphone
With the continuous progress of aerospace, military technology, and marine development, the MEMS resonance pressure sensor puts forward the requirements of not only a wide range but also high sensitivity. However, traditional resonators are hardly compatible with both. In response, we propose a new sensor structure. By arranging the resonant beam and the sensitive diaphragm vertically in space, the new structure improves the rigidity of the diaphragm without changing the thickness of the diaphragm and achieves the purpose of increasing the range without affecting the sensitivity. To find the optimal structural parameters for the sensor sensitivity and range, and to prevent the effects of modal disturbances, we propose a multi-objective optimization design scheme based on the BP and NSGA-II algorithms. The optimization of the structure parameters not only improved the sensitivity but also increased the interference frequency to solve the issue of mode interference. The optimized structure achieves a sensitivity and range of 4.23 Hz/kPa and 1-10 MPa, respectively. Its linear influence factor is 38.07, significantly higher than that of most resonant pressure sensors. The structural and algorithmic optimizations proposed in this paper provide a new method for designing resonant pressure sensors compatible with a wide range and high sensitivity.
Making metal nanoparticle aggregates is a common way to improve surface-enhanced Raman scattering (SERS) enhancement via the formation of hot spots between nanoparticles. Here, we propose a "freeze-thaw-ultrasonication" method to obtain stable colloidal Ag nano-aggregates (AgNAs) with controllable sizes, which can remain stable for a few days. Compared with other method using aggregation reagents (e.g., organic molecules and salt), this method can maintain metal surface charges and adsorption affinity, which ensures the excellent SERS stability and sensitivity. The SERS detection window during the experiment can reach more than 25 min, which makes it a prerequisite for accurate SERS detection during a long-time range. Combining the obtained stable AgNAs with microfluidic devices, we established a sequential SERS on-line continuous detection method for the high-throughput detection of multiplex samples. The UV-Fenton degradation process of methylene blue (MB) is continuously on-line monitored through this platform, which is more sensitive than the UV-Vis Spectrum. Moreover, we have realized the sensitive and accurate detection of 5-nitro-8-hydroxyquinoline (5-NQ) with antibacterial and anticancer activities based on chloride-functionalized silver, which paved a way for SERS high-throughput analysis in bioanalysis and other fields.
Natural structures and motion behaviors open new avenues for effective small-scale transport, such as the plant-inspired energy-free liquid transport surfaces and cilia-inspired propulsion systems. However, they are restricted by either the fixed structure or nonself-regulating beating modes, making many complex tasks remain challenging, e.g., the controllable multidirectional liquid transport and flexible propulsion. Herein, inspired by pine needles and natural cilia, we report an asymmetric-structured intelligent magnetic pillar actuator (AI-MPA) with both the "passive" and "active" transport features. Under the control of the magnetic field, the AI-MPA shows an all-space liquid transport ability toward arbitrary directions. Moreover, benefiting from the material's magnetoelasticity and asymmetric-structured design, the AI-MPA enables self-regulation of two-dimensional (2D)/three-dimensional (3D) cilia-like beating modes and can be further developed for robotic crawling and self-rotatable motion. The AI-MPA integrates the superiority of static and dynamic systems in nature and exhibits intelligent self-regulation that could not be achieved before. Confirmed theoretically and demonstrated experimentally, this work provides insights into increasingly functional and intelligent miniature biomimetic systems, with applications from directional liquid transport to robotic locomotion.
Untethered microrobots provide the prospect for performing minimally invasive surgery and targeted delivery of drugs in hard-to-reach areas of the human body. Recently, inspired by the way the prokaryotic flagella rotates to drive the body forward, numerous studies have been carried out to study the swimming properties of helical swimmers. In this study, the resistive force theory (RFT) was applied to analyze the influence of dimensional and kinematical parameters on the propulsion performance of conventional helical swimmers. The propulsion efficiency index was applied to quantitatively evaluate the swimming performance of helical swimmers. Quantitative analysis of the effect of different parameters on the propulsion performance was performed to optimize the design of structures. Then, RFT was modified to explore the tapered helical swimmers with the helix radius changing uniformly along the axis. Theoretical results show that the helical swimmer with a constant helix angle exhibits excellent propulsion performance. The evaluation index was found to increase with increased tapering, indicating that the tapered structures can produce more efficient motion. Additionally, the analysis method extended from RFT can be used to analyze the motion of special-shaped flagella in microorganisms.
Automation of the bin picking task with robots entails the key step of pose estimation, which identifies and locates objects so that the robot can pick and manipulate the object in an accurate and reliable way. This paper proposes a novel point pair feature-based descriptor named Boundary-to-Boundary-using-Tangent-Line (B2B-TL) to estimate the pose of industrial parts including some parts whose point clouds lack key details, for example, the point cloud of the ridges of a part. The proposed descriptor utilizes the 3D point cloud data and 2D image data of the scene simultaneously, and the 2D image data could compensate the missing key details of the point cloud. Based on the descriptor B2B-TL, Multiple Edge Appearance Models (MEAM), a method using multiple models to describe the target object, is proposed to increase the recognition rate and reduce the computation time. A novel pipeline of an online computation process is presented to take advantage of B2B-TL and MEAM. Our algorithm is evaluated against synthetic and real scenes and implemented in a bin picking system. The experimental results show that our method is sufficiently accurate for a robot to grasp industrial parts and is fast enough to be used in a real factory environment.
