Near-infrared Water Research Articles

Understanding the protein conformation transition within polymer hydrogels using a near-infrared water spectroscopy probe

Understanding the protein conformation transition within polymer hydrogels using a near-infrared water spectroscopy probe

STCFCM: A Spatial and Temporal Cloud Fraction-Based Calibration Method for Satellite-Derived Near-Infrared Water Vapor Product

STCFCM: A Spatial and Temporal Cloud Fraction-Based Calibration Method for Satellite-Derived Near-Infrared Water Vapor Product

NH3 absorption line study and application near 1084.6 cm−1

Ammonia (NH3) holds significant importance as an industrial product, ambient trace pollutant, and a promising zero-carbon energy carrier, underscoring the critical need for accurate quantification in various applications. In this study, a mid-infrared quantum cascade laser (Mid-IR QCL) based tunable diode laser absorption spectroscopy (TDLAS) spectrometer was developed. It was coupled with two reactors, namely a gas cell and a shock tube and operated in three modes: low- and high-frequency (140 Hz and 10 kHz) scan modes and fixed-wavelength mode, tailored to the specific needs of each experimental scenario. The primary objects were NH3 line parameters measurement and absolute NH3 quantification. With the 140 Hz low-frequency scan mode, NH3-Ar pressure broadening coefficients of six transition lines near 1084.6 cm−1 were measured in a gas cell at 295 K and 1–11 mbar for the first time. These coefficients were subsequently employed to quantify the initial NH3 mole fraction in shock tube experiments, considering the substantial adsorption effect of NH3. Using the high-frequency scan mode (10 kHz), spectrally resolved NH3 absorption cross-sections were obtained in a shock tube across a pressure range of 1.46–3.25 bar and a temperature range of 1000–1800 K. This data, acquired for the first time, significantly contributes to the understanding of NH3 behavior in high-temperature environments. Additionally, potential interference from high-temperature water absorption near 1084.6 cm−1 was thoroughly examined. The high-temperature water absorption cross-section was measured over a pressure range of 0.99–3.02 bar and a temperature range of 1322–2905 K, utilizing a near-infrared water laser. Leveraging these comprehensive datasets, the study quantified the NH3 mole fraction during the NH3 oxidation process in the shock tube, employing the fixed-wavelength mode to achieve high time resolution. The quantified NH3 mole fraction was then compared to predictions from eleven recent chemical kinetic mechanisms, demonstrating the utility of the developed spectrometer in validating these mechanisms.

Improving the Accuracy of MODIS Near-Infrared Water Vapor Product Under all Weather Conditions Based on Machine Learning Considering Multiple Dependence Parameters

We developed six machine learning based calibration models to improve the all-weather accuracy of precipitable water vapor (PWV) product from near-infrared (NIR) observations of the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, i.e. MOD05 PWV. The six machine learning approaches are: Back Propagation Neural Network (BPNN), Gradient Boosting Decision Tree (GBDT), Generalized Regression Neural Network (GRNN), K-Nearest Neighbor (KNN), Multilayer Perceptron Neural Network (MLPNN), and eXtreme Gradient Boosting (XGBoost). The input of the models included MOD05 PWV, latitude, longitude, elevation, cloud, season, and solar zenith angle, in association with the quality of the MOD05 PWV product. PWV data measured from in-situ 453 Global Positioning System (GPS) stations in Australia in 2017 were utilized as the target water vapor data for model training. The validation results in Australia in 2018–2019 indicate that the models can significantly improve the all-weather quality (increased R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , reduced root-mean-square error (RMSE), and reduced mean bias (MB)) of the MOD05 PWV product, exhibiting a reduction in RMSE of 53.33% for BPNN, 55.25% for GBDT, 53.24% for GRNN, 37.81% for KNN, 54.98% for MLPNN, and 55.16% for XGBoost. The R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> was 0.58 ~ 0.79 and the MB was 0.12 mm ~ 0.72 mm, much better than the MOD05 all-weather PWV product (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.26 and MB = -1.75 mm). Different from previous studies that focused on clear-sky conditions only, this work is the first one to enhance the quality of official MODIS NIR PWV products under all weather conditions, reducing the impact of clouds on PWV products.

A Back Propagation Neural Network-Based Calibration Approach for Sentinel-3 OLCI Near-Infrared Water Vapor Product

A back propagation neural network (BPNN)-based calibration method is developed to enhance the all-weather quality of official integrated water vapor (IWV) products from near-infrared (NIR) observations of the Ocean and Land Color Instrument (OLCI) onboard Sentinel-3A and Sentinel-3B satellites. The model utilizes multiple variables that link with the derivation of satellite NIR IWV products, including official OLCI NIR IWV, latitude, land quality and science flag, month, and solar zenith angle. The in situ IWV observations, collected from 100 Global Positioning System (GPS) stations, are employed as the desired IWV estimates. The model is evaluated using one-year water vapor data at additional 114 GPS stations and 97 radiosonde stations from June 1, 2019 to May 31, 2020 in China and its surrounding regions. The results show that the BPNN-based calibration model reduces the root-mean-square error (RMSE) of official OLCI NIR all-weather IWV products by 24.52% from 3.10 to 2.34 mm for Sentinel-3A and by 25.00% from 3.44 to 2.58 mm for Sentinel-3B, when compared with in situ GPS-observed reference IWV. When compared with in situ radiosonde-observed IWV, the RMSE reduces 21.01% from 4.57 to 3.61 mm and 20.81% from 5.19 to 4.11 mm for Sentinel-3A and Sentinel-3B, respectively.

Sub-percent accuracy for the intensity of a near-infrared water line at 10,670 cm−1: experiment and analysis

Laser measurements of the intensity of near-infrared water absorption line at 10,670.1 cm are made using three different Herriott cells. These measurements determine the line intensity with an standard deviation below of 0.3% by consideration of the new geometrically derived formula for the optical path length without approximations. This determination together with the current accepted value lead to an overall uncertainty of 0.7% of the experimentally assessed line intensity which is compared with previous ab initio predictions. It is found that steady improvements in both the dipole moment surface (DMS) and the potential energy surface (PES) used in the theoretical studies lead to a systematically better agreement with the observation, with the most recent prediction agreeing closely with the experiment.

Detection of Near-infrared Water Ice at the Surface of the (Pre)Transitional Disk of AB Aur: Informing Icy Grain Abundance, Composition, and Size

Abstract We present near-infrared Large Binocular Telescope LMIRCam imagery of the disk around the Herbig Ae/Be star AB Aurigae. A comparison of the surface brightness at K s (2.16 μm), H2O narrowband (3.08 μm), and L ′ (3.7 μm) allows us to probe the presence of icy grains in this (pre)transitional disk environment. By applying reference differential imaging point-spread function subtraction, we detect the disk at high signal-to-noise ratios in all three bands. We find strong morphological differences between the bands, including asymmetries consistent with the observed spiral arms within 100 au in L ′ . An apparent deficit of scattered light at 3.08 μm relative to the bracketing wavelengths (K s and L ′ ) is evocative of ice absorption at the disk surface layer. However, the Δ(K s − H2O) color is consistent with grains with little to no ice (0%–5% by mass). The Δ ( H 2 O − L ′ ) color, conversely, suggests grains with a much higher ice mass fraction (∼0.68), and the two colors cannot be reconciled under a single grain population model. Additionally, we find that the extremely red Δ ( K s − L ′ ) disk color cannot be reproduced under conventional scattered light modeling with any combination of grain parameters or reasonable local extinction values. We hypothesize that the scattering surfaces at the three wavelengths are not colocated, and that the optical depth effects in each wavelength result from probing the grain population at different disk surface depths. The morphological similarity between K s and H2O suggests that their scattering surfaces are near one another, lending credence to the Δ(K s − H2O) disk color constraint of &lt;5% ice mass fraction for the outermost scattering disk layer.

The effect of the differences in near-infrared water vapour continuum models on the absorption of solar radiation

There are currently significant disagreements in the strength of the water vapour continuum in the near-infrared region. To understand the effects of these disagreements on the absorption of solar radiation, line-by-line radiative transfer calculations were performed from 2000 to 10,000 cm−1 (1–5 μm) for three standard atmospheres; tropical, mid-latitude summer and sub-arctic winter atmospheres. These calculations were carried out at a solar zenith angle of 60° using line parameters from HITRAN (HIgh-resolution TRANsmission). Three currently available water vapour continuum models were selected for this study; versions 2.5 and 3.2 of the semi-empirical MT_CKD (Mlawer-Tobin-Clough-Kneizys-Davies) model and the laboratory-measured CAVIAR (Continuum Absorption at Visible and Infrared Wavelengths and its Atmospheric Relevance) model. The differences between the contributions of both MT_CKD models to near-infrared absorption and heating are modest for all three atmospheres. The additional absorption due the CAVIAR model more than doubles those due to both MT_CKD models for the tropical and mid-latitude summer atmospheres. For both atmospheres, the extra heating of the CAVIAR model is up to a factor of 5 more than those of the MT_CKD models. For the sub-arctic winter atmosphere, the differences between the extra absorption and heating of the CAVIAR and those of both MT_CKD models are relatively less. Thus, an update of the MT_CKD model from version 2.5 to 3.2 has a relatively small impact on near-infrared spectrally integrated absorbed solar fluxes and heating rates. But their contributions to the calculations of these quantities differ significantly from that of the much stronger CAVIAR model.

Chemometrics and Experimental Design for the Quantification of Nitrate Salts in Nitric Acid: Near-Infrared Spectroscopy Absorption Analysis.

Implementing remote, real-time spectroscopic monitoring of radiochemical processing streams in hot cell environments requires efficiency and simplicity. The success of optical spectroscopy for the quantification of species in chemical systems highly depends on representative training sets and suitable validation sets. Selecting a training set (i.e., calibration standards) to build multivariate regression models is both time- and resource-consuming using standard one-factor-at-a-time approaches. This study describes the use of experimental design to generate spectral training sets and a validation set for the quantification of sodium nitrate (0-1 M) and nitric acid (0.1-10 M) using the near-infrared water band centered at 1440 nm. Partial least squares regression models were built from training sets generated by both D- and I-optimal experimental designs and a one-factor-at-a-time approach. The prediction performance of each model was evaluated by comparing the bias and standard error of prediction for statistical significance. D- and I-optimal designs reduced the number of samples required to build regression models compared with one-factor-at-a-time while also improving performance. Models must be confirmed against a validation sample set when minimizing the number of samples in the training set. The D-optimal design performed the best when considering both performance and efficiency by improving predictive capability and reducing number of samples in the training set by 64% compared with the one-factor-at-a-time approach. The experimental design approach objectively selects calibration and validation spectral data sets based on statistical criterion to optimize performance and minimize resources.

Estimating Water Reflectance at Near-Infrared Wavelengths for Turbid Water Atmospheric Correction: A Preliminary Study for GOCI-II

Atmospheric correction is a fundamental process to remove the atmospheric effect from the top-of-atmosphere level. The atmospheric correction algorithm developed by the Korea Institute of Ocean Science and Technology employs a near-infrared (NIR) water reflectance model to deal with non-negligible NIR water reflectance over turbid waters. This paper describes the NIR water reflectance models using visible bands of the Second Geostationary Ocean Color Imager (GOCI-II). Whereas the previous GOCI uses the 660 nm band to estimate NIR water reflectance (SR660), GOCI-II uses additional 620 and 709 nm bands, which improves estimation of NIR water reflectance. We developed two reflectance models with the additional bands based on a spectral relationship of water reflectance (SR709) and a spectral relationship of inherent optical properties (SRIOP) from red to NIR wavelengths. A preliminary validation of these two reflectance models was performed using both simulations and an in situ dataset. The validation result showed that the mean absolute percentage error of the SR709 model compared with SR660 was reduced by approximately 6% and 10% at 745 and 865 nm, respectively. Moreover, the mean absolute percentage error of the SRIOP model compared with SR660 was reduced by approximately 12% and 16% at 745 and 865 nm, respectively. Note that SR709 produces the most accurate result when there is only one sediment type, and SRIOP shows the most accurate result when various sediment types exist. Users will be able to optionally select the appropriate NIR water reflectance models in the GOCI-II atmospheric correction process to enhance the accuracy of aerosol reflectance correction over turbid waters.

An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data

The atmosphere has substantial effects on optical remote sensing imagery of the Earth’s surface from space. These effects come through the functioning of atmospheric particles on the radiometric transfer from the Earth’s surface through the atmosphere to the sensor in space. Precipitable water vapor (PWV), CO2, ozone, and aerosol in the atmosphere are very important among the particles through their functioning. This study presented an algorithm to retrieve total PWV from the Chinese second-generation polar-orbiting meteorological satellite FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) data, which have three near-infrared (NIR) water vapor absorbing channels, i.e., channel 16, 17, and 18. The algorithm was improved from the radiance ratio technique initially developed for Moderate-Resolution Imaging Spectroradiometer (MODIS) data. MODTRAN 5 was used to simulate the process of radiant transfer from the ground surfaces to the sensor at various atmospheric conditions for estimation of the coefficients of ratio technique, which was achieved through statistical regression analysis between the simulated radiance and transmittance values for FY-3D MERSI-2 NIR channels. The algorithm was then constructed as a linear combination of the three-water vapor absorbing channels of FY-3D MERSI-2. Measurements from two ground-based reference datasets were used to validate the algorithm: the sun photometer measurements of Aerosol Robotic Network (AERONET) and the microwave radiometer measurements of Energy’s Atmospheric Radiation Measurement Program (ARMP). The validation results showed that the algorithm performs very well when compared with the ground-based reference datasets. The estimated PWV values come with root mean square error (RMSE) of 0.28 g/cm2 for the ARMP and 0.26 g/cm2 for the AERONET datasets, with bias of 0.072 g/cm2 and 0.096 g/cm2 for the two reference datasets, respectively. The accuracy of the proposed algorithm revealed a better consistency with ground-based reference datasets. Thus, the proposed algorithm could be used as an alternative to retrieve PWV from FY-3D MERSI-2 data for various remote sensing applications such as agricultural monitoring, climate change, hydrologic cycle, and so on at various regional and global scales.

HST Survey of the Orion Nebula Cluster in the H2O 1.4 μm Absorption Band. II. The Substellar IMF Down to Planetary Masses*

Abstract We utilize the ability of the Hubble Space Telescope to probe near-infrared water absorption present in the atmosphere of low-mass stars and brown-dwarf and planetary-mass objects to create a pure sample of Orion Nebula Cluster (ONC) members, not affected by contamination from background stars and galaxies that lack water absorption. Thanks to these data, we infer the Initial Mass Function (IMF) of the ONC in the 0.005–1.4M ⊙ regime (i.e., down to a few Jupiter masses). The young age of the ONC, ∼1 Myr, provides a snapshot of the outcome of star formation for the present-day conditions (metallicity, temperature, pressure) of typical Milky Way disk molecular clouds. We demonstrate that the IMF of the ONC is well described by either a log-normal function or a broken power law, with parameter values qualitatively in agreement with the canonical Chabrier or Kroupa forms for the Milky Way disk IMF. This continuity in the mass distribution provides clues to the fact that the same physical processes may be regulating the formation of stars, brown dwarfs, and planetary-mass objects. Both the canonical IMF forms underpredict the observed number of very-low-mass members (below 0.1 M ⊙), a regime where our data allows more precise constraints. Nevertheless, we do not observe a rise or secondary peak in the brown dwarfs or planetary-mass regimes. Our study thus contradicts findings based on broadband near-infrared ground-based photometry, which predict an extremely high number of free-floating planets, but likely suffer from unaccounted background contamination.

Atmospheric observations of the water vapour continuum in the near-infrared windows between 2500 and 6600 cm−1

Abstract. Water vapour continuum absorption is potentially important for both closure of the Earth's energy budget and remote sensing applications. Currently, there are significant uncertainties in its characteristics in the near-infrared atmospheric windows at 2.1 and 1.6 µm. There have been several attempts to measure the continuum in the laboratory; not only are there significant differences amongst these measurements, but there are also difficulties in extrapolating the laboratory data taken at room temperature and above to temperatures more widely relevant to the atmosphere. Validation is therefore required using field observations of the real atmosphere. There are currently no published observations in atmospheric conditions with enough water vapour to detect a continuum signal within these windows or where the self-continuum component is significant. We present observations of the near-infrared water vapour continuum from Camborne, UK, at sea level using a Sun-pointing, radiometrically calibrated Fourier transform spectrometer in the window regions between 2000 and 10 000 cm−1. Analysis of these data is challenging, particularly because of the need to remove aerosol extinction and the large uncertainties associated with such field measurements. Nevertheless, we present data that are consistent with recent laboratory datasets in the 4 and 2.1 µm windows (when extrapolated to atmospheric temperatures). These results indicate that the most recent revision (3.2) of the MT_CKD foreign continuum, versions of which are widely used in atmospheric radiation models, requires strengthening by a factor of ∼5 in the centre of the 2.1 µm window. In the higher-wavenumber window at 1.6 µm, our estimated self- and foreign-continua are significantly stronger than MT_CKD. The possible contribution of the self- and foreign-continua to our derived total continuum optical depth is estimated by using laboratory or MT_CKD values of one, to estimate the other. The obtained self-continuum shows some consistency with temperature-extrapolated laboratory data in the centres of the 4 and 2.1 µm windows. The 1.6 µm region is more sensitive to atmospheric aerosol and continuum retrievals and therefore more uncertain than the more robust results at 2.1 and 4 µm. We highlight the difficulties in observing the atmospheric continuum and make the case for additional measurements in both the laboratory and field and discuss the requirements for any future field campaign.

Water Vapor Retrieval From MODIS NIR Channels Using Ground-Based GPS Data

A novel algorithm for water vapor retrieval from Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared (NIR) channels is proposed in this research. In contrast to conventional retrieval algorithms based on radiative transfer methods, this algorithm uses the empirical regression functions to calculate precipitable water vapor (PWV). In this article, water vapor data observed from January 1, 2003, to December 31, 2017, from 464 GPS stations situated in western North America serve as reference data to determine the relationship between the transmittance of the water vapor absorption channels and atmospheric water vapor content. The model is trained on different subsets of the training data through the bootstrap resampling method. Validation results against PWV observations during the period 2010–2017 from five globally distributed GPS stations illustrate that the algorithm can significantly improve the accuracy of MODIS NIR water vapor data, with root-mean-square error (RMSE) reduction of 22.48% from 7.670 to 5.946 mm for two-channel ratio method and 21.69% from 7.670 to 6.006 mm for three-channel ratio method for MODIS/Terra satellite data, and RMSE reduction of 16.42% from 7.191 to 6.010 mm and 15.26% from 7.191 to 6.094 mm for PWV derived from two-channel and three-channel ratio methods from Aqua, respectively, for MODIS/Aqua satellite data.

Near infrared spectroscopic assessment of loosely and tightly bound cortical bone water.

Water is an important component of bone and plays a key role in its mechanical and structural integrity. Water molecules in bone are present in different locations, including loosely or tightly bound to the matrix and/or mineral (biological apatite) phases. Identification of water location and interactions with matrix components impact bone function but have been challenging to assess. Here, we used near infrared (NIR) spectroscopy to identify loosely and tightly bound water present in cortical bone. In hydrated samples, NIR spectra have two primary water absorption bands at frequencies of ∼5200 and 7000 cm-1. Using lyophilization and hydrogen-deuterium exchange assays, we showed that these absorption bands are primarily associated with loosely bound bone water. Using further demineralization assays, thermal denaturation, and comparison to standards, we found that these absorption bands have underlying components associated with water molecules tightly bound to bone. In dehydrated samples, the peak at ∼5200 cm-1 was assigned to a combination of water tightly bound to collagen and to mineral, whereas the peak at 7000 cm-1 was exclusively associated with tightly bound mineral water. We also found significant positive correlations between the NIR mineral absorption bands and the mineral content as determined by an established mid infrared spectroscopic parameter, phosphate/amide I. Moreover, the NIR water data showed correlation trends with tissue mineral density (TMD) in cortical bone tissues. These observations reveal the ability of NIR spectroscopy to non-destructively identify loosely and tightly bound water in bone, which could have further applications in biomineralization and biomedical studies.

Analysis of residual moisture in a freeze-dried sample drug using a multivariate fitting regression model

The moisture content of many pharmaceutical products, like most vaccines, is an important control parameter in the product qualification. Freeze-drying is a widely applied technique for the preservation and storage of such products. Karl Fischer titration is the standard method for determination of residual moisture in freeze-dried samples; however, it is a time-consuming and destructive method that requires the handling of organic solvents. Instead, near-infrared (NIR) spectroscopy is a fast and non-invasive method that is well suited to the measurement of water due to the strong adsorption band of water in NIR. In this study, multivariate fitting regression with Gaussian function (MFRG) was applied to predict the water content of a freeze-dried sample drug using NIR spectra. Moreover, the prediction performance of the MFRG was compared to the results of the well-known PLS method. Several simulated datasets and experimental data were used to evaluate the performance of the MFRG method. In the case of experimental data, a number of mathematical pre-treatments were applied to evaluate whether they led to better models. In addition, several calibration and test sets were designed and applied to compare the quantification results of MFRG and PLS methods. It was found that the performance of the MFRG model was comparable or better compared to the PLS regression method in nearly all the examined cases, which is due to fact that MFRG models nonlinearity better than the PLS method.

Comparison of Satellite-Derived Precipitable Water Vapor Through Near-Infrared Remote Sensing Channels

The retrieval accuracies of three typical near-infrared (NIR) precipitable water vapor (PWV) products are thoroughly discussed in this article. The NIR PWV data are obtained from three satellite sensors: the Moderate-Resolution Imaging Spectroradiometer (MODIS)/Terra, the medium-resolution imaging spectrometer (MERIS)/Envisat, and the medium-resolution spectral imager (MERSI)/FY-3A. Collocated Global Positioning System (GPS) PWV data from GPS network are employed as the reference data set because of its high precision in water vapor measurement. Relative difference and root-mean-square (rms) difference are computed for “Clear,” “Cloudy,” and “All Weather” categories for each NIR water vapor product. The results reveal that PWV derived from NIR sensors tend to underestimate the water vapor values with the existence of cloud, as NIR signals cannot penetrate the cloud. Under “Clear” condition, the overall rms for remote sensors are close to the expected goal accuracies, namely, with root-mean-square-error (RMSE) of 5.480 mm for MODIS/Terra, 3.708 mm for MERIS/Envisat, 8.644 mm for MERSI/FY-3A. MERIS/Envisat has the highest PWV retrieval accuracy, while the MODIS/Terra PWV product has the best correlation with GPS PWV ( $R^{2}$ is 0.951). The MODIS/Terra tends to overestimate PWV value, while MERSI/FY-3A tends to underestimate the PWV value. Moreover, a comprehensive comparison of seasonal variation and wet/dry variation for each NIR PWV product is also performed in this study. The results indicate that the RMSE increases significantly under wet conditions (PWV larger than 20 mm) than under dry conditions (PWV smaller than 20 mm) for all remote sensing PWV products.

Recent Advances in Tungsten-Oxide-Based Materials and Their Applications

Among several active photothermal nanomaterials, tungsten-oxide-based materials have received considerable attention recently because of their ability to absorb near-infrared (NIR) light and their efficient light-to-heat conversion properties. In addition, tungsten-oxide-based materials have an unusual oxygen defect structure and strong local surface plasma resonance (LSPR), which offers strong photoabsorption in a broad wavelength range of the NIR region. In the past, several light-absorbing nanomaterials such as noble metals, polymeric materials, and other inorganic nanomaterials were of interest for their use in photothermal therapy for cancer treatment. In this study, we review the synthesis, properties, and applications of tungsten-oxide-based nanomaterials as a new type of photothermal material. The basic ideas behind photothermal nanomaterial development as well as the factors that influence their structural designs are also discussed in this study. In addition, recent progress in various fields such as NIR light-shielding, pyroelectric, water evaporation, photocatalysis, gas sensors, and energy-related applications for WO3-x- and MxWO3-based nanomaterials (including their hybrids) are highlighted. Finally, this review presents promising insights into this rapidly growing field that may inspire additional research leading to practical applications.

Cascaded crystalline Raman lasers for extended wavelength coverage: continuous-wave, third-Stokes operation

The development of high-power laser sources with narrow emission, tunable within the water transmission window around 1.7 μm, is of interest for applications as diverse as medical imaging and atmospheric sensing. Where suitable laser gain media are not available, operation in this spectral region is often achieved via nonlinear frequency conversion, and optical parametric oscillators (OPOs) are a common solution. A practical alternative to OPOs, to avoid birefringent- or quasi-phase-matching requirements, is the use of stimulated Raman scattering within a suitable material to convert a pump source to longer wavelengths via one or more Stokes shifts; however, as this is a χ(3) nonlinear process, such frequency conversion is usually the preserve of high-energy pulsed lasers. Semiconductor disk lasers (SDLs), on the other hand, have very high-finesse external resonators, suitable for efficient intracavity nonlinear conversion even in continuous-wave (CW) operation. Here we report, to the best of our knowledge, the first continuous-wave third-Stokes crystalline Raman laser and the longest emission wavelength from an SDL-pumped Raman laser, achieving high power, CW output, and broad wavelength tuning around 1.73 μm. The KGd(WO4)2 (KGW) Raman laser, which was intracavity-pumped by a 1.18 μm InGaAs-based SDL, demonstrated cascaded CW Stokes oscillation at 1.32 μm, 1.50 μm, and 1.73 μm with watt-level output achievable at each wavelength. The 1.73 μm Stokes emission was diffraction limited (M2<1.01) and narrow linewidth (<46 pm FWHM; measurement limited). By rotation of a birefringent filter placed within the fundamental resonator, we attained three tunable emission wavelength bands, one centred at each Stokes component, and achieved up to 65 nm tuning for the third-Stokes Raman laser from 1696 nm to 1761 nm. We have thus demonstrated a platform laser technology that takes well-developed InGaAs-based SDLs and provides spectral coverage and high performance in the near-infrared water transmission windows using commercially available components.

Concentration determination of inorganic acids that do not absorb near-infrared (NIR) radiation through recognizing perturbed NIR water bands by them and investigation of accuracy dependency on their acidities

When near-infrared (NIR) spectroscopy is employed to determine the concentrations of inorganic acids in etchant solutions, the perturbation of the water bands resulting from the interactions with these acids is the only information available for analysis, since inorganic acids do not directly absorb NIR radiation. The water bands perturbed by dissociated hydronium ions and respective anions of the acids are not highly component-specific; therefore, characterization of their different interactions with water is necessary to understand the results of the multivariate quantitative analysis. For this purpose, the variations in the water bands that occurred with the inclusion of HCl, H2SO4, H3PO4, and HNO3 were initially examined with the aid of a two-dimensional (2D) correlation analysis. According to this analysis, components with higher acidity, such as HCl, perturbed the water hydrogen bonding network more strongly. Also, the interactions between each dissociated ionic species and water molecules were somewhat dissimilar. This dissimilarity enabled differentiation between the four acids, although the spectral specificity was not high owing to the absence of direct NIR absorption. The accuracy in the determination of concentrations was better for components with lower pKas, such as HCl and H2SO4, owing to their stronger perturbation of the water bands. When multicomponent samples were measured, the resulting accuracies deteriorated due to the further degradation in component specificity. Acquisition of reproducible spectra and avoidance of model over-fitting are critical for reliable NIR analysis of these types of samples, as the analyte-induced spectral features are broad and rather specificity-insufficient.