A Simulation Method for Underwater SPAD Depth Imaging Datasets.

In recent years, underwater imaging and vision technologies have received widespread attention, and the removal of the backward-scattering interference caused by impurities in the water has become a long-term research focus for scholars. With the advent of new single-photon imaging devices, single-photon avalanche diode (SPAD) devices, with high sensitivity and a high depth resolution, have become cutting-edge research tools in the field of underwater imaging. However, the high production costs and small array areas of SPAD devices make it very difficult to conduct underwater SPAD imaging experiments. To address this issue, we propose a fast and effective underwater SPAD data simulation method and develop a denoising network for the removal of backward-scattering interference in underwater SPAD images based on deep learning and simulated data. The experimental results show that the distribution difference between the simulated and real underwater SPAD data is very small. Moreover, the algorithm based on deep learning and simulated data for the removal of backward-scattering interference in underwater SPAD images demonstrates effectiveness in terms of both metrics and human observation. The model yields improvements in metrics such as the PSNR, SSIM, and entropy of 5.59 dB, 9.03%, and 0.84, respectively, demonstrating its superior performance.

Hyperspectral Characteristics and SPAD Estimation of Wheat Leaves under CO2 Microleakage Stress.

To non-destructively and rapidly monitor the chlorophyll content of winter wheat leaves under CO2 microleakage stress, and to establish the quantitative relationship between chlorophyll content and sensitive bands in the winter wheat growing season from 2023 to 2024, the leakage rate was set to 1 L/min, 3 L/min, 5 L/min, and 0 L/min through field experiments. The dimensional reduction was realized, fractional differential processing of a wheat canopy spectrum was carried out, a multiple linear regression (MLR) and partial least squares regression (PLSR) estimation model was constructed using a SPA selection band, and the model's accuracy was evaluated. The optimal model for hyperspectral estimation of wheat SPAD under CO2 microleakage stress was screened. The results show that the spectral curves of winter wheat leaves under CO2 microleakage stress showed a "red shift" of the green peak and a "blue shift" of the red edge. Compared with 1 L/min and 3 L/min, wheat leaves were more affected by CO2 at 5 L/min. Evaluation of the accuracy of the MLR and PLSR models shows that the MLR model is better, where the MLR estimation model based on 1.1, 1.8, 0.4, and 1.7 differential SPAD is the best for leakage rates of 1 L/min, 3 L/min, 5 L/min, and 0 L/min, with validation set R2 of 0.832, 0.760, 0.928, and 0.773, which are 11.528, 14.2, 17.048, and 37.3% higher than the raw spectra, respectively. This method can be used to estimate the chlorophyll content of winter wheat leaves under CO2 trace-leakage stress and to dynamically monitor CO2 trace-leakage stress in crops.

Position-Sensitive Silicon Photomultiplier Arrays with Large-Area and Sub-Millimeter Resolution.

Silicon photomultipliers (SiPMs) are solid-state single-photon-sensitive detectors that show excellent performance in a wide range of applications. In FBK (Trento, Italy), we developed a position-sensitive SiPM technology, called "linearly graded" (LG-SiPM), which is based on an avalanche-current weighted-partitioning approach. It shows position reconstruction resolution below 250 µm on an 8 × 8 mm2 device area with four readout channels and minimal distortions. A recent development in terms of LG-SIPM is a larger chip version (10 × 10 mm2) based on FBK NUV-HD technology (near-ultraviolet sensitive), with a peak photon detection efficiency at 420 nm. Such a large-area detector with position sensitivity is very interesting in applications like MR-compatible PET, high-energy physics experiments, and readout of time-projection chambers, gamma and beta cameras, or scintillating fibers, with a reduced number of channels. These SiPMs were characterized in terms of noise, photon detection efficiency, and position resolution. We also developed tiles of 2 × 2 and 3 × 3 LG-SiPMs, reaching very large sensitive areas of 20 × 20 mm2 and 30 × 30 mm2. We implemented a "smart-channel" configuration, which allowed us to have just six output channels for the 2 × 2 elements and eight channels for the 3 × 3 element tiles, preserving a position resolution below 0.5 mm. These kinds of detectors provide a great advantage in compact and low-power applications by maintaining position sensitivity over large areas with a small number of channels.

Radiation Damage on Silicon Photomultipliers from Ionizing and Non-Ionizing Radiation of Low-Earth Orbit Operations.

Silicon Photomultipliers (SiPMs) are single photon detectors that gained increasing interest in many applications as an alternative to photomultiplier tubes. In the field of space experiments, where volume, weight and power consumption are a major constraint, their advantages like compactness, ruggedness, and their potential to achieve high quantum efficiency from UV to NIR makes them ideal candidates for spaceborne, low photon flux detectors. During space missions however, SiPMs are usually exposed to high levels of radiation, both ionizing and non-ionizing, which can deteriorate the performance of these detectors over time. The goal of this work is to compare process and layout variation of SiPMs in terms of their radiation damage effects to identify the features that helps reduce the deterioration of the performance and develop the next generation of more radiation-tolerant detectors. To do this, we used protons and X-rays to irradiate several Near Ultraviolet High-Density (NUV-HD) SiPMs with small areas (single microcell, 0.2 × 0.2 mm2 and 1 × 1 mm2) produced at Fondazione Bruno Kessler (FBK), Italy. We performed online current-voltage measurements right after each irradiation step, and a complete functional characterization before and after irradiation. We observed that the main contribution to performance degradation in space applications comes from proton damage in the form of an increase in primary dark count rate (DCR) proportional to the proton fluence and a reduction in activation energy. In this context, small active area devices show a lower DCR before and after irradiation, and we propose light or charge-focusing mechanisms as future developments for high-sensitivity radiation-tolerant detectors.

A 64 × 128 3D-Stacked SPAD Image Sensor for Low-Light Imaging.

Low-light imaging capabilities are in urgent demand in many fields, such as security surveillance, night-time autonomous driving, wilderness rescue, and environmental monitoring. The excellent performance of SPAD devices gives them significant potential for applications in low-light imaging. This article presents a 64 (rows) × 128 (columns) SPAD image sensor designed for low-light imaging. The chip utilizes a three-dimensional stacking architecture and microlens technology, combined with compact gated pixel circuits designed with thick-gate MOS transistors, which further enhance the SPAD's photosensitivity. The configurable digital control circuit allows for the adjustment of exposure time, enabling the sensor to adapt to different lighting conditions. The chip exhibits very low dark noise levels, with an average DCR of 41.5 cps at 2.4 V excess bias voltage. Additionally, it employs a denoising algorithm specifically developed for the SPAD image sensor, achieving two-dimensional grayscale imaging under 6 × 10-4 lux illumination conditions, demonstrating excellent low-light imaging capabilities. The chip designed in this paper fully leverages the performance advantages of SPAD image sensors and holds promise for applications in various fields requiring low-light imaging capabilities.

Underwater Single-Photon 3D Reconstruction Algorithm Based on K-Nearest Neighbor.

The high sensitivity and picosecond time resolution of single-photon avalanche diodes (SPADs) can improve the operational range and imaging accuracy of underwater detection systems. When an underwater SPAD imaging system is used to detect targets, backward-scattering caused by particles in water often results in the poor quality of the reconstructed underwater image. Although methods such as simple pixel accumulation have been proven to be effective for time-photon histogram reconstruction, they perform unsatisfactorily in a highly scattering environment. Therefore, new reconstruction methods are necessary for underwater SPAD detection to obtain high-resolution images. In this paper, we propose an algorithm that reconstructs high-resolution depth profiles of underwater targets from a time-photon histogram by employing the K-nearest neighbor (KNN) to classify multiple targets and the background. The results contribute to the performance of pixel accumulation and depth estimation algorithms such as pixel cross-correlation and ManiPoP. We use public experimental data sets and underwater simulation data to verify the effectiveness of the proposed algorithm. The results of our algorithm show that the root mean square errors (RMSEs) of land targets and simulated underwater targets are reduced by 57.12% and 23.45%, respectively, achieving high-resolution single-photon depth profile reconstruction.

Research on SPAD Estimation Model for Spring Wheat Booting Stage Based on Hyperspectral Analysis.

With the rapid progression of agricultural informatization technology, the methodologies of crop monitoring based on spectral technology are constantly upgraded. In order to carry out the efficient, precise and nondestructive detection of relative chlorophyll (SPAD) during the booting stage, we acquired hyperspectral reflectance data about spring wheat vertical distribution and adopted the fractional-order differential to transform the raw spectral data. After that, based on correlation analysis, fractional differential spectra and fractional differential spectral indices with strong correlation with SPAD were screened and fused. Then, the least-squares support vector machine (LSSSVM) and the least-squares support vector machine (SMA-LSSSVM) optimized on the slime mold algorithm were applied to construct the estimation models of SPAD, and the model accuracy was assessed to screen the optimal estimation models. The results showed that the 0.4 order fractional-order differential spectra had the highest correlation with SPAD, which was 9.3% higher than the maximum correlation coefficient of the original spectra; the constructed two-band differential spectral indices were more sensitive to SPAD than the single differential spectra, in which the correlation reached the highest level of 0.724. The SMA-LSSSVM model constructed based on the two-band fractional-order differential spectral indices was better than the single differential spectra and the integration of both, which realized the assessment of wheat SPAD.

Correlation-Assisted Pixel Array for Direct Time of Flight.

Time of flight is promising technology in machine vision and sensing, with an emerging need for low power consumption, a high image resolution, and reliable operation in high ambient light conditions. Therefore, we propose a novel direct time-of-flight pixel using the single-photon avalanche diode (SPAD) sensor, with an in-pixel averaging method to suppress ambient light and detect the laser pulse arrival time. The system utilizes two orthogonal sinusoidal signals applied to the pixel as inputs, which are synchronized with a pulsed laser source. The detected signal phase indicates the arrival time. To evaluate the proposed system's potential, we developed analytical and statistical models for assessing the phase error and precision of the arrival time under varying ambient light levels. The pixel simulation showed that the phase precision is less than 1% of the detection range when the ambient-to-signal ratio is 120. A proof-of-concept pixel array prototype was fabricated and characterized to validate the system's performance. The pixel consumed, on average, 40 µW of power in operation with ambient light. The results demonstrate that the system can operate effectively under varying ambient light conditions and its potential for customization based on specific application requirements. This paper concludes by discussing the system's performance relative to the existing direct time-of-flight technologies, identifying their strengths and limitations.

A Method to Correct the Temporal Drift of Single-Photon Detectors Based on Asynchronous Quantum Ghost Imaging.

Single-photon detection and timing has attracted increasing interest in recent years due to their necessity in the field of quantum sensing and the advantages of single-quanta detection in the field of low-level light imaging. While simple bucket detectors are mature enough for commercial applications, more complex imaging detectors are still a field of research comprising mostly prototype-level detectors. A major problem in these detectors is the implementation of in-pixel timing circuitry, especially for two-dimensional imagers. One of the most promising approaches is the use of voltage-controlled ring resonators in every pixel. Each of these runs independently based on a voltage supplied by a global reference. However, this yields the problem that the supply voltage can change across the chip which, in turn, changes the period of the ring resonator. Due to additional parasitic effects, this problem can worsen with increasing measurement time, leading to drift in the timing information. We present here a method to identify and correct such temporal drifts in single-photon detectors based on asynchronous quantum ghost imaging. We also show the effect of this correction on recent quantum ghost imaging (QGI) measurement from our group.

Resolving the Emission Transition Dipole Moments of Single Doubly Excited Seeded Nanorods via Heralded Defocused Imaging.

Semiconductor nanocrystal emission polarization is a crucial probe of nanocrystal physics and an essential factor for nanocrystal-based technologies. While the transition dipole moment for the lowest excited state to ground state transition is well characterized, the dipole moment of higher multiexcitonic transitions is inaccessible via most spectroscopy techniques. Here, we realize direct characterization of the doubly excited-state relaxation transition dipole by heralded defocused imaging. Defocused imaging maps the dipole emission pattern onto a fast single-photon avalanche diode detector array, allowing the postselection of photon pairs emitted from the biexciton-exciton emission cascade and resolving the differences in transition dipole moments. Type-I1/2 seeded nanorods exhibit higher anisotropy of the biexciton-to-exciton transition compared to the exciton-to-ground state transition. In contrast, type-II seeded nanorods display a reduction of biexciton emission anisotropy. These findings are rationalized in terms of an interplay between the transient dynamics of the refractive index and the excitonic fine structure.

Simultaneously predicting SPAD and water content in rice leaves using hyperspectral imaging with deep multi-task regression and transfer component analysis.

BACKGROUND: Water content and chlorophyll content are important indicators for monitoring rice growth status. Simultaneous detection of water content and chlorophyll content is of significance. Different varieties of rice show differences in phenotype, resulting in the difficulties of establishing a universal model. In this study, hyperspectral imaging was used to detect the Soil and Plant Analyzer Development (SPAD) values and water content of fresh rice leaves of three rice varieties (Jiahua 1, Xiushui 121 and Xiushui 134). RESULTS: Both partial least squares regression and convolutional neural networks were used to establish single-task and multi-task models. Transfer component analysis (TCA) was used as transfer learning to learn the common features to achieve an approximate identical distribution between any two varieties. Single-task and multi-task models were also built using the features of the source domain, and these models were applied to the target domain. These results indicated that for models of each rice variety the prediction accuracy of most multi-task models was close to that of single-task models. As for TCA, the results showed that the single-task model achieved good performance for all transfer learning tasks. CONCLUSION: Compared with the original model, good and differentiated results were obtained for the models using features learned by TCA for both the source domain and target domain. The multi-task models could be constructed to predict SPAD values and water content simultaneously and then transferred to another rice variety, which could improve the efficiency of model construction and realize rapid detection of rice growth indicators. © 2024 Society of Chemical Industry.

High Frequency of Specific Polysaccharide Antibody Deficiency in Adults With Unexplained, Recurrent and/or Severe Infections With Encapsulated Bacteria.

BACKGROUND: Primary immunodeficiencies (PIDs) in adults are mainly revealed by recurrent and/or severe bacterial infections. The objective of this study was to evaluate a systematic research strategy of PIDs in adults with unexplained bacterial infections, with a special focus on specific polysaccharide antibody deficiency (SPAD). METHODS: In this prospective multicenter study, inclusion criteria were recurrent benign upper and lower respiratory tract infections (RTIs) for at least two years (group 1), at least one upper or lower RTI requiring hospitalization (group 2), and/or at least one invasive infection documented with encapsulated bacteria (group 3). Main exclusion criteria were all local and general conditions that could explain infections. If no PID diagnosis was made, response to polysaccharide antigens was assessed using a pneumococcal polysaccharide vaccine. RESULTS: From March 2015 to March 2020, 118 patients were included (37 males, median age of 41 years): 73, 17, and 28 in groups 1, 2, and 3, respectively. Forty-seven PIDs were diagnosed, giving an estimated frequency of 39.8% (95% confidence interval [CI] [30.4, 48.8]). SPAD was the most frequent diagnosis by far (n = 37/47, 78.7%), and was made in 23, 5, and 9 patients from groups 1 to 3, respectively. All SPAD patients received conjugate vaccines and, according to their infectious history, were on surveillance or treated with preventive antibiotics (n = 6) and/or with immunoglobulins replacement therapy (n = 10), the latter being dramatically efficient in all cases. CONCLUSIONS: Considering its high prevalence among adults with unexplained recurrent and/or severe bacterial infections, SPAD should be screened in those patients. CLINICAL TRIALS REGISTRATION: NCT02972281.

Transcriptome modulation by endophyte drives rice seedlings response to Pb stress.

This study investigated the growth, SPAD value, chlorophyll fluorescence and transcriptome response of endophyte uninoculated and inoculated rice seedlings under Pb stress after treatment of 1 d and 5 d. Inoculation of endophytes significantly improved the plant height, SPAD value, Fv/F0, Fv/Fm and PIABS by 1.29, 1.73, 0.16, 1.25 and 1.90 times on the 1 d, by 1.07, 2.45, 0.11, 1.59 and 7.90 times on the 5 d, respectively, however, decreased the root length by 1.11 and 1.65 times on the 1 d and 5 d, respectively under Pb stress. Analysis of rice seedlings leaves by RNA-seq, there were 574 down-regulated and 918 up-regulated genes after treatment of 1 d, 205 down-regulated and 127 up-regulated genes after treatment of 5 d, of which 20 genes (11 up-regulated and 9 down-regulated) exhibited the same changing pattern after treatment of 1 d and 5 d. Using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) to annotate these DEGs, and it was found that many of DEGs involved in photosynthesis, oxidative detoxification, hormone synthesis and signal transduction, protein phosphorylation/kinase and transcription factors. These findings provide new insights into the molecular mechanism of interaction between endophyte and plants under heavy metal stress, and contribute to agricultural production in limited environments.

A dToF Ranging Sensor with Accurate Photon Detector Measurements for LiDAR Applications.

Direct time-of-flight (dToF) ranging sensors based on single-photon avalanche diodes (SPADs) have been used as a prominent depth-sensing devices. Time-to-digital converters (TDCs) and histogram builders have become the standard for dToF sensors. However, one of the main current issues is the bin width of the histogram, which limits the accuracy of depth without TDC architecture modifications. SPAD-based light detection and ranging (LiDAR) systems require new methods to overcome their inherent drawbacks for accurate 3D ranging. In this work, we report an optimal matched filter to process the raw data of the histogram to obtain high-accuracy depth. This method is performed by feeding the raw data of the histogram into the different matched filters and using the Center-of-Mass (CoM) algorithm for depth extraction. Comparing the measurement results of different matched filters, the filter with the highest depth accuracy can be obtained. Finally, we implemented a dToF system-on-chip (SoC) ranging sensor. The sensor is made of a configurable array of 16 × 16 SPADs, a 940 nm vertical-cavity surface-emitting laser (VCSEL), an integrated VCSEL driver, and an embedded microcontroller unit (MCU) core to implement the best matched filter. To achieve suitably high reliability and low cost, the above-mentioned features are all packaged into one module for ranging. The system resulted in a precision of better than 5 mm within 6 m with 80% reflectance of the target, and had a precision better than 8 mm at a distance within 4 m with 18% reflectance of the target.

A 3.06 µm Single-Photon Avalanche Diode Pixel with Embedded Metal Contact and Power Grid on Deep Trench Pixel Isolation for High-Resolution Photon Counting.

In this study, a 3.06 µm pitch single-photon avalanche diode (SPAD) pixel with an embedded metal contact and power grid on two-step deep trench isolation in the pixel is presented. The embedded metal contact can suppress edge breakdown and reduce the dark count rate to 15.8 cps with the optimized potential design. The embedded metal for the contact is also used as an optical shield and a low crosstalk probability of 0.4% is achieved, while the photon detection efficiency is as high as 57%. In addition, the integration of a power grid and the polysilicon resistor on SPAD pixels can help to reduce the voltage drop in anode power supply and reduce the power consumption with SPAD multiplication, respectively, in a large SPAD pixel array for a high-resolution photon-counting image sensor.

First-Arrival Differential Counting for SPAD Array Design.

We present a novel architecture for the design of single-photon detecting arrays that captures relative intensity or timing information from a scene, rather than absolute. The proposed method for capturing relative information between pixels or groups of pixels requires very little circuitry, and thus allows for a significantly higher pixel packing factor than is possible with per-pixel TDC approaches. The inherently compressive nature of the differential measurements also reduces data throughput and lends itself to physical implementations of compressed sensing, such as Haar wavelets. We demonstrate this technique for HDR imaging and LiDAR, and describe possible future applications.

Analysis of Cadmium Contamination in Lettuce (Lactuca sativa L.) Using Visible-Near Infrared Reflectance Spectroscopy.

In order to rapidly and accurately monitor cadmium contamination in lettuce and understand the growth conditions of lettuce under cadmium pollution, lettuce is used as the test material. Under different concentrations of cadmium stress and at different growth stages, relative chlorophyll content of lettuce leaves, the cadmium content in the leaves, and the visible-near infrared reflectance spectra are detected and analyzed. An inversion model of the cadmium content and relative chlorophyll content in the lettuce leaves is established. The results indicate that cadmium concentrations of 1 mg/kg and 5 mg/kg promote relative chlorophyll content, while concentrations of 10 mg/kg and 20 mg/kg inhibit relative chlorophyll content. The cadmium content in the leaves increases with increasing cadmium concentrations. Cadmium stress caused a "blue shift" in the red edge position only during the mature period, while the red valley position underwent a "blue shift" during the seedling and growth periods and a "red shift" during the mature period. The green peak position exhibited a "blue shift". After model validation, it was found that the model constructed using the ratio of red edge area to yellow edge area and the normalized values of red edge area and yellow edge area effectively estimated the cadmium content in lettuce leaves. The model established using the normalized vegetation index of the red edge and the ratio of the peak green value to red shoulder amplitude can effectively estimate the relative chlorophyll content in lettuce leaves. This study demonstrates that the visible-near infrared spectroscopy technique holds great potential for monitoring cadmium contamination and estimating chlorophyll content in lettuce.

Multi-Channel Gating Chip in 0.18 µm High-Voltage CMOS for Quantum Applications.

A gating circuit for a photonic quantum simulator is introduced. The gating circuit uses a large excess bias voltage of up to 9.9 V and an integrated single-photon avalanche diode (SPAD). Nine channels are monolithically implemented in an application-specific integrated circuit (ASIC) including nine SPADs using 0.18 µm high-voltage CMOS technology. The gating circuit achieves rise and fall times of 480 ps and 280 ps, respectively, and a minimum full-width-at-half-maximum pulse width of 1.26 ns. Thanks to a fast and sensitive comparator, a detection threshold for avalanche events of less than 100 mV is possible. The power consumption of all nine channels is about 250 mW in total. This gating chip is used to characterize the integrated SPADs. A photon detection probability of around 50% at 9.9 V excess bias and for a wavelength of 635 nm is found.

Pion Detection Using Single Photon Avalanche Diodes.

We present the first reported use of a CMOS-compatible single photon avalanche diode (SPAD) array for the detection of high-energy charged particles, specifically pions, using the Super Proton Synchrotron at CERN, the European Organization for Nuclear Research. The results confirm the detection of incident high-energy pions at 120 GeV, minimally ionizing, which complements the variety of ionizing radiation that can be detected with CMOS SPADs.

N-Channel MOSFET Reliability Issue Induced by Visible/Near-Infrared Photons in Image Sensors.

Image sensors such as single-photon avalanched diode (SPAD) arrays typically adopt in-pixel quenching and readout circuits, and the under-illumination first-stage readout circuits often employs high-threshold input/output (I/O) or thick-oxide metal-oxide-semiconductor field-effect transistors (MOSFETs). We have observed reliability issues with high-threshold n-channel MOSFETs when they are exposed to strong visible light. The specific stress conditions have been applied to observe the drain current (Id) variations as a function of gate voltage. The experimental results indicate that photo-induced hot electrons generate interface trap states, leading to Id degradation including increased off-state current (Ioff) and decreased on-state current (Ion). The increased Ioff further activates parasitic bipolar junction transistors (BJT). This reliability issue can be avoided by forming an inversion layer in the channel under appropriate bias conditions or by reducing the incident photon energy.