Microelectromechanical systems (MEMS) technology allows the integration of magnetic field sensors with electronic components, which presents important advantages such as small size, light weight, minimum power consumption, low cost, better sensitivity and high resolution. We present a discussion and review of resonant magnetic field sensors based on MEMS technology. In practice, these sensors exploit the Lorentz force in order to detect external magnetic fields through the displacement of resonant structures, which are measured with optical, capacitive, and piezoresistive sensing techniques. From these, the optical sensing presents immunity to electromagnetic interference (EMI) and reduces the read-out electronic complexity. Moreover, piezoresistive sensing requires an easy fabrication process as well as a standard packaging. A description of the operation mechanisms, advantages and drawbacks of each sensor is considered. MEMS magnetic field sensors are a potential alternative for numerous applications, including the automotive industry, military, medical, telecommunications, oceanographic, spatial, and environment science. In addition, future markets will need the development of several sensors on a single chip for measuring different parameters such as the magnetic field, pressure, temperature and acceleration.

A resonant magnetic field microsensor with a high quality factor at atmospheric pressure has been designed, fabricated and tested. This microsensor does not require vacuum packaging to operate efficiently and presents a compact and simple geometrical configuration of silicon. This geometry permits us to decrease the size of the structure and facilities its fabrication and operation. It is constructed of a seesaw plate (400 × 150 × 15 μm 3 ), two torsional beams (60 × 40 × 15 μm 3 ), four flexural beams (130 × 12 × 15 μm 3 ) and a Wheatstone bridge with four p-type piezoresistors. The resonant device exploits the Lorentz force principle and operates at its first resonant frequency (136.52 kHz). A sinusoidal excitation current of 22.0 mA with a frequency of 136.52 kHz and magnetic fields from 1 to 400 G are considered. The mechanical response of the microsensor is modeled with the finite element method (FEM). The structure of the microsensor registered a maximum von Mises stress of 53.8 MPa between the flexural and the torsional beams. Additionally, a maximum deflection (372.5 nm) is obtained at the extreme end of the plate. The proposed microsensor has the maximum magnetic sensitivity of 40.3 μV G −1 (magnetic fields <70 G), theoretical root-mean square (rms) noise voltage of 57.48 nV Hz −1/2 , theoretical resolution of 1.43 mG Hz −1/2 and power consumption less than 10.0 mW.

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We describe a simple procedure to characterize a magnetic field sensor based on microelectromechanical systems (MEMS) technology, which exploits the Lorentz force principle. This sensor is designed to detect, in future applications, the spiking activity of neurons or muscle cells. This procedure is based on the well-known capability that a magnetic MEMS device can be used to sense a small magnetic flux density. In this work, an electronic neuron (FitzHugh-Nagumo) is used to generate controlled spike-like magnetic fields. We show that the magnetic flux density generated by the hardware of this neuron can be detected with a new MEMS magnetic field sensor. This microdevice has a compact resonant structure (700 × 600 × 5 μm) integrated by an array of silicon beams and p-type piezoresistive sensing elements, which need an easy fabrication process. The proposed microsensor has a resolution of 80 nT, a sensitivity of 1.2 V.T(-1), a resonant frequency of 13.87 kHz, low power consumption (2.05 mW), quality factor of 93 at atmospheric pressure, and requires a simple signal processing circuit. The importance of our study is twofold. First, because the artificial neuron can generate well-controlled magnetic flux density, we suggest it could be used to analyze the resolution and performance of different magnetic field sensors intended for neurobiological applications. Second, the introduced MEMS magnetic field sensor may be used as a prototype to develop new high-resolution biomedical microdevices to sense magnetic fields from cardiac tissue, nerves, spinal cord, or the brain.

Magnetic fields generated by the brain or the heart are very useful in clinical diagnostics. Therefore, magnetic signals produced by other organs are also of considerable interest. Here we show first evidence that thoracic muscles can produce a strong magnetic flux density during respiratory activity, that we name respiratory magnetogram. We used a small magnetometer based on microelectromechanical systems (MEMS), which was positioned inside the open thoracic cage of anaesthetized and ventilated rats. With this new MEMS sensor of about 20 nT resolution, we recorded a strong and rhythmic respiratory magnetogram of about 600 nT.

Natural sources of green energy include sunshine, water, biomass, geothermal heat, and wind. These energies are alternate forms of electrical energy that do not rely on fossil fuels. Green energy is environmentally benign, as it avoids the generation of greenhouse gases and pollutants. Various systems and equipment have been utilized to gather natural energy. However, most technologies need a huge amount of infrastructure and expensive equipment in order to power electronic gadgets, smart sensors, and wearable devices. Nanogenerators have recently emerged as an alternative technique for collecting energy from both natural and artificial sources, with significant benefits such as light weight, low-cost production, simple operation, easy signal processing, and low-cost materials. These nanogenerators might power electronic components and wearable devices used in a variety of applications such as telecommunications, the medical sector, the military and automotive industries, and internet of things (IoT) devices. We describe new research on the performance of nanogenerators employing several green energy acquisition processes such as piezoelectric, electromagnetic, thermoelectric, and triboelectric. Furthermore, the materials, applications, challenges, and future prospects of several nanogenerators are discussed.

Micro-and nanoresonator sensors have important applications such as in chemical and biological sensing, environmental control, monitoring of viscosity and magnetic fields, and inertial forces detection. However, most of these resonators are designed as complex structures that complicate the estimation of their resonant frequencies (generally of the bending or torsional mode). In this paper, we present an analytical model to estimate the resonant frequency of the first bending mode of micro-and nanoresonators based on a beam system under different load types. This system is constructed of beams with different cross sections joined through a series-parallel arrangement. The analytical model is derived using the Rayleigh and Macaulay methods, as well as the Euler-Bernoulli beam theory. In addition, we determined the deflection function of the beam system, which can be used to establish its bending structural response under several load types. We applied the model to both a silicon microresonator (with a thickness of 5 m) for an experimental magnetic field sensor developed in our laboratory and for a polycrystalline silicon nanoresonator (with a thickness of 160 nm) of a mass sensor reported in the literature. The results of our analytical model have a comparable agreement with those obtained from the finite-element models (FEMs) and with the experimental measurements. Our analytical model can be useful in the mechanical design of microand nanoresonators with complex structural configurations.

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