In this paper, we introduce a novel design of a metamaterial unit cell absorber, which is based on a metal/insulator/metal sandwich structure. The design is subjected to comprehensive finite element method computational analysis to ensure accurate and reliable results. The proposed metamaterial sandwich structure demonstrates exceptional absorption performance, achieving a nearly perfect absorption rate of 99.996% at the resonance infrared frequency of 39.8 THz. To provide a detailed theoretical explanation of nearly perfect absorption, we employ the effective medium theory, impedance matching, and field distribution analysis. Additionally, we have optimized the structural parameters of the sensor to maximize its absorption peak. This includes optimizing the thickness of the gold (Au) layer (from 0.03 to 0.28 μm), the distance between the L shape corners (from 0.60 to 0.90 μm), and the thickness of SiC dielectric spacer (from 0.20 to 0.45 μm). Furthermore, we showcase the remarkable sensitivity of the proposed metamaterial unit cell in detecting subtle changes in the refractive index through the implementation of a sensing medium setup in our model. Remarkably, we achieve a frequency shift sensitivity of 3.74 THz/RIU, along with a quality factor of 10.33, for a wide range of refractive indices (1.0–2.0). Moreover, for cancer detection, we attain a sensitivity of 3.5 THz/RIU. These findings highlight the exceptional performance of our approach in accurately detecting changes in refractive index, making it a promising candidate for various sensing applications. The novelty of our work lies in the design of a metamaterial unit cell structure. This configuration exhibits several noteworthy features, including wide incident angle ( θ ) coverage up to 60°, polarization insensitivity, exceptional frequency shift sensitivity, high absorption peaks across a wide range of refractive indices, and the ability to distinguish cancer cells from healthy ones.

Recent years have seen the development of spintronic devices and their applications in biomedical areas. Spintronic devices rely on detecting or manipulating a magnetic field, a field to which biological matter is relatively transparent. The recent use of spintronic devices in biomedical areas has included diagnosing diseases such as cancer and cirrhosis, genotyping DNA, point-of-care devices, and flexible electronics. Up to date, most of the spintronic devices in biomedical applications fall into three mainstream types: anisotropic, giant, and tunneling magnetoresistance devices. Each of these has its advantages and drawbacks, which are explored and discussed in this article. The advent of spintronics gives us a new low-power, low-cost, ease-of-manufacture alternative to standard CMOS sensors. The sensitivity of spintronic biosensors has been progressing steadily, expected to increase tremendously in the next few years.

Since its first report in 2006, magnetic particle spectroscopy (MPS)-based biosensors have flourished over the past decade. Currently, MPS are used for a wide range of applications, such as disease diagnosis, foodborne pathogen detection, etc. In this work, different MPS platforms, such as dual-frequency and mono-frequency driving field designs, were reviewed. MPS combined with multi-functional magnetic nanoparticles (MNPs) have been extensively reported as a versatile platform for the detection of a long list of biomarkers. The surface-functionalized MNPs serve as nanoprobes that specifically bind and label target analytes from liquid samples. Herein, an analysis of the theories and mechanisms that underlie different MPS platforms, which enable the implementation of bioassays based on either volume or surface, was carried out. Furthermore, this review draws attention to some significant MPS platform applications in the biomedical and biological fields. In recent years, different kinds of MPS point-of-care (POC) devices have been reported independently by several groups in the world. Due to the high detection sensitivity, simple assay procedures and low cost per run, the MPS POC devices are expected to become more widespread in the future. In addition, the growth of telemedicine and remote monitoring has created a greater demand for POC devices, as patients are able to receive health assessments and obtain results from the comfort of their own homes. At the end of this review, we comment on the opportunities and challenges for POC devices as well as MPS devices regarding the intensely growing demand for rapid, affordable, high-sensitivity and user-friendly devices.

Magnetic particle spectroscopy (MPS) is an emerging biosensing technique that detects target analytes by exploiting the dynamic magnetic responses of magnetic nanoparticles (MNPs). Due to the ease of synthesis and surface chemical functionalization of MNPs, MPS-based bioassays have gained popularity around the globe. One limiting factor for MPS-based assay is the ability to detect multiple analytes simultaneously in a single run, namely, multiplexed bioassay. Several groups have reported the realization of multiplexed bioassays on surface-based MPS platforms by spatially separating reaction areas by using the unique magnetic responses of different MNPs. In this work, we systematically study the magnetization curves (M-H curves) of different types of MNPs and their relationship to the dynamic magnetic responses when subjected to AC magnetic driving fields. Due to the different structures, sizes, and magnetic properties of each kind of MNP, the resulting harmonics are unique. Thus, concurrent quantification (also called ‘colorization’) of each type of MNP in a mixture is possible by solving the harmonic matrix function. Our results show that the uniqueness of M-H response curves of selected types of MNP and the signal-to-noise ratio of the system can affect the accuracy of multiplexed, volumetric-based MPS bioassays. The reported method assumes that each type of MNPs nanoparticles does not interact, and that the magnetic response of the mixture is a linear combination of the responses of each kind of MNP. This assumption may not hold for very dense systems where inter-particle interactions become significant and may require more complex models.

Nowadays, magnetic nanoparticles (MNPs) have been extensively used in biomedical fields such as labels for magnetic biosensors, contrast agents in magnetic imaging, carriers for drug/gene delivery, and heating sources for hyperthermia, among others. They are also utilized in various industries, including data and energy storage and heterogeneous catalysis. Each application exploits one or more physicochemical properties of MNPs, including magnetic moments, magnetophoretic forces, nonlinear dynamic magnetic responses, magnetic hysteresis loops, and others. It is generally accepted that the static and dynamic magnetizations of MNPs can vary due to factors such as material composition, crystal structure, defects, size, shape of the MNP, as well as external conditions like the applied magnetic fields, temperature, carrier fluid, and inter-particle interactions (i.e., MNP concentrations). A subtle change in any of these factors leads to different magnetization responses. In order to optimize the MNP design and external conditions for the best performance in different applications, researchers have been striving to model the macroscopic properties of individual MNPs and MNP ensembles. In this review, we summarize several popular mathematical models that have been used to describe, explain, and predict the static and dynamic magnetization responses of MNPs. These models encompass both individual MNPs and MNP ensembles and include the Stoner-Wohlfarth model, Langevin model, zero/non-zero field Brownian and Néel relaxation models, Debye model, empirical Brownian and Néel relaxation models under AC fields, the Landau–Lifshitz–Gilbert (LLG) equation, and the stochastic Langevin equation for coupled Brownian and Néel relaxations, as well as the Fokker–Planck equations for coupled/decoupled Brownian and Néel relaxations. In addition, we provide our peers with the advantages, disadvantages, as well as suitable conditions for each model introduced in this review. The shrinking size of magnetic materials brings about a significant surface spin canting effect, resulting in higher anisotropy and lower magnetization in MNPs compared to bulk materials. Accurate prediction of static and dynamic magnetizations in MNPs Requires both precise data on their magnetic properties and an accurate mathematical model. Hence, we introduced the spin canting effect and models to estimate anisotropy and saturation magnetization in MNPs.