Electronic Noise Research Articles

Performance Investigations of Two Channel Readout Configurations on the Cross-Strip Cadmium Zinc Telluride Detector.

In a detector system where the number of channels exceeds the number of channels available on an application-specific integrated circuit (ASIC), there is a need to configure channels among multiple ASICs to achieve the lowest electronic noise and highest count rate. In this work, two board configurations were designed to experimentally assess which one provides the more favorable performance. In the half-half configuration, contiguous channels from one edge to the center of CZT detector are read by one ASIC, and the other half are read by the other ASIC. In the alternate configuration, the CZT channels are read by alternating ASICs. A lower electronic noise level, better FWHM energy resolution performance (5.35% ± 1.08% compared to 7.84% ± 0.98%), and higher count rate was found for the anode electrode strips with half-half configuration. Cross-talk between ASICs and deadtime play a role in the different performances, and the total count rate of the half-half configuration has a count rate 18.1% higher than that of the alternate configuration.

Assessing myocardial tissue in the acute setting with Photon-Counting CT (PCCT) in comparison with Cardiac Magnetic Resonance (CMR)

Abstract Background Cardiac magnetic resonance (CMR) characterization of myocardial tissue is routinely used in clinical practice. Compared to traditional CT, Photon counting CT (PCCT) uses photon-counting detectors offering higher spatial resolution, elimination of electronic noise and improved contrast-to-noise ratio. A comparison between CMR and PCCT for myocardial characterizazion in an urgent setting, however, has not yet been explored. Purpose The aim of this study was to compare the ability to characterize myocardial tissue between PCCT and CMR in patients presenting with acute chest pain in the emergency department (ED). Methods This single-center prospective study enrolled all consecutive patients presenting to the ED of our hospital from November 2023 to January 2024 with chest pain, ECG alterations and troponin rise consistent with myocardial injury. Patients needing urgent coronary angiography according to guidelines were excluded. PCCT was performed urgently for triple rule-out, but also for tissue characterization through post-iodine-contrast administration images. Within 24 hours, all patients underwent a CMR protocol including T2-weighted and late gadolinium enhancement (LGE) images for tissue characterization. Results Six male patients with a mean age of 20 ± 10 years were enrolled. All clinical, PCCT, and CMR parameters are presented in Table 1. All patients presented with diffuse ST-segment elevation and exhibited T2-weighted images (for edema detection) and LGE distribution (subepicardial and intramyocardial) consistent with acute myocarditis. Mean radiation exposure for PCCT was 0.8±0.1 mSv. A strong linear correlation emerged between PCCT-derived delayed enhancement (DE) volume and CMR-derived late gadolinium enhancement (LGE) volume (r = 0.970; p value 0.001) (Table 1). Similar results were achieved when comparing the number of DE and LGE myocardial segments (r = 0.871; p value 0.026). Significant correlations also emerged between DE, LGE, and high-sensitive troponin (hsTN) at presentation (respectively: PCCT-DE vs hsTN r = 0.951, p value 0.004; CMR-LGE vs hsTN r = 0.918, p value 0.010). CMR showed a much higher signal-to-noise ratio (SNR) for the delayed enhanced myocardium and contrast-to-noise (CNR) ratio between the delayed enhanced and normal myocardium with respect to PCCT in post-contrast images (respectively 7.4 ± 3.9 vs 27.2 ± 17.7, p value 0.024 and 5.5 ± 3.7 vs 38.8 ± 30.2, p value 0.023). In T2-weighted images both SNR for the hyperintense myocardium (30.3 [20.4-122.4]) and CNR between the hyperintense and normal myocardium (26.7 [13.3-60.2]) resulted to be higher compared to PCCT (p value 0.027 and 0.045, respectively) (Table 1). Conclusions PCCT appears to be reliable when compared to CMR for detecting myocardial edema through the acquisition of post-contrast images in the acute setting with an acceptable CNR.

Single-Shot Readout and Weak Measurement of a Tin-Vacancy Qubit in Diamond

The negatively charged tin-vacancy center in diamond (SnV−) is an emerging platform for building the next generation of long-distance quantum networks. This is due to the SnV−’s favorable optical and spin properties including bright emission, insensitivity to electronic noise, and long spin coherence times at temperatures above 1 K. Here, we demonstrate measurement of a single SnV− electronic spin with a single-shot readout fidelity of 87.4%, which can be further improved to 98.5% by conditioning on multiple readouts. In the process, we develop understanding of the relationship between strain, magnetic field, spin readout, and microwave spin control. We show that high-fidelity readout is compatible with rapid microwave spin control, demonstrating a favorable parameter regime for use of the SnV− center as a high-quality spin-photon interface. Finally, we use weak quantum measurement to study measurement-induced dephasing; this illuminates the fundamental interplay between measurement and decoherence in quantum mechanics, and provides a universal method to characterize the efficiency of color-center spin readout. Taken together, these results overcome an important hurdle in the development of the SnV−-based quantum technologies and, in the process, develop techniques and understanding broadly applicable to the study of solid-state quantum emitters. Published by the American Physical Society 2024

Optimizing charge transport simulation for hybrid pixel detectors

To enhance the spatial resolution of the MÖNCH 25 µm pitch hybrid pixel detector, deep learning models have been trained using both simulation and measurement data. Challenges arise when comparing simulation-based deep learning models to measurement-based models for electrons, as the spatial resolution achieved through simulations is notably inferior to that from measurements. Discrepancies are also observed when directly comparing X-ray simulations with measurements, particularly in the spectral output of single pixels. These observations collectively suggest that current simulations require optimization. To address this, the dynamics of charge carriers within the silicon sensor have been studied using Monte Carlo simulations, aiming to refine the charge transport modeling. The simulation encompasses the initial generation of the charge cloud, charge cloud drift, charge diffusion and repulsion, and electronic noise. The simulation results were validated with measurements from the MÖNCH detector for X-rays, and the agreement between measurements and simulations was significantly improved by accounting for the charge repulsion.

Comparative study of optical properties and photocatalytic performance of Cd0.4Mn0.6O nanocomposites incorporated with different metal oxides

The structural, optical, and photocatalytic properties of Cd0.4Mn0.6XO nanocomposites with 50 wt% of X were investigated (X denotes ZnO, SnO, CuO, Al2O3, Fe2O3, NiO, and CoO). The crystal structure of Cd0.4Mn0.6XO nanocomposites is composed of the monoclinic Cd2Mn3O8 phase, along with other individual phases dependent on the type of X dopant. The crystallite sizes are between 11.07 nm for CoO and 23.65 nm for ZnO, whereas the particle sizes are between 9.75 nm for ZnO and 35.61 nm for Fe2O3. The SnO, NiO, and CoO nanocomposites had the highest values of the effective surface area of 29.71, 26.3, and 24.1 m2/g, respectively. The NiO and SnO nanocomposites had the highest and lowest absorbance, respectively, notably at wavelength below 400 nm. SnO, NiO, CuO, and Fe2O3 nanocomposites have the highest values of energy gap (Eg > 2 eV), whereas CoO, ZnO, and Al2O3 nanocomposites have the lowest Eg values (<2 eV). The SnO nanocomposite exhibited the highest values of refractive index, q-factor, lattice dielectric constant (εL), free carrier density (Nm∗), and optical/electrical conductivity when compared to the other Cd0.4Mn0.6XO nanocomposites. Interestingly, the values of εL, and Nm∗ were enhanced to 21.2 and 4.9 × 1057 cm−3g−1 for SnO nanocomposite, followed by NiO and Fe2O3 nanocomposites. The photodegradation efficiency towards methylene blue (MB) using the Cd0.4Mn0.6XO catalysts after 3 h of irradiation equals 97.94, 76.43, 74.43, 71.32, 65.98, 62.86, and 48.55 % for ZnO, NiO, SnO, Fe2O3, Al2O3, CuO and CoO nanocomposites, respectively. The photocatalytic performance of Cd0.4Mn0.6XO catalysts towards MB was compared to earlier investigations and a scavenger test was performed to validate the formation of reactive oxygen species. The features of Cd0.4Mn0.6XO nanocomposites are convenient for light-emitting diodes, solar cells, reduced electronic noise, high-power operation, and water purification.

Evolution of Single Photon Lidar: From Satellite Laser Ranging to Airborne Experiments to ICESat-2

In September 2018, NASA launched the ICESat-2 satellite into a 500 km high Earth orbit. It carried a truly unique lidar system, i.e., the Advanced Topographic Laser Altimeter System or ATLAS. The ATLAS lidar is capable of detecting single photons reflected from a wide variety of terrain (land, ice, tree leaves, and underlying terrain) and even performing bathymetric measurements due to its green wavelength. The system uses a single 5-watt, Q-switched laser producing a 10 kHz train of sub-nanosecond pulses, each containing 500 microjoules of energy. The beam is then split into three “strong” and three “weak” beamlets, with the “strong” beamlets containing four times the power of the “weak” beamlets in order to satisfy a wide range of Earth science goals. Thus, ATLAS is capable of making up to 60,000 surface measurements per second compared to the 40 measurements per second made by its predecessor multiphoton instrument, the Geoscience Laser Altimeter System (GLAS) on ICESat-1, which was terminated after several years of operation in 2009. Low deadtime timing electronics are combined with highly effective noise filtering algorithms to extract the spatially correlated surface photons from the solar and/or electronic background noise. The present paper describes how the ATLAS system evolved from a series of unique and seemingly unconnected personal experiences of the author in the fields of satellite laser ranging, optical antennas and space communications, Q-switched laser theory, and airborne single photon lidars.

Contrast and quantum noise in single-exposure dual-energy thoracic imaging with photon-counting x-ray detectors

Objective.Photon-counting x-ray detectors (PCDs) can produce dual-energy (DE) x-ray images of lung cancer in a single x-ray exposure. It is important to understand the factors that affect contrast, noise and the contrast-to-noise ratio (CNR). This study quantifies the dependence of CNR on tube voltage, energy threshold and patient thickness in single exposure, DE, bone-suppressed thoracic imaging with PCDs, and elucidates how the fundamental processes inherent in x-ray detection by PCDs contribute to CNR degradation.Approach.We modeled the DE CNR for five theoretical PCDs, ranging from an ideal PCD that detects every primary photon in the correct energy bin while rejecting all scattered radiation to a non-ideal PCD that suffers from charge-sharing and electronic noise, and detects scatter. CNR was computed as a function of tube voltage and high energy threshold for average and larger-than-average patients. Model predictions were compared with experimental data extracted from images acquired using a cadmium telluride (CdTe) PCD with two energy bins and analog charge summing for charge-sharing suppression. The imaging phantom simulated attenuation, scatter and contrast in lung nodule imaging. We quantified CNR improvements achievable with anti-correlated noise reduction (ACNR) and measured the range of exposure rates over which pulse pile-up is negligible.Main Results.The realistic model predicted overall trends observed in the experimental data. CNR improvements with ACNR were approximately five-fold, and modeled CNR-enhancements were on average within 10% of experiment. CNR increased modestly (i.e.<20%) when increasing the tube voltage from 90 kV to 130 kV. Optimal energy thresholds ranged from 50 keV to 70 keV across all tube voltages and patient thicknesses with and without ACNR. Quantum efficiency, electronic noise, charge sharing and scatter degraded CNR by ~50%. Charge sharing and scatter had the largest effect on CNR, degrading it by ~30% and ~15% respectively. Dead-time losses were less than 5% for patient exposure rates within the range of clinical exposure rates.Significance.In this study, we (1) employed analytical and computational models to assess the impact of different factors on CNR in single-exposure DE imaging with PCDs, (2) evaluated the accuracy of these models in predicting experimental trends, (3) quantified improvements in CNR achievable through ACNR and (4) determined the range of patient exposure rates at which pulse pile-up can be considered negligible. To the best of our knowledge, this study represents the first systematic investigation of single-exposure DE imaging of lung nodules with PCDs.

Research on denoising method based on temperature and humidity profile lidar

Due to the fact that the vibration and pure rotational Raman signals collected by the temperature and humidity profile lidar were 3–4 orders of magnitude weaker than the Mie scattering signal, they were susceptible to electronic and white noise interference, which seriously affected the system signal-to-noise ratio. In this paper, an improved VMD-WT filtering method was adopted to extract effective signals and denoise. The processing outcome of several filtering algorithms was evaluated, and noisy signals were simulated to confirm the algorithm's efficacy. Based on the quantitative computation of evaluation indicators, such as signal-to-noise ratio, root mean square error, and correlation, the improved VMD-WT algorithm had more significant advantages in indicators such as signal-to-noise ratio. In order to further verify the robustness and adaptability of the proposed algorithm, experimental analysis of the filtering algorithm was conducted on the continuously collected temperature and humidity measured signals. The results demonstrated that the algorithm not only improved the detection range of lidar and suppressed high-altitude noise effectively, but also performed well in processing strong interference signals, like clouds, which led to a significant improvement in the atmospheric optical parameter inversion results. Furthermore, pseudo-color images of aerosols, temperature, and humidity changes over time and space have been used to further illustrate the algorithm's dependability and wide range of potential uses.

Machine Learning for Accurate Energy Analysis of Double Beta Decay Events

Point-contact germanium detectors are used to detect and analyze particles and their decay processes. This research focuses on the search for a phenomenon known as neutrinoless double beta decay, where two neutrons within a nucleus transform into two protons, emitting electrons in the process. Unlike standard double beta decay, no neutrinos are emitted, suggesting that the neutrino may act as its own antiparticle, effectively canceling itself out. Detecting this process would provide crucial insights into the nature of neutrino mass. During such an event, the detector registers a spike in energy due to the emitted electrons, producing a step-like pulse in the output channels. The energy of the event is determined by the difference in charge between the ‘top’ and ‘bottom’ steps of the pulse. However, accurately determining the energy is complicated by the presence of a resistor in the detector, which causes the top step to decay exponentially back to a baseline in preparation for the next event. This decay makes it challenging to determine the true energy of the pulse. My work this summer focused on developing machine learning models to reconstruct the step-like nature of pulses from their decayed versions recorded by the detector. This involved constructing deep neural networks trained on inputs (decayed pulses) and corresponding targets (the original step pulses) to learn to accurately reconstruct the target from the input. Initially, the networks were trained on simulated detector data. Once proficient in reconstruction, electronic noise was added to the input pulses to simulate real-world conditions, under which the models were trained to remove both electronic noise and decay. The models were trained to handle pulses with varying decay constants to improve their generalization ability. These neural networks can now be applied to real detector data for accurate energy analysis of double beta decay events.

Studies on the temperature dependent drift velocity for the HELIX Drift Chamber Tracker

HELIX (High Energy Light Isotope eXperiment) is a ballon experiment designed to measure abundance of cosmic ray isotopes from hydrogen to neon, with a particular interest in abundances of beryllium isotopes. HELIX aim to provide essential data to study the cosmic ray propagation in our galaxy. The Drift Chamber Tracker (DCT) in HELIX is a multi-wire gas drift chamber designed to measure the position of incident cosmic rays. It is located inside a magnet, bending the trajectory of incoming particles through 72-layers of tracking, enabling the measurement of the momentum of incoming particles.Before the data can be used for scientific analysis, the background must be taken out, and the instrument must be well calibrated. In order to exclude electronic noise from the DCT data it was necessary to determine the maximum drift velocity of each wire over a short period of time. To do this I developed an algorithm to be able to identify the maximum drift velocity for each wire over each dataset. This revealed a position dependence of the data within the detector. In order to attempt to characterize this dependence, so it can be accounted for in the calibration stage, I preformed a study on the temperature dependence of the drift velocities analyzing at data from different time periods over the course of the flight. To characterize this dependence I built a predicted heat map of the gas within the detector over the course of the flight. This involved calibrating the thermistors based on data collected when the experiment was on the ground. This helped confirm that the predicted temperature was reasonable and that the variation was temperature dependent. This algorithms and this study can now be applied to the full data set to develop a calibration method.

Exploring the Multifunctional aspects of SrBi2-X(CoFe2O4)XNb2O9 Nanocomposite Materials Emphasizing the Structural, Elastic, and Optical Properties

Nanocomposites of SrBi(2-X)(CF)XNb2O9 (SBNCF) (CF=CoFe2O4 for X = 0.0 to 0.5 with a step increment of 0.1) were synthesized using the hydrothermal method and characterized for their structural, morphological, elastic, and optical properties. The incorporation of CF into SrBi2Nb2O9 (SBN) resulted in hybrid composites with tailored properties. X-ray Diffraction (XRD) with Rietveld refinement analysis confirmed the formation of orthorhombic SBN and spinel CF phases. Field Emission Gun Scanning Electron Microscopy (FEG-SEM) revealed that SBN exhibits a plate-like morphology, with the incorporation of CF into the SBN matrix resulting in both plate-like and octahedral-shaped grains. The Brunauer–Emmett–Teller (BET) method was used to determine the pore radius and surface area, both of which were found to have increased, indicating an enhancement in photocatalytic performance. The presence of the constituent elements in the prepared compositions was confirmed by Energy Dispersive Spectroscopy (EDS). Fourier Transform Infrared Spectroscopy (FTIR) spectra were used to determine elastic properties, suggesting potential applications in electronic noise filtering. From Diffuse Reflectance Spectroscopy (DRS), a recognizable semiconducting behavior and band gap bowing were noticed in SBNCF nanocomposites on the obtained energy band gap values (2.20 eV - 1.56 eV) compared to the SBN host matrix (3.16 eV). The materials exhibited strong emission peaks at 470 nm, 528 nm, 584 nm, and 703 nm upon the excitation of 425 nm light using Photoluminescence (PL) spectroscopy. The white emission was predominant at room temperature in all the produced samples and the corresponding color temperature values range from 5865.93 K to 7599.05 K from the CIE diagram. The SBNCF materials are promising candidates in photocatalytic reactions and white light-emitting diodes (w-LEDs) based on their enhanced optical properties.

Measurements of the Limit of Detection for Electrochemical Gas Sensors

Abstract Electrochemical amperometric gas cells are becoming the sensor of choice when measuring polluting gases using low-cost air quality networks. A number of technical issues remain to be resolved to deliver fit-for-purpose monitoring systems: humidity corrections are needed but not well understood, interfering gases such as ozone can have variable cross-sensitivity and calibration intervals, and procedures are still being investigated. Another unanswered question is the limit of detection (LOD) for electrochemical gas sensors. Estimates range from hundreds of equivalent parts per billion (ppbv) to single-digit ppbv concentrations. We discuss the LOD for nitrogen dioxide (NO2), an important gas when monitoring air quality. Multiple NO2 sensor systems were tested in an environmental chamber to determine, among other parameters, the LOD for NO2 electrochemical gas sensors. Low-noise electronics and battery powering further reduced electronic noise, allowing the intrinsic LOD of the electrochemical cell to be determined. Noise, quantified as the standard deviation in zero air in a very stable temperature and relative humidity–controlled chamber was &amp;lt;500 pA, which translated into 1.6 ppbv, so the LOD, 3 × standard deviation, was 4.8 ppb. Interestingly, the LOD calculated with 300 ppbv NO2 test gas was the same (±0.1 ppbv). Further tests with a higher resolution analog-to-digital converter resulted in the same LOD, further leading to the conclusion that for the Alphasense NO2-A43F NO2 sensor, the limiting value for LOD is 4.8 ppbv.

Low Frequency Electronic Noise Characterization of Au-W/β-Ga2O3 Schottky Diodes

Ultra-wide bandgap (UWBG) semiconductors have attracted tremendous amount of interest for applications in high-power electronics and solar-blind UV photodetectors. In particular, β-Ga2O3 has attracted significant research attention in recent years due to its promising electrical and optical characteristics including a large bandgap, high breakdown electrical field, and large Baliga’s figure of merit compared to well-established wide-bandgap technologies such as GaN and SiC [1].Low frequency electronic noise, which is present in all electronic devices, can be used as a diagnostic tool for semiconductor material and device characterization. By studying the low frequency noise in semiconductor materials and devices, the physics associated with the noise properties of bulk and interface defects and traps can be investigated [2]. Measurement of low frequency noise is also crucial for evaluating material quality and device reliability.In this work, we investigate the forward-bias diode parameters and low-frequency electronic noise in Au-W/β-Ga2O3 Schottky barrier diodes. The Schottky contact is formed by depositing 20 nm of Tungsten (W) using dc sputtering followed by 340 nm of Gold (Au) using e-beam evaporation, and subsequent annealing [3].We first measure the I-V characteristics and extract important diode parameters, such as the Schottky barrier height, ideality factor, and series resistance from room temperature forward-bias current-voltage characteristics. The extracted Schottky barrier height for these devices is in the range 0.7-0.8 eV and the ideality factor is approximately 1.2.We next measure the low-frequency electronic noise in Au-W/β-Ga2O3 Schottky diodes at different forward bias voltages at room temperature. We find that the current noise spectral density exhibits 1/f-type behavior for all forward bias voltages at low frequency with an exponent ranging from 0.75 to 1.15, indicating that the low frequency noise of these devices is dominated by excess (flicker) noise. No Lorentzian-shaped generation-recombination (G-R) noise is observed. At low frequencies, the shot noise contribution is found to be negligible for the values of the current in our devices, and the total noise is 1/f-limited.We also investigate the dependence of the current noise spectral density on forward bias current, revealing different relationships in different current regimes. At low currents, the noise spectral density is found to scale approximately as the square of current, whereas at high currents, the noise spectral density begins to saturate. Such noise behavior can be attributed to different noise sources dominating in different current regimes. Furthermore, using the noise figure of merit adapted for ultra-wide bandgap semiconductor devices [4], we find that the Au-W/β-Ga2O3 devices have lower noise levels compared to other emerging UWBG materials and similar noise levels as well-established technologies such as GaN.These results provide important insights into the electronic noise properties of Au-W/β-Ga2O3 Schottky diodes and show that low frequency noise characterization is an important diagnostic tool for assessing the quality and reliability of gallium oxide based wide-bandgap materials and device technologies.

(Invited) Continuous Monitoring of Small Molecules Using Electrochemical Aptamer-Based Biosensors with CMOS Electronics

The ability to continuously monitor specific “molecules” over a long period of time can provide fundamentally new insights into disease dynamics and the transition from a healthy state and lead to the design of next-generation screening and detection tools. However, currently only a few biomolecules, such as glucose, oxygen, and dopamine, can be continuously and real-time monitored with significant relevance to chronic disease management. The prevalent glucose sensor uses glucose oxidase (GOx), an enzyme designed to oxidize glucose persistently in its proximity, producing an electrochemical current proportional to the glucose concentration. The enzyme's specificity means it cannot be readily adapted to target different biomolecules, thus constraining its versatility. This limitation also extends to many enzyme-based sweat sensors. In contrast, oxygen and dopamine measurements exploit their inherent molecular characteristics. Oxygen saturation (SpO2) in blood is determined via pulse oximetry, which uses the distinct light absorption properties of deoxygenated and oxygenated blood under red and infrared lights. Dopamine, a neurotransmitter integral to our emotional responses, is highly electrochemically active and can undergo reversible oxidation, allowing it to be detected by analytical methods like fast-scan cyclic voltammetry (FSCV). Nevertheless, such distinct properties are not common among biomolecules, making these methods non-transferable to a broader range.To this end, our group and others have previously utilized aptamers to achieve continuous detection of small molecules in vivo. Aptamers are “synthetic antibodies” composed of nucleic acids that can specifically bind to the target analytes in complex samples, such as the whole blood (Fig. 1(a)). Importantly, they can be engineered into “aptamer-switches” that undergo structure-switching upon target binding in a reversible manner. By conjugating electroactive reporters to the aptamers, the changes in their structure (thus, the analyte concentration) can be detected electrochemically. As sample preparation is not needed, aptamer switches are capable of continuous monitoring of biomolecules in vivo.Coupling with structure-switching aptamers, our team has presented the first wireless, electrochemical aptamer-sensing chip in the 65-nm CMOS technology and achieved continuous recording of small-molecule drugs, e.g., antibiotics or chemotherapeutics, from a freely moving rodent (Fig. 1(b) and 1(c)). The chip features a chronoamperometric (CA) sensing circuit that probes the electron transfer (ET) kinetics of the structure-switching aptamers that are correlated to the concentration of target analytes. Notably, we have innovated a sample-and-hold (S/H) circuit technique into our readout front end to overcome the noise/power trade-off commonly experienced in conventional circuit design (Fig. 1(d)). This technique employs two switched-capacitor circuits that maintain the electrode potentials on an open-loop basis, disabling the power-intensive and noise-contributing on-chip amplifiers during the recording phase. The technique achieves simultaneous reductions of 286× in circuit noise (4.36 nArms to 15.2pArms) and 23× in power consumption (5.25 mW to 0.22 mW), along with a 10× increase in throughput compared to the traditional square-wave voltammetry (SWV) readout methods that have been commonly used in interrogating E-AB sensors (5 vs. 0.5 Samples/sec). Fig. 1(d) shows the measured current transients that reflects the changes in ET kinetics at different target concentrations.While previous circuit focuses on lowering the electronics noise, we also develop a second electrochemical readout circuit that aims at boosting the detection signal through redox current integration at the circuit domain. This integration process captures the charges, instead of the current, leading us to term this technique square-wave voltcoulometry (SWVC, Fig. 1(e)). Our analysis demonstrates that the proposed SWVC technique can yield a remarkable signal improvement of 250×. Importantly, this improvement is achieved while maintaining nearly identical levels of input-referred noise (5 pArms) at a power consumption of only few mW. Fig. 1(f) compares the measurements obtained using conventional SWV readout and the proposed SWVC technique. The results demonstrate a remarkable 25-fold improvement in the signal-to-noise ratio (SNR), and we anticipate another 4× boosting once we optimize the test setup.We've also addressed issues related to drift and biofouling. We utilize kinetic-differential measurements (KDM) that monitor the rate of current change rather than absolute current values, mitigating the effects of biosensor detachment from the electrode surface. We also develop a dual-aptamer strategy where two aptamer sensors responding differentially to the same analyte targets are utilized to increase the signal while rejecting the slow-moving drifts (Fig. 1(g)). For biofouling, we employ a combinatorial-selected polyacrylamide hydrogel coating to specifically resist platelet adhesion (Fig. 1(h)). By integrating these advancements, we have validated our technology in vivo within whole blood via a probe catheterized into a rat's vein and interstitial fluids (ISF) through whole-system implantation (Fig. 1(i)). This technology also holds promise for the multiplexed monitoring. Figure 1

Fast and low power SiPM amplifier operating in a wide temperature range

The next generation of Ring Imaging CHerenkov detectors in high energy physics experiments may use SiPMs as photon sensing elements. This upgrade is necessary to achieve greater detector granularity and speed, however SiPMs need to be cooled down to cryogenic temperatures to detect single photons in high-radiation environments and avoid being overwhelmed by the presence of “dark signals”. It is therefore necessary to study and characterize SiPM models in dedicated campaigns, using a custom-built amplifying chain that can also operate in an extended temperature range, between 80 K and 300 K, for detector characterization purposes. The proposed amplifier configuration consists of two amplifying stages and achieves low jitter values (<10−20psRMS) thanks to the low electronic noise and the high amplifier bandwidth. The circuit achieves a signal bandwidth of 500MHz<BW<1GHz, a phase margin of approximately 45° and a power consumption of about 65−135mW. The amplifier prototype unit can be adjusted to cover the considered temperature range and still achieve low jitter values.

A triangular-trapezoidal dual-channel shaping algorithm for resistive anode readout systems and its FPGA implementation.

This paper introduces a novel digital triangular-trapezoidal double-channel shaping algorithm to enhance the counting rate of resistive anode detectors. The algorithm is based on the trapezoidal shaping algorithm and improves it. At the extreme counting rate, the trapezoidal shaping algorithm cannot alleviate the pulse pileup, so the counting rate cannot meet the requirements of a high performance detector. The triangular-trapezoidal double-channel shaping algorithm is introduced in the resistance anode detector, which can replace the trapezoidal shaping filtering algorithm to process the output signal of the resistance anode detector and obtain the single photon position information. This improvement improves the counting rate of the resistor anode detector and reduces the resolution degradation caused by pulse pileup. The algorithm is simulated by System Generator software and implemented on FPGA (field programmable gate array). The triangular-trapezoidal double-channel shaping algorithm presented in this paper plays an important role in reducing electronic noise and pulse pileup. The algorithm is subjected to simulation testing, and it can recognize signals with a minimum pulse interval of 1 µs and counting rate up to 1000 kcps.

Technical challenges and benefits of photon counting detector computed tomography

X-ray detector is the essential part of a computed tomography (CT) system that controls dose efficiency and image quality. All clinical CT scanners utilized scintillating detectors up until the first clinical photon-counting-detector (PCD) system was approved in 2021. These detectors do not record information about individual photons during the two-step detection process. PCDs, on the other hand, employ a single step process that transforms X-ray radiation straight into an electrical signal. This retains information on individual photons, allowing one to count the quantity of X-rays in various energy ranges. Better spatial resolution, reduced dosages of iodinated contrast material, enhanced iodine signal, enhanced radiation dose efficiency, and the lack of electronic noise are the main benefits of PCDs. PCDs with multiple energy thresholds are able to separate detected photons into two or more energy bins, allowing for the availability of energy-resolved data for each record. In the event of dual-source CT, this permits high pitch or high temporal resolution acquisitions in addition to high spatial resolution for tasks involving material quantification or classification. PCDCT imaging of anatomy, where excellent spatial resolution provides clinical benefit, is one of the most promising uses of the technology. Inner ear, bone, small blood artery, heart, and lung imaging are among them. Photon-counting CT will become the wave of the future for workhorse CT imaging systems. An overview of the PCDCT principle, possible clinical benefits, and limitations of conventional CT is provided in this review paper, along with potential future developments for this CT imaging technology.

High energy resolution CsPbBr3 alpha particle detector with a full-customized readout application specific integrated circuit

α particles must be monitored to be managed as radioactive diagnostic agents or nuclear activity indicators. The new generation of perovskite detectors suffer from limited energy resolution, which affects spectroscopy and imaging applications. Here, we report that the solution-grown CsPbBr3 crystal exhibits a low and stable dark current (34.6 nA·cm−2 at 200 V) by thinning the as-grown crystal to decrease the high concentration CsPb2Br5 phase near the surface. The introduction of the Schottky electrode for the CsPbBr3 detector further reduces the dark current and improves the high-temperature stability. An energy resolution of 6.9% is achieved with the commercial electronic system, while the effects of air scattering and absorption are investigated. Moreover, 1.1% energy resolution is recognized by a full-customized readout application-specific integrated circuit without any additional signal processing, which matches well with the given parameters of the CsPbBr3 detector by reducing the parasitic capacitance and electronic noise.

Denoising Search doubles the number of metabolite and exposome annotations in human plasma using an Orbitrap Astral mass spectrometer.

Chemical exposures may impact human metabolism and contribute to the etiology of neurodegenerative disorders like Alzheimer's Disease (AD). Identifying these small metabolites involves matching experimental spectra to reference spectra in databases. However, environmental chemicals or physiologically active metabolites are usually present at low concentrations in human specimens. The presence of noise ions can significantly degrade spectral quality, leading to false negatives and reduced identification rates. In response to this challenge, the Spectral Denoising algorithm removes both chemical and electronic noise. Spectral Denoising outperformed alternative methods in benchmarking studies on 240 tested metabolites. It improved high confident compound identifications at an average 35-fold lower concentrations than previously achievable. Spectral Denoising proved highly robust against varying levels of both chemical and electronic noise even with >150-fold higher intensity of noise ions than true fragment ions. For human plasma samples of AD patients that were analyzed on the Orbitrap Astral mass spectrometer, Denoising Search detected 2.3-fold more annotated compounds compared to the Exploris 240 Orbitrap instrument, including drug metabolites, household and industrial chemicals, and pesticides. This combination of advanced instrumentation with a superior denoising algorithm opens the door for precision medicine in exposome research.

In-silico study of the impact of system design parameters on microcalcification detection in wide-angle digital breast tomosynthesis.

Accurate detection of microcalcifications ( ) is crucial for the early detection of breast cancer. Some clinical studies have indicated that digital breast tomosynthesis (DBT) systems with a wide angular range have inferior detectability compared with those with a narrow angular range. This study aims to (1)provide guidance for optimizing wide-angle (WA) DBT for improving detectability and (2)prioritize key optimization factors. An in-silico DBT pipeline was constructed to evaluate detectability of a WA DBT system under various imaging conditions: focal spot motion (FSM), angular dose distribution (ADS), detector pixel pitch, and detector electronic noise (EN). Images were simulated using a digital anthropomorphic breast phantom inserted with clusters. Evaluation metrics included the signal-to-noise ratio (SNR) of the filtered channel observer and the area under the receiver operator curve (AUC) of multiple-reader multiple-case analysis. Results showed that FSM degraded sharpness and decreased the SNR and AUC by 5.2% and 1.8%, respectively. Non-uniform ADS increased the SNR by 62.8% and the AUC by 10.2% for filtered backprojection reconstruction with a typical clinical filter setting. When EN decreased from 2000 to 200 electrons, the SNR and AUC increased by 21.6% and 5.0%, respectively. Decreasing the detector pixel pitch from 85 to improved the SNR and AUC by 55.6% and 7.5%, respectively. The combined improvement of a pixel pitch and EN200 was 89.2% in the SNR and 12.8% in the AUC. Based on the magnitude of impact, the priority for enhancing detectability in WA DBT is as follows: (1)utilizing detectors with a small pixel pitch and low EN level, (2)allocating a higher dose to central projections, and (3)reducing FSM. The results from this study can potentially provide guidance for DBT system optimization in the future.