A stiffness-tunable MEMS accelerometer

Guo, Yixuan; Zhang, Tengfei; Zheng, Xudong; Jin, Zhonghe

doi:10.1088/1361-6439/abcedb

Cited by 17 publications

(14 citation statements)

References 22 publications

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“…As illustrated in figure 1(a), the MEMS accelerometer employed in this study includes a proof mass, four flexures, and three groups of capacitors [18]. The proof mass attached with movable electrodes is suspended by the flexures onto the anchors.…”

Section: Stiffness-tunable Mems Accelerometermentioning

confidence: 99%

“…The spring softening effect arising from the tuning capacitors can be described by a net force and a negative stiffness. As displayed in figure 1(c), the stiffness-tunable accelerometer has been successfully fabricated through a standard silicon-on-glass process [18]. The geometric parameters of the fabricated accelerometers are shown in table 2.…”

Section: Stiffness-tunable Mems Accelerometermentioning

confidence: 99%

“…where, m is the mass, b is the damping coefficient, a ext (t) is the input acceleration and x(t) is the displacement, k eff is the effective stiffness, F t0 is the electrostatic force generated by the tuning capacitors, and F fb is the electrostatic force generated by the feedback capacitors, respectively. The stiffness tuning mechanism is explained in detail in [18,20]. The effective stiffness and the applied force by the tuning capacitors as a function of the displacement are given by…”

Section: Stiffness-tunable Mems Accelerometermentioning

confidence: 99%

“…Only considered the temperature effect of the readout circuit [14] Open The stiffness-tunable MEMS accelerometers are increasing attractive recently due to its flexibility to adjust the effective stiffness according to the input range and high sensitivity to acceleration under quasi-zero stiffness [15][16][17]. We previously proposed a stiffness-tunable accelerometer based on singlesided parallel plates (SSPPs) capacitors [18][19][20], which exhibits a remarkable improvement of noise floor yet a severe bias drift arising from the temperature change. In order to improve the thermal stability performance of the proposed accelerometer, we built a temperature drift model and carried out the characterization of the temperature effect on the mechanical stiffness and circuit gains of the proposed accelerometer.…”

Section: Introductionmentioning

confidence: 99%

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Characterization and compensation of thermal bias drift of a stiffness-tunable MEMS accelerometer

Zhang¹,

Jin²,

Ye³

et al. 2022

J. Micromech. Microeng.

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This paper presents characterization and compensation of the thermal bias drift of a MEMS accelerometer whose effective stiffness is electrostatically tuned to a low value with the help of the single-sided parallel plates (SSPP) capacitors. A temperature drift model for the proposed accelerometer is built and the temperature effect on the mechanical stiffness and the circuit gains is characterized. The characterization reveals that the variations of the feedforward coefficient including the mechanical stiffness and the readout gain due to the temperature change play a significant role in the bias drift of output of the proposed closed-loop accelerometer. On the other hand, the variations of both feedback gain and tuning gain as a function of temperature are one-order-of-magnitude less than that of the feedforward coefficient. To calibrate the feedforward coefficient, an excitation signal as a form of AC reference displacement is introduced to drive the proof mass and the readout response is demodulated to calibrate the variance of the feedforward coefficient correspondingly. An open-loop compensation scheme for the temperature-induced bias drift using the variance of the calibrated response is proposed accordingly. Alternatively, the calibrated response can be controlled to a preset value by a new proportion integral derivative (PID) controller by the adjustment of the SSPP tuning voltage. The output of the PID controller is used for the calibration of the introduced bias from the electrostatic tuning force. Therefore, a closed-loop compensation of the thermal bias drift is achieved by remaining the feedforward coefficient while eliminating the calibrated bias. Experiments under a temperature cooling process and different tuning voltages are carried out to verify two proposed compensation schemes. The temperature drift coefficients of both compensated outputs exhibit at least one-order-of-magnitude reduction in response to the temperature change. When the effective stiffness of the accelerometer is tuned to about 4.19 N/m, the temperature drift coefficient (TDC) of the compensated output using the proposed open-loop or closed-loop compensation schemes is reduced to about 0.1136 mg/°C or 0.0391 mg/°C, respectively and meanwhile, the Allan bias instability (BI) is slightly increased to 48.63 μg or 56.14 μg, respectively.

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Section: Stiffness-tunable Mems Accelerometermentioning

confidence: 99%

Section: Stiffness-tunable Mems Accelerometermentioning

confidence: 99%

Section: Stiffness-tunable Mems Accelerometermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Characterization and compensation of thermal bias drift of a stiffness-tunable MEMS accelerometer

Zhang¹,

Jin²,

Ye³

et al. 2022

J. Micromech. Microeng.

Self Cite

View full text Add to dashboard Cite

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“…Getter films have attracted significant attention for their sorption performance in maintaining and improving the vacuum degree in MEMS vacuum devices for extended periods [ 10 , 11 , 12 , 13 ]. Vacuum package and long-term reliability are important in MEMS gyroscopes to ensure their detection accuracy [ 12 , 14 , 15 ]. The vacuum encapsulation can provide a high-quality factor and reduce noise interference in MEMS accelerators [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

Influence of Barrier Layers on ZrCoCe Getter Film Performance

Shi

Xiong

Wu³

2023

Materials

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Improving the vacuum degree inside the vacuum device is vital to the performance and lifespan of the vacuum device. The influence of the Ti and ZrCoCe barrier layers on the performance of ZrCoCe getter films, including sorption performance, anti-vibration performance, and binding force between the ZrCoCe getter film and the Ge substrate were investigated. In this study, the Ti and ZrCoCe barrier layers were deposited between the ZrCoCe getter films and Ge substrates. The microtopographies of barrier layers and the ZrCoCe getter film were analyzed using scanning electron microscopes. The sorption performance was evaluated using the constant-pressure method. The surface roughness of the barrier layers and the getter films was analyzed via atomic force microscopy. The binding force was measured using a nanoscratch tester. The anti-vibration performance was examined using a vibration test bench. The characterization results revealed that the Ti barrier layer significantly improved the sorption performance of the ZrCoCe getter film. When the barrier material was changed from ZrCoCe to Ti, the initial sorption speed of the ZrCoCe getter film increased from 141 to 176 cm3·s−1·cm−2, and the sorption quantity increased from 223 to 289 Pa·cm3·cm−2 in 2 h. The binding force between the Ge substrate and the ZrCoCe getter film with the Ti barrier layer was 171 mN, whereas that with the ZrCoCe barrier layer was 154 mN. The results showed that the Ti barrier layer significantly enhanced the sorption performance and binding force between the ZrCoCe getter film and the Ge substrate, which improved the internal vacuum level and the stability of the microelectromechanical system vacuum devices.

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Learning Stiffness Tensors in Self‐Activated Solids via a Local Rule

Tang,

Ye,

Jia

et al. 2024

Advanced Science

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Mechanical metamaterials are often designed with particular properties for specific load‐bearing functions. Alternatively, this study aims to create a class of active lattice metamaterials, dubbed self‐activated solids, that can learn desired stiffness tensors from the elastic deformations they experienced, a crucial feature to improve the performance, efficiency, and functionality of materials. Artificial adaptive matters that combine sensory, control, and actuation elements can offer appealing solutions. However, challenges still remain: The designs will rely on accurate off‐line and global computations, as well as intricate coordination among individual elements. Here, a simple online and local learning strategy is initiated based on contrastive Hebbian learning to gradually guide self‐activated solids to possess sought‐after stiffness tensors autonomously and reversibly. During learning, the bond stiffness of the active lattice varies depending only on its local strain. The numerical tests show that the self‐activated solid can not only achieve the desired bulk, shear, and coupling moduli but also manifest uni‐mode and bi‐mode extremal materials by itself after experiencing the corresponding elastic deformations. Further, the self‐activated solid can also achieve the desired time‐varying moduli when exposed to temporally different loads. The design is applicable to any lattice geometries and is resistant to damage and instabilities. The material design approach and the physical learning strategy suggested can benefit the design of autonomous materials, physical learning machines, and adaptive robots.

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A stiffness-tunable MEMS accelerometer

Cited by 17 publications

References 22 publications

Characterization and compensation of thermal bias drift of a stiffness-tunable MEMS accelerometer

Characterization and compensation of thermal bias drift of a stiffness-tunable MEMS accelerometer

Influence of Barrier Layers on ZrCoCe Getter Film Performance

Learning Stiffness Tensors in Self‐Activated Solids via a Local Rule

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