MEMS Energy Harvester Research Articles

Comprehensive simulation study on AlN, ZnO, and PZT-5H piezoelectric materials for microcantilever-based MEMS energy harvesters: Mechanical and electrical insights

Comprehensive simulation study on AlN, ZnO, and PZT-5H piezoelectric materials for microcantilever-based MEMS energy harvesters: Mechanical and electrical insights

Design and experimentation of width tapered meandered array structure for low frequency broadband vibration energy harvesting

A novel 6DoF Tapered beam energy harvester, capable of operating across a broad and low frequency range, is proposed in this work. The hybrid structure incorporates regular beam array and zig-zag sections, enhancing deformation and bending. Width tapering with constant thickness optimizes the structural performance and energy harvesting capabilities of the beam. Tapering ensures even strain distribution, reducing the risk of structural failure. The proposed structure demonstrates wide band characteristics at low frequencies, delivering higher power output compared to an array of cantilevers for a given area. FEM analysis is conducted to optimize proof mass, aiming for closely spaced resonance frequencies and high-power output. Experimental validation on a prototype confirms the accuracy of the frequency response predicted by the models. Under harmonic base excitation of 0.4 g, the harvester yields an average DC power of 2497 μW, accounting for signal conditioning losses, within the frequency range of 9–20 Hz. The suggested structure offers excellent design flexibility, allowing adjustment of resonant frequencies by varying the number of beams, the slope and the proof mass of individual beams. The geometry of the proposed structure provides versatility, mechanical resilience, uniform strain distribution make it suitable for developing MEMS energy harvesters.

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.

Biomechanical MEMS Electrostatic Energy Harvester for Pacemaker Application: A Study of Optimal Interface Circuit.

The leadless pacemaker is the most recent pacemaker concept, developed to overcome conventional pacemakers' limitations. This technology offers better comfort to the patients, lower risk from implantation, and higher reliability. However, these devices suffer from limited battery lifetime due to the extreme miniaturization required for implantation inside the heart cavities. This work proposes extending the battery lifetime by converting biomechanical heartbeat energy into electricity using an innovative electrostatic MEMS energy harvesting device. Based on theoretical models and experiments, we propose a general approach to choosing the optimal interface circuit which considers the parasitic capacitance of the circuit, as it is an imperfection that significantly affects the power performance. According to the energy consumed by the last generation commercial leadless pacemakers, the proposed MEMS solution with optimal interface circuit experimentally showed the possibility of extending the pacemaker battery lifetime by up to 44%.

Dynamic analysis of a novel two-sided nonlinear MEMS electrostatic energy harvester

In this work, we investigate the frequency response of an electrostatic MEMS energy harvester with innovative gap-overlap transducer design. We prove theoretically and experimentally that this design solution gives rise to a strongly nonlinear behaviour in MEMS dynamics. This is the first time that this phenomenon is demonstrated in a gap-overlap electrostatic MEMS along with a theoretical explanation. When increasing the bias voltage, the frequency response shifts towards lower frequencies while bending towards higher ones. The main consequence of this bending is a significant increase of the system bandwidth (+280 % compared to a linear situation with no bias voltage for the same device) when the bias voltage increases up to 30 V. A proposed gap-overlap transducer configuration is demonstrated to be a simple and efficient solution for MEMS energy harvester bandwidth increase.

A wide-bandwidth MEMS energy harvester based on a novel voltage-sliding stiffness tunability

Due to the significance of power harvesting technologies in making use of the energy sources available in the surroundings, in this research, an innovative piezoelectric energy harvesting mechanism with adjustable stiffness is presented. The presented design performs based on the transverse motion of the two microbeams supported at one end. The beams are sandwiched between two piezoelectric layers and are in exposure to an external acceleration field. At the free end of the microbeams, a rectangular microplate is embedded as a slip-over electrode without an electric charge. A thin dielectric layer separates the microplate and two other stationary electrodes. Once a constant adjusting voltage is applied through the stationary electrodes, the free electrons’ displacement in the microplate causes the plate to encounter a nonlinear deflection-dependent electrostatic force. The produced electrostatic will perform as an electric spring so that its stiffness can be altered by the applied adjusting DC voltage. As the rigidity coefficient of the electric spring can be controlled easily, it makes the structure a wide-frequency bandwidth energy harvester. Mathematical modeling of the design has been analyzed to demonstrate the structure's nonlinear vibration behavior coupled with the harvesting section of the system. The derived equations are solved altogether after being discretized by the use of the Galerkin method. The energy harvester's steady-state response in various harmonies is found by applying a learning-based method. Also, the appearance of the main resonance as well as secondary resonances in the energy harvester's response in the frequency domain in different harmonies can be analyzed. The design's geometric effect on the power harvester's effective performance is examined in detail. The power harvester's output power versus the impedance and also the structure's output power density undergoing the external acceleration are investigated.

Multimodal MEMS vibration energy harvester with cascaded flexible and silicon beams for ultralow frequency response

Scavenged energy from ambient vibrations has become a promising energy supply for autonomous microsystems. However, restricted by device size, most MEMS vibration energy harvesters have much higher resonant frequencies than environmental vibrations, which reduces scavenged power and limits practical applicability. Herein, we propose a MEMS multimodal vibration energy harvester with specifically cascaded flexible PDMS and “zigzag” silicon beams to simultaneously lower the resonant frequency to the ultralow-frequency level and broaden the bandwidth. A two-stage architecture is designed, in which the primary subsystem consists of suspended PDMS beams characterized by a low Young’s modulus, and the secondary system consists of zigzag silicon beams. We also propose a PDMS lift-off process to fabricate the suspended flexible beams and the compatible microfabrication method shows high yield and good repeatability. The fabricated MEMS energy harvester can operate at ultralow resonant frequencies of 3 and 23 Hz, with an NPD index of 1.73 μW/cm3/g2 @ 3 Hz. The factors underlying output power degradation in the low-frequency range and potential enhancement strategies are discussed. This work offers new insights into achieving MEMS-scale energy harvesting with ultralow frequency response.

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.

Analysis of Wind-Induced Vibrations on HVTL Conductors Using Wireless Sensors.

In a world accelerating the energy transition towards renewable sources, high voltage transmission lines represent strategic infrastructure for power delivery. Being slender and low-damped structures, HVTL conductors are affected by wind-induced vibrations that can lead to severe fatigue issues in conductors and other components. Vibration monitoring could represent a key activity to assess the safety level of the line and perform condition-based maintenance activities. This work proposes an innovative approach based on the knowledge of the physical phenomena and smart technological devices. A wireless monitoring system based on MEMS accelerometers and energy harvesting techniques has been designed to measure the fymax parameter in the field, which represents a fatigue indicator useful to identify the different wind-induced phenomena and assess the conductors' strain level. A field test on a Canadian transmission line was used in the check of the efficiency of the system and collection of significant data. Vibrations due to vortex shedding were identified with a maximum value of fymax = 50 m/s, while subspan oscillation and galloping were not observed. We show the novel method can detect the different wind-induced phenomena and pave the way to the development of suitable software able to compute a conductor's residual fatigue life.

Fully Integrated High-Performance MEMS Energy Harvester for Mechanical and Contactless Magnetic Excitation in Resonance and at Low Frequencies.

Energy harvesting and storage is highly demanded to enhance the lifetime of autonomous systems, such as IoT sensor nodes, avoiding costly and time-consuming battery replacement. However, cost efficient and small-scale energy harvesting systems with reasonable power output are still subjects of current development. In this work, we present a mechanically and magnetically excitable MEMS vibrational piezoelectric energy harvester featuring wafer-level integrated rare-earth micromagnets. The latter enable harvesting of energy efficiently both in resonance and from low-g, low-frequency mechanical energy sources. Under rotational magnetic excitation at frequencies below 50 Hz, RMS power output up to 74.11 µW is demonstrated in frequency up-conversion. Magnetic excitation in resonance results in open-circuit voltages > 9 V and RMS power output up to 139.39 µW. For purely mechanical excitation, the powder-based integration process allows the realization of high-density and thus compact proof masses in the cantilever design. Accordingly, the device achieves 24.75 µW power output under mechanical excitation of 0.75 g at resonance. The ability to load a capacitance of 2.8 µF at 2.5 V within 30 s is demonstrated, facilitating a custom design low-power ASIC.

Piezoelectric MEMS Energy Harvester from Airflow at Low Flow Velocities

Piezoelectric MEMS Energy Harvester from Airflow at Low Flow Velocities

Hetero Integration of Ferromagnetic NdFeB and Piezoelectric PZT for Vibratory MEMS Energy Harvesting Devices

Hetero Integration of Ferromagnetic NdFeB and Piezoelectric PZT for Vibratory MEMS Energy Harvesting Devices

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.

Self-Packaged, Flexible, Bendable MEMS Sensors and Energy Harvesters

Desire to integrate electronic devices more closely into the everyday life of the consumer led to the emergence of flexible devices, which can conform to any shape surface. These flexible devices are lighter, thinner, and more resilient than their rigid counterparts. Since consumers these days are heavily concerned about the visual look of any product along with its technological features, the flexible devices also pave the way for innovation and creativity from the aesthetic point of view. As more and more electronics including wearable devices and displays are shifting towards the flexible regime, their basic components like sensors and integrated circuits are also required to be flexible and conformal. This paper reviews the development and evolution of several types of flexible MEMS sensors, accelerometers, and energy harvesters from the design, fabrication, and performance perspective.

SIMULATION AND ANALYSIS OF DIFFERENT PIEZOELECTRIC MATERIALS IN MEMS CANTILEVER FOR ENERGY HARVESTING

MEMS Energy Harvesting(EH) devices are excepted to grow in the upcoming years, due to the increasing aspects of MEMS EH devices in vast applications. In Recent advancements in energy harvesting (EH) technologies wireless sensor devices play a vital role to extend their lifetime readily available in natural resources. In this paper the design of MEMS Cantilever at low frequency (100Hz) with different piezoelectric materials Gallium Arsenide (GaAs), Lead Zirconate Titanate (PZT-8), Tellurium Dioxide (TeO2), Zinc oxide (ZnO) is simulated and performance with different materials are compared. The results are analyzed with various parameters such as electric potential voltage, von mises stress, displacement. The paper discusses the suitability of the piezoelectric material for MEMS fully cochlear implantable sensor application.

DRIE Si Nanowire Arrays Supported Nano-Carbon Film for Deriving High Specific Energy Supercapacitors On-Chip

Supercapacitor is a promising solution to storage of pulsed energy generated by MEMS energy harvesting systems, relying on its faster charging/discharging capability than secondary battery. To improve the energy density of on-chip supercapacitor which shows potential for integration with MEMS devices, in this paper we first present a successful electrode design for high specific energy pseudo-supercapacitors on the basis of deep reactive ion etched Si nanowire array supported nano-carbon matrix. Widely used pseudo-capacitive manganese oxide active material is facilely deposited into the conductive nano-carbon matrix by a chemical bath deposition. The derived electrode exhibits a remarkable capacitance increase (around 4.5x enhancement) compared with the nano-carbon matrix benefiting from the contribution of pseudo-capacitive manganese oxide. Assembled sandwich prototype on-chip supercapacitors with a symmetric configuration offer a high specific capacitance of 741.6 mF cm−2 when discharged at 1 mA cm−2, and the energy density can attain as high as 51.5 μWh cm−2. The achieved high specific energy makes such on-chip supercapacitors attractive in the field of energy collection when cooperated with micro-or nano-energy generators.

Implementation of Dual-Nonlinearity Mechanism for Bandwidth Extension of MEMS Multi-Modal Energy Harvester

This paper presents a planar architecture implementing dual-nonlinearity mechanism for broadening bandwidth of a two-degree-of-freedom MEMS energy harvester. The proposed device consists of an electromagnetic-based inner resonator for power generation, and an outer resonator for accessory frequency tuning. In comparison with conventional 2DOF configuration, different high-order nonlinearity is subjected to the first two resonances by nonlinear springs incorporated into the inner and outer resonator, respectively, achieving double hardening responses with increased bandwidth at elevated excitation. Moreover, independent tuning of the resonant frequency and working bandwidth of both resonances could be achieved through concordant control of inner and outer nonlinear resonator, and with further adjust of mass and frequency ratio, the low-efficiency power generation range separating adjacent resonances could be effectively reduced. It's numerically shown that with proper nonlinearity at both oscillation stages, the approximate convergence of two nonlinear resonances with broadband and narrow low-efficiency range could be achieved following the mass ratio of μ <; 0.07 and linear frequency ratio of 0.7 <; α <; 1 between inner and outer stage. At acceleration of 1 g, test result further confirms that under dual-nonlinearity with nonlinearity ratio of 0.5, a continuous energy harvesting spectrum covering two nonlinear responses is realized with mass ratio of 0.02 and frequency ratio of 1, showing 3-dB bandwidth of 65 Hz. Power output of 127.7 μW and normalized power density of 1064 μWcm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> g <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> are achieved with the optimum load resistance of 37.5 Ω. This mechanism could be further applied to multi-DOF VEH for ultra-wide bandwidth of energy harvesting. [2020-0231]