Spectral Separation Research Articles

Color-tunable persistent luminescence in 1D zinc–organic halide microcrystals for single-component white light and temperature-gating optical waveguides

Information security of photonic communications has become an important societal issue and can be greatly improved when photonic signals are propagated through active waveguides with tunable wavelengths in different time and space domains. Moreover, the development of active waveguides that can work efficiently at extreme temperatures is highly desirable but remains a challenge. Herein, we report new types of low-dimensional Zn(ii)–organic halide microcrystals with fluorescence and room-temperature phosphorescence (RTP) dual emission for use as 1D color-tunable active waveguides. Benefiting from strong intermolecular interactions (i.e., hydrogen bonds and π–π interactions), these robust waveguide systems exhibit colorful photonic signals and structural stability at a wide range of extreme simulated temperatures (>300 K), that covers natural conditions on Earth, Mars, and the Moon. Both experimental and theoretical studies demonstrate that the molecular self-assembly can regulate the singlet and triplet excitons to allow thermally assisted spectral separation of fluorescence and RTP, in combination with the single-component standard white-light emission. Therefore, this work demonstrates the first use of metal–organic halide microcrystals as temperature-gating active waveguides with promising implications for high-security information communications and high-resolution micro/nanophotonics.

Activatable photothermal agents with target-initiated large spectral separation for highly effective reduction of side effects.

Photothermal agents (PTAs) with minimized side effects are critical for transforming cancer photothermal therapy (PTT) into clinical applications. However, most currently available PTAs lack true selective activation to reduce side effects because of heavy spectral overlap between photothermal agents and their corresponding products. This study reports the construction of activatable PTAs with target-initiated large spectral separation for highly effective reduction of side effects. Such designed probes involve two H2O2-activatable PTAs, aza-BOD-B1 (single activatable site) and aza-BOD-B2 (multiple activatable site). After interacting with H2O2, aza-BOD-B1 only displays a mild absorption redshift (60 nm) from 750 nm to 810 nm with serious spectral overlap, resulting in a mild photothermal effect on normal tissues upon 808 nm light irradiation. In contrast, aza-BOD-B2 displays a large absorption spectral separation (150 nm) from 660 nm to 810 nm, achieving true selective activation to minimize side effects during PTT of cancer. Besides, in vitro and in vivo investigations demonstrated that aza-BOD-B2 can specifically induce photothermal ablation of cancer cells and tumors while leaving normal sites undamaged, whereas aza-BOD-B1 exhibits undesirable side effects on normal cells. Our study provides a practical solution to the problem of undesired side effects of phototherapy, an advance in precision medicine.

Hyperspectral Remote Sensing Detection of Marine Oil Spills Using an Adaptive Long-Term Moment Estimation Optimizer

Marine oil spills can damage marine ecosystems, economic development, and human health. It is important to accurately identify the type of oil spills and detect the thickness of oil films on the sea surface to obtain the amount of oil spill for on-site emergency responses and scientific decision-making. Optical remote sensing is an important method for marine oil-spill detection and identification. In this study, hyperspectral images of five types of oil spills were obtained using unmanned aerial vehicles (UAV). To address the poor spectral separability between different types of light oils and weak spectral differences in heavy oils with different thicknesses, we propose the adaptive long-term moment estimation (ALTME) optimizer, which cumulatively learns the spectral characteristics and then builds a marine oil-spill detection model based on a one-dimensional convolutional neural network. The results of the detection experiment show that the ALTME optimizer can store in memory multiple batches of long-term oil-spill spectral information, accurately identify the type of oil spills, and detect different thicknesses of oil films. The overall detection accuracy is larger than 98.09%, and the Kappa coefficient is larger than 0.970. The F1-score for the recognition of light-oil types is larger than 0.971, and the F1-score for detecting films of heavy oils with different film thicknesses is larger than 0.980. The proposed optimizer also performs well on a public hyperspectral dataset. We further carried out a feasibility study on oil-spill detection using UAV thermal infrared remote sensing technology, and the results show its potential for oil-spill detection in strong sunlight.

In-Plane Strain Measurement in Composite Structures with Fiber Bragg Grating Written in Side-Hole Elliptical Core Optical Fiber.

In this paper, the application of a fiber Bragg grating written in a highly birefringent side-hole elliptical core optical fiber for two-axial strain measurement is presented. Hybrid optical fiber structures achieved by combining large side-holes and elliptical core result in a very high birefringence of 1 × 10−3 and thus high initial Bragg peak spectral separation of 1.16 nm, as well as a very high transverse force sensitivity, of up to 650 pm/(N/mm) or even −1150 pm/(N/mm), depending on the fiber orientation with respect to the applied force. Due to the ~22 %m/m GeO2 concentration in the core the fiber being highly photosensitive, which significantly simplifies FBG fabrication by UV illumination without the need for prior hydrogen loading, which worsens thermal stability. Finally, the developed FBGs written in the highly birefringent side-hole elliptical core optical fiber were embedded in the square composite plates and applied for strain measurements. Tests of two-directional four-point bending have shown usability of such FBG for two-axial in-plane strain measurement with a single FBG in iso-thermal conditions.

Simultaneous investigation of thermal and vapour concentration fields around an impinging droplet using dual wavelength interferometry

We report simultaneous investigation of temperature and vapour concentration fields around an evaporating droplet as it impinges on a heated surface using the concept of dual wavelength interferometry. Experiments have been conducted with acetone as the model fluid. To decouple the temperature and vapour concentration fields from a single interferogram, the interferometer employs two light sources of considerable spectral separation (λBlue= 458 nm and λRed= 632.8 nm). Dynamical aspects of impinging and evaporating droplet have been simultaneously recorded using high speed videography. Results have been presented in the form of spatio-temporally resolved temperature and concentration fields along with their polar plots around the droplet interface at different stages of droplet evaporation process. During the initial spreading phase, dominance of contact line evaporation was captured in quantitative terms as densely-spaced temperature and mole fraction contours in these regions. The spreading and receding phase of the droplet is followed by its sessile phase wherein polar plots of the transported properties indicated towards continuous evaporation at droplet interface with contact line evaporation being the dominant mechanism. Plausible signatures of thermo-capillary convection along the droplet interface have been explained on the basis of interferometric measurements. To the best of our knowledge, the work reported is one of the first attempts to simultaneously map the spatio-temporally resolved thermal and vapour concentration fields around an evaporating droplet and is important since the phenomenon of droplet heat transfer is governed by the coupled mechanisms of diffusion and buoyancy-induced convection, which, in turn, are affected by temperature and concentration distributions around the droplet.

Is it possible to use spectral signatures of materials in the visible and near-infrared range to identify real targets?

Using existing methods to identify and find goals in different fields, the method of using spectral signatures of materials in naval domain is important because of the more precision and fingerprinting properties of each material. If we have a spectral signature for a specific purpose, we will be able to easily identify it. However, when a material is combined at a significant level with another material, or so close that the emission and reflection of light reaches the sensor, we need spectral separation and spectral signature extraction of the combined materials. In this paper, we introduce two methods for distinguishing and identifying the signing of the spectrum of ambiguous goals that are combined with the specified materials in laboratorial environment. In these methods, by forming a matrix of data in the text of the sensor, we take the addition and subtraction operations on the data and eventually identify the target spectrum of the unknown. The first method is to deduct the spectrum of materials from the compound composition spectrum and the second method to combine the spectrum of the goals with the specified target spectrum. The method is similar to solving a first-order equation with an unknown one.

Six-primary-laser projection display system: demonstration and stereo color gamut measurement

The mainstream light sources of display systems currently include LEDs, OLEDs, micro-LEDs, and lasers, primarily based on the three primary color systems with different color rendering abilities. A narrow-spectrum light source, such as laser, is typically used to enlarge the color gamut of a display system. Another approach is to add more primaries. In this regard, we develop a six-primary-laser projection display system compatible with 2D and 3D display, with wavelengths of 445 nm, 465 nm, 520 nm, 550 nm, 638 nm and 660 nm. We propose a simple, fast method to determine the luminance of each primary laser, by which the gamut volume can be calculated. We also propose a gamut measurement method for the six-primary-laser display system, describe the gamut boundary, and measure the gamut volume. The calculated maximum color gamut of the proposed system is 2347400, corresponding to 184.49% NTSC, while the measured color gamut is 2269900, corresponding to 178.4% NTSC. These results are in good agreement with the theoretical calculations, indicating the accuracy of the proposed analytical and experimental methods. Moreover, the time-multiplexed stereoscopic display technology and the spectral separation method would allow the development of a remarkable three-dimensional visual experience with high light efficiency and low crosstalk in full-field of view.

Probing biexciton in monolayer WS2 through controlled many-body interaction

The monolayers of semiconducting transition metal dichalcogenides host strongly bound excitonic complexes and are an excellent platform for exploring many-body physics. Here we demonstrate a controlled kinetic manipulation of the five-particle excitonic complex, the charged biexciton, through a systematic dependence of the biexciton peak on excitation power, gate voltage, and temperature using steady-state and time-resolved photoluminescence. With the help of a combination of the experimental data and a rate equation model, we argue that the binding energy of the charged biexciton is less than the spectral separation of its peak from the neutral exciton. We also note that while the momentum-direct radiative recombination of the neutral exciton is restricted within the light cone, such restriction is relaxed for a charged biexciton recombination due to the presence of near-parallel excited and final states in the momentum space.

Low concentration Phloxine B staining for high chemical contrast, nonlinear microscope mosaic imaging of skin alterations in pseudoxanthoma elasticum.

Pseudoxanthoma elasticum (PXE) is an autosomal recessive metabolic disorder characterized by ectopic mineralization of soft connective tissue. Histopathology findings include fragmented, mineralized elastic fibers and calcium deposits in the mid-dermis. Nonlinear microscopy (NLM) can be used for visualization of these histopathological alterations of the mid-dermis in PXE-affected skin sections. Upon introducing a normalized 3D color vector representation of emission spectra of three of the main tissue components (collagen, elastin and calcification) we found that due to their broad, overlapping emission spectra, spectral separation of emission from elastin and calcification is practically impossible in fresh-frozen or unstained, deparaffinized PXE sections. However, we found that the application of a low concentration Phloxine B staining after the deparaffinization process creates an imaging contrast for these two tissue components, which enables spectral decomposition of their fluorescence images. The obtained concentration maps for calcium deposits can be well suited for the determination of illness severity by quantitative analysis.

Spin-Orbit Torque Nano-oscillators by Dipole-Field-Localized Spin Wave Modes.

We demonstrate a high-quality spin-orbit torque nano-oscillator comprised of spin wave modes confined by the magnetic field by the strongly inhomogeneous dipole field of a nearby micromagnet. This approach enables variable spatial confinement and systematic tuning of magnon spectrum and spectral separations for studying the impact of multimode interactions on auto-oscillations. We find these dipole-field-localized spin wave modes exhibit good characteristic properties as auto-oscillators─narrow line width and large amplitude─while persisting up to room temperature. We find that the line width of the lowest-lying localized mode is approximately proportional to temperature in good agreement with theoretical analysis of the impact of thermal fluctuations. This demonstration of a clean oscillator with tunable properties provides a powerful tool for understanding the fundamental limitations and line width contributions to improve future spin-Hall oscillators.

Mapping standing dead trees in temperate montane forests using a pixel- and object-based image fusion method and stereo WorldView-3 imagery

Information about the distribution of standing dead trees (SDT) is essential for forest biodiversity estimation, forest disturbances monitoring, and forest management strategy planning. Although remote sensing techniques offer unique capabilities to map SDT over large areas, three major hurdles exist: (1) the sporadic distribution of SDT in the study area; (2) often poor spectral separability between SDT and bare ground in forests; (3) the prominent spectral variability within SDT due to variations in background effect and canopy illumination. To address these problems, we proposed a pixel- and object-based image fusion (POBIF) approach using very high-resolution (VHR) stereo WorldView-3 (WV-3) data. The stereo WV-3 derived spectral bands, canopy height model (CHM), vegetation indices (VIs), and texture features were used as inputs in six classification scenarios with different variable combinations. A deep learning algorithm, deep neural network (DNN), and two machine learning algorithms, support vector machine (SVM) and random forest (RF), were utilized to process the pixel-based (PB) and object-based (OB) information. All PB and OB classifiers were then combined using a stacked generalization strategy to develop the POBIF model. Comparing the six scenarios we assessed the importance of the CHM, VIs, and textures for accurate SDT mapping. As a result, we found (1) the POBIF outperformed both PB and OB methods for SDT mapping, generating notably higher F1-score (p < 0.05); (2) Adding the CHM reduced the commission and omission errors caused by bare ground and artificial surfaces, and the highest classification accuracy was achieved when combing all the WV-3 derived variables; (3) SDT covered 0.89% of the forest areas in the study area and was particularly distributed on higher and steeper north-facing (northeast and northwest) slopes. Large tracts of SDT were found in the strictly protected forests. The study highlights the potential of VHR stereo WV-3 imagery and the POBIF for SDT mapping in a temperate montane forest area with high accuracy. The map created in this study could be used for guiding field investigations and for planning management measures.

K-edge coded aperture optimization for uniform illumination in compressive spectral X-ray tomosynthesis

Compressive spectral X-ray imaging (CSXI) introduces a pixelated spectral modulator called K-edge coded aperture (KCA) in front of the X-ray source, which enables both, lower dosage to the subject, as well as the capability of spectral tomography while using low-cost integrating X-ray detectors. CSXI systems generally use hundreds of different spectral modulators, each with a distinct pattern to uniquely modulate the illumination at every view angle. In contrast, this paper introduces the use of a single and static coded aperture placed in a tomosynthesis gantry. The compressive system thus interrogates the subject with a fixed coded illumination pattern on all view angles. The advantages of the system are many including reduced cost and the feasibility of implementation. Given the reduced set of coded measurement and the limited spectral separation ability in the resulting architecture, the nonlinear inverse reconstruction problem results in a highly ill-posed problem. An efficient alternating minimization method with three-dimensional total variation regularization is developed for image reconstruction. Furthermore, rather than simply using a random pattern, the coded aperture is optimized under a uniform sensing criterion that shapes the spatial and spectral pattern of the coded aperture so as to minimize the overall radiation exposure placed on any volumetric area of the patient. This is of particular importance in medical imaging where patients at risk are recommended to have periodical X-ray tomosynthesis screenings. The coded aperture optimization is then posed as a binary programming problem solved by a gradient-based algorithm with equilibrium constraints. Numerical experiments show that spatial and spectral coding used in the proposed system to interrogate the subject not only reduces the radiation dose but it also improves the quality of image reconstruction. Gains close to 5dB in peak signal to noise ratio are observed in simulations. Furthermore, it is shown that the optimization of the KCA can effectively improve the uniformity of X-ray radiation compared to random KCA modulation, thus reducing the radiation dose throughout all volumetric sub-areas of the subject — an objective that is not possible with the use of random KCAs.

Cucumber powdery mildew detection using hyperspectral data

This study aimed to understand the spectral changes induced by Podosphaera xanthii, the causal agent of powdery mildew, in cucumber leaves from the moment of inoculation until visible symptoms are apparent. A principal component analysis (PCA) was applied to the spectra to assess the spectral separability between healthy and infected leaves. A spectral ratio between infected and healthy leaf spectra was used to determine the best wavelengths for detecting the disease. Additionally, the spectra were used to compute two spectral variables [i.e., the red-well point (RWP) and the red-edge inflexion point (REP)]. A linear support vector machine (SVM) classifier was applied to certain spectral features to assess how well these features can separate the infected leaves from the healthy ones. The PCA showed that a good separability could be achieved from 4 days post-inoculation (DPI). The best model to fit the RWP and REP wavelengths corresponded to a linear model. The linear model had a higher adjusted R2 for the infected leaves than for the healthy leaves. The SVM trained with five first principal components scores achieved an overall accuracy of 95% at 4 DPI (i.e., two days before the visible symptoms). With the RWP and REP parameters, the SVM accuracy increased as a function of the day of inoculation, reaching 89% and 86%, respectively, when symptoms were visible at 6 DPI. Further research must consider a higher number of samples and more temporal repetitions of the experiment.

Influence of Spectral Filtration on Pulse Dynamics in Ring-Cavity Mamyshev Oscillator

Here we present a numerical study of pulsing build-up dynamics inside the fiber Mamyshev Oscillator (MO). The main scope of the investigation is to describe the influence of the spectral separation between the filters on self-starting MO dynamics and transition from multipulse to single-pulse generation regimes. It was found that Floquet stability analysis provides a straightforward way to determine whether the system will be self-starting or if it has to be excited by external source and predicts the repetition rate of the pulse train. We showed that spectrally overlapped bandpass filters provide reliable multi-pulse generation due to Faraday instability. Adiabatic increase in the spectral separation between the filters decreases the number of pulses down to single-pulse regime, therefore providing a flexible way to generate adjustable number of mode-locked pulses on demand.

Analysis of linear and non-linear effects in the frequency domain for a three-channel optical transmission system

This paper presents the analysis of a wavelength division multiplexer communication system in the frequency domain, with the objective of visualizing the incidence of the linear phenomena of attenuation and chromatic dispersion, together with the phenomenon of phase self-modulation, the Kerr electro-optical effect and fourth wave mixing. The analyzed system consists of a laser transmitter with a Mach-Zender modulator and a standard G.625b single-mode fiber link transmitting three optical signals of 10 mW, 25 mW and 50 mW at a fundamental wavelength of 1550 nm at a rate of 10 Gbps. This system is analyzed through a graphical user interface programmed by the authors in the Python environment, which calculates the parameters corresponding to each phenomenon and graphically represents the transmission results at distances of 50 km and 100 km. The analysis methodology consists of varying the spectral separation of the transmitted channels, initially considering a spectral separation of 2 nm and subsequently a spectral separation of 0.2 nm, observing as a result that the harmonics generated by the fourth wave mixing phenomenon considerably alter the spectral density of the transmitted signals, since the energy of the harmonics is equal to the power of the transmitted signals. On the other hand, with the spectral spacing of 0.2 nm, it is obtained that, although the harmonics alter the spectral density waveform, the bandwidth is not compromised by these additional signals.

Erratum: Spectral separation of the stochastic gravitational-wave background for LISA in the context of a modulated Galactic foreground

Erratum: Spectral separation of the stochastic gravitational-wave background for <i>LISA</i> in the context of a modulated Galactic foreground

Sensor System based on in-fiber Bragg Grats and Interrogator with Spectral Time Channel Separation

The principle of construction and a variant of the software and hardware implementation of the sensor system based on intra-fiber Bragg gratings (FBG) by the example of temperature measurement are proposed. The use of spectral-time separation of measuring channels, which takes into account the features of the functioning and placement of sensors based on FBGs, can significantly reduce the cost, dimensions, weight and power consumption of the interrogator, and neutralize the difficulties in setting up and periodic calibration typical for serial products. The test results of the system show the directions and prospects of using the developed equipment as part of portable and on-board monitoring and control systems.

Multi-Scale Spectral Separability of Submerged Aquatic Vegetation Species in a Freshwater Ecosystem

Optical remote sensing has been suggested as a preferred method for monitoring submerged aquatic vegetation (SAV), a critical component of freshwater ecosystems that is facing increasing pressures due to climate change and human disturbance. However, due to the limited prior application of remote sensing to mapping freshwater vegetation, major foundational knowledge gaps remain, specifically in terms of the specificity of the targets and the scales at which they can be monitored. The spectral separability of SAV from the St. Lawrence River, Ontario, Canada, was therefore examined at the leaf level (i.e., spectroradiometer) as well as at coarser spectral resolutions simulating airborne and satellite sensors commonly used in the SAV mapping literature. On a Leave-one-out Nearest Neighbor criterion (LNN) scale of values from 0 (inseparable) to 1 (entirely separable), an LNN criterion value between 0.82 (separating amongst all species) and 1 (separating between vegetation and non-vegetation) was achieved for samples collected in the peak-growing season from the leaf level spectroradiometer data. In contrast, samples from the late-growing season and those resampled to coarser spectral resolutions were less separable (e.g., inter-specific LNN reduction of 0.25 in late-growing season samples as compared to the peak-growing season, and of 0.28 after resampling to the spectral response of Landsat TM5). The same SAV species were also mapped from actual airborne hyperspectral imagery using target detection analyses to illustrate how theoretical fine-scale separability translates to anin situ, moderate-spatial scale application. Novel radiometric correction, georeferencing, and water column compensation methods were applied to optimize the imagery analyzed. The SAV was generally well detected (overall recall of 88% and 94% detecting individual vegetation classes and vegetation/non-vegetation, respectively). In comparison, underwater photographs manually interpreted by a group of experts (i.e., a conventional SAV survey method) tended to be more effective than target detection at identifying individual classes, though responses varied substantially. These findings demonstrated that hyperspectral remote sensing is a viable alternative to conventional methods for identifying SAV at the leaf level and for monitoring at larger spatial scales of interest to ecosystem managers and aquatic researchers.

Optimization of in vivo Cherenkov imaging dosimetry via spectral choices for ambient background lights and filtering.

.Significance: The Cherenkov emission spectrum overlaps with that of ambient room light sources. Choice of room lighting devices dramatically affects the efficient detection of Cherenkov emission during patient treatment.Aim: To determine optimal room light sources allowing Cherenkov emission imaging in normally lit radiotherapy treatment delivery rooms.Approach: A variety of commercial light sources and long-pass (LP) filters were surveyed for spectral band separation from the red to near-infrared Cherenkov light emitted by tissue. Their effects on signal-to-noise ratio (SNR), Cherenkov to background signal ratio, and image artifacts were quantified by imaging irradiated tissue equivalent phantoms with an intensified time-gated CMOS camera.Results: Because Cherenkov emission from tissue lies largely in the near-infrared spectrum, a controlled choice of ambient light that avoids this spectral band is ideal, along with a camera that is maximally sensitive to it. An RGB LED light source produced the best SNR out of all sources that mimic room light temperature. A 675-nm LP filter on the camera input further reduced ambient light detected (optical density > 3), achieving maximal SNR for Cherenkov emission near 40. Reduction of the room light signal reduced artifacts from specular reflection on the tissue surface and also minimized spurious Cherenkov signals from non-tissue features such as bolus.Conclusions: LP filtering during image acquisition for near-infrared light in tandem with narrow band LED illuminated rooms improves image quality, trading off the loss of red wavelengths for better removal of room light in the image. This spectral filtering is also critically important to remove specular reflection in the images and allow for imaging of Cherenkov emission through clear bolus. Beyond time-gated external beam therapy systems, the spectral separation methods can be utilized for background removal for continuous treatment delivery methods including proton pencil beam scanning systems and brachytherapy.

A Principal Components Analysis-Based Method for the Detection of Cannabis Plants Using Representation Data by Remote Sensing

Integrating the representation of the territory, through airborne remote sensing activities with hyperspectral and visible sensors, and managing complex data through dimensionality reduction for the identification of cannabis plantations, in Albania, is the focus of the research proposed by the multidisciplinary group of the Benecon University Consortium. In this study, principal components analysis (PCA) was used to remove redundant spectral information from multiband datasets. This makes it easier to identify the most prevalent spectral characteristics in most bands and those that are specific to only a few bands. The survey and airborne monitoring by hyperspectral sensors is carried out with an Itres CASI 1500 sensor owned by Benecon, characterized by a spectral range of 380–1050 nm and 288 configurable channels. The spectral configuration adopted for the research was developed specifically to maximize the spectral separability of cannabis. The ground resolution of the georeferenced cartographic data varies according to the flight planning, inserted in the aerial platform of an Italian Guardia di Finanza’s aircraft, in relation to the orography of the sites under investigation. The geodatabase, wherein the processing of hyperspectral and visible images converge, contains ancillary data such as digital aeronautical maps, digital terrain models, color orthophoto, topographic data and in any case a significant amount of data so that they can be processed synergistically. The goal is to create maps and predictive scenarios, through the application of the spectral angle mapper algorithm, of the cannabis plantations scattered throughout the area. The protocol consists of comparing the spectral data acquired with the CASI1500 airborne sensor and the spectral signature of the cannabis leaves that have been acquired in the laboratory with ASD Fieldspec PRO FR spectrometers. These scientific studies have demonstrated how it is possible to achieve ex ante control of the evolution of the phenomenon itself for monitoring the cultivation of cannabis plantations.