Middle Infrared Research Articles

Contribution to the Research of the Effects of Etna Volcano Activity on the Features of the Ionospheric Total Electron Content Behaviour

This research represents a contribution to the theory on the coupling of the volcanic activity and the ionospheric dynamics, represented by total electron content (TEC) patterns and their behaviour. The ionospheric response to the activity of the Etna volcano has been analysed using global navigation satellite system (GNSS)-derived TEC values, employing data from International GNSS Service (IGS) reference station near the volcano and on two distant IGS locations. Volcanic activity has been modelled using volcanic radiative power (VRP) data obtained by the Middle InfraRed Observation of Volcanic Activity (MIROVA) system. The estimated minimal night TEC values have been averaged over defined index days of the VRP increase. During the analysed period of 19 years, the volcano activity was categorised according to pre-defined criteria. The influence of current space weather and short-term solar activity on TEC near the volcano was systematically minimised. The results showed mean/median TEC increases of approximately +3 standard deviations from the overall mean values, with peak values placed approximately 5 days before the VRP increase and followed by general TEC depletion around the time of the actual volcanic activity increase. Additionally, TEC oscillation pattern was found over the volcano site with a half-period of 6.25 days. The main interpretation of results indicates that the volcanic activity has modified the ionospheric dynamics within the nearby ionospheric region before the actual VRP increase, and that the residual impact in the volcano’s surrounding area refers to terrestrial endogenous processes and air–earth currents. Those changes can be detected during criteria predefined in the research: during quiet space weather conditions, observing night-time TEC values and within the limits of low short-term solar influence.

Land Surface Temperature and Emissivity Retrieval from Nighttime Middle and Thermal Infrared Images of Chinese Fengyun-3D MERSI-II

The second-generation Chinese polar-orbit meteorological satellite Fengyun-3D carries the MEdium-Resolution Spectral Imager (MERSI-II). MERSI-II has 19 solar channels and 6 middle and thermal infrared channels and can provide daily global coverage observation at daytime and nighttime. Land surface temperature (LST) products have a wide range of application requirements. Unfortunately, there is no official LST product of MERSI-II yet. This article proposed a temperature-emissivity separation algorithm to estimate LST and emissivity from two mid-infrared (MIR) and two thermal infrared (TIR) nighttime MERSI-II images. The sensitive analysis and ground validation show the following. First, the algorithm can theoretically retrieve LST with an error of less than 0.7 K, emissivity with errors of about 0.025 for MIR channel and 0.01 for TIR channel, respectively. Second, the nighttime LST retrieval error was approximately 2.19 K, and the bias was approximately 0.60 K among 6 SURFRAD sites and 2 PKULSTNet sites. The retrieved emissivity was cross-validated using MODIS emissivity product over a desert area and its difference was obtained as 0.01 and 0.016 for two TIR channels. Finally, the TES algorithm was applied to obtain LST and emissivity images over North China Plain as an example, and the nighttime LST and land surface emissivity (LSE) were obtained well. As a result, this study shows that the proposed TES algorithm provides an effective way to get LST and LSE image from FY-3D/ MERSI-II nighttime observation, which will improve their applications in different fields.

Improving the quantification of sediment source contributions using different mathematical models and spectral preprocessing techniques for individual or combined spectra of ultraviolet–visible, near- and middle-infrared spectroscopy

In recent years, several sediment fingerprinting studies have used ultraviolet–visible (UV–Vis), near-infrared (NIR) and middle-infrared (MIR) spectroscopy as a low cost, non-destructive and fast alternative to obtain tracer properties to estimate sediment source contributions. For this purpose, partial last square regression (PLSR) has often been used to build predictive parametric models. However, spectra preprocessing and more robust and non-parametric models such as support vector machines (SVM) has gained little attention in these studies. Accordingly, the objectives of the current research were to evaluate (i) the accuracy of two multivariate methods (PLSR and SVM), (ii) the effect of eight spectra preprocessing techniques, and (iii) the effect of using the information contained in the UV–Vis, NIR and MIR regions considered either separately or in combination on sediment source apportionment. The estimated source contribution was then compared with contributions obtained by the conventional fingerprinting approach based on geochemical tracers. This study was carried out in the Arvorezinha catchment (1.23 km2) located in southern Brazil. Forty soil samples were collected in three main potential source (cropland surface, unpaved roads and stream channels) and twenty-nine suspended sediment samples collected at the catchment outlet during nine rainfall-runoff events were used in this study. Both PLSR and SVM models showed a higher accuracy when calibrated and validated with the spectra submitted to spectral processing when compared to the direct use of the raw spectra. The best model results were obtained with PLSR and SVM mathematical models associated with the spectral preprocessing techniques 1st derivative Savitzky-Golay (SGD1), normalization (NOR) and combining NOR + SGD1 in the UV–Vis + NIR + MIR. The lowest errors were observed when the UV–Vis + NIR + MIR bands were combined due to the gain in information and, consequently, the increase in discriminant power achieved by the models. Despite the good accuracy of the models calibrated and validated with the artificial mixtures, significant errors remain when results of source contributions are compared to those obtained with the conventional sediment fingerprinting technique based on geochemical tracers. Nevertheless, the magnitude of the contributions calculated by the spectroscopy and geochemical approaches remains very similar for all sources, especially when using the SVM-UV–Vis + NIR + MIR model. Therefore, spectroscopy proved to be a fast, cheap and accurate technique, offering an alternative to the conventional geochemical approach for discriminating sediment source contributions in agricultural catchments located in subtropical regions.

Technical Note: Noninvasive mid-IR fiber-optic evanescent wave spectroscopy (FEWS) for early detection of skin cancers.

Melanoma is the most lethal of the three primary skin cancers, including also basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), which are less lethal. The accepted diagnosis process involves manually observing a suspicious lesion through a Dermascope (i.e., a magnifying glass), followed by a biopsy. This process relies on the skill and the experience of a dermatologist. However, to the best of our knowledge, there is no accepted automatic, noninvasive, and rapid method for the early detection of the three types of skin cancer, distinguishing between them and noncancerous lesions, and identifying each of them. It is our aim to develop such a system. We developed a fiber-optic evanescent wave spectroscopy (FEWS) system based on middle infrared (mid-IR) transmitting AgClBr fibers and a Fourier-transform infrared spectrometer (FTIR). We used the system to perform mid-IR spectral measurements on suspicious lesions in 90 patients, before biopsy, in situ, and in real time. The lesions were then biopsied and sent for pathology. The spectra were analyzed and the differences between pathological and healthy tissues were found and correlated. Five of the lesions measured were identified as melanomas, seven as BCC, and three as SCC. Using mathematical analyses of the spectra of these lesions we were able to tell that all were skin cancers and we found specific and easily identifiable differences between them. This FEWS method lends itself to rapid, automatic and noninvasive early detection and characterization of skin cancers. It will be easily implemented in community clinics and has the potential to greatly simplify the diagnosis process.

First study of Sentinel-3 SLSTR active fire detection and FRP retrieval: Night-time algorithm enhancements and global intercomparison to MODIS and VIIRS AF products

The Sea and Land Surface Temperature Radiometer (SLSTR) now operates concurrently onboard the European Sentinel-3A and 3B satellites. Its observations are expected ultimately to become the main global source of active fire (AF) detections and fire radiative power (FRP) retrievals for the mid-morning and evening low earth orbit timeslots – data currently supplied by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra. Here we report for the first-time the significant adjustments made to the pre-launch Sentinel-3 AF detection and fire characterisation algorithm required to optimize its performance with real SLSTR data collected from the Sentinel-3A and 3B satellites. SLSTR possesses both an S7 ‘standard’ and an F1 ‘fire’ channel that operate in the same middle infrared (MIR) waveband, but which use different detectors with differing dynamic ranges and which are located at different focal plane locations. When S7 provides saturated observations, for example over higher FRP active fire pixels, F1 must be used to provide a reliable MIR spectral measurement. However, the two channels differing data characteristics (slightly different size, shape and spatial location of the matching pixels) means that swapping between their measurements is non-trivial. The main algorithm enhancement has therefore been the addition of a dedicated active fire pixel clustering component, required to cluster the detected AF pixels into individual fires as a solution to this issue. Focusing on night-time data due to the added complexity of daytime implementation, we compare AF information derived with this updated SLSTR algorithm to that from near-simultaneous MODIS Terra, and we find that SLSTR has a lower minimum FRP detection limit which enables more lower FRP active fire pixels to be identified than is the case with MODIS. When both sensors detect the same fire cluster at the same time, SLSTR typically measures a slightly higher FRP due to it being able to detect more of the low FRP AF pixels lying at the cluster edge (the OLS linear best fit between matched SLSTR and MODIS per-fire FRP matchups has a slope of 1.08). At the regional scale, SLSTR detects 90% of the AF pixels that the matching MODIS data contains, but also identifies an additional 44% more AF pixels – the vast majority of which have FRP < 5 MW. Regional FRP totals derived from SLSTR appear slightly higher than those from MODIS because of this, and the OLS linear best fit between these regional FRP matchup datasets has a slope of 1.10. Global fire mapping at 1° grid cell resolution for January 2019 shows very similar fire patterns and FRP totals from SLSTR onboard of Sentinel-3B and MODIS Terra, with SLSTR detecting seven times more AF pixels but very similar FRP totals. Case studies in 5° grid cell areas show the same pattern, and longer-term comparisons like these will provide the data required to mesh MODIS and SLSTR data into a single compatible time-series for long-term trend analysis. The night-time SLSTR AF product based largely on this algorithm has been fully operational from March 2020 and is available from near real-time feeds. A non-time critical (NTC) version based on a similar processing chain will follow shortly after, with products available from the Sentinel-3 Data Hub.

Land Surface Temperature and Emissivity Retrieval From Nighttime Middle-Infrared and Thermal-Infrared Sentinel-3 Images

The Sea and Land Surface Temperature Radiometer (SLSTR) onboard the two Sentinel-3 satellites provides daily global coverage observation at daytime and nighttime. The split-window (SW) algorithm is currently used to retrieve the land surface temperature (LST) from SLSTR images; however, this algorithm has to utilize visible and near-infrared (VNIR) images and land cover to determine pixel emissivity. For nighttime observation, VNIR cannot be observed, and this limitation complicates the LST retrieval from nighttime images using the SW algorithm. This article proposed a three-channel temperature–emissivity separation (TES) algorithm that estimates the nighttime LST and emissivity from one middle-infrared (MIR) and two thermal-infrared (TIR) nighttime Sentinel-3 SLSTR images. The sensitive analysis showed that the algorithm could theoretically retrieve the LST and emissivity with errors less than 0.8 K and 0.015, respectively. Ground validation showed that the nighttime LST retrieval error was approximately 1.84 K and the bias was approximately −0.33 K. Finally, the TES algorithm was applied to obtain the LST and emissivity images over northern China as an example. The emissivity retrieved from the nighttime observation can be used in the daytime SW algorithm to improve its feasibility in the LST retrieval process.

Crystal chemistry, second-order nonlinear optical, and magnetic properties of Eu8Sn4Se20

Second-order nonlinear optical (NLO) materials in the middle infrared (MIR) region have attracted widespread interest in view of their importance and deficiency to the laser market’s requirement. Here, we report a new MIR NLO material Eu8Sn4Se20 (1), which represents a new structure type one and the pioneer of the (MII2MIVQ5)n (MII ​= ​divalent alkali-earth metal, Eu, Yb, Pb, and Sn; MIV ​= ​Si, Ge, Sn; Q ​= ​S, Se, Te. n ​= ​1, 2, 4) family. It demonstrates obvious second-harmonic generation (SHG) activity. Its optical band gap is determined to be 1.30 ​eV and its magnetic data exhibits antiferromagnetic-type behavior. Its electronic structure is performed as well.

Thermal behaviour of vitreous ceramic coatings obtained by electrophoretic deposition for furnace components

In this study, three different vitreous ceramic coatings have been designed to improve radiation heat transfer and thereby increase the thermal efficiency of fired heaters or furnaces working at high temperatures. The vitreous ceramic coatings were produced through Electrophoretic Deposition technique (EPD) of ceramic suspensions. These ceramic formulations were designed based on components which increase emissivity, such as SiO2 and a Black dye (based on chromium, copper and iron oxides), added in 25 wt%. These coatings showed emissivity values around 0.89 at room temperature and around 0.82 at 550 °C in the middle infrared (MIR) spectral range, with slight differences between them. The SiO2 and Black dye additions provide an important protective effect on the coatings’ thermal stability as it was proved by the absorbance level at long times, higher than 85% in the near infrared (NIR) spectral range. These results were also supported by microstructural characterisation, substrate-coatings adhesion strength and thermal stability tests.

Status Quo and Application of Middle and Long Wave Dual-band Infrared Imaging Technologies in Occident

Depending on the capability of detecting scene radiance in both MWIR(middle wave infrared radiation)and LWIR(long wave infrared radiation)spectral bands,the dual-band IR(infrared radiation)technology ensures the use of two single-band sensors.Using the spectral advantages associated with the use of two single-band sensors,the dual-band IR technology can improve all-weather performance and the probability of mission success in almost all cases.Over the past 20 years,main occident have developed from dual-camera dual-band to single-camera dual-band infrared camera systems and equipped military,with higher resolution and greater range being the current requirements.At present,the dual-band IR technology mainly has three different applications.First,it improves the adaptability to different operational environments.Second,it improves the target detection and recognition probability of automatic systems.Third,through deep data processing,it is used to obtain more information about the target such as temperature and spectral feature,which helps prevent jammer and camouflage.

Volcanic Hot-Spot Detection Using SENTINEL-2: A Comparison with MODIS–MIROVA Thermal Data Series

In the satellite thermal remote sensing, the new generation of sensors with high-spatial resolution SWIR data open the door to an improved constraining of thermal phenomena related to volcanic processes, with strong implications for monitoring applications. In this paper, we describe a new hot-spot detection algorithm developed for SENTINEL-2/MSI data that combines spectral indices on the SWIR bands 8a-11-12 (with a 20-meter resolution) with a spatial and statistical analysis on clusters of alerted pixels. The algorithm is able to detect hot-spot-contaminated pixels (S2Pix) in a wide range of environments and for several types of volcanic activities, showing high accuracy performances of about 1% and 94% in averaged omission and commission rates, respectively, underlining a strong reliability on a global scale. The S2-derived thermal trends, retrieved at eight key-case volcanoes, are then compared with the Volcanic Radiative Power (VRP) derived from MODIS (Moderate Resolution Imaging Spectroradiometer) and processed by the MIROVA (Middle InfraRed Observation of Volcanic Activity) system during an almost four-year-long period, January 2016 to October 2019. The presented data indicate an overall excellent correlation between the two thermal signals, enhancing the higher sensitivity of SENTINEL-2 to detect subtle, low-temperature thermal signals. Moreover, for each case we explore the specific relationship between S2Pix and VRP showing how different volcanic processes (i.e., lava flows, domes, lakes and open-vent activity) produce a distinct pattern in terms of size and intensity of the thermal anomaly. These promising results indicate how the algorithm here presented could be applicable for volcanic monitoring purposes and integrated into operational systems. Moreover, the combination of high-resolution (S2/MSI) and moderate-resolution (MODIS) thermal timeseries constitutes a breakthrough for future multi-sensor hot-spot detection systems, with increased monitoring capabilities that are useful for communities which interact with active volcanoes.

Potential Underestimation of Satellite Fire Radiative Power Retrievals over Gas Flares and Wildland Fires

Fire Radiative Power (FRP) is related to fire combustion rates and is used to quantify the atmospheric emissions of greenhouse gases and aerosols. FRP over gas flares and wildfires can be retrieved remotely using satellites that observe in shortwave infrared (SWIR) to middle infrared (MIR) wavelengths. Heritage techniques to retrieve FRP developed for wildland fires using the MIR 4 μm radiances have been adapted for the hotter burning gas flares using the SWIR 2 μm observations. Effects of atmosphere, including smoke and aerosols, are assumed to be minimal in these algorithms because of the use of longer than visual wavelengths. Here we use Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS) and Landsat 8 observations acquired before and during emergency oil and gas flaring in eastern Saudi Arabia to show that dark, sooty smoke affects both 4 μm and 2 μm observations. While the 2 μm observations used to retrieve gas FRP may be reliable during clear atmospheric conditions, performance is severely impacted by dark smoke. Global remote sensing-based inventories of wildfire and gas flaring need to consider the possibility that soot and dark smoke can potentially lead to an underestimation of FRP over fires.

Multi-band middle-infrared-compatible camouflage with thermal management via simple photonic structures

Perpetual advancements in modern detection technologies have augmented the need of multi-band (such as laser radar, visual) middle-infrared (MIR) compatible camouflage; however, its development is impeded by incompatible structural requirements of different camouflage effects and thermal challenge. This study demonstrates two simple photonic structures (Designs I and II) for visual and MIR camouflage with thermal management utilizing thin-film interference. The additional laser camouflage is realized by further incorporating simple wavelength-scale grating structures in Design I (Design II). The fabricated structures exhibit dual-band MIR camouflage by low emission (ε‾3–5μm = 0.25 and ε‾8–14μm = 0.33), radar camouflage to CO2 laser by high absorption at 10.6 μm (α10.6 μm = 0.90), visual camouflage by structural colors and thermal management by high emission in 5–8 μm band (ε‾5–8μm = 0.77). This study provides a guideline on coordinated control of electromagnetic wave and heat through simple structural design, thus has broad implications in energy harvesting and thermal information processing.

Enhanced MIR emission of Er3+/Yb3+ co-doped fluorochloride glass with energy transfer and MIR light source application

The novel Er3+/Yb3+ co-doped fluorochloride glasses with good luminescent properties in the infrared region have been prepared. The middle infrared (MIR) luminescence of fluorochloride glasses is improved by anion substitution and rare-earth ion co-doping strategy. The chloridion doping reduces the phonon state density of the host matrix significantly. The ytterbium ions co-doping promotes the effective energy transfer of Yb3+:2F5/2 → Er3+:4I11/2. The Ω2 value of samples increases with the introduction of Yb3+, which means great asymmetry and strong covalency. The emission cross-section area σem (1.06 × 10−20 cm2) and the absorption cross-sectional area σabs (0.97 × 10−20 cm2) of Er3+/Yb3+ co-doped sample are all larger than that in the previous report. The fluorescence decay characteristics of samples at 980 nm and 1550 nm were investigated. In addition, a MIR light source was prepared preliminarily. Therefore, Er3+/Yb3+ co-doped fluorochloride glass is a potential MIR laser material.

IR-Band Conversion of Target and Background Using Surface Temperature Estimation and Error Compensation for Military IR Sensor Simulation.

Military infrared (IR) imaging systems utilize one or more IR wavelength-bands, among short wavelength IR (SWIR), middle wavelength IR (MWIR), and long wavelength IR (LWIR) band. The IR image wavelength-band conversion which transforms one arbitrary IR wavelength-band image to another IR wavelength-band image is needed for IR signature modeling and image synthesis in the IR systems. However, the IR wavelength-band conversion is very challenging because absorptivity and transmittance of objects and background (atmosphere) are different according to the IR wavelength band and because radiation and reflectance characteristics of the SWIR are very different from the LWIR and MWIR. Therefore, the IR wavelength-band conversion in this paper applies to only IR targets and monotonous backgrounds at a long distance for military purposes. This paper proposes an IR wavelength-band conversion method which transforms one arbitrary IR wavelength-band image to another IR wavelength-band image by using the surface temperature estimation of an object and the error attenuation method for the estimated temperature. The surface temperature of the object is estimated by an approximated Planck’s radiation equation and the error of estimated temperature is corrected by using the slope information of exact radiance along with the approximated one. The corrected surface temperature is used for generating another IR wavelength-band image. The verification of the proposed method is demonstrated through the simulations using actual IR images obtained by thermal equipment.

Early prediction of sugarcane genotypes susceptible and resistant to Diatraea saccharalis using spectroscopies and classification techniques.

The aim of this work was to use spectroscopic methods and partial least squares discriminant analysis (PLS-DA) for the early prediction of genotype resistance or susceptibility to sugarcane borer. The sugarcane leaf +1 was directly analyzed with no sample preparation by ultraviolet-visible-near-infrared (UV-VIS-NIR), middle-infrared (MID), and near-infrared (NIR) spectroscopies. Also, laser-induced breakdown spectroscopy (LIBS) was used to analyze pellets of dried and ground leaves and stalks of sugarcane. Classification models were built using PLS-DA. The models built using UV-VIS-NIR, MID or NIR spectra exhibited ideal sensitivity, specificity, and classification errors, i.e., 1 for both sensitivity and specificity and 0 for classification errors. Regarding the models built using LIBS spectra, those using spectra of pellets made from dried and ground leaves also presented ideal sensitivity, specificity, and classification errors; on the other hand, models built using the spectra of pellets made of dried and ground stalks did not present ideal values for these parameters. Thus, the models built, except for the one using LIBS of pellets made of stalks, showed excellent predictive capacity, making them suitable for predicting the resistance or susceptibility of sugarcane genotypes in the early stages of a plant's life.

Land Surface Temperature Retrieval from Sentinel-3A Sea and Land Surface Temperature Radiometer, Using a Split-Window Algorithm

Land surface temperature (LST) is a crucial parameter in the interaction between the ground and the atmosphere. The Sentinel-3A Sea and Land Surface Temperature Radiometer (SLSTR) provides global daily coverage of day and night observation in the wavelength range of 0.55 to 12.0 μm. LST retrieved from SLSTR is expected to be widely used in different fields of earth surface monitoring. This study aimed to develop a split-window (SW) algorithm to estimate LST from two-channel thermal infrared (TIR) and one-channel middle infrared (MIR) images of SLSTR observation. On the basis of the conventional SW algorithm, using two TIR channels for the daytime observation, the MIR data, with a higher atmospheric transmittance and a lower sensitivity to land surface emissivity, were further used to develop a modified SW algorithm for the nighttime observation. To improve the retrieval accuracy, the algorithm coefficients were obtained in different subranges, according to the view zenith angle, column water vapor, and brightness temperature. The proposed algorithm can theoretically estimate LST with an error lower than 1 K on average. The algorithm was applied to northern China and southern UK, and the retrieved LST captured the surface features for both daytime and nighttime. Finally, ground validation was conducted over seven sites (four in the USA and three in China). Results showed that LST could be estimated with an error mostly within 1.5 to 2.5 K from the algorithm, and the error of the nighttime algorithm involved with MIR data was about 0.5 K lower than the daytime algorithm.

Effect of Etching Depth on Threshold Characteristics of GaSb-Based Middle Infrared Photonic-Crystal Surface-Emitting Lasers.

We study the effect of etching depth on the threshold characteristics of GaSb-based middle infrared (Mid-IR) photonic-crystal surface-emitting lasers (PCSELs) with different lattice periods. The below-threshold emission spectra are measured to identify the bandgap as well as band-edge modes. Moreover, the bandgap separation widens with increasing etching depth as a result of enhanced diffraction feedback coupling. However, the coupling is nearly independent of lattice period. The relationship between threshold gain and Bragg detuning is also experimentally determined for PCSELs and is similar to that calculated theoretically for one-dimensional distributed feedback lasers.

RADIATIVE TRANSFER MODEL SIMULATIONS TO DETERMINE THE NIGHT TIME FOG DETECTION THRESHOLD

Abstract. Every winter the Indo-Gangetic plains (IGP) of northern India are severely impacted both socially and economically by fog. For night time fog detection, visible imagery cannot be used. Also, as emissions from ground and fog is almost similar in thermal infrared (TIR, 10.8 μm) channel, TIR channel cannot help in identifying fog. However, emission in middle infrared (MIR, 3.9 μm) channel is less than emission in TIR channel over foggy area. Therefore, brightness temperature difference (BTD) between TIR and MIR is positive during night time over fog area. This BTD technique cannot be directly used during day time as MIR channel is contaminated by solar radiations. In the present work, a spectral sensitivity analysis study has been done for these two spectral channels using radiative transfer model (RTM) simulations to determine a threshold BTD for night time fog detection. SBDART (Santa Barbara DISORT Radiative Transfer) model was used for this study to simulate brightness temperatures (BT). The RTM simulations of BT of the two spectral channels was carried out for different fog microphysical characteristics like fog optical depth (FOD) and fog droplet size (Re). The fog episode of January 2018 over IGP was studied by applying threshold BTD obtained from simulation results for INSAT-3D data. A threshold BTD value &gt; 5 K detected night time fog over IGP with good accuracy. The threshold BTD obtained from satellite image is compared with different cases established from simulation result which gave idea about microphysical properties of fog over IGP during winter seasons.

Crude oil spectral signatures and empirical models to derive API gravity

Infrared spectroscopy is presented as a quick alternative method for establishing crude oil properties such as density (°API gravity) and content of saturates, aromatics, resins and asphaltenes (SARA). Here, thirty seven (37) samples of crude oils with different °API gravities and SARA fractions were measured in the visible, near infrared and short wave infrared (VIS – NIR – SWIR/350–2500 nm), and in the middle and longwave infrared (MWIR – LWIR/3000–15,000 nm) ranges. Main CH absorption bands and optimal intervals for the discrimination among oil types were identified in all spectral regions. Based on diffuse reflectance spectroscopy and equivalent wavelet spectra, Principal Component Analysis allowed distinguishing between three major groups of crude oils with varied densities. Partial Least Squares Regression analysis yielded sixteen predictive models tailored to estimate the °API of crude oils based on their spectral signatures in the NIR – SWIR – MWIR – LWIR intervals. These data and methods are swift and nondestructive ways to estimate the °API of crude oils, with latent applications in several chains of the petroleum industry, particularly to assess and manage the environmental impact caused by oil discharge, leakage and spill events. Additionally, considering that airborne and orbital sensor systems currently in operation can sense some of the crude oil absorption bands highlighted in this study, the oil signatures revealed here could be potentially used to map oil contamination in diverse settings and globally using remote sensing.

Colloidal Plasmonic Nanoparticles for Ultrafast Optical Switching and Laser Pulse Generation

Light-matter interactions are greatly enhanced and spatially well-confined in plasmonic nanostructures in the spectral resonance range. In colloidal plasmonic nanoparticle (NP), this effect is manifested by the strong absorption caused by the collective oscillation of conduction electrons in NPs, known as the localized surface plasmon resonance (LSPR). The strong spectral resonance due to LSPR also contributes to the large enhancement in optical nonlinearity, such as nonlinear absorption and optical Kerr effect, and the ultrafast transient photo-bleaching in those materials making them ideal platforms for exploring optical switching behavior that is needed in all optical devices. Here, we review the recent advances in the use of colloidal processed noble metal, metalloid, chalcogenide and oxide plasmonic NPs for ultrafast optical switches to drive pulse laser generation in both solid state and fiber lasers. The broadband and ultrafast response of these plasmonic NPs offers a significant advantage in devices performance and allows the pulse generation from near infrared (NIR) to middle infrared (MIR) spectral range with pulse duration down to 100-femtosecond level. Compared with commercial products and other optical switches based on 2D materials, these plasmonic NPs are expected to provide a competitive and cost-efficient material solution to compact ultrafast pulse lasers and relevant devices.