Inherent Optical Properties Research Articles

Quantifying Photodegradation of Peatland‐Derived Dissolved Organic Carbon in the Coastal Ocean of Southeast Asia

AbstractSoutheast Asia's peatlands are a globally significant source of terrigenous dissolved organic carbon (tDOC) to the ocean, and field observations show that this tDOC is extensively remineralized within the shelf sea. Yet the processes that drive this remineralization remain unclear. Here, we combined incubation experiments and model simulations to quantify the rate and extent of photodegradation of tDOC in the Sunda Shelf Sea. During laboratory photodegradation experiments, 26%–74% of the peatland tDOC was photomineralized, but realistic in situ rates of photodegradation have not yet been estimated in this region. Based on spectrally resolved apparent quantum yields for tDOC remineralization calculated from experiments, modeled in situ solar irradiance, and measured in‐water inherent optical properties, we simulated peatland tDOC photomineralization for two coastal regions of the Sunda Shelf Sea. These simulations show that sunlight can directly remineralize 25 ± 9% of the tDOC input over its maximum 2‐year residence time in the Sunda Shelf Sea, accounting for 38% of the total tDOC remineralization. We also found that photobleaching can remove 54 ± 4% of colored dissolved organic matter over this time‐scale. We further derived a simplified photochemical decay constant ∅ref of 0.016 day−1 for Southeast Asia's peatland‐derived tDOC, which can be used to parameterize the recently proposed UniDOM model. We conclude that direct photodegradation may be a greater sink for tDOC in Southeast Asia's coastal ocean compared to higher latitudes, although it is insufficient to account for the total tDOC remineralization observed in the Sunda Shelf Sea.

Monte-Carlo based vertical underwater optical communication performance analysis with chlorophyll depth profiles

Although underwater wireless optical communication (UWOC) has the advantages of high speed, low latency, and high confidentiality, the transmission of light in water will be affected by the absorption and scattering of particles, which will lead to the aggravation of channel path loss as well as channel pulse spreading, finally causing false codes. Therefore, how to analyze the channel impulse response (CIR) effectively is a key task in channel modeling. In this paper, we consider a two-way underwater vertical line-of-sight (LOS) communication system model, based on the inherent optical property (IOP) model of chlorophyll, using the Kopelevich phase function containing water depth information, the CIR curves under different water types and transceiver configurations are plotted using the Monte-Carlo Simulation (MCS). The obtained simulation results are fitted with the double gamma function (DGF) model and the Gaussian model, respectively. The Gaussian model exhibits better properties than the DGF model in each water condition. Based on the closed-form expression of the CIR obtained from the Gaussian model, we solve for the bit error rate (BER) and 3-dB bandwidth of the system under different settings. The conclusions obtained can be used for the design and optimization of underwater vertical channels.

Semi-analytical model for deep-water hyperspectral imaging.

We propose a semi-analytical (SA) model for relating seafloor reflectance to measured radiance in deep-water hyperspectral imaging in artificially illuminated scenes. Using accurate sensor-seafloor geometry from photogrammetry and the principle of two-viewpoint observation, we estimate the inherent optical properties (IOPs) of the water column. We demonstrate the SA model and estimation of IOPs for hyperspectral imaging of a deep-water coral reef from a remotely operated vehicle. For the calibrated SA model, evaluation of across-viewpoint similarity demonstrates the model's ability to compensate for water column and light source effects.

Informing ocean color inversion products by seeding with ancillary observations.

Ocean reflectance inversion algorithms provide many products used in ecological and biogeochemical models. While a number of different inversion approaches exist, they all use only spectral remote-sensing reflectances (Rrs(λ)) as input to derive inherent optical properties (IOPs) in optically deep oceanic waters. However, information content in Rrs(λ) is limited, so spectral inversion algorithms may benefit from additional inputs. Here, we test the simplest possible case of ingesting optical data ('seeding') within an inversion scheme (the Generalized Inherent Optical Property algorithm framework default configuration (GIOP-DC)) with both simulated and satellite datasets of an independently known or estimated IOP, the particulate backscattering coefficient at 532 nm (bbp(532)). We find that the seeded-inversion absorption products are substantially different and more accurate than those generated by the standard implementation. On global scales, seasonal patterns in seeded-inversion absorption products vary by more than 50% compared to absorption from the GIOP-DC. This study proposes one framework in which to consider the next generation of ocean color inversion schemes by highlighting the possibility of adding information collected with an independent sensor.

Neural network spectral relationship to improve an inherent optical properties data processing system for residual error correction.

The residual error was a critical indicator to measure the data quality of ocean color products, which allows a user to decide the valuable envisioned application of these data. To effectively remove the residual errors from satellite remote sensing reflectance (Rrs) using the inherent optical data processing system (IDAS), we expressed the residual error spectrum as an exponential plus linear function, and then we developed neural network models to derive the corresponding spectral slope coefficients from satellite Rrs data. Coupled with the neural network models-based spectral relationship, the IDAS algorithm (IDASnn) was more effective than an invariant spectral relationship-based IDAS algorithm (IDAScw) in reducing the effects of residual errors in Rrs on IOPs retrieval for our synthetic, field, and Chinese Ocean Color and Temperature Scanner (COCTS) data. Particularly, due to the improved spectral relationship of the residual errors, the IDASnn algorithm provided more accurate and smoother spatiotemporal ocean color product than the IDAScw algorithm for the open ocean. Furthermore, we could monitor the data quality with the IDASnn algorithm, suggesting that the residual error was exceptionally large for COCTS images with low effective coverage. The product effective coverage should be rigorously controlled, or the residual error should be accurately corrected before temporal and spatial analysis of the COCTS data. Our results suggest that an accurate spectral relationship of residual errors is critical to determine how well the IDAS algorithm corrects for residual error.

A novel Pt modified AlGaN/Si double-junction nanostructure for stable and self-powered solar blind photoelectrochemical photodetection

Simultaneously searching for self-powered, efficient, stable photoelectrode is the key to realizing the next-generation energy-efficient and sustainable integrated solar blind photoelectrochemical (PEC) photodetector. In this work, a Pt modified AlGaN/Si double-junction nanostructure with an n++ AlGaN/p++ AlGaN tunnel junction (TJ) and a AlGaN/Si junction is reported to achieve stable and self-powered solar blind photodetection. PEC tests demonstrate that the photocurrent density of the Pt modified AlGaN with n++ AlGaN/p++ AlGaN TJ photoelectrode can reach up to −56.1 μA/cm2 under 255 nm light irradiation with 1.1 mW/cm2 at 0 V bias versus a Pt counter electrode in a three-electrode configuration. Time-steady photoluminescence and XRD spectra are carried out and confirm the inherent optical and physical properties of this nanostructure. In addition, the multicycle and long-term stability measurement shows an excellent switching behavior even after being placed in the air for one month with a photocurrent density of −44.9 μA/cm2 (80% of its initial photocurrent). Furthermore, the PEC performance of the Pt modified AlGaN with n++ AlGaN/p++ AlGaN tunnel junction photoelectrode is evaluated in different light wavelengths, light intensities, bias potential and H2SO4 concentrations. These results demonstrate that the as-prepared photoelectrode has a great potential application in stable self-powered solar blind photodetector.

Assessing the suitability of lakes and reservoirs for recreation using Landsat 8

Water clarity has long been used as a visual indicator of the condition of water quality. The clarity of waters is generally valued for esthetic and recreational purposes. Water clarity is often assessed using a Secchi disk attached to a measured line and lowered to a depth where it can be no longer seen. We have applied an approach which uses atmospherically corrected Landsat 8 data to estimate the water clarity in freshwater bodies by using the quasi-analytical algorithm (QAA) and Contrast Theory to predict Secchi depths for more than 270 lakes and reservoirs across the continental US. We found that incorporating Landsat 8 spectral data into methodologies created to retrieve the inherent optical properties (IOP) of coastal waters was effective at predicting in situ measures of the clarity of inland water bodies. The predicted Secchi depths were used to evaluate the recreational suitability for swimming and recreation using an assessment framework developed from public perception of water clarity. Results showed approximately 54% of the water bodies in our dataset were classified as “marginally suitable to suitable” with approximately 31% classed as “eminently suitable” and approximately 15% classed as “totally unsuitable–unsuitable”. The implications are that satellites engineered for terrestrial applications can be successfully used with traditional ocean color algorithms and methods to measure the water quality of freshwater environments. Furthermore, operational land-based satellite sensors have the temporal repeat cycles, spectral resolution, wavebands, and signal-to-noise ratios to be repurposed to monitor water quality for public use and trophic status of complex inland waters.

Algal Biological Features Viewed in Satellite Observations: A Case Study of the Bohai Sea

Algal cell abundance weakly depends on inherent optical properties and chlorophyll-a concentration in the Bohai Sea, so it is very hard to derive algal cell abundance (ACA) from ocean color data using a simple bio-optical model. To obtain ACA for biological communication at large scale, a neural network model has been developed and then applied for investigating the changing monthly trend of ACA, intracellular chlorophyll-a concentration, and cell size in the Bohai Sea using MODIS data from 2002 to 2015. The results showed that the neural network model could provide an accurate log-transformed value of algal cell abundance (LACA) from ocean color images whose retrieval uncertainty did not exceed 9%. Furthermore, when the model was applied to map the monthly mean LACA and then further convert it to cell size in the Bohai Sea, the results showed that the satellite-derived monthly mean cell size varied from 4.81 to 15.29 μm. The decreasing monthly mean algal cell abundance and increasing monthly mean chlorophyll-a concentration imply that the monthly mean intracellular chlorophyll-a concentration from 2002 to 2015 increased, which indicates that the waters in the Bohai Sea became more eutrophic over those 14 years. Moreover, due to seasonal variations in vertical mixing or other physical forcing factors, the ACA and cell size exhibited significant seasonal variations. Although further tests are required to validate the model’s robustness, these preliminary results indicate that the neural network model is an encouraging approach to exploiting more novel biological parameters such as the LACA from ocean color satellites for oceanic communication.

Optical closure in highly absorptive coastal waters: significance of inelastic scattering processes.

In hydrological optics, "optical closure" means consistency between the apparent optical properties (AOPs) determined from radiometric measurements and those derived from radiative transfer modelling based on concurrently measured inherent optical properties (IOPs) and boundary conditions (sea and sky states). Good optical closure not only provides confidence in the data quality but also informs on the adequacy of the radiative transfer parameterization. Achieving optical closure in highly absorptive coastal waters is challenging due to the low signal-to-noise ratio of radiometric measurements and uncertainties in the measurements of IOPs, namely the spectral absorption and backscattering coefficients. Here, we present an optical closure assessment using a comprehensive set of in situ IOPs acquired in highly absorptive coastal waters optically dominated by chromophoric dissolved organic matter (CDOM). The spectral remote sensing reflectance, Rrs(λ), was modeled using the software HydroLight (HL) with measured IOPs and observed boundary conditions. Corresponding in-water in situRrs(λ) was derived from radiometric measurements made with a Compact Optical Profiling System (C-OPS; Biospherical). The assessment revealed that the inclusion of inelastic scattering processes in the model, specifically sun-induced CDOM fluorescence (fDOM) and sun-induced chlorophyll fluorescence (SICF) from Chlorophyll-a ([chl]), significantly improved the optical closure and led to good agreement between measured and modeled Rrs (i.e., for 440 ≤ λ ≤ 710 nm with no inelastic processes: R2=0.90, slope=0.64; with inelastic processes: R2=0.96, slope=0.90). The analysis also indicated that fDOM and SICF contributed a substantial fraction of the green-red wavelength Rrs in these waters. Specifically, fDOM contributed ∼18% of the modeled Rrs in the green region and SICF accounted for ∼20% of the modeled Rrs in the red region. Overall, this study points out the importance of accounting for fDOM in remote sensing applications in CDOM-dominated waters.

Non-invasive investigation of the morphology and optical properties of the upside-down jellyfish Cassiopea with optical coherence tomography.

The jellyfish Cassiopea largely cover their carbon demand via photosynthates produced by microalgal endosymbionts, but how holobiont morphology and tissue optical properties affect the light microclimate and symbiont photosynthesis in Cassiopea remain unexplored. Here, we use optical coherence tomography (OCT) to study the morphology of Cassiopea medusae at high spatial resolution. We include detailed 3D reconstructions of external micromorphology, and show the spatial distribution of endosymbionts and white granules in the bell tissue. Furthermore, we use OCT data to extract inherent optical properties from light-scattering white granules in Cassiopea, and show that granules enhance local light-availability for symbionts in close proximity. Individual granules had a scattering coefficient of µs = 200-300 cm-1, and scattering anisotropy factor of g = 0.7, while large tissue-regions filled with white granules had a lower µs = 40-100 cm-1, and g = 0.8-0.9. We combined OCT information with isotopic labelling experiments to investigate the effect of enhanced light-availability in whitish tissue regions. Endosymbionts located in whitish tissue exhibited significantly higher carbon fixation compared to symbionts in anastomosing tissue (i.e. tissue without light-scattering white granules). Our findings support previous suggestions that white granules in Cassiopea play an important role in the host modulation of the light-microenvironment.

Ultra-high performance flexible and controllable superhydrophobic films based on microsphere/micro-pyramid hierarchical arrays

Ultra-high performance flexible superhydrophobic surfaces have attracted great research interests, which are widely used in anti-fog, anti-icing, anti-fouling, self-cleaning, and other fields. However, ultra-high hydrophobic properties and complex manufacturing processes are still huge challenges to be solved. In this paper, a facile construction strategy of ultra-high performance flexible and controllable superhydrophobic films was proposed, combining the template transfer and electrospinning methods. The effects of electrospinning parameters on the microstructure and surface wettability were systematically studied, and the controllable preparation of films with different wettability was realized. Under the stable Cassie-Baxter state, the contact angle of prepared superhydrophobic films could reach 172° and the sliding angle could reach 3°. In addition, the stretchability, abrasion resistance, and chemical durability tests were also conducted in simulated harsh real-world environments. The results indicated that the films still exhibited superior performances. For the practical demonstration, the films are expected to be used as protective films for windshields, outdoor electronic screens, and solar cells due to the inherent optical properties and excellent fouling resistance performance.

Confocal corrected attenuation coefficient imaging in phantoms and in vivo using chromatic focal shift calibration.

Optical coherence tomography (OCT) is conventionally used for structural imaging of tissue. Calibrating the intensity values of OCT images can give information on the tissue's inherent optical properties, such as the attenuation coefficient, which can provide an additional parameter to quantify possible pathological changes. To obtain calibrated intensity values, the focus position and Rayleigh length of the incident beam need to be known. We explore the feasibility of extracting the focus position from an OCT scan acquired with a single focus setting using the chromatic aberration of the system. The chromatic focal shift of an OCT system is exploited to achieve different focus positions for sub-spectrum reconstructed OCT images. The ratios of these images are used to estimate the focus position. Reconstruction of a high-resolution B-scan from coherent addition of sub-spectrum confocal function corrected B-scans and subsequent high-resolution OCT attenuation coefficient imaging is demonstrated. Furthermore, we introduce a method to experimentally determine the chromatic focal shifts of an OCT system in phantoms and an in vivo human retina. These shifts are compared to the theoretically expected shifts calculated with ray tracing.

Impact of subsurface chlorophyll maxima on satellite-based Arctic spring primary production estimates

In recent years several regional and pan-Arctic ocean color algorithms, which consider the unique bio-optical properties of the Arctic Ocean, have been developed to accurately extract surface chlorophyll a (Chl a), a key input into net primary production (NPP) algorithms, from spectral remote sensing reflectance (Rrs). However, most satellite derived NPP (NPPSAT) algorithms used in the Arctic do not account for production at deep subsurface chlorophyll maxima (SCMs), a prominent feature in the Arctic Ocean during the summer months, leading to underestimations of NPP during the post-bloom period. In this study, a shallow SCM was observed in early summer (June/July 2016) in Baffin Bay at the time of the sea ice edge bloom, raising the question to what extent this SCM contributes to Rrs and how it is captured in NPPSAT estimates. Radiative transfer simulations based on in situ data of inherent and apparent optical properties and Chl a concentration in the water column were used to examine the effects of heterogeneous vertical Chl a profiles of various strength and depth on spectral reflectance, algorithm-derived surface Chl aSAT and NPPSAT. NPPSAT estimates for varying Chl a profile shapes were then compared to NPPSAT estimates of reference simulations for homogenous Chl a profiles, and to measured NPP calculated using observed Chl a profiles. Results show a significant impact of shallow SCMs on Rrs with the depth of maximum Chl a < 30 m, causing an increase in Chl aSAT by 17 ± 6% relative to a vertically homogenous ocean. Interestingly, SCMs significantly influencing Rrs were found down to the fifth light penetration depth. The increase in Chl aSAT reduced the difference between predicted and measured NPP estimates to −25 ± 12% at stations with a shallow SCM. Furthermore, due to the significant contribution of these shallow SCM stations to regional NPP, regional predicted NPPSAT was only 16% lower than measured NPP. Our results demonstrate that the partial representation of a shallow and very productive SCM in Chl aSAT minimizes errors in satellite-based NPPSAT estimates of the Arctic spring bloom during the sea ice melt period.

Light Absorption by Optically Active Components in the Arctic Region (August 2020) and the Possibility of Application to Satellite Products for Water Quality Assessment

In August 2020, during the 80th cruise of the R/V “Akademik Mstislav Keldysh”, the chlorophyll a concentration (Chl-a) and spectral coefficients of light absorption by phytoplankton pigments, non-algal particles (NAP) and colored dissolved organic matter (CDOM) were measured in the Norwegian Sea, the Barents Sea and the adjacent area of the Arctic Ocean. It was shown that the spatial distribution of the three light-absorbing components in the explored Arctic region was non-homogenous. It was revealed that CDOM contributed largely to the total non-water light absorption (atot(λ) = aph(λ) + aNAP(λ) + aCDOM(λ)) in the blue spectral range in the Arctic Ocean and the Barents Sea. The fraction of NAP in the total non-water absorption was low (less than 20%). The depth of the euphotic zone depended on atot(λ) in the surface water layer, which was described by a power equation. The Arctic Ocean, the Norwegian Sea and the Barents Sea did not differ in the Chl-a-specific light absorption coefficients of phytoplankton. In the blue maximum of phytoplankton absorption spectra, Chl-a-specific light absorption coefficients of phytoplankton in the upper mixed layer (UML) were higher than those below the UML. Relationships between phytoplankton absorption coefficients and Chl-a were derived by least squares fitting to power functions for the whole visible domain with a 1 nm interval. The OCI, OC3 and GIOP algorithms were validated using a database of co-located results (day-to-day) of in situ measurements (n = 63) and the ocean color scanner data: the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra (EOS AM) and Aqua (EOS PM) satellites, the Visible and Infrared Imager/Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (S-NPP) and JPSS-1 satellites (also known as NOAA-20), and the Ocean and the Land Color Imager (OLCI) onboard the Sentinel-3A and Sentinel-3B satellites. The comparison showed that despite the technological progress in optical scanners and the algorithms refinement, the considered standard products (chlor_a, chl_ocx, aph_443, adg_443) carried little information about inherent optical properties in Arctic waters. Based on the statistic metrics (Bias, MdAD, MAE and RMSE), it was concluded that refinement of the algorithm for retrieval of water bio-optical properties based on remote sensing data was required for the Arctic region.

Uncertainty of atmospheric scattering functions relevant for Satellite Ocean Colour Radiometry in European Seas

ABSTRACT Uncertainty assessment of Ocean Colour Radiometry (OCR) usually relies on the comparison between satellite marine reflectance and concurrent in situ radiometric measurements. However, when dealing with the standard atmospheric correction (AC), uncertainty of marine reflectance originates fundamentally from two sources: (i) uncertainty of the Level-1 calibration at top of the atmosphere, and (ii) uncertainty of the atmospheric scattering functions computed by the AC (atmospheric path reflectance and transmittance). The aim of this alternative work is thus to assess the uncertainty of these scattering functions, thanks to inherent optical properties of aerosols extracted from the AErosol Robotic NETwork (AERONET) and ingested in a radiative transfer code. The study is conducted for the MEdium Resolution Imaging Spectrometer (MERIS), over three AERONET sites selected in European seas (Aqua Alta Oceanographic Tower, AAOT; Gustav Dalen Tower, GDT; Lampedusa) and Lanai in the Pacific Ocean as a reference. We develop an uncertainty budget based on the statistical analysis of the errors between MERIS and AERONET-derived data. At 443 nm, uncertainty of MERIS atmospheric path reflectance due to random effects is estimated around 2%, while that of total atmospheric transmittance is between 0.6% and 1%. Propagation of these uncertainties to OCR is achieved following metrological principles and varies between match-ups and sites due to the distinctive contribution of the marine signal to the total radiometry: uncertainty of MERIS marine reflectance at 443 nm is 10.8% (±1.1%) at Lanai, 18.3% (±4.6%) at Lampedusa, 29.4% (±12.2%) at AAOT and up to 68.7% (±127.4%) at GDT (i.e. with a significant intra-site variability). The methodology is a first step aimed at deriving a pixel-by-pixel uncertainty budget of OCR, instead of providing overall estimates as generally done in the OC community. Limitations due to uncertainties in the AERONET data are also discussed, with a tentative quantification.

Analysis of bio-optical active constituents for lentic ecosystem through spectral-spatial and in-vitro observation.

The neural network algorithm approach was adopted in Kolavai Lake to retrieve the inherent optical properties (IOP) of active constituents. The retrieval of IOP by absorption and the scattering of optically active constituents (OAC) through employing Sentinel-2 MSI reflectance and field measured the salinity and temperature. The result illustrates the relationship between the IOP and measured OAC's concentrations and its sensitivity towards spectral wavelength. It shows that the phytoplankton absorption ap is highly related with chlorophyll-a concentration and has an R2 value of 0.808. Furthermore, at the total absorption of water has high correlation with chl-a which indicates the significant dominance in the lentic water. Also, the pigment constituents are showing an R2 value of 0.754. The total backscattering of water (btot) is strongly related to the total suspended matter with R value > 0.73. The spatial distribution of OAC in Kolavai Lake helps monitor the lake water quality. This approach is well-performed in estimating the inherent optical properties of optically active constituents that gives insight for assessing the relationship between IOP and water quality. The research has proved to be a good potential for monitoring lentic water quality through Sentinel-2 MSI.

A synthetic optical database generated by radiative transfer simulations in support of studies in ocean optics and optical remote sensing of the global ocean

Abstract. Radiative transfer (RT) simulations have long been used to study the relationships between the inherent optical properties (IOPs) of seawater and light fields within and leaving the ocean, from which ocean apparent optical properties (AOPs) can be calculated. For example, inverse models used to estimate IOPs from ocean color radiometric measurements have been developed and validated using the results of RT simulations. Here we describe the development of a new synthetic optical database based on hyperspectral RT simulations across the spectral range of near-ultraviolet to near-infrared performed with the HydroLight radiative transfer code. The key component of this development is the generation of a synthetic dataset of seawater IOPs that serves as input to RT simulations. Compared to similar developments of optical databases in the past, the present dataset of IOPs is characterized by the probability distributions of IOPs that are consistent with global distributions representative of vast areas of open-ocean pelagic environments and coastal regions, covering a broad range of optical water types. The generation of synthetic data of IOPs associated with particulate and dissolved constituents of seawater was driven largely by an extensive set of field measurements of the phytoplankton absorption coefficient collected in diverse oceanic environments. Overall, the synthetic IOP dataset consists of 3320 combinations of IOPs. Additionally, the pure seawater IOPs were assumed following recent recommendations. The RT simulations were performed using 3320 combinations of input IOPs, assuming vertical homogeneity within an infinitely deep ocean. These input IOPs were used in three simulation scenarios associated with assumptions about inelastic radiative processes in the water column (not considered in previous synthetically generated optical databases) and three simulation scenarios associated with the sun zenith angle. Specifically, the simulations were made assuming no inelastic processes, the presence of Raman scattering by water molecules, and the presence of both Raman scattering and fluorescence of chlorophyll a pigment. Fluorescence of colored dissolved organic matter was omitted from all simulations. For each of these three simulation scenarios, the simulations were made for three sun zenith angles of 0, 30, and 60∘ assuming clear skies, standard atmosphere, and a wind speed of 5 m s−1. Thus, overall 29 880 RT simulations were performed. The output results of these simulations include radiance distributions, plane and scalar irradiances, and a whole set of AOPs, including remote-sensing reflectance, vertical diffuse attenuation coefficients, and mean cosines, where all optical variables are reported in the spectral range of 350 to 750 nm at 5 nm intervals for different depths between the sea surface and 50 m. The consistency of this new synthetic database has been assessed through comparisons with in situ data and previously developed empirical relationships involving IOPs and AOPs. The database is available at the Dryad open-access repository of research data (https://doi.org/10.6076/D1630T, Loisel et al., 2023).

Structural Transition in (C2H5NH3)3Bi2-xSbxI9:[(Bi/Sb)2I9]3- Dimers to [(Bi/Sb)3I12]3- Trimers to (∞1)[(Bi/Sb)2I93-] 1D Infinite Chains.

Antimony/bismuth-based lead-free hybrid halide defect 2D perovskites have been generating enormous research interest due to their inherent excellent optical properties. Exploration of new phases and understanding of their structural and optoelectronic properties are of paramount importance in the process of developing materials for practical solar cell applications. In this article, we have reported a structural transition from the 0D hexagonal phase containing isolated [M2I9]3- (M = Bi/Sb) units to the 1D orthorhombic phase via a new monoclinic phase with novel isolated trimeric [M3I12]3- units in (C2H5NH3)3Bi2-2xSb2xI9. The hexagonal phase is stable up to 2x = 0.6 in (C2H5NH3)3Bi2-2xSb2xI9. With gradual substitution of Sb, the cation-cation repulsion increases, which destabilizes the [M2I9]3- unit, and hence, the hexagonal phase becomes unstable. At intermediate composition, 2x = 0.8-1.6, a new monoclinic phase (S.G.: C2/m) with the composition (C2H5NH3)2Bi2-2xSb2xI8 is formed, containing isolated [M3I12]3- units. The symmetry reduction resulted in larger distortion, which relaxes the strain and stabilizes the trimeric unit in the intermediate compositions. Finally, at higher Sb compositions (2x = 1.9-2.0), the compounds crystallize in the orthorhombic 1D phase. In all three phases of (C2H5NH3)3Bi2-2xSb2xI9, the cationic ethylammonium units are completely disordered over the whole unit cell. Raman study clearly shows the phase transition in (C2H5NH3)3Bi2-2xSb2xI9 and also the structural distortion in (C2H5NH3)2Bi2-2xSb2xI8. Optical property study shows that all the compounds are of indirect band gap type. Furthermore, PL study shows better emission properties of the 1D orthorhombic Sb compounds as compared to the 0D hexagonal and monoclinic phases.

The Coastal Surveillance Through Observation of Ocean Color (COASTℓOOC) dataset

Abstract. Coastal Surveillance Through Observation of Ocean Color (COASTℓOOC) oceanographic expeditions were conducted in 1997 and 1998 to examine the relationship between the optical properties of seawater and related biological and chemical properties across the coastal to open-ocean gradient in various European seas. A total of 379 stations were visited along the coasts of the Gulf of Lion in the Mediterranean Sea (n=61), the Adriatic Sea (n=39), the Baltic Sea (n=57), the North Sea (n=99), the English Channel (n=85), and the Atlantic Ocean (n=38). Particular emphasis was placed on the collection of a comprehensive set of apparent and inherent optical properties (AOPs and IOPs) to support the development of ocean color remote-sensing algorithms. The data were collected in situ using traditional ship-based sampling but also from a helicopter, which is a very efficient means for that type of coastal sampling. The dataset collected during the COASTℓOOC campaigns is unique in that it is fully consistent in terms of operators, protocols, and instrumentation. This rich and historical dataset is still today frequently requested and used by other researchers. Therefore, we present the result of an effort to compile and standardize a dataset which will facilitate its reuse in future development and evaluation of new bio-optical models adapted for optically complex waters. The dataset is available at https://doi.org/10.17882/93570 (Massicotte et al., 2023).

Difunctional Magnetic Nanoparticles Employed in Immunochromatographic Assay for Rapid and Quantitative Detection of Carcinoembryonic Antigen.

Immunochromatographic assay (ICA) plays an important role in in vitro diagnostics because of its simpleness, convenience, fastness, sensitivity, accuracy, and low cost. The employment of magnetic nanoparticles (MNPs), possessing both excellent optical properties and magnetic separation functions, can effectively promote the performances of ICA. In this study, an ICA based on MNPs (MNP-ICA) has been successfully developed for the sensitive detection of carcinoembryonic antigen (CEA). The magnetic probes were prepared by covalently conjugating carboxylated MNPs with the specific monoclonal antibody against CEA, which were not only employed to enrich and extract CEA from serum samples under an external magnetic field but also used as a signal output with its inherent optical property. Under the optimal parameters, the limit of detection (LOD) for qualitative detection with naked eyes was 1.0 ng/mL, and the quantitative detection could be realized with the help of a portable optical reader, indicating that the ratio of optical signal intensity correlated well with CEA concentration ranging from 1.0 ng/mL to 64.0 ng/mL (R2 = 0.9997). Additionally, method comparison demonstrated that the magnetic probes were beneficial for sensitivity improvement due to the matrix effect reduction after magnetic separation, and the MNP-ICA is eight times higher sensitive than ICA based on colloidal gold nanoparticles. The developed MNP-ICA will provide sensitive, convenient, and efficient technical support for biomarkers rapid screening in cancer diagnosis and prognosis.