MEMS Piezoelectric Energy Research Articles

Piezoelectric MEMS Energy Harvester by Using Collision Impact of Droplets

Piezoelectric MEMS Energy Harvester by Using Collision Impact of Droplets

Piezoelectric MEMS Energy Harvester for Low-Power Applications

With the global market value of sensors on the rise, this paper focuses on the fabrication and testing of a proof-of-concept piezoelectric energy harvester which is able to harvest mechanical energy from the ambient environment and convert it into electrical energy in order to power wireless sensor networks. We focused on obtaining a new device structure based on a comb-type array of piezoelectric MEMS cantilevers (2 × 10) for a resonant frequency in the environmental application domain (a few hundred Hz) and a chip area of only 1 cm2. The configuration of the lead-free piezoelectric cantilever consists of a Si substrate, a pair of Ti-Pt electrodes and a sputtered piezoelectric layer of 12% Sc-doped AlN with a thickness of 1000 nm, a dielectric constant of ~13 and e31,f = 1.3 C/m2. At a resonant frequency of 465.2 Hz and an acceleration of 1 g, the maximum value for the collected power was 2.53 µW for an optimal load resistance of 1 MΩ resulting in a power density of 60.2 nW/mm3 for the unpacked device, without taking into account the vibration volume. By increasing the excitation acceleration to 2 g RMS and using LTC3588-1 for the power circuitry we were able to obtain a stabilized output voltage of 1.8 V.

FEM-Inclusive Transfer Learning for Bistable Piezoelectric MEMS Energy Harvester Design

In this article, a bistable piezoelectric MEMS energy harvester is presented to operate in a low-frequency range, around 100–200 Hz. The proposed design has an M-shaped structure with a couple of proof masses to not only lower the operating frequencies but also enlarge the frequency bandwidth. This specific structure has multidegrees of freedom, making it fit for a bistable piezoelectric energy harvester on the MEMS scale. An artificial neural network (ANN) is used to tackle this design in order to facilitate the optimization process and determine proper physical dimensions. To improve the accuracy and boost the training process of deep neural network (DNN), we utilize a transfer learning technique in this work. The analytical modeling and finite-element modeling (FEM) simulation data have been used for the DNN model training. Here, a DNN is first trained with a large dataset computed from the lumped-parameter model, and then, the trained network is transferred to a new DNN model for another round of training with a small dataset of highly accurate FEM simulation data samples to further reduce the estimation error. It is shown that the new model can estimate the device features with over 94% accuracy, which is considerably higher than the regular DNN. Next, the trained model is used as a performance estimator in a genetic algorithm (GA) to optimize the topology of the device to improve the operating frequency range and the generated voltage. An optimized design with a total volume of 1.02 mm3 was fabricated by the micromachining process. Our experimental results confirm that the proposed transfer-learning-based method can not only reduce the prototype’s first and second resonant frequencies to 123.8 and 175.7 Hz, respectively, but also enhance the generated power up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2.83 ~\mu \text{W}$ </tex-math></inline-formula> under 0.2-g input acceleration.

Piezoelectric MEMS Energy Harvester from Airflow at Low Flow Velocities

Piezoelectric MEMS Energy Harvester from Airflow at Low Flow Velocities

Broadband Zero-Power Wakeup MEMS Device for Energy-Efficient Sensor Nodes.

A zero-power wakeup scheme for energy-efficient sensor applications is presented in this study based on a piezoelectric MEMS energy harvester featuring wafer-level-integrated micromagnets. The proposed setup overcomes a hybrid assembly of magnets on a chip-level, a major drawback of similar existing solutions. The wakeup device can be excited at low frequencies by frequency up-conversion, both in mechanical contact and contactless methods due to magnetic force coupling, allowing various application scenarios. In a discrete circuit, a wakeup within 30–50 ms is realized in frequency up-conversion at excitation frequencies < 50 Hz. A power loss in the off state of 0.1 nW renders the scheme virtually lossless. The potential extension of battery lifetime compared to cyclical wakeup schemes is discussed for a typical wireless sensor node configuration.

Deep-Learning-Based Optimization for a Low-Frequency Piezoelectric MEMS Energy Harvester

High operational frequency is one of the major limitations of the conventional MEMS vibration energy harvesters. In this work, we present a piezoelectric MEMS energy harvester with the capability of operating at a low resonant frequency (i.e., less than 200 Hz). The proposed harvester has a symmetric serpentine structure with a doubly clamped configuration comprising several proof masses at the junctions. In order to facilitate the design process and determine the optimum physical dimensions, an artificial neural network is used to model the design. In the first step, a dataset with 108 samples is generated by finite element modeling (FEM) to train a deep neural network. The validation results indicate that the trained deep neural network model can achieve around 90% estimation accuracy of device features, such as resonant frequency and harvested voltage. Next, this trained model is integrated with genetic algorithm as a performance estimator to optimize the geometry of the harvester to lower the resonant frequency and improve the harvested voltage. An optimized harvester with a total area of 8.7 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> has been fabricated through a standard micromachining process. Our measurement results confirm that the proposed deep-learning-based method can help reach the balanced summit of both higher power density and lower resonant frequency among the published works. Our prototype device features the first resonant frequency of 121.7 Hz and the harvested power of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.73~\mu \text{W}$ </tex-math></inline-formula> under 0.1g input acceleration.

Artificial Intelligence-Based Optimization of a Bimorph-Segmented Tapered Piezoelectric MEMS Energy Harvester for Multimode Operation

This paper presents a study on the design and multiobjective optimization of a bimorph-segmented linearly tapered piezoelectric harvester for low-frequency and multimode vibration energy harvesting. The procedure starts with a significant number of FEM simulations of the structure with different geometric dimensions—length, width, and tapering ratio. The datasets train the artificial neural network (ANN) that provides the fitting function to be modified and used in algorithms for optimization, aiming to achieve minimal resonant frequency and maximal generated power. Levenberg–Marquardt (LM) and scaled conjugate gradient (SCG) methods were used to train the ANN, then the goal attainment method (GAM) and genetic algorithm (GA) were used for optimization. The dominant solution resulted from optimization by the genetic algorithm integrated with the ANN fitting function obtained by the SCG training method. The optimal piezoelectric harvester is 121.3 mm long and 71.56 mm wide and has a taper ratio of 0.7682. It ensures over five times greater output power at frequencies below 200 Hz, which benefits the low frequency of the vibration spectrum. The optimized design can harness the power of higher-resonance modes for multimode applications.

A Lead-Free Spiral Bimorph Piezoelectric MEMS Energy Harvester for Enhanced Power Density

Tiny sensor nodes are the demand of smart and intelligent systems. These sensor nodes require on-board self-powered generating systems. Also, such generators should have lesser size. MEMS energy harvesters are profoundly used as the on-board self-powered generators. However, the size constrain imposes an important design trade-off on such devices. This trade-off is in-between areal dimension and the resonant frequency. In this paper, we have proposed an efficient bimorph energy harvester design which produces higher power density at very low resonance frequency. We have considered the poisonous behavior of lead-based devices as well and proposed lead-free designs in our work. The proposed design consists of a bimorph square plate of 2.25 mm2 with two Zinc Oxide (ZnO) layers of 0.5 µm each sandwiched a copper electrode layer of 1 µm. A spiral cut of 5 µm thickness is made over the plate in order to form a fixed free beam structure. Furthermore, without the inclusion of tip mass, the resonant frequency of the beam is controlled by varying the number of spiral turns. Our proposed design outperformed the previous designs by producing maximum output power of 15 nW at 110 Hz with seven spiral turns with very lower active volume. Also, it has a normalized volumetric power density of 3 × 10−2 µW/mm3 g2 Hz.

Two-degree-of-freedom Piezoelectric MEMS Energy Harvester Based on Bulk PZT Film

Two-degree-of-freedom Piezoelectric MEMS Energy Harvester Based on Bulk PZT Film

MEMS Energy Harvesting Based on Uniform-Stress Cantilever with Multilayer PZT Thin Films

Multilayered piezoelectric MEMS energy harvesters based on sputtering depositions are designed and fabricated. To obtain high endurance and output power, the unimorph cantilever structure with totally 10 μm-thick multilayered PZT thin films and 80 μm-thick Si elastic layer is designed. In addition, the cantilever is designed to undergo a uniform stress on the PZT. The output power and voltage was 90 μW and 1.0 Vrms under the input acceleration of approximately 1.2 G (=11.76 m/s2) and optimum load resistance.

Design of the Squared Daisy: A Multi-Mode Energy Harvester, with Reduced Variability and a Non-Linear Frequency Response.

With the rise of the Internet of Things (IoT) and the ever-increasing number of integrated sensors, the question of powering these devices represents an additional challenge. The traditional approach is to use a battery; however, harvesting energy from the environment seems to be the most practical approach. To that end, the use of piezoelectric MEMS energy has been proven as a potential power source in a wide range of applications. In this work, a proof of concept for a new architecture for MEMS energy harvesters is presented. The influence of the dimensions and different characteristics of these designs is discussed. These designs have been proven to be resilient to process variation thanks to their unique architecture. This work presents the use of vibration enhancement petals in order to widen the bandwidth of the energy harvester and provide a non-linear frequency response. The use of these vibration enhancement petals has allowed the fabrication of three design variations, each using an area of 1700 µm by 1700 µm. These designs have an operating bandwidth between 3.9 kHz and 14.5 kHz and can be scaled to achieve other targeted resonant frequencies.

Design and Simulation of MEMS Piezoelectric Vibration Energy Harvesters with Center Mass Block

MEMS-based piezoelectric vibration energy harvesters (MEMS-PVEHs) with center mass block are designed with the overall size 10 × 10 × 2 mm3, two prototypes including piezoelectric unimorph and bimorph beams are used respectively. This paper studies the characteristics of MEMS-PVEHs by modeling and simulation in COMSOL. Their eigenfrequencies are analyzed firstly, their optimal piezoelectric outputs are explored by changing excitation frequency and load resistance secondly, then the piezoelectric unimorph and bimorph beams are compared finally. The simulation results show that the optimal excitation frequency is slightly higher than the eigenfrequency, and the maximum piezoelectric power of the PVEH can be obtained only when the appropriate excitation frequency and load resistance are selected, and the power generation efficiency is 0.5. It has little difference between unimorph and bimorph to improve the MEMS-PVEH piezoelectric output. Finally, the piezoelectric unimorph with double opposite electrodes is designed based on the MEMS fabrication process.

Buckled MEMS Beams for Energy Harvesting from Low Frequency Vibrations.

Vibration energy harvesters based on the resonance of the beam structure work effectively only when the operating frequency window of the beam resonance matches with the available vibration source. None of the resonating MEMS structures can operate with low frequency, low amplitude, and unpredictable ambient vibrations since the resonant frequency goes up very high as the structure gets smaller. Bistable buckled beam energy harvester is therefore developed for lowering the operating frequency window below 100Hz for the first time at the MEMS scale. This design does not rely on the resonance of the MEMS structure but operates with the large snapping motion of the beam at very low frequencies when input energy overcomes an energy threshold. A fully functional piezoelectric MEMS energy harvester is designed, monolithically fabricated, and tested. An electromechanical lumped parameter model is developed to analyze the nonlinear dynamics and to guide the design of the nonlinear oscillator based energy harvester. Multilayer beam structure with residual stress induced buckling is achieved through the progressive residual stress control of the deposition processes along the fabrication steps. Surface profile of the released device shows bistable buckling of 200μm which matches well with the amount of buckling designed. Dynamic testing demonstrates the energy harvester operates with 50% bandwidth under 70Hz at 0.5g input, operating conditions that have not been demonstrated by MEMS vibration energy harvesters before.

Piezoelectric MEMS with multilayered Pb(Zr,Ti)O3 thin films for energy harvesting

This study aims to report the design of high-performance piezoelectric MEMS energy harvesters using a full batch MEMS-fabrication process with a Si proof mass and multilayered Pb(Zr,Ti)O3 (PZT) thin films without bonding of a proof mass and/or bulk piezoelectric ceramics. These devices contain sputtered multilayered PZT thin films with internal metal electrodes as a thick energy-conversion layer. The thickening of the piezoelectric layer by multilayer sputter deposition technique enabled the batch fabrication of high-performance piezoelectric MEMS harvesters. These fabricated device with the footprint of 10 × 10 mm2 was found to provide a high output power of 53.7 μW per gravitational acceleration. These results are expected to be useful for the future development of alternatives to batteries for autonomous sensor systems.

T-shaped Piezoelectric Vibratory MEMS Harvester with Integration of Highly Efficient Power Management System

This paper introduces a T-shaped piezoelectric vibratory MEMS energy harvester. The prototype measurement results clearly demonstrate that the T-shaped harvester can achieve higher normalized power efficiency by a factor of 1.95 in comparison with the conventional piezoelectric harvester. Since the magnitude of harvested voltage in this type of energy harvesters is only a few millivolts, utilizing the traditional power electronic components is impractical. Thus, in this paper we also propose a highly efficient power management system without requiring external bias voltages. The numerical simulation illustrates that our proposed power management system can rectify and boost the harvested voltage up to 5V. In order to keep the output voltage on the load side at a stable level, a JFET transistor is utilized as a voltage limiter. Thus, the processed output voltage cannot exceed 4V even if a higher harvested voltage may be produced by the harvester.

Impact-driven up-conversion in piezoelectric MEMS energy harvesters with pulsed excitation

The potential of impact-driven frequency up-conversion in a MEMS EH is evaluated using numerical simulations. The investigated design is compared to a conventional cantilever EH in terms of output power and loss rate. The upshifting can lead to significantly increased output power at a similar loss rate but as the time scale for the loss is long, the benefit is limited. This also requires an effective upshifting process. The design of the impact introduces a length scale that must be selected with excitation, gravity, and pre-stress taken into account. This makes this type of EH application-dependent as a non-optimal choice may result in low output power.

Multilayer piezoelectric MEMS energy harvester based on longitudinal effect

Piezoelectric MEMS energy harvesters based on multilayer (ML) Pb(Zr,Ti)O3 (PZT) thin films with interdigitated electrodes (IDE) as their internal and top electrodes are proposed and designed. Thick PZT thin films with good piezoelectric characteristics can be deposited by using multilayer deposition technique. Furthermore, IDE is adopted to the harvester design in order to take advantage of the longitudinal piezoelectric effect, which typically has twice piezoelectric constant as large as transverse effect. The energy harvesters with two electrode configurations, parallel plate electrodes (PPE) and IDE, are designed and estimate these output power. According to the result of finite element analysis, the output power per gravitational acceleration is about 124 μW for the PPE configuration. On the other hand, the output power per gravitational acceleration for the IDE configuration is about three times as large as that for PPE. Moreover, the influence of IDE patterns and the number of PZT layers were investigated. The larger number of layers results in the larger output power.

Lead-free Mn-doped (K0.5,Na0.5)NbO3 piezoelectric thin films for MEMS-based vibrational energy harvester applications

Lead-free Mn-doped (K0.5, Na0.5)NbO3 (KNN) thin films were fabricated by the chemical solution deposition method. The addition of small concentration of Mn dopant effectively reduced the leakage current density and enhanced the piezoelectric properties of the films. The leakage current density of 0.5 mol. % Mn-doped KNN film showed the lowest value of ∼10-7 A/cm2 at 10 V compared to the films with other doping concentrations and the piezoelectric d33 and e31 coefficients of this film were ∼90 pm/V and −8.5 C/m2, respectively. The maximum power and power density of the lead-free thin film-based vibrational energy harvesting device were 3.62 μW and 1800 μW/cm3 at the resonance frequency of 132 Hz and the acceleration of 1.0 G. The results prove that the 0.5 mol. % Mn-doped KNN film is an attractive candidate transducer layer for the piezoelectric MEMS energy harvesting device applications with a small volume and a long-lasting power source.

A Micro Inertial Energy Harvesting Platform With Self-Supplied Power Management Circuit for Autonomous Wireless Sensor Nodes

A 0.25 cm 3 autonomous energy harvesting micro-platform is realized to efficiently scavenge, rectify and store ambient vibration energy with batteryless cold start-up and zero sleep-mode power consumption. The fabricated compact system integrates a high-performance vacuum-packaged piezoelectric MEMS energy harvester with a power management IC and surface-mount components including an ultra-capacitor. The power management circuit incorporates a rectification stage with ~30 mV voltage drop, a bias-flip stage with a novel control system for increased harvesting efficiency, a trickle charger for permanent storage of harvested energy, and a low power supply-independent bias circuitry. The overall system weighs less than 0.6 grams, does not require a pre-charged battery, and has power consumption of 0.5 µW in active-mode and <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$&lt; $</tex></formula> 10 pW in sleep-mode operation. While excited with 1 g vibration, the platform is tested to charge an initially depleted 70 mF ultra-capacitor to 1.85 V in 50 minutes (at 155 Hz vibration), and a 20 mF ultra-capacitor to 1.35 V in 7.5 min (at 419 Hz). The end-to-end rectification efficiency from the harvester to the ultra-capacitor is measured as 58–86%. The system can harvest from a minimum vibration level of 0.1 g.

Compositional dependence of Pb(Mg1/3,Nb2/3)O3–PbTiO3 piezoelectric thin films by combinatorial sputtering

We evaluated the compositional dependence of Pb(Mg1/3,Nb2/3)O3–PbTiO3 (PMN–PT) polycrystalline thin films by combinatorial sputtering. We prepared compositional gradient (1 − x)PMN–xPT polycrystalline thin films with preferential orientation along the 〈001〉 direction in the composition range of x = 0–0.62. We determined that the morphotropic phase boundary (MPB) composition of PMN–PT polycrystalline thin film existed at around x = 0.35, from the X-ray diffraction (XRD) measurements. The maximum value of relative dielectric constants (εr = 1498) was obtained at approximately x = 0.23. On the other hand, the piezoelectric coefficients (|e31,f| = 14.1 C/m2) peaked at the determined MPB composition of x = 0.35. From the results of the compositional dependence of dielectric and piezoelectric characteristics, the FOM () of the PMN–PT (x = 0.35) thin film reached 21 GPa, which is much higher than that of the other polycrystalline piezoelectric thin films. These results suggest that PMN–PT (x = 0.35) thin film is a promising material for high-efficiency piezoelectric MEMS energy harvesters.