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Abstract Hepatocellular carcinoma (HCC) stands as the most prevalent form of primary liver cancer, predominantly affecting patients with chronic liver diseases such as hepatitis B or C-induced cirrhosis. Diagnosis typically involves blood tests (assessing liver functions and HCC biomarkers), imaging procedures such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), and liver biopsies requiring the removal of liver tissue for laboratory analysis. However, these diagnostic methods either entail lengthy lab processes, require expensive imaging equipment, or involve invasive techniques like liver biopsies. Hence, there exists a crucial need for rapid, cost-effective, and noninvasive techniques to characterize HCC, whether in serum or tissue samples. In this study, we developed a spiral sensor implemented on a printed circuit board (PCB) technology that utilizes impedance spectroscopy and applied it to 24 tissues and sera samples as proof of concept. This newly devised circuit has successfully characterized HCC and normal tissue and serum samples. Utilizing the distinct dielectric properties between HCC cells and serum samples versus the normal samples across a specific frequency range, the differentiation between normal and HCC samples is achieved. Moreover, the sensor effectively characterizes two HCC grades and distinguishes cirrhotic/non-cirrhotic samples from tissue specimens. In addition, the sensor distinguishes cirrhotic/non-cirrhotic samples from serum specimens. This pioneering study introduces Electrical Impedance Spectroscopy (EIS) spiral sensor for diagnosing HCC and liver cirrhosis in clinical serum—an innovative, low-cost, rapid (

A new second-order matrix formulation is proposed in this work to model any nonlinear electronic system. This new formulation is developed and implemented by using a recasting method that increases the number of variables but limits the non-linearity to a quadratic form. Nonlinearity is modeled without any approximation and can model complex nonlinearities such as exponential and Tanh-based models. The new quadratic method is applied to the extended tanh MOSFET model and an exponential diode model to illustrate the power and reliability of this method. The method also has the advantage of directly stamping transistors and diodes into matrix forms in ways similar to linear elements. To demonstrate the validity of the new formulation, several circuits are examined, and the results compare very well to SPICE simulations. The simulation time as well as numerical stability improve significantly when using time marching techniques with the quadratic formulation as compared to directly stamping transistor and diode exponential nonlinearities.

Abstract Background Microelectrical Impedance Spectroscopy (µEIS) is a tiny device that utilizes fluid as a working medium in combination with biological cells to extract various electrical parameters. Dielectric parameters of biological cells are essential parameters that can be extracted using µEIS. µEIS has many advantages, such as portability, disposable sensors, and high-precision results. Results The paper compares different configurations of interdigitated microelectrodes with and without a passivation layer on the cell contact tracks. The influence of the number of electrodes on the enhancement of the extracted impedance for different types of cells was provided and discussed. Different types of cells are experimentally tested, such as viable and non-viable MCF7, along with different buffer solutions. This study confirms the importance of µEIS for in vivo and in vitro applications. An essential application of µEIS is to differentiate between the cells’ sizes based on the measured capacitance, which is indirectly related to the cells’ size. The extracted statistical values reveal the capability and sensitivity of the system to distinguish between two clusters of cells based on viability and size. Conclusion A completely portable and easy-to-use system, including different sensor configurations, was designed, fabricated, and experimentally tested. The system was used to extract the dielectric parameters of the Microbeads and MCF7 cells immersed in different buffer solutions. The high sensitivity of the readout circuit, which enables it to extract the difference between the viable and non-viable cells, was provided and discussed. The proposed system can extract and differentiate between different types of cells based on cells’ sizes; two other polystyrene microbeads with different sizes are tested. Contamination that may happen was avoided using a Microfluidic chamber. The study shows a good match between the experiment and simulation results. The study also shows the optimum number of interdigitated electrodes that can be used to extract the variation in the dielectric parameters of the cells without leakage current or parasitic capacitance.

The Dielectrophoresis force delivers an effective and appropriate way to control particles, especially for cell-selective manipulation and cell separation. It has been applied in cell sorting and drug development. Dielectrophoresis force has been applied in the cell trapping process, cell alignment, separation, and isolation of different sized particles, which are applied in a variety of biological applications. Micro electric impedance spectroscopy (µEIS) are very tiny devices that use fluid as a working medium in conjunction with biological cells to extract different electrical parameters. Many advantages can be provided by using these tiny microfluidic devices, such as portability, disposable, and high accuracy.Polystyrene beads are extensively utilized as reference particles to show the efficiency and to validate quantitatively the detection of Dielectrophoresis systems. In this work, two different forms of trapping dielectrophoresis force combined with a new strategy of impedance extraction are presented and discussed. The study aims to enhance the microfluidic system to differentiate between cells and particles with low conductivity and different sizes. The analysis technique is combined with impedance spectroscopy in a single microfluidic chip that not only enables efficient trapping of cells but also enhances the electric impedance of cells in a label-free and non-invasive using different sizes of Polystyrene Particles.

Abstract The characterization and tracking of biological cells using biosensors are necessary for many scientific fields, specifically cell culture monitoring. Capacitive sensors offer a great solution due to their ability to extract many features such as the biological cells' position, shape, and capacitance. Through this study, a CMOS-based biochip that consists of a matrix of capacitive sensors (CSM), utilizing a ring oscillator-based pixel readout circuit (PRC), is designed and simulated to track and characterize a single biological cell based on its aforementioned different features. The proposed biochip is simulated to characterize a single Hepatocellular carcinoma cell (HCC) and a single normal liver cell (NLC). COMSOL Multiphysics was used to extract the capacitance values of the HCC and NLC and test the CSM's performance at different distances from the analyte. The PRC's ability to detect the extracted capacitance values of the HCC and NLC is evaluated using Virtuoso Analog Design Environment. A novel algorithm is developed to animate and predict the location and shape of the tested biological cell depending on CSM's capacitance readings simultaneously using MATLAB R2022a script. The results of both models, the measured capacitance from CSM and the correlated frequency from the readout circuit, show the biochip's ability to characterize and distinguish between HCC and NLC.

Abstract In this paper, we showed how a bulky Axicon lens can be transformed to a compact binary zone plate with conical phase profile. We built three zone plates made of three different materials and designed each zone plate to be used in high sensitivity refractive index sensing. This work is complementary to another work we have done before in which we showed mathematically how maximum sensitivity can be achieved in case of using an Axicon lens in sensing. The zone plates are designed to generate a Bessel–Gauss beam at the wavelength of 3.3 microns at which the absorption of methane gas is maximum leading to a maximum change in the refractive index. The generated intensity in the output is very sensitive to any slight change in the refractive index of the surrounding medium. Therefore, if an optical detector is positioned at the point of maximum change in the intensity with refractive index, we can easily measure the change in refractive index and hence the percentage of the gas with very high sensitivity.

Delay and transition timetables plus voltage waveforms are used to characterize standard cell delays. More accurate models explode cell library size and degrades design flow performance. Our proposed deep learning non-linear delay model, DL-NLDM, technique outperformed 7×7 NLDM-LUT in average percentage errors with up to 1.4% error compared to SPICE and outperformed the non-standard 100×100 NLDM-LUT in maximum percentage errors. The proposed DL Autoencoder-based waveform compression outperformed singular value decomposition by 1.79×. Additionally, a novel DL waveform-delay model, DL-WFDM, models cell delays using encoded waveforms instead of delay and transition time. DL-WFDM outperformed DL-NLDM in maximum delay percentage errors.

A novel modeling methodology is developed for interconnect parasitic capacitances in rule-based extraction tools. Traditional rule-based extraction tools rely on pattern matching operations to match every interconnect structure with corresponding pre-characterized capacitance formulas. Such a method suffers from three main problems including limited pattern coverages, potential pattern mismatches, and limited handling of systematic process variations. These problems prohibit rule-based methods from coping with the new capacitance extraction accuracy requirements in advanced process nodes. The proposed methodology overcomes these problems by providing machine learning compact models for interconnect parasitic capacitances that cover varieties of realistic cross-section metal patterns. Those models efficiently include the impact of systematic process variations on parasitic capacitances. Moreover, each model can handle thousands of patterns replacing thousands of existing capacitance formulas. The input to the models is a cross-section pattern that is represented by a novel vertex-based pattern representation. The models are implemented using two different machine learning methods: neural networks and support vector regressions. The two methods are tested and compared to each other. The proposed methodology is tested over thirteen test chips of 28nm, 14nm, and 7nm process nodes with more than 6.7M interconnect cross-section patterns. The results show that the proposed methodology provided outstanding accuracy as compared to field-solvers and rule-based models with an average error < 0.15% and a standard deviation < 3.3%, whereas the average errors and standard deviations of rule-based models exceed 6%, for the same test chips. Also, the computational runtimes of the compact models are almost 2.5X faster than rule-based models.

A parasitic-aware routing optimization and analysis methodology for integrated circuits is developed based on an incremental parasitic extraction and a fast optimization methodology. Existing routing optimization methodologies rely on many circuit simulations, detailed sensitivity analysis, and inefficient simple parasitic models to optimize routes. Moreover, they do not provide a mechanism to help layout designers in identifying problematic layout geometries that have a bad impact on a route’s performance. The proposed methodology works on overcoming such problems by providing three features. First, it provides novel sensitivity circuit models to analyze the integrity of signals in layout routes. Such circuit models are based on an accurate matrix circuit representation, a cost function, and an accurate parasitic sensitivity extraction. The circuit models identify critical parasitic elements along with the corresponding layout geometries in a certain route, where they measure the sensitivity of a route’s performance to corresponding layout geometries very fast. Therefore, they can correlate the problems of a route’s performance to specific layout geometries. Second, the proposed methodology uses a nonlinear programming technique to optimize problematic routes with pre-determined degrees of freedom using the proposed circuit models. Third, the proposed methodology uses a novel incremental parasitic extraction method to extract parasitic elements of modified geometries efficiently. The incremental extraction is used as a part of the routing optimization process to improve the optimization runtime and increase the optimization accuracy. The proposed methodology is tested over different designs of 7nm and 65nm process nodes. The results show that the proposed methodology managed to identify and optimize the problematic geometries in critical routes efficiently with up to 10% performance improvements and a speedup of 3 to 9X as compared to traditional template-based methods.

Abstract In this work, for the first time, a study was conducted of the existence of Extraordinary Optical Transmission (EOT) in Silicon (Si) thin films with subwavelength holes array and high excess carrier concentration. Typically EOT is studied in opaque perforated metal films. Using Si would bring EOT and its many applications to the silicon photonics realm and the mid-IR range. Since Si thin film is a semi-transparent film in mid-IR, a generalization was proposed of the normalized transmission metric used in literature for EOT studies in opaque films. The plasma dispersion effect was introduced into the studied perforated Si film through either doping or carriers’ generation. Careful consideration for the differences in optical response modeling in both cases was given. Full-wave simulation and analysis showed an enhanced transmission when using Si with excess carriers, mimicking the enhancement reported in perforated metallic films. EOT was found in the mid-IR instead of the visible range which is the case in metallic films. The case of Si with generated excess carriers showed a mid-IR EOT peak reaching 157% around 6.68 µm, while the phosphorus-doped Si case showed a transmission enhancement of 152% around 8.6 µm. The effect of varying the holes’ dimensions and generated carriers’ concentration on the transmission was studied. The analogy of the relation between the fundamental mode cutoff and the EOT peak wavelength in the case of Si to the case of metal such as silver was studied and verified. The perforated Si thin film transmission sensitivity for a change in the refractive index of the holes and surroundings material was investigated. Also, a study of the device potential in sensing the hole and surroundings materials that have almost the same refractive index yet with different absorption fingerprints was performed as well.

This paper demonstrates the effect of microelectrodes configuration on the sensitivity and accuracy of the micro-electrical impedance spectroscopy (μEIS). Bi-polar and tri-polar microelectrodes configurations were presented, fabricated and experimentally used to extract the electrical parameters of Human Bone Osteosarcoma Epithelial (U2OS) viable and dead cells. A comparison between the experimental results are presented and discussed. These experimental results show that the tri-polar electrode configuration has higher sensitivity compared to bi-polar configuration. Keywords: Bio impedance, U2OS cells, μEIS, Microfluidic platform

Electrical interconnects are becoming a bottleneck in the way towards meeting future performance requirements of integrated circuits. Moore’s law, which observes the doubling of the number of transistors in integrated circuits every couple of years, can no longer be maintained due to reaching a physical barrier for scaling down the transistor’s size lower than 5 nm. Heading towards multi-core and many-core chips, to mitigate such a barrier and maintain Moore’s law in the future, is the solution being pursued today. However, such distributed nature requires a large interconnect network that is found to consume more than 80% of the microprocessor power. Optical interconnects represent one of the viable future alternatives that can resolve many of the challenges faced by electrical interconnects. However, reaching a maturity level in optical interconnects that would allow for the transition from electrical to optical interconnects for intra-chip and inter-chip communication is still facing several challenges. A review study is required to compare the recent developments in the optical interconnects with the performance requirements needed to reach the required maturity level for the transition to happen. This review paper dissects the optical interconnect system into its components and explains the foundational concepts behind the various passive and active components along with the performance metrics. The performance of different types of on-chip lasers, grating and edge couplers, modulators, and photodetectors are compared. The potential of a slot waveguide is investigated as a new foundation since it allows for guiding and confining light into low index regions of a few tens of nanometers in cross-section. Additionally, it can be tuned to optimize transmissions over 90° bends. Hence, high-density opto-electronic integrated circuits with optical interconnects reaching the dimensions of their electrical counterparts are becoming a possibility. The latest complete optical interconnect systems realized so far are reviewed as well.