Self-sensing Detection Research Articles

Integration of silver nanowires into SU-8 hollow cantilevers for piezoresistive-based sensing

We established a process for the microfabrication of SU-8 AFM cantilevers with an embedded microchannel and an integrated layer of silver nanowires as piezoresistive element. The self-sensing detection is based on the electrical resistance increase of the silver nanowire network associated with the strain applied upon deflection of the cantilever. We observed a sensitivity of 1.4 × 10−6 nm−1 at large strains of 4 % (gauge factor of 10) and a sensitivity of 0.1 × 10−6 nm−1 at small strains of 0.6 % (gauge factor of 1). We obtained a still higher sensitivity (gauge factor of 28) by coating the silver nanowires network with a thin (∼10 nm) aluminum oxide layer acting as an insulating barrier. As application, we studied the cantilever deformation as a function of the overpressure applied in the microchannel while the cantilever was kept in contact with a glass surface confirming their large deflection detection capabilities. The results were qualitatively rationalized in the percolation framework. The presented self-sensing micropipettes could be used for experiments that require remarkably important bending, such as localized single cell deposition by squeezing the micropipette against the substrate, as well as force-controlled electrochemical additive manufacturing at the sub-mm scale.

Research on the least squares support vector machine displacement observer of a bearingless induction motor

To achieve the radial displacement self-sensing detection of a bearingless induction motor, an observation method based on the LS-SVM (least squares support vector machine) is proposed. The state-space model of a magnetic suspension system is derived firstly. Then the LS-SVM is introduced to the radial displacement observer of the bearingless induction motor, the design principle and Lyapunov stability of the LS-SVM displacement observer are analysed in detail, and the construction method of the LS-SVM displacement observer is presented also. Simulation and verification results show that both in the starting suspension stage and in the process of stable suspension operation, the LS-SVM displacement observer can quickly track the radial displacement with high accuracy. Then, a new method is found for the radial displacement self-sensing detection of the bearingless induction motor.

A Self-Sensing Piezoelectric MicroCantilever Biosensor for Detection of Ultrasmall Adsorbed Masses: Theory and Experiments

Detection of ultrasmall masses such as proteins and pathogens has been made possible as a result of advancements in nanotechnology. Development of label-free and highly sensitive biosensors has enabled the transduction of molecular recognition into detectable physical quantities. Microcantilever (MC)-based systems have played a widespread role in developing such biosensors. One of the most important drawbacks of all of the available biosensors is that they all come at a very high cost. Moreover, there are certain limitations in the measurement equipments attached to the biosensors which are mostly optical measurement systems. A unique self-sensing detection technique is proposed in this paper in order to address most of the limitations of the current measurement systems. A self-sensing bridge is used to excite piezoelectric MC-based sensor functioning in dynamic mode, which simultaneously measures the system's response through the self-induced voltage generated in the piezoelectric material. As a result, the need for bulky, expensive read-out equipment is eliminated. A comprehensive mathematical model is presented for the proposed self-sensing detection platform using distributed-parameters system modeling. An adaptation strategy is then implemented in the second part in order to compensate for the time-variation of piezoelectric properties which dynamically improves the behavior of the system. Finally, results are reported from an extensive experimental investigation carried out to prove the capability of the proposed platform. Experimental results verified the proposed mathematical modeling presented in the first part of the study with accuracy of 97.48%. Implementing the adaptation strategy increased the accuracy to 99.82%. These results proved the measurement capability of the proposed self-sensing strategy. It enables development of a cost-effective, sensitive and miniaturized mass sensing platform.

Self-sensing tapping mode atomic force microscopy

We demonstrate self-sensing tapping mode using commercially available, low-stress, piezoelectric cantilevers with sharp, integrated, silicon tips. Previous work has been limited by stress in the cantilevers, thickness and size of the cantilevers, un-optimized electrical trace design, and/or a lack of a probing tip. Tests indicate amplitude resolution with self-sensing to be as good or better than optical detection, and sensitivities up to twice as good, with the same type cantilever. A tapping mode image of an evaporated gold film and force curves that compare optical and self-sensing detection methods are presented.