Search Results (36)

Despite the success of artificial neural networks in solving numerous tasks, they face significant challenges, including difficulties in online adaptation and rapidly increasing energy consumption. As a biologically plausible alternative, spiking neural networks offer promising capabilities for efficient cognitive computing. Recently, a three-element spiking neuron model consisting of a threshold selector, a tunnel diode, and a capacitor was proposed. In this work, we experimentally validate this model using a threshold selector hardware emulator and demonstrate its dynamical equivalence to the biologically plausible Izhikevich neuron model. To evaluate the novel neuron’s applicability for cognitive computing, we implement a liquid state machine (LSM) reservoir architecture with spatially dependent random topology for synaptic weight distribution. Our simulations on the MNIST and Fashion-MNIST benchmarks demonstrate competitive classification accuracy (97.9% and 89.5%, respectively) while offering estimated energy efficiency and processing speed enhancements compared to existing FPGA-based and memristor-based spiking reservoir implementations. The developed reservoir is feasible for processing neuromorphic sensors output, including visual perception tasks. Full article

This study details the design and development of an ultra-sensitive microwave sensor for non-invasive blood glucose monitoring, achieved by analyzing variations in the response of a split-ring resonator (SRR) through advanced engineering methodologies. There were three design phases in the development process. In the first phase, a standard SRR design was used. It had a resonant frequency of 2.975 GHz in S₂₁ and a sensitivity of only 0.0032 dB/(mg/dL). In the second phase, an interdigital capacitor (IDC) was added to the SRR structure. This made it work better and made it more sensitive, with a sensitivity of 0.015 dB/(mg/dL) at 4.1 GHz. The third phase was to use a fourth-order Moore fractal geometry to improve the resonance properties of the design a lot. From the obtained S₁₁, the maximum sensitivity was 0.042 dB/(mg/dL), which was a huge improvement in sensing efficiency compared to earlier designs. Several resonant frequencies were recorded between 4.84 and 7.56 GHz. The addition of the fractal structure made the electromagnetic field stronger in the resonant space and made the waves interact more with small changes in the biological medium, all without changing the sensor’s size (80 mm × 40 mm). These results show that fractal architecture is a promising way to create non-invasive, accurate, and easily integrated sensors in biological systems that can continuously measure blood glucose levels. Full article

A simplified kinetic model for the quantitative analysis of a potentiometric, pH-based urea biosensor is presented. The device was an electrolyte–insulator–semiconductor capacitor (EISCAP) with a pH-sensitive Ta₂O₅ gate functionalized by a polyallylamine hydrochloride (PAH)/urease bilayer. Within the steady-state approximation, the kinetic equations yielded an implicit algebraic relation linking the bulk urea concentration to the local pH at the sensor surface. Numerical solution of this equation, combined with a fitting routine, provides the apparent Michaelis–Menten constant ($K_M$) and the normalized maximum reaction rate (${\overline{k}}_V$). Validation against the literature data confirmed the reliability of the approach. Experimental results were then analyzed in both phosphate buffer (PBS) and artificial urine (AU), covering urea concentrations of 0.1–50 mM. The fitted parameters showed comparable $K_M$ values of 10.9 mM (PBS) and 32.4 mM (AU), but strongly different ${\overline{k}}_V$ values: $2.2\times {10}^{-4}$ (PBS) versus $8.6\times {10}^{-7}$ (AU). The three-order reduction in AU was attributed to the inhibitory effects inherent to complex biological fluids. These findings highlight the importance of the model-based quantitative analysis of EISCAP biosensors, enabling the accurate characterization of immobilized enzyme layers and guiding optimization for applications in realistic sample matrices. Full article

Biomaterials have assumed a decisive role in modern medicine by enabling significant advancements in medical care practices. These materials are designed to interact with biological systems, offering substantial solutions for various medical needs. In this research, bioceramic materials consisting of a bioactive hydroxyapatite-based matrix with Ti nanoparticles were processed as promising materials. These bioceramics were obtained using mechanical milling, uniaxial pressing, and sintering as powder processing techniques. This study evaluates the effect of Ti additions on the structural, electrochemical, and mechanical properties of the hydroxyapatite ceramic material. Titanium additions were about 1, 2 and 3 wt%. The experimental results demonstrate that the biocomposite’s structure has two hexagonal phases: one corresponding to the hydroxyapatite matrix and the other to the Ti as a reinforced phase. The biomaterials’ microstructure is completely fine and homogeneous. The biomaterial reinforced with 1 wt. % Ti exhibits the best mechanical behavior. In this context, electrochemical tests reveal that bioceramics can achieve stability through an ion adsorption mechanism when exposed to a physiological electrolyte. Bioceramics, particularly those containing 1%Ti, develop their bioactivity through the formation of a high-density hydroxide film during a porous sealing process at potentials around −782.71 mV, with an ionic charge transfer of 0.43 × 10⁻⁹ A/cm². Finally, this biofilm behaves as a capacitor Cc = 0.18 nF/cm², resulting in lower ionic charge transfer resistance (Rct = 1.526 × 106 Ω-cm²) at the interface. This mechanism promotes the material’s biocompatibility for bone integration as an implant material. Full article

This work presents the design, fabrication, and rigorous validation of a flexible, wireless, capacitive pressure sensor for the full-range continuous monitoring of ventricular pressure. The proposed system consists of an implantable set and an external readout device; both modules were designed to form an RCL resonant circuit for passive, wireless pressure sensing and signal retrieving. Using surface micromachining and flexible electronics techniques, a two-variable capacitor array and a dual-layer planar coil were integrated into a flexible ergonomic substrate, avoiding hybrid-like connections in the implantable set. The proposed arrangement (capacitor array and dual-layer coil) allows us to optimize the operation pressure range and sensing distance. The use of polyimide as both the flexible substrate and the passivation material is a key feature, ensuring a biocompatible, implantable set that is mechanically flexible and can be folded to a compact size to achieve minimally invasive implantation. An external readout device has also been developed using a discrete printed circuit board (PCB) approach to support pressure measurements. The pressure responsivity of the sensor was validated to the laboratory level using a controlled pressure chamber. The results obtained show that the capacitance value of the sensor changed from 5.68 pF to 33.26 pF as the pressure varied from 0 to 300 mmHg. Correspondingly, the resonance frequency of the implantable set shifted from 12.75 MHz to 5.27 MHz. The sensitivity of the capacitive sensor was approximately 0.58 pF/mmHg and the typical response time was 220 ms. The wireless system performance was evaluated in both air and synthetic biological tissue using a Maxwell–Wien bridge circuit. The results showed a sensing distance longer than 3.5 cm, even under moderate misalignment conditions (up to 1.5 cm). The output voltage was successfully measured, ranging from 502.54 mV to 538.29 mV, throughout the full pressure range, with a measurement error of ±2.2 mV. Full article

The recent commercial availability of stacked dielectric elastomer actuators (SDEAs) has unlocked new opportunities for their application as “artificial skeletal muscles” in rehabilitation robots and powered exoskeletons. Composed of multiple layers of thin, elastic capacitors, these actuators present a lightweight, soft, and acoustically noiseless alternative to traditional DC motor actuators commonly used in rehabilitation robotics, thereby enhancing the natural feel of such systems. Building on our previous research, this study aimed to evaluate the most recent version of commercial SDEAs to assess their potential for mechanizing rehabilitation robots. We quantified the stress and strain behavior and stiffness of these actuators in both single and 1 × 3 configurations (with three SDEAs connected in series). The actuators demonstrated the capability to generate up to 25 N of force and 115 KPa, a value surpassing human biceps, with a longitudinal strain measured at about 11%. The significant increase in force generation from 10 N in the previous version to 25 N and displacement from 3.3% to 11% substantially enhances the applicability of this actuator in rehabilitation robotics. SDEAs’ high force generation capability, combined with their strain and stress characteristics comparable to that of human biological muscles, make them ideal alternative actuators for biomimetic robots and applications where actuators must operate in the vicinity of the human body. Full article

This study introduces an innovative two-range, 12-stage Marx pulse generator employing thyristor switches designed specifically for the electroporation of biological cells. The generator consists of two module capacitors of different capacitances (1 μF and 0.25 μF), which enable the generation of electrical pulses with different durations and amplitudes of up to 25 kV. Safety aspects, including overcurrent and overvoltage protection mechanisms, are implemented in both the software and the hardware. In the experimental section, the tests of the Marx generator with resistive load are described in detail, and the results for the voltage fluctuations, pulse duration, and output characteristics of the generator are presented. The advantages of the design, including the high output voltage, the wide range of repetition rates, and the flexibility of the pulse parameters, are emphasized. Additionally, the research showcases the utilization of the devised generator for industrial purposes. Hence, an investigation into the efficiency of protein extraction from microalgae (Chlorella vulgaris) and the impacts of pulsed electric fields (PEFs) on the structural characteristics of casein micelles (CSMs) was chosen as an illustrative example. The obtained results provide valuable insights into the application of PEF in food processing and biotechnology and underline the potential of the developed generator for sustainable and environmentally friendly practices. Full article

In recent years, renewable and sustainable triboelectric nanogenerators have attracted attention due to their high energy conversion rate, and enhancing their functionality further contributes to their applicability across various fields. A pH-sensitive triboelectric nanogenerator (pH-TENG) has been prepared by electrostatic spinning technology, with anthocyanin as the pH indicator and environmentally friendly polyvinyl alcohol (PVA) as the substrate. Among many friction-negative materials, the pH-TENG exhibits the best combination with fluorinated ethylene propylene (FEP) and yields an open-circuit voltage of 62 V, a short-circuit current of 370 nA, and a transferred charge of 21.8 nC. At a frequency of 3 Hz, it can charge a 4.7 μF capacitor to 2 V within 45 s, effectively powering a thermometer. Furthermore, the presence of anthocyanin does not affect the pH-TENG’s power generation performance and enables the monitoring of a wide range of environmental pH changes, with an ΔE change of 28.8 ± 7.6. Therefore, pH-TENG prepared with environmentally friendly materials can bring new available materials to the biological and medical fields. Full article

Since different quantities of white blood cells (WBCs) in solution possess an adaptive osmotic pressure of cells, the WBCs themselves and in solution have similar concentrations, resulting in them having similar dielectric properties. Therefore, a microwave sensor could have difficulty in sensing the quantity variation when WBCs are in solution. This paper presents a highly sensitive, linear permittivity-inspired microwave biosensor for WBCs, counting through the evaporation method. Such a measurement method is proposed to record measurements after the cell solution is dripped onto the chip and is completely evaporated naturally. The proposed biosensor consists of an air-bridged asymmetric differential inductor and a centrally located circular fork-finger capacitor fabricated on a GaAs substrate using integrated passive fabrication technology. It is optimized to feature a larger sensitive area and improved Q-factor, which increases the effective area of interaction between cells and the electromagnetic field and facilitates the detection of their changes in number. The sensing relies on the dielectric properties of the cells and the change in the dielectric constant for different concentrations, and the change in resonance properties, which mainly represents the frequency shift, corresponds to the macroscopic change in the concentration of the cells. The microwave biosensors are used to measure biological samples with concentrations ranging from 0.25 × 10⁶ to 8 × 10⁶ cells per mL in a temperature (26.00 ± 0.40 °C) and humidity (54.40 ± 3.90 RH%) environment. The measurement results show a high sensitivity of 25.06 Hz/cells·mL⁻¹ with a highly linear response of r² = 0.99748. In addition, a mathematical modeling of individual cells in suspension is performed to estimate the dielectric constant of individual cells and further explain the working mechanism of the proposed microwave biosensor. Full article

The primary objective of neuromorphic electronic devices is the implementation of neural networks that replicate the memory and learning functions of biological synapses. To exploit the advantages of electrolyte gate synaptic transistors operating like biological synapses, we engineered electric double-layer transistors (EDLTs) using phosphorus-doped silicate glass (PSG). To investigate the effects of phosphorus on the EDL and synaptic behavior, undoped silicate spin-on-glass-based transistors were fabricated as a control group. Initially, we measured the frequency-dependent capacitance and double-sweep transfer curves for the metal-oxide-semiconductor (MOS) capacitors and MOS field-effect transistors. Subsequently, we analyzed the excitatory post-synaptic currents (EPSCs), including pre-synaptic single spikes, double spikes, and frequency variations. The capacitance and hysteresis window characteristics of the PSG for synaptic operations were verified. To assess the specific synaptic operational characteristics of PSG-EDLTs, we examined EPSCs based on the spike number and established synaptic weights in potentiation and depression (P/D) in relation to pre-synaptic variables. Normalizing the P/D results, we extracted the parameter values for the nonlinearity factor, asymmetric ratio, and dynamic range based on the pre-synaptic variables, revealing the trade-off relationships among them. Finally, based on artificial neural network simulations, we verified the high-recognition rate of PSG-EDLTs for handwritten digits. These results suggest that phosphorus-based EDLTs are beneficial for implementing high-performance artificial synaptic hardware. Full article

Double-layer capacitance (C_dl) is essential for chemical and biological sensors and capacitor applications. The correct formula for C_dl is a controversial subject for practically useful graphene interfaces with water, aqueous solutions, and other liquids. We have developed a model of C_dl, considering the capacitance of a charge accumulation layer (C_ca) and capacitance (C_e) of a capacitance-limiting edge region with negligible electric susceptibility and conductivity between this layer and the capacitor electrode. These capacitances are connected in series, and C_dl can be obtained from 1/C_dl = 1/C_ca + 1/C_e. In the case of aqueous graphene interfaces, this model predicts that C_dl is significantly affected by C_e. We have studied the graphene/water interface capacitance by low-frequency impedance spectroscopy. Comparison of the model predictions with the experimental results implies that the distance from charge carriers in graphene to the nearest molecular charges at the interface can be ~(0.05–0.1)nm and is about a typical length of the carbon-hydrogen bond. Generalization of this model, assuming that such an edge region between a conducting electrode and a charge accumulating region is intrinsic for a broad range of non-faradaic capacitors and cannot be thinner than an atomic size of ~0.05 nm, predicts a general capacitance upper limit of ~18 μF/cm². Full article

Spiking neural networks (SNNs) are quickly gaining traction as a viable alternative to deep neural networks (DNNs). Compared to DNNs, SNNs are computationally more powerful and energy efficient. The design metrics (synaptic weights, membrane threshold, etc.) chosen for such SNN architectures are often proprietary and constitute confidential intellectual property (IP). Our study indicates that SNN architectures implemented using conventional analog neurons are susceptible to side channel attack (SCA). Unlike the conventional SCAs that are aimed to leak private keys from cryptographic implementations, SCANN $(\underline{\mathrm{SCA}}$ of spiking $\underline{\mathrm{n}}$eural $\underline{\mathrm{n}}$etworks) can reveal the sensitive IP implemented within the SNN through the power side channel. We demonstrate eight unique SCANN attacks by taking a common analog neuron (axon hillock neuron) as the test case. We chose this particular model since it is biologically plausible and is hence a good fit for SNNs. Simulation results indicate that different synaptic weights, neurons/layer, neuron membrane thresholds, and neuron capacitor sizes (which are the building blocks of SNN) yield distinct power and spike timing signatures, making them vulnerable to SCA. We show that an adversary can use templates (using foundry-calibrated simulations or fabricating known design parameters in test chips) and analysis to identify the specifications of the implemented SNN. Full article

Resistors with memory (memristors), inductors with memory (meminductors) and capacitors with memory (memcapacitors) play different roles in novel computing architectures. We found that a coil with a magnetic core is an inductor with memory (meminductor) in terms of its inductance L(q) being a function of charge q. The history of the current passing through the coil is remembered by the magnetization inside the magnetic core. Such a meminductor can play a unique role (that cannot be played by a memristor) in neuromorphic computing, deep learning and brain-inspired computers since the time constant (${\mathit{t}}_{\mathbf{0}}=\sqrt{\mathit{L}\mathit{C}}$) of a neuromorphic RLC circuit is jointly determined by the inductance $L$ and capacitance $C$, rather than the resistance $R$. As an experimental verification, this newly invented meminductor was used to reproduce the observed biological behavior of amoebae (the memorizing, timing and anticipating mechanisms). In conclusion, a beyond-memristor computing paradigm is theoretically sensible and experimentally practical. Full article

Recently, research on artificial neuron circuits imitating biological systems has been actively studied. The neuron circuit can implement an artificial neural network (ANN) capable of low-power parallel processing by configuring a biological neural network system in hardware. Conventional CMOS analog neuron circuits require many MOSFETs and membrane capacitors. Additionally, it has low energy efficiency in the first inverter stage connected to the capacitor. In this paper, we propose a low-power neuron circuit with a multi-gate feedback field effect transistor (FBFET) that can perform integration without a capacitor to solve the problem of an analog neuron circuit. The multi-gate FBFET has a low off-current due to its low operating voltage and excellent sub-threshold characteristics. We replace the n-channel MOSFET of the inverter with FBFET to suppress leakage current. FBFET devices and neuron circuits were analyzed using TACD and SPICE mixed-mode simulation. As a result, we found that the neuron circuit with multi-gate FBFET has a low subthreshold slope and can completely suppress energy consumption. We also verified the temporal and spatial integration of neuron circuits. Full article

This study proposed a biocompatible polymeric organic material-based synaptic transistor gated with a biopolymer electrolyte. A polyvinyl alcohol (PVA):chitosan (CS) biopolymer blended electrolyte with high ionic conductivity was used as an electrical double layer (EDL). It served as a gate insulator with a key function as an artificial synaptic transistor. The frequency-dependent capacitance characteristics of PVA:CS-based biopolymer EDL were evaluated using an EDL capacitor (Al/PVA: CS blended electrolyte-based EDL/Pt configuration). Consequently, the PVA:CS blended electrolyte behaved as an EDL owing to high capacitance (1.53 µF/cm²) at 100 Hz and internal mobile protonic ions. Electronic synaptic transistors fabricated using the PVA:CS blended electrolyte-based EDL membrane demonstrated basic artificial synaptic behaviors such as excitatory post-synaptic current modulation, paired-pulse facilitation, and dynamic signal-filtering functions by pre-synaptic spikes. In addition, the spike-timing-dependent plasticity was evaluated using synaptic spikes. The synaptic weight modulation was stable during repetitive spike cycles for potentiation and depression. Pattern recognition was conducted through a learning simulation for artificial neural networks (ANNs) using Modified National Institute of Standards and Technology datasheets to examine the neuromorphic computing system capability (high recognition rate of 92%). Therefore, the proposed synaptic transistor is suitable for ANNs and shows potential for biological and eco-friendly neuromorphic systems. Full article