Chengyu Jiang

Superhydrophobic silicon surfaces with micro–nano hierarchical structures via deep reactive ion etching and galvanic etching

An effective fabrication method combining deep reactive ion etching and galvanic etching for silicon micro-nano hierarchical structures is presented in this paper. The method can partially control the morphology of the nanostructures and enables us to investigate the effects of geometry changes on the properties of the surfaces. The forming mechanism of silicon nanostructures based on silver nanoparticle galvanic etching was illustrated and the effects of process parameters on the surface morphology were thoroughly discussed. It is found that process parameters have more impact on the height of silicon nanostructure than its diameter. Contact angle measurement and tilting/dropping test results show that as-prepared silicon surfaces with hierarchical structures were superhydrophobic. Whats more, two-scale model composed of micropillar arrays and nanopillar arrays was proposed to study the wettability of the surface with hierarchical structures. Wettability analysis results indicate that the superhydrophobic surface may demonstrate a hybrid state at which water sits on nanoscale pillars and immerses into microscale grooves partially.

Signal Processing of MEMS Gyroscope Arrays to Improve Accuracy Using a 1st Order Markov for Rate Signal Modeling

This paper presents a signal processing technique to improve angular rate accuracy of the gyroscope by combining the outputs of an array of MEMS gyroscope. A mathematical model for the accuracy improvement was described and a Kalman filter (KF) was designed to obtain optimal rate estimates. Especially, the rate signal was modeled by a first-order Markov process instead of a random walk to improve overall performance. The accuracy of the combined rate signal and affecting factors were analyzed using a steady-state covariance. A system comprising a six-gyroscope array was developed to test the presented KF. Experimental tests proved that the presented model was effective at improving the gyroscope accuracy. The experimental results indicated that six identical gyroscopes with an ARW noise of 6.2 °/√h and a bias drift of 54.14 °/h could be combined into a rate signal with an ARW noise of 1.8 °/√h and a bias drift of 16.3 °/h, while the estimated rate signal by the random walk model has an ARW noise of 2.4 °/√h and a bias drift of 20.6 °/h. It revealed that both models could improve the angular rate accuracy and have a similar performance in static condition. In dynamic condition, the test results showed that the first-order Markov process model could reduce the dynamic errors 20% more than the random walk model.

Combining Numerous Uncorrelated MEMS Gyroscopes for Accuracy Improvement Based on an Optimal Kalman Filter

In this paper, an approach to improve the accuracy of microelectromechanical systems (MEMS) gyroscopes by combining numerous uncorrelated gyroscopes is presented. A Kalman filter (KF) is used to fuse the output signals of several uncorrelated sensors. The relationship between the KF bandwidth and the angular rate input is quantitatively analyzed. A linear model is developed to choose suitable system parameters for a dynamic application of the concept. Simulation and experimental tests of a six-gyroscope array proved that the presented approach was effective to improve the MEMS gyroscope accuracy. The experimental results indicate that six identical gyroscopes with a noise density of 0.11°/s/√Hz and a bias instability of 62°/h can be combined to form a virtual gyroscope with a noise density of 0.03°/s/√Hz and a bias instability of 16.8°/h . The accuracy improvement is better than that of a simple averaging process of the individual sensors.

Noise Reduction of MEMS Gyroscope Based on Direct Modeling for an Angular Rate Signal

In this paper, a novel approach for processing the outputs signal of the microelectromechanical systems (MEMS) gyroscopes was presented to reduce the bias drift and noise. The principle for the noise reduction was presented, and an optimal Kalman filter (KF) was designed by a steady-state filter gain obtained from the analysis of KF observability. In particular, the true angular rate signal was directly modeled to obtain an optimal estimate and make a self-compensation for the gyroscope without needing other sensor’s information, whether in static or dynamic condition. A linear fit equation that describes the relationship between the KF bandwidth and modeling parameter of true angular rate was derived from the analysis of KF frequency response. The test results indicated that the MEMS gyroscope having an ARW noise of 4.87°/h0.5 and a bias instability of 44.41°/h were reduced to 0.4°/h0.5 and 4.13°/h by the KF under a given bandwidth (10 Hz), respectively. The 1σ estimated error was reduced from 1.9°/s to 0.14°/s and 1.7°/s to 0.5°/s in the constant rate test and swing rate test, respectively. It also showed that the filtered angular rate signal could well reflect the dynamic characteristic of the input rate signal in dynamic conditions. The presented algorithm is proved to be effective at improving the measurement precision of the MEMS gyroscope.

MEMS-based multi-sensor integrated attitude estimation technology for MAV applications

In this paper we proposed an integrated attitude estimation Kalman filtering technology based on the MEMS sensors for the guidance and navigation of MAV. In the designing of algorithm, the outputs of accelerometer were compensated by airspeed meter, then the gravitational and geomagnetic field vectors were used to correct the attitude solved from gyroscopes through a fifteen-state Extended Kalman Filter. The measurement values of Kalman filter were calculated from the attitude errors obtained through introducing the magnetic yaw and horizontal attitude. Furthermore, the stochastic errors of the gyroscope and accelerometer were set into state vector, which could correct the outputs of the inertial sensors and improve the measurement accuracy. The foremost advantage with presented approach was that the state equations and measurement equations were linear which making it easily to implement. The simulation of dynamic flight tests demonstrated that the estimated error of yaw, pitch and roll less than 1.0°, 1.2° and 0.5° respectively. It also proved the presented Kalman filter could improve the accuracy of attitude estimation effectively.

Controllable fabrication of periodic arrays of high-aspect-ratio micro-nano hierarchical structures and their superhydrophobicity

This paper demonstrates a flexible and controllable fabrication of vertically aligned and high-aspect-ratio (HAR) micro-nano hierarchical structures using conventional micro-technologies. We first masked the nanopatterns on a photoresist mold by shifting the same photomask, which could be performed using conventional contact microlithography. Thereby replicating nanopatterns onto an aluminium mold and successfully fabricating silicon nanopillar arrays about 300 nm in diameter and 5 µm in height via the deep reactive etching (DRIE) process. We also fabricated micro-nano hierarchical structures with variable aspect ratios using the proposed nanopattern technology and DRIE process without using any special nanopatterning equipment or techniques. The proposed method not only simplified the fabrication process but also produced HAR (higher than 15) structures. We also investigate the replica molding steps from the fabricated silicon stamp to a UV-curable polymer replica using a PDMS mold and conventional nano-imprinting, where each nanopillar diameter was 320 nm with 95% fidelity. As a result, the hierarchical structure arrays show stable superhydrophobic surface properties with a contact angle of approximately 160°. Owing to the cost efficiency of mass production and the fidelity of the strategy, the methodology could provide a general approach for fabricating complex three-dimensional periodic hierarchical structures onto a single chip and can be applied to various fields of multifunctional applications.

Analysis of Dynamic Performance of a Kalman Filter for Combining Multiple MEMS Gyroscopes

In this paper, the dynamic performance of a Kalman filter (KF) was analyzed, which is used to combine multiple measurements of a gyroscopes array to reduce the noise and improve the accuracy of the individual sensors. A principle for accuracy improvement by the KF was briefly presented to obtain an optimal estimate of input rate signal. In particular, the influences of some crucial factors on the KF dynamic performance were analyzed by simulations such as the factors input signal frequency, signal sampling, and KF filtering rate. Finally, a system that was comprised of a six-gyroscope array was designed and implemented to test the dynamic performance. Experimental results indicated that the 1σ error for the combined rate signal was reduced to about 0.2°/s in the constant rate test, which was a reduction by a factor of more than eight compared to the single gyroscope. The 1σ error was also reduced from 1.6°/s to 0.48°/s in the swing test. It showed that the estimated angular rate signal could well reflect the dynamic characteristic of the input signal in dynamic conditions.

Ice shear fracture on nanowires with different wetting states.

Understanding the function of nanoscale structure morphology in ice adhesion properties is important in deicing applications. The correlation between ice adhesion and nanowire morphology as well as the corresponding ice shear fracture mechanism are presented for the first time. Ice adhesion on nanowires was measured using a tangential ice-detaching instrument that was developed in-house. Stress analysis was performed using a COMSOL software. Nanowire surface shifted from Wenzel to Cassie transition and Cassie wetting states when the nanowire length was increased. Tangential ice-detaching forces were greater on the hydrophilic surface than those on the hydrophobic surface. Ice-ice internal shear fracture occurred on the ice and force probe contact area at the Wenzel state or on the ice and nanowire contact area at Cassie transition and Cassie state. Different lengths of nanowires caused different wetting states; thus, different fracture areas were formed, which resulted in different tangential ice-detaching forces. This paper presents a new way of tailoring surface ice adhesion via rational design of nanowire morphology with different wetting states.

Large-scale Patterning of Hydrophobic Silicon Nanostructure Arrays Fabricated by Dual Lithography and Deep Reactive Ion Etching

We describe a simple but efficient technique to fabricate large-scale arrays of highly ordered silicon nanostructures. By coupling dual lithography using light of 351.1 nm wavelength with deep reactive ion etching (DRIE), silicon nanostructures of excellent regularity and uniform coverage were achieved. The proposed nanofabrication method not only simplified the nanofabrication process but also produced high-aspect-ratio (higher than 15) nanostructures. The scalloping problem was also controlled by regulating DRIE parameters. The process is rapid, cheap, examined to optimize the fabrication process, and has the potential to be scaled up to large areas. The contact angle of a water droplet atop the surface is larger than 15°. Moreover, by coupling black silicon process with DRIE-based microfabrication, three-dimensional nano/nano dual-scale structures which show robust and stable hydrophobicity have been achieved. This process opens new application possibilities in optical, photoelectric, microelectronic, catalytic and biomedical applications.

System-level modeling of segmented deformable micromirror using multi-port-element network method

This paper presents the development of system-level modeling and simulation of segmented deformable micromirror. We represent a system-level modeling methodology called Multi-Port-Element Network (MuPEN) method for micromirror design which is different from conventional finite-element analysis(FEA) and boundary-element analysis(BEA) method in the paper. Based on this method, the segmented deformable micromirror is decomposed into functional components such as rigid plate-mass, spring beam and electrostatic gap. MuPEN models of functional components have been generated and are coded in MAST language. Then a system-level model of segmented deformable micromirror is established using MuPEN models and both static and dynamic simulation is implemented in SABER. The resonance frequency, the pull-in voltage and the response time of the micromirror are ascertained through different simulations and the simulation results show that the micromirror we designed can satisfy the adaptive optical system requirements. Besides, the frequency analysis results are verified by comparison with ANSYS simulations, and the results prove that MuPEN method has near FEM accuracy. In addition, transient analysis results indicate that the computation cost is low enough and the simulation of complicated electro-mechanical coupled system which is hardly completed by FEM software can be accomplished quickly in this way.