Spectral Sensitivity Research Articles

Integration and first operation of the Gotthard-II detector at European XFEL

Gotthard-II (G-II) is a 1-D silicon microstrip hybrid detector developed by the Paul Scherrer Institut within the framework of a collaboration agreement with the European XFEL. The ASIC features a dynamic gain switching architecture, in order to cope with the luminosity of European XFEL, and a 12-bit analog-to-digital converter with a sampling/conversion rate of more than 18 MS/s as well as a Static random-access memory, making it capable of matching the European XFEL pulse train structure, thus acquiring up to 2700 images at 4.5 MHz per burst. The sensor’s strip pitch can be either of 50 μm or 25 μm , for a total of 1280 or 2560 output channels per detector, respectively, with a spectral sensitivity that allows either X-ray detection (optimized in the 5–20 keV range) or visible light detection. Its exceptionally good compliance with the European XFEL beam conditions will make G-II the most widely employed detector across the facility, with a total of 29 modules of different flavors that will be installed in scientific instruments and beam diagnostic setups. Although the detector will be predominantly used for spectroscopic measurements it will have a variety of other applications, including X-ray diffraction/emission/absorption experiments, relative pulse arrival time monitoring (of fundamental importance for pump–probe experiments), spectral diagnostics, and beam quality monitoring, with the possibility for the detector itself to generate a veto patterns for the large area MHz framerate pixel detectors employed at the scientific instruments, such as AGIPD, LPD and DSSC. In this paper, an overview of G-II detector technology and its usage at the European XFEL will be presented; the focus will then move on towards the process of detector integration in the European XFEL control system, data acquisition, and data correction infrastructure, highlighting its challenges. Finally, an overview of the first results obtained at scientific instruments will be given.

Accuracy Assessment of different classifiers for Sustainable Development in Landuse and Landcover mapping using Sentinel SAR and Landsat-8 data

Sentinel satellites make use of Synthetic Aperture Radar (SAR) which produces images with backscattered signals at fine spatial resolution from 10 m to 50 m. This study is mainly focused on evaluating and assessing the accuracy of various supervised classifiers like Random Forest classifier, Minimum Distance to mean classifier, KDTree KNN classifier, and Maximum Likelihood classifier for landuse / landcover mapping in Maduranthakam Taluk, Kancheepuram district, Tamilnadu, India. These classifiers are widely used for classifying the Sentinel SAR images. The SAR images were processed using speckle and terrain correction and converted to backscattered energy. The training datasets for the landcover classes, such as vegetation, waterbodies, settlement, and barren land, were collected from Google Earth images in high-resolution mode. These collected training datasets were given as input for the various classifiers during the classification. The obtained classified output results of various classifiers were analyzed and compared using the overall classification accuracy. The overall accuracy achieved by the Random Forest classifier for the polarization VV and VH was 92.86%, whereas the classified accuracy of various classifiers such as KDTree KNN, Minimum distance to mean, and Maximum Likelihood are found to be 81.68%, 83.17%, and 85.64% respectively. The random forest classifier yields a higher classification accuracy value due to its greater stability in allocating the pixels to the right landuse class. In order to compare and validate the results with sentinel data, the random classifier is applied with optical Landsat-8 satellite data. The classification accuracy obtained for Landsat-8 data is 84.61%. It is clearly proved that the random forest classifier with sentinel data gives the best classification accuracy results due to its high spatial resolution and spectral sensitivity. Thus accurate landuse and landcover mapping promote sustainable development by supporting decision-making at local, regional, and national levels.

Spectral Tunability, Luminescence Enhancement, and Temperature Sensitivity of Sb3+-Doped Bismuth-Based Halide Emission Crystals for Anti-Counterfeiting Applications.

The synthesis of sustainable luminescent materials with simplicity, low energy consumption, and nontoxicity is of great importance in the field of chemistry and materials science. In this study, a room temperature evaporation method was employed to synthesize Sb3+-doped bismuth-based halide emission crystals, allowing for investigation of spectral tuning, luminescence enhancement, and temperature sensitivity. By substitution of Rb+ with varying concentrations of Cs+ in Rb3BiCl6 (RBC), the luminescent color of the crystals can be tuned from orange to yellow. The resulting alloyed yellow-emitting crystals were identified as Rb2CsBiCl6 (RCBC). Remarkably, when one-third of the Rb+ ions were replaced by Cs+ in the RBC, the crystals exhibited improved thermal stability and a 20-fold increase in luminescence intensity. The temperature-sensitive behavior was observed for RBC:Sb, with emission shifting from 590 to 574 nm upon heating while the yellow emission of RCBC:Sb exhibited no significant peak shift with temperature. Notably, the yellow emission of RBC:Sb could be reversibly converted back to orange light upon cooling to room temperature. In contrast, RCBC:Sb exhibited no significant peak shift with temperature. The differential temperature sensitivity between RBC:Sb and RCBC:Sb offers potential applications in anti-counterfeiting measures.

Switching and photosensitive analysis of dopingless tunnel field effect transistor based on cladding layer concept

— In this paper, the switching and photo sensing analysis of cladding layer based dopingless Tunnel FET (CDL-TFET) has been examined under visible range of spectrum. Initially, the impact of cladding layer in DL-TFET on electrical parameter is observed by varying the source material and thickness of source region. Furthermore, CDL-TFET is used for photo sensing application under the light state at various wavelength of light incident. The various optical figure of merits (FoMs) like spectral sensitivity (Sn), Signal to noise ratio (SNR), Responsivity (R), and quantum efficiency (η) is extracted to realize the behavior of photosensor. The maximum value of Sn is 48, R of 0.74 (A/Watt), SNR of 68.8 dB, and η of 3 are obtained at λ = 300 nm. Further, impurity trap charge effects are also observed at the interface and bulk of TFET. Finally, a comparison table has been presented to signify the importance of cladding layer based DL-TFET photo sensor with existing literature.

Photon-Counting CT Material Decomposition in Bone Imaging.

The accurate screening of osteoporosis is important for identifying persons at risk. The diagnosis of bone conditions using dual X-ray absorptiometry is limited to extracting areal bone mineral density (BMD) and fails to provide any structural information. Computed tomography (CT) is excellent for morphological imaging but not ideal for material quantification. Advanced photon-counting detector CT (PCD-CT) possesses high spectral sensitivity and material decomposition capabilities to simultaneously determine qualitative and quantitative information. In this study, we explored the diagnostic utility of PCD-CT to provide high-resolution 3-D imaging of bone microarchitecture and composition for the sensitive diagnosis of bone in untreated and ovariectomized rats. PCD-CT accurately decomposed the calcium content within hydroxyapatite phantoms (r = 0.99). MicroCT analysis of tibial bone revealed significant differences in the morphological parameters between the untreated and ovariectomized samples. However, differences in the structural parameters of the mandible between the treatment groups were not observed. BMD determined with microCT and calcium concentration decomposed using PCD-CT differed significantly between the treatment groups in both the tibia and mandible. Quantitative analysis with PCD-CT is sensitive in determining the distribution of calcium and water components in bone and may have utility in the screening and diagnosis of bone conditions such as osteoporosis.

Utilising spectral lighting simulation technique for evaluating transmitted daylight through glazing: Exploring the non-visual effects and colour appearance

Modern humans spend more time indoors than their ancestors. In indoor environments, windows are the primary building elements that provide access to daylight and views. The advancement of the building industry has introduced new glazing and coating technologies for windows. Electrochromic glazing, in particular, has gained popularity in recent decades. These glazings’ tint varies with light exposure and electrical voltage, affecting the spectral power distribution of transmitted daylight. The growing knowledge of the impacts of light on sleep and health encourages an evaluation of the non-visual effects of daylight transmitted through glazing. Therefore, the aim of this paper is to investigate the non-visual effects of transmitted daylight through one clear and one smart glazing and evaluate the colour appearance variations. However, conventional visualisation tools are inadequate for this purpose, necessitating the use of alternative techniques that consider the spectral power distribution of light. To accomplish this, the Radiance-based Lark spectral lighting simulation tool was utilised. The non-visual effects were analysed by examining the responses of the five photoreceptors (Short-, Medium-, Long-wavelength cones, Rods, and ipRGCs) to light using the CIE spectral sensitivity functions. Additionally, the changes in colour appearance were assessed using six attributes: lightness, hue, chroma, vividness, depth, and clarity. The results demonstrate the effect of the studied glazing on non-visual light stimulation and colour appearance while presenting the challenges, applicability, and limitations of spectral simulation techniques. The proposed method yields promising results and can be a valuable tool for evaluating the effects of glazing on humans.

Design of a novel D-shaped SPR sensor with high sensitivity based on PCF for ultra-low refractive index detection

In this paper, a novel D-shaped plasmon resonance sensor based on photonic crystal fiber (PCF) is proposed to detect analytical materials with low refractive index. There are three arc-shaped small holes on both upper and lower edges of the fiber core, which can enhance the surface plasmon effect. The operation wavelength of the sensor is from 2243 nm to 2651 nm when its measurable refractive index range is between 1.17 and 1.27. The maximum spectral sensitivity of the sensor can be reached to 20 300 nm RIU−1, and the optimal resolution is 4.93 × 10−6 RIU. In our knowledge, the current literature indicates that when the refractive index is less than 1.3, this is the sensor with the highest spectral sensitivity among the reported low refractive index PCF-surface plasmon resonance sensors.

Fiber-optic temperature sensor based on glass Fabry–Perot interferometer

The paper presents a theoretical and experimental study of a fiber-optic all-glass microthermometer based on a Fabry–Perot interferometer. The interferometer is fabricated by applying borosilicate glass to the cleaved end of a standard telecom single-mode optical fiber using a microforge. According to the results of experimental studies, the spectral sensitivity of the fabricated interferometer was about 40 pm/°C. A mathematical model of the Fabry–Perot interferometer based on the method of scattering and transfer matrices is presented and verified, which makes it possible to calculate the spectral response of an interferometer with arbitrary structure parameters.

Analysis of Infrared Spectral Radiance of O2 1.27 μm Band Based on Space-Based Limb Detection

The infrared spectral radiance of O2 is of great significance for space-based infrared detection. In this work, based on the demand for near-infrared spectral radiance of O2 limb detection, a method of spectral radiance calculation coupled with an atmospheric remote sensing model of limb detection is proposed. According to the selection criteria of fine spectral lines, the most suitable spectral lines of the O2 1.27 μm band for detection are given. Specifically, the limb infrared radiances of the O2 1.27 μm band were simulated by using the spectral line data from the spectral database, and the effects of molecular self-absorption were also considered. Furthermore, the infrared spectral radiance distribution of the O2 1.27 μm band was simulated under the influence of altitude, and finally, the detectability of the 1.27 μm band of O2 molecules was analyzed using the criteria of spectral line selection, radiance intensity, spectral separation range and temperature sensitivity. The calculation results show that the spectral radiance of the 1.27 μm band of O2 molecules first increases and then decreases with the decrease of the limb height, and the radiance reaches the peak value in the range of 40–50 km. In terms of the selection of spectral lines, the two groups of spectral lines R7R7, R7Q8 and R11R11, R11Q12 are most suitable for the limb detection and measurement of the O2 1.27 μm band.

Wide refractive index detection range sensors based on D-shape photonic crystal fiber with a nanoscale gold wire

Optical sensing based on photonic crystal fiber (PCF) is attracting interests. Currently, PCF sensing suffered from the insensitivity with the changes of environmental surroundings with low refractive index. A D-shape PCF supporting plasmonic resonances based on gold nanowires is designed to demonstrated the sensitivity optical sensing in the refractive index range from 1.00 to 1.30. The finite element method is performed to optimize the device parameters, including the diameter of the large and tiny air holes, the size of the gold nanowire, and the space between the air holes. Utilizing plasmon-induced confined electrical around gold nanowires, the predicted device performance in spectral and amplitude sensitivities are up to 19,400 nm/RIU and 5.15 × 10−6 RIU, respectively. It is believed that the designed sensor can promote the development of applications in biological and pharmaceutical.

Synthesis and characterization of a new azo quinoline ligand and its metal complexes with spectrophotometric determination and biological efficacy study of its Hg(II) complex

ABSTRACT. An azo quinoline ligand, (E)-2-((4-iodophenyl)diazenyl)-8-hydroxyquinoline (IPDHQ), was synthesized by the coupling reaction of 4-iodoaniline diazonium salt with 8-hydroxyquinoline. The synthesized ligand and its Cd(II), Pd(II), Cu(II) and Hg(II) complexes were spectrally characterized by UV‒Vis spectrophotometry, FT-IR, mass spectral analysis, 1H-NMR, magnetic sensitivity and molar conductivity. The general formula of the Cd(II), Cu(II) and Hg(II) complexes is [M(L)2].Cl2.H2O with octahedral geometry, while the general formula of the Pd(II) complex is [M(L).Cl2].H2O with square planer geometry. A simple and rapid spectrophotometric procedure was suggested for the determination of Hg(II) using the synthesized ligand as a spectrophotometric reagent. By measuring the absorbance for the resulting orange complex at 430 nm, the linearity range was 0.5-15 µg mL-1, and the interfering effect was also studied. The synthesized azo ligand and its Hg(Ⅱ) complex were tested for their biological activity against four bacterial strains.
 KEY WORDS: Azo quinoline ligand, 8-Hydroxy quinoline, 4-Iodoaniline, Azo metal complexes, Spectrophotometric determination, Biological efficacy study
 Bull. Chem. Soc. Ethiop. 2023, 37(6), 1459-1470. DOI: https://dx.doi.org/10.4314/bcse.v37i6.13

Prediction of Potassium Content in Rice Leaves Based on Spectral Features and Random Forests

The information acquisition about potassium, which affects the quality and yield of crops, is of great significance for crop nutrient management and intelligent decision making in smart agriculture. This article proposes a method for predicting the rice leaf potassium content (LKC) using spectral characteristics and random forests (RF). The method screens spectral characteristic variables based on the linear correlation analysis results of rice LKC and four transformed spectra (original reflectance (R), first derivative reflectance (FDR), continuum-removed reflectance (CRR), and normalized reflectance (NR)) of leaves and the PCA dimensionality reduction results of vegetation indices. Following a second screening of the correlated single band and vegetation index variables of the four transformed spectra, the RF is used to obtain the mixed variable (MV), and regression models are developed to achieve an accurate prediction of rice LKC. Additionally, the effect of potassium spectral sensitivity bands, indices, spectral transformation form, and different modeling methods on rice LKC prediction accuracy is assessed. The results showed that the mixed variable obtained with the second screening using the random forest feature selection method could effectively improve the prediction accuracy of rice LKC. The regression models based on the single band variables (BV) and the vegetation index variables (IV), FDR–RF and IV–RF, with R2 values of 0.62301 and 0.7387 and RMSE values of 0.24174 and 0.15045, respectively, are the best models. In comparison to the previous two models, the MV–RF validation had a higher R2 and a lower RMSE, reaching 0.77817 and 0.14913, respectively. It can be seen that the RF has a better processing ability for the MV that contains vegetation indices and IV than for the BV. Furthermore, the results of different variable screening and regression analyses also revealed that the single band’s range of 1402–1428 nm and 1871–1907 nm, as well as the vegetation indices constituted of reflectance 1799–1881 nm and 2276–2350 nm, are of great significance for predicting rice LKC. This conclusion can provide a reference for establishing a universal vegetation index related to potassium.

Spectral sensitivity of the compound eyes and behavioral attraction to light stimuli with different intensities and wavelengths in Lucilia sericata (Meigen, 1826) from Colombia

Lucilia sericata (Meigen, 1826) (Diptera: Calliphoridae) is a synanthropic fly with a worldwide distribution that pollinates plants and is relevant in medical, veterinary, and forensic sciences. L. sericata is a diurnal species whose vision plays an important role in spatial orientation. Here we evaluated the electrophysiological responses (ERG) of L. sericata’s compound eyes in adults of both sexes from Colombia and their behavioral attraction to LED lights with different wavelengths. The ERG revealed a dichromatic vision with peaks at blue (450 nm) and green (510-530 nm) wavelengths in individuals of both sexes. Behavioral experiments with a two-sided light tunnel showed that both sexes were mainly attracted to blue, white, and red lights of different intensities (0.34, 0.15, and 0.034 μW/cm2). Attraction to the lights decreased at lower intensities; however, attraction to blue, white, and red lights was still observed. The electrophysiological and behavioral results we obtained in the laboratory were complementary and explain how Colombian untrained L. sericata adults interact with their environment using mainly the sunlight wavelengths reflected under natural conditions.

Contributed Session I: Towards General Video Percepts Cone-by-Cone.

We aim to reprogram visual perception through an Adaptive Optics Scanning Laser Ophthalmoscope (AOSLO) Display, using a GPU renderer that rasterizes a target color image or video into cone-by-cone single-wavelength laser light pulses ("microdoses"). We imaged and tracked at ~ 2° eccentricity a 0.9° x 0.9° field of view of the retina in 840 nm. Stimulated in 543 nm, all resolved, spectrally classified cones receive microdoses of varying intensities. The renderer updates for each AOSLO frame (30 frames / sec) an underlying stimulation image buffer, encoding a desired color percept pattern that takes into account the cone locations, cone spectral sensitivity to the 543 nm stimulation light, and the corresponding color percept pixel values. Within one frame, the buffer gets pixelated strip-by-strip at 1 kHz into actual world-fixed microdose intensity values, each centered on a cone within that strip at that instant. The resulting frame of microdoses visually occupies the whole raster view. We showed multiple color percepts to a cone-classified subject, with logging data. The subject saw spatially-varying colors, e.g. a red box moving on a green canvas - these percepts validated the accuracy of the prototype. These initial prototyping experiments allude to the potential of presenting general percepts to a cone-classified subject, at cone-level accuracy in a fully programmable way. The technology allows us to probe neural plasticity and towards generation of novel percepts.

D-shaped microstructure fiber temperature sensor based on surface plasmon resonance

In order to solve the problems of oxidation of the metal film coated on the outer surface of the photonic crystal fiber and the low sensitivity of the sensor, a side polishing temperature sensor based on surface plasmon resonance is proposed. First, the sensor is modelled with a metal coating on the side of the optical fiber of the sensor, using a temperature sensitive liquid as the temperature sensing substance. Then, simulations were carried out to calculate the structural parameters of the optical fiber and the effect of the metal material on the resonant wavelength of the loss spectrum. By comparing the sensitive sensing of different metal films, gold was chosen as the surface plasma sensing material. Finally, the sensing characteristics of the sensor are simulated using the finite element method. The results show that when gold is used as the surface plasmon material, the wavelength range is 675–1117 nm, and the high sensitivity sensing in the temperature range of 0 °C–60 °C can be realized. When the temperature is 0 °C, the maximum spectral sensitivity is 24.6 nm °C−1. The designed sensors have excellent performance and can be widely used for temperature sensing.

Poster Session: Eliciting Color Percepts over Extended Fields through Cone-by-Cone Stimulation.

Purpose Human color vision is informed by the relative activations of the long-, medium-, and short-wavelength sensitive cones. We have developed a display that can produce a variety of color sensations using only a single wavelength of light, by programming the activity levels of the three cone types at population scales. Methods With an Adaptive Optics Scanning Laser Ophthalmoscope, we image the retina at 840 nm over a 0.9° x 0.9° field and track the eye's fixational motion in order to deliver discrete microdoses of 543 nm light to ~2500 individual cones per frame. Using each cone type's spectral sensitivity to 543 nm, we can recapitulate the relative activations consistent with colors that are distinct from the stimulating laser, resulting in percepts of uniform colored squares that appear stable in the world. Results Using stimulation from only 543 nm light, we can elicit color percepts ranging from green to red-orange in 2 subjects who have cone spectral types classified in a region of their retina. Additionally, we find through color matching data that the distinct color percepts are lost for intentional misdeliveries that exceed 30% of the cone diameter in both subjects. Conclusions These results demonstrate our system's ability to track the retina at high speed, stimulate with cone-level precision, and generate color percepts by directly programming the activity of the human cone mosaic. These technical capabilities provide a novel platform for studying color vision.

The morphology and spectral characteristics of the compound eye of Agasicleshygrophila (Selman & Vogt, 1971) (Coleoptera, Chrysomelidae, Galerucinae, Alticini).

The first exploratory study was conducted on the compound eye morphology and spectral characteristics of Agasicleshygrophila (Selman & Vogt, 1971) to clarify its eye structure and its spectral sensitivity. Scanning electron microscopy, paraffin sectioning, and transmission electron microscopy revealed that A.hygrophila has apposition compound eyes with both eucones and open rhabdom. The micro-computed tomography (CT) results after 3D reconstruction demonstrated the precise position of the compound eyes in the insect's head and suggested that the visual range was mainly concentrated in the front and on both sides of the head. The electroretinogram (ERG) experiment showed that red, yellow, green, blue, and ultraviolet light could stimulate the compound eyes of A.hygrophila to produce electrical signals. The behavioural experiment results showed that both males and females had the strongest phototaxis to yellow light and positive phototaxis to red, green, and blue light but negative phototaxis to UV light. This study of the compound eyes of A.hygrophila will be helpful for decoding its visual mechanism in future studies.

Laboratory Characterisation of a Commercial RGB CMOS Camera for Measuring Night Sky Brightness

The use of RGB cameras in photometric applications has grown over the last few decades in many fields such as industrial applications, light engineering and the analysis of the quality of the night sky. In this last field, they are often used in conjunction with a Sky Quality Meter (SQM), an instrument used for the measurement of night sky brightness (NSB), mainly when there is a significant amount of artificial light at night (ALAN). The performances of these two instruments are compared here. A simple source composed of nine narrowband LEDs in an integrating sphere was used to excite the two instruments and therefore measure the spectral responsivity of the SQM and of the three channels of the camera. The estimated uncertainties regarding spectral responsivity were less than 10%. A synthetic instrument approximating the SQM’s responsivity can be created using a combination of the R, G and B channels. The outputs of the two instruments were compared by measuring the spectral radiance of the night sky. An evaluation of the spectral mismatch between the two instruments completed the analysis of their spectral sensitivity. Finally, the measurements of real SQMs in four sites experiencing different levels of light pollution were compared with the values obtained by processing the recorded RGB images. Overall, the analysis shows that the two instruments have significantly different levels of spectral responsivity, and the alignment of their outputs requires the use of a correction which depends on the spectral distribution of the light coming from the sky. A synthetic SQM will always underestimate real SQM measures; an average correction factor was evaluated considering nine sky spectra under low and medium levels of light pollution; this was determined to be 1.11 and, on average, compensated for the gap. A linear correction was also supposed based on the correlation between the NSB levels measured by the two instruments; the mean squared error after the correction was 0.03 mag arcsec−2.

Calibrating Nighttime Satellite Imagery with Red Photometer Networks

The data retrieved from satellite imagery and ground-based photometers are the two main sources of information on light pollution and are thus the two main tools for tackling the problem of artificial light pollution at night (ALAN). While satellite data offer high spatial coverage, on the other hand, photometric data provide information with a higher degree of temporal resolution. Thus, studying the proper correlation between both sources will allow us to calibrate and integrate them to obtain data with both high temporal resolution and spatial coverage. For this purpose, more than 15,000 satellite measurements and 400,000 measurements from 72 photometers for the year 2022 were used. The photometers used were the Sky-Glow Wireless Autonomous Sensor (SG-WAS) and Telescope Encoder and Sky Sensor WIFI (TESS-W) types, located at different ground-based locations, mainly in Spain. These photometers have a spectral sensitivity closer to that of VIIRS than to the Sky Quality Meter (SQM). In this study, a good correlation of data from the Day–Night Band (DNB) from the Visible Infrared Imaging Radiometer Suite (VIIRS) with a red photometric network between 19.41 mag/arcsec2 and 21.12 mag/arcsec2 was obtained.

Study the Effect of Changing the Etching Current in a Si Nanostructure to Improve the Spectral Sensitivity of the Detector

Study the Effect of Changing the Etching Current in a Si Nanostructure to Improve the Spectral Sensitivity of the Detector