Search Results (269)

This review explores the variety of diamond-based sensing applications, emphasizing their material properties, such as high Young’s modulus, thermal conductivity, wide bandgap, chemical stability, and radiation hardness. These diamond properties give excellent performance in mechanical, pressure, thermal, magnetic, optoelectronic, radiation, biosensing, quantum, and other applications. In vibration sensing, nano/poly/single-crystal diamond resonators operate from MHz to GHz frequencies, with high quality factor via CVD growth, diamond-on-insulator techniques, and ICP etching. Pressure sensing uses boron-doped piezoresistive, as well as capacitive and Fabry–Pérot readouts. Thermal sensing merges NV nanothermometry, single-crystal resonant thermometers, and resistive/diode sensors. Magnetic detection offers FeGa/Ti/diamond heterostructures, complementing NV. Optoelectronic applications utilize DUV photodiodes and color centers. Radiation detectors benefit from diamond’s neutron conversion capability. Biosensing leverages boron-doped diamond and hydrogen-terminated SGFETs, as well as gas targets such as NO₂/NH₃/H₂ via surface transfer doping and Pd Schottky/MIS. Imaging uses AFM/NV probes and boron-doped diamond tips. Persistent challenges, such as grain boundary losses in nanocrystalline diamond, limited diamond-on-insulator bonding yield, high temperature interface degradation, humidity-dependent gas transduction, stabilization of hydrogen termination, near-surface nitrogen-vacancy noise, and the cost of high-quality single-crystal diamond, are being addressed through interface and surface chemistry control, catalytic/dielectric stack engineering, photonic integration, and scalable chemical vapor deposition routes. These advances are enabling integrated, high-reliability diamond sensors for extreme and quantum-enhanced applications. Full article

This article presents the design of a perovskite photovoltaic (PV)-based power management system, which uses a power converter (a four-stage bootstrap charge pump) to boost the output of the solar cell and supply selectable rectified power rails to CMOS image sensor circuit blocks. A perovskite photovoltaic, also known as a perovskite solar cell (PSC) was fabricated in the laboratory. The PSC has an open-circuit voltage of 1.14 V, short-circuit current of 1.24 mA, maximum power of 0.88 mW, and a current density of 20.68 mA/cm² at 62% fill factor. These measured forward scan parameters were closely reproduced with a solar cell simulation model. In a Cadence simulation that used 180 nm CMOS process, the power converter efficiently boosts the maximum output voltage of the PSC from 0.85 V to a rectified 3.7 V. Stage modulation and level shifting enable selectable output rails in the 1.2–3.3 V range to supply the image sensor circuit blocks. Keeping the output capacitance of the power converter much larger than the flying capacitance reduces the ripple voltage to approximately 73 µV, much smaller than the typical 1 mV in several other literatures. Through simulation, this work demonstrates the concept of directly using PSC (to be implemented on an outer ‘packaging’, not on a die) to supply CMOS image sensor power rails, in the same sense as in wearable devices and other consumer devices. This work highlights a path toward self-powered image sensors with improved conversion efficiency, compactness, and adaptability in low-light and variable operating environments. Full article

This research examines the electrochemical polymerization of 3-Methyl-4-phenylpyrrole on carbon microfibers and compares its electrode performance with similar structures utilizing Poly-pyrrole and Poly-3-Phenylpyrrole on carbon microfibers. For technological considerations, going beyond a rate of 90 mV/s for the electrochemical deposition of the 3-Methyl-4-phenylpyrrole polymer is not advisable. By examining the Nyquist diagram, it is noted that the highest phase angle, exceeding 80°, occurs for the carbon–polymer structure created at a deposition rate of 70 mV/s, displaying the most pronounced capacitive behavior. Similar results at a deposition rate of 70 mV/s regarding SEM and AFM images were noted, revealing a structure that resembles the shape of the deposited polymer granules as “droplets” with a reduced average roughness level, at under 60 nm, and achieving a layer thickness of over 0.7 μm. Considering the results from cyclic voltammetry and electrochemical impedance, it was observed that the carbon micro-fiber structure coated with 3-Methyl-4-phenylpyrrole polymer shows superior capacitive behavior when compared to similar structures using pyrrole and 3-Phenyl-pyrrole polymers. 3-Methyl-4-phenylpyrrole also showed a lower admittance value than 3-Phenyl-pyrrole, and presented the highest capacitance, leading to a maximum increase of +27.3% in relation to pyrrole, emphasizing the significance of studying this PPy derivative for energy storage applications. Full article

The biophysical characteristics of cellular membranes, particularly their electrical properties in the $\alpha$-dispersion frequency domain, offer valuable insights into cellular states and are increasingly important for cancer diagnostics through epidermal growth factor receptor (EGFR) expression analysis. However, a critical limitation in these electrical measurements is the confounding effect of morphological changes that inevitably occur during prolonged observation periods. These shape alterations significantly impact measured capacitance values, potentially masking true biological responses to epidermal growth factor (EGF) stimulation that are essential for cancer detection. In this study, we attempted to address this fundamental challenge by developing a deep learning method that establishes a direct computational relationship between cellular morphology and electrical properties. We combined optical trapping technology and capacitance measurements to generate a comprehensive dataset of HeLa cells under two different experimental conditions: (i) DPBS treatment and (ii) EGF stimulation. Our convolutional neural network (CNN) architecture accurately predicts 401-point capacitance spectra (0.1–2 kHz) from binary morphological images at low frequencies (0.1–0.8 kHz, < 10% error rate). This capability allows for the identification and subtraction of morphology-dependent components from measured capacitance changes, effectively isolating true biological responses from morphological artefacts. The model demonstrates remarkable prediction performance across diverse cell morphologies in both experimental conditions, validating the robust relationship between cellular shape and electrical characteristics. Our method significantly improves the precision and reliability of EGFR-based cancer diagnostics by providing a computational framework for a morphology-induced measurement error correction. Full article

Traditional zero-compensation techniques employed to improve sub-sampling phase-locked loop (SSPLL) stability often exacerbate spur degradation or incur excessive area overhead, rendering them unsuitable for high-resolution image sensor applications. This paper proposes a novel SSPLL based on capacitor multiplication technology. This capacitor multiplication technology employs dual charge pumps (CP1 and CP2) in a coordinated operational scheme where their charge/discharge states are inversely synchronized. The effective capacitance of the loop filter is thereby amplified without expanding the physical layout area dedicated to capacitive components. Meanwhile, the continued use of zero-compensation technology ensures the stability of the SSPLL. The proposed SSPLL is designed and verified in a 55 nm CMOS process. At a 1.2 GHz output frequency, simulation results show a spot phase noise of −131.5 dBc/Hz at 1 MHz offset, accompanied by an integrated RMS jitter of 549 fs across the 10 kHz to 40 MHz spectrum, spurs suppressed to −51.3 dB, while maintaining a power efficiency of 3.81 mW and a compact layout area of 0.064 mm². All the above results show that by introducing the novel dual-CP charge multiplication technology, the SSPLL can achieve low jitter and low power consumption performance while reducing the layout area, providing a new technical approach for its application in high-resolution image sensors. Full article

In many monitoring scenarios, repeated and operator-independent assessments are needed. Wearable ultrasound technology has the potential to continuously provide the vital information traditionally obtained from conventional ultrasound scanners, such as in fetal monitoring for high-risk pregnancies. This work is an engineering study motivated by that setting. A 144-element annular capacitive micromachined ultrasonic transducer (CMUT) is hereby proposed for 3-D ultrasound imaging. The array is characterized by its compact size and cost-effectiveness, with a geometry and low-voltage operation that make it a candidate for future wearable integration. To enhance the imaging performance, we propose the utilization of a Fermat’s spiral virtual source (VS) pattern for diverging wave transmission and conduct a performance comparison with other VS patterns and standard techniques, such as focused and plane waves. To facilitate this analysis, a simplified and versatile simulation framework, enhanced by GPU acceleration, has been developed. The validation of the simulation framework aligned closely with expected values (0.002 ≤ MAE ≤ 0.089). VSs following a Fermat’s spiral led to a balanced outcome across metrics, outperforming focused wave transmissions for this specific aperture. The proposed transducer presents imaging limitations that could be improved in future developments, but it establishes a foundational framework for the design and fabrication of cost-effective, compact 2-D transducers suitable for 3-D ultrasound imaging, with potential for future integration into wearable devices. Full article

This study investigates the influence of variable electrode positions on image reconstruction in capacitively coupled electrical impedance tomography (CC-EIT) of the human thorax. Images were reconstructed by an adversarial neural network trained on a synthetic dataset generated using a tomographic model that included a wearable elastic band with 32 electrodes attached. Dataset generation was conducted using a previously developed numerical phantom of the thorax, combined with a newly developed algorithm for random selection of electrode positions based on physical limitations resulting from the elasticity of the band and possible position inaccuracies while putting the band on the patient’s chest. The thorax phantom included the heart, lungs, aorta, and spine. Four training and four testing datasets were generated using four different levels of electrode displacement. Reconstruction was conducted using four versions of neural networks trained on the datasets, with random ellipses included and noise added to achieve an SNR of 30 dB. The quality was assessed using pixel-to-pixel metrics such as the root-mean-square error, structural similarity index, 2D correlation coefficient, and peak signal-to-noise ratio. The results showed a strong negative influence of electrode displacement on reconstruction quality when no samples with displaced electrodes were present in the training dataset. Training the network on the dataset containing samples with electrode displacement allowed us to significantly improve the quality of the reconstructed images. Introducing samples with misplaced electrodes increased neural network robustness to electrode displacement while testing. Full article

Hundred-micron-sized microdroplets are widely used in microbial culture, chemical investigations and industrial processes. The size, velocity and frequency of microdroplets significantly affect the cultivation and processing effects. The detections of droplets mainly rely on capacitance detection or imaging, but it requires expensive and complex systems for capacitance detection, and high-throughput imaging detections are challenging. In this study, four-way microfluid structure (FWMS) is proposed for microdroplets generation and detection. FWMS, fixed on a 3D-printed holder, is designed to generate microdroplets (100–500 µm), with optical fibers embedded to collect double photoresist method pulses of scattering light by fast-moving microdroplets. The size and volume of the microdroplets are retrieved by tracking the double pulse signal in the time sequence. In the experiments, 50 groups of microdroplets (a total of 10⁵ microdroplets) with size ranging from 100 to 450 µm were generated and detected. Compared with traditional imaging detection, this method has a better sampling rate and detection error of less than 1.42%, which can provide a simple and accurate integrated microfluid system for microdroplet generation and synchronous detection. Full article

The Electrical Capacitance Tomography (ECT) imaging pipeline relies on accurate estimation of electric field distributions to compute electrode capacitances and reconstruct permittivity maps. Traditional ECT forward model methods based on the Finite Element Method (FEM) offer high accuracy but are computationally intensive, limiting their use in real-time applications. In this proof-of-concept study, we investigate the use of Graph Convolutional Networks (GCNs) for direct, one-step prediction of electric field distributions associated with a circular ECT sensor numerical model. The network is trained on FEM-simulated data and outputs of full 2D electric field maps for all excitation patterns. To evaluate physical fidelity, we compute capacitance matrices using both GCN-predicted and FEM-based fields. Our results show strong agreement in both direct field prediction and derived quantities, demonstrating the feasibility of replacing traditional solvers with fast, learned approximators. This approach has significant implications for further real-time ECT imaging and control applications. Full article

High parasitic capacitance from poly-insulator-poly capacitors in complementary metal oxide semiconductor (CMOS) processes presents a major bottleneck to achieving high-resolution successive approximation register (SAR) analog-to-digital converters (ADCs) in imaging systems. This study proposes a Phase-Adjustable SAR ADC that addresses this limitation through a reconfigurable architecture. The design utilizes a phase-adjustable logic unit to switch between a conventional SAR mode for high-speed operation and a noise-shaping (NS) SAR mode for high-resolution conversion, actively suppressing in-band quantization noise. An improved SAR logic unit facilitates the insertion of an adjustable phase while concurrently achieving an 86% area reduction in the core logic block. A prototype was fabricated and measured in a 0.35-µm CMOS process. In conventional mode, the ADC achieved a 7.69-bit effective number of bits at 2 MS/s. By activating the noise-shaping circuitry, performance was significantly enhanced to an 11.06-bit resolution, corresponding to a signal-to-noise-and-distortion ratio (SNDR) of 68.3 dB, at a 125 kS/s sampling rate. The results demonstrate that the proposed architecture effectively leverages the trade-off between speed and accuracy, providing a practical method for realizing high-performance ADCs despite the inherent limitations of non-ideal passive components. Full article

Compared with traditional piezoelectric transducers, Capacitive Micromachined Ultrasonic Transducers (CMUTs) have advantages such as better impedance matching with air, smaller size, lighter weight, higher sensitivity, and ease of array formation. Acoustic temperature measurement is a technology that utilizes the relationship between sound velocity and temperature to achieve non-contact temperature detection, with advantages such as fast response and non-invasiveness. CMUT-based acoustic temperature field measurement can achieve temperature detection in situations with narrow spaces, portability, and high measurement accuracy. This paper investigates an air-coupled CMUT device for acoustic temperature measurement, featuring a resonant frequency of 220 kHz, and composed of 16 × 8 cells. The design and fabrication of the CMUT array were completed, and the device characteristics were tested and characterized. A temperature field measurement method using mechanical scanning was proposed. A temperature measurement experimental system based on CMUT devices was constructed, achieving preliminary measurement of acoustic transmission time in both uniform and non-uniform temperature fields. Using a temperature field reconstruction algorithm, the measurement and imaging of the temperature field above an electric heating wire were accomplished and compared with the thermocouple-based temperature measurement experiment. The experimental results verified the feasibility of CMUT devices for non-contact temperature field measurement. Full article

This article proposes a novel three-dimensional trench electrode detector, named the through-type three-dimensional quasi-hemispherical electrode detector. The detector adopts a trench structure to package each independent unit and achieves complete penetration of trench electrodes with the help of an SOI substrate. The horizontal distances from the center anode of the detector to the trench cathode and the detector thickness are equal. It has a near-spherical structure and exhibits spherical-like electrical performance. In this study, we modeled the device physics of the new structure and conducted a systematic three-dimensional simulation of its electrical characteristics, including the electric field, electric potential, electron concentration distribution of the detector, the inducted current caused by incident ions, and the crosstalk between detector units. Computational and technology computer-aided design (TCAD) simulation results show that the detector has an ultra-small capacitance (2.7 fF), low depletion voltage (1.4 V), and uniform electric field distribution. The trench electrodes electrically isolate the pixel units from each other so that the coherence effect between the units is small and can be applied in high-resolution X-ray photon counting detectors to enhance the contrast-to-noise ratio of low-dose imaging and the detection rate of tiny structures, among other things. Full article

Gas–water two-phase flow in horizontal and inclined wells is significantly influenced by gravitational forces and spatial asymmetry around the wellbore, resulting in complex and variable flow patterns. Accurate measurement of water holdup is essential for analyzing phase distribution and understanding multiphase flow behavior. Water holdup imaging provides a valuable means for visualizing the spatial distribution and proportion of gas and water phases within the wellbore. In this study, air and tap water were used to simulate downhole gas and formation water, respectively. An array capacitance arraay tool (CAT) was employed to measure water holdup under varying total flow rates and water cuts in a horizontal well experimental setup. A total of 228 datasets were collected, and the measurements were processed in MATLAB (2020 version) using three interpolation algorithms: simple linear interpolation, inverse distance interpolation, and Lagrangian nonlinear interpolation. Water holdup across the wellbore cross-section was also calculated using arithmetic averaging and integration methods. The results obtained from the three imaging algorithms were compared with these reference values to evaluate accuracy and visualize imaging performance. The CAT demonstrated reliable measurement capabilities under low- to medium-flow conditions, accurately capturing fluid distribution. For stratified flow regimes, the linear interpolation algorithm provided the clearest depiction of the gas–water interface. Under low- to medium-flow rates with high water content, both inverse distance and Lagrangian methods produced more refined images of phase distribution. In dispersed flow conditions, the Lagrangian nonlinear interpolation algorithm delivered the highest accuracy, effectively capturing subtle variations within the complex flow field. Full article

We present a 1024 × 512, 1000 fps, high-dynamic-range global shutter CMOS image sensor. The pixel is based on a voltage domain global shutter architecture, featuring a pitch of 24 μm × 24 μm. Both high-gain and low-gain signals can be captured within a single frame. The combined dynamic range is 95 dB, and the full well capacity is 620 ke-. In this paper, we analyze the pixel noise performance as well as the non-linearity and image lag that arise from parasitic capacitance in the pixel. The ramp generator is based on a 12-bit full thermometer code current-steering DAC with high driving capability. We discuss the design considerations for the ramp generator, particularly addressing the phenomenon of non-linear response. Finally, the comparator design and the column readout noise are analyzed. Full article

Capacitive micromachined ultrasonic transducers (CMUTs) have been developed for air-coupled applications to address key challenges such as noise, prolonged ringing, and side-lobe interference. This study introduces an optimized CMUT design that leverages the squeeze-film damping effect to achieve a low-quality factor, enhancing resolution and temporal precision for imaging as one of the suggested airborne application. The device was fabricated using the PolyMUMPs process, ensuring high structural accuracy and consistency. Finite element analysis (FEA) simulations validated the optimized parameters, demonstrating improved displacement, reduced side-lobe artifacts, and sharper main lobes for superior imaging performance. Experimental validation, including Laser Doppler Vibrometer (LDV) measurements of membrane displacement and mode shapes, along with ring oscillation tests to assess Q-factor and signal decay, confirmed the device’s reliability and consistency across four CMUT arrays. Additionally, this study explores the implementation of multi-frequency CMUT arrays, enhancing imaging versatility across different air-coupled applications. By integrating multiple frequency bands, the proposed CMUTs enable adaptable imaging focus, improving their suitability for diverse diagnostic scenarios. These advancements highlight the potential of the proposed design to deliver a superior performance for airborne applications, paving the way for its integration into advanced diagnostic systems. Full article