Real Time Monitoring of Calcium Oxalate Precipitation Reaction by Using Corrosion Resistant Magnetoelastic Resonance Sensors

Real-Time Monitoring of Breath Biomarkers with A Magnetoelastic Contactless Gas Sensor: A Proof of Concept

In the quest for effective gas sensors for breath analysis, magnetoelastic resonance-based gas sensors (MEGSs) are remarkable candidates. Thanks to their intrinsic contactless operation, they can be used as non-invasive and portable devices. However, traditional monitoring techniques are bound to slow detection, which hinders their application to fast bio-related reactions. Here we present a method for real-time monitoring of the resonance frequency, with a proof of concept for real-time monitoring of gaseous biomarkers based on resonance frequency. This method was validated with a MEGS based on a Metglass 2826 MB microribbon with a polyvinylpyrrolidone (PVP) nanofiber electrospun functionalization. The device provided a low-noise (RMS = 1.7 Hz), fast (<2 min), and highly reproducible response to humidity (Δf = 46−182 Hz for 17−95% RH), ammonia (Δf = 112 Hz for 40 ppm), and acetone (Δf = 44 Hz for 40 ppm). These analytes are highly important in biomedical applications, particularly ammonia and acetone, which are biomarkers related to diseases such as diabetes. Furthermore, the capability of distinguishing between breath and regular air was demonstrated with real breath measurements. The sensor also exhibited strong resistance to benzene, a common gaseous interferent in breath analysis.

A Nonlinear Magnetoelastic Energy Model and Its Application in Domain Wall Velocity Prediction

In this letter, we propose a nonlinear Magnetoelastic Energy (ME) with a material parameter related to electron interactions. An attenuating term is contained in the formula of the proposed nonlinear ME, which can predict the variation in the anisotropic magneto-crystalline constants induced by external stress more accurately than the classical linear ME. The domain wall velocity under stress and magnetic field can be predicted accurately based on the nonlinear ME. The proposed nonlinear ME model is concise and easy to use. It is important in sensor analysis and production, magneto-acoustic coupling motivation, magnetoelastic excitation, etc.

Magnetoelastic Resonance Sensors: Principles, Applications, and Perspectives

Magnetoelastic resonators are gaining attention as an incredibly versatile and sensitive transduction platform for the detection of varied physical, chemical, and biological parameters. These sensors, based on the coupling effect between mechanical and magnetic properties of ME platforms, stand out in comparison to alternative technologies due to their low cost and wireless detection capability. Several parameters have been optimized over the years to improve their performance, such as their composition, surface functionalization, or shape geometry. In this review, the working principles, recent advances, and future perspectives of magnetoelastic resonance transducers are introduced, highlighting their potentials as a versatile platform for sensing applications. First, the fundamental principles governing the magnetoelastic resonators performance are introduced as well as the most common magnetoelastic materials and their main fabrication methods are described. Second, the versatility and technical feasibility of magnetoelastic resonators for biological, chemical, and physical sensing are highlighted and the most recent results and functionalization processes are summarized. Finally, the forefront advances to further improve the performance of magnetoelastic resonators for sensing applications have been identified.

Magnetoelastic Sensor Optimization for Improving Mass Monitoring

Magnetoelastic sensors, typically made of magnetostrictive and magnetically-soft materials, can be fabricated from commercially available materials into a variety of shapes and sizes for their intended applications. Since these sensors are wirelessly interrogated via magnetic fields, they are good candidates for use in both research and industry, where detection of environmental parameters in closed and controlled systems is necessary. Common applications for these sensors include the investigation of physical, chemical, and biological parameters based on changes in mass loading at the sensor surface which affect the sensor’s behavior at resonance. To improve the performance of these sensors, optimization of sensor geometry, size, and detection conditions are critical to increasing their mass sensitivity and detectible range. This work focuses on investigating how the geometry of the sensor influences its resonance spectrum, including the sensor’s shape, size, and aspect ratio. In addition to these factors, heterogeneity in resonance magnitude was mapped for the sensor surface and the effect of the magnetic bias field strength on the resonance spectrum was investigated. Analysis of the results indicates that the shape of the sensor has a strong influence on the emergent resonant modes. Reducing the size of the sensor decreased the sensor’s magnitude of resonance. The aspect ratio of the sensor, along with the bias field strength, was also observed to affect the magnitude of the signal; over or under biasing and aspect ratio extremes were observed to decrease the magnitude of resonance, indicating that these parameters can be optimized for a given shape and size of magnetoelastic sensor.

Improved Determination of Q Quality Factor and Resonance Frequency in Sensors Based on the Magnetoelastic Resonance Through the Fitting to Analytical Expressions

The resonance quality factor Q is a key parameter that describes the performance of magnetoelastic sensors. Its value can be easily quantified from the width and the peak position of the resonance curve but, when the resonance signals are small, for instance when a lot of damping is present (low quality factor), this and other simple methods to determine this parameter are highly inaccurate. In these cases, numerical fittings of the resonance curves allow to accurately obtain the value of the quality factor. We present a study of the use of different expressions to numerically fit the resonance curves of a magnetoelastic sensor that is designed to monitor the precipitation reaction of calcium oxalate. The study compares the performance of both fittings and the equivalence of the parameters obtained in each of them. Through these numerical fittings, the evolution of the different parameters that define the resonance curve of these sensors is studied, and their accuracy in determining the quality factor is compared.

Magnetoimpedance and Stress-Impedance Effects in Amorphous CoFeSiB Ribbons at Elevated Temperatures

The temperature dependencies of magnetoimpedance (MI) and stress impedance (SI) were analyzed both in the as-quenched soft magnetic Co_68.5Fe₄Si₁₅B_12.5 ribbons and after their heat treatment at 425 K for 8 h. It was found that MI shows weak changes under the influence of mechanical stresses in the temperature range of 295–325 K and SI does not exceed 10%. At higher temperatures, the MI changes significantly under the influence of mechanical stresses, and SI variations reach 30%. Changes in the magnetoelastic properties for the different temperatures were taken into consideration for the discussion of the observed MI and SI responses. The solutions for the problem of thermal stability of the magnetic sensors working on the principles of MI or SI were discussed taking into account the joint contributions of the temperature and the applied mechanical stresses.