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Efficient and accurate computation of the single‐scattering properties of black carbon (BC) aerosols is fundamental in various fields, including remote sensing and climate simulations. In this study, we developed a composite model of fractal aggregates of BC encapsulated with hygroscopic aerosols to represent the ambient BC. We used the invariant imbedding T‐matrix method to compute the optical properties of fully and partially encapsulated BC aerosols. In this new model, the traditional assumption of unoverlapped surfaces in the super‐position T‐matrix method is unnecessary. After extensive simulations, we established a database of single‐scattering properties, including the extinction efficiency, the single‐scattering albedo, the asymmetry factor and six phase matrix elements. Moreover, we obtained deep neural networks (DNNs) from this database using a deep learning method. These DNN models provide a universal interface for predicting the optical properties of ambient BC aerosols. Specifically, through a modified architecture of the DNN, we trained two models based on the database to predict three integrated optical properties (extinction efficiency, single‐scattering albedo, and asymmetry factor) and six phase matrix elements. We performed statistical assessments based on the true values in the database and the predicted values from the DNNs, demonstrating that the DNNs accurately predicted all single‐scattering properties. Therefore, the developed DNN models can be conveniently implemented in aerosol optical parameterization for remote sensing studies and atmospheric models. Plain Language Summary: Black carbon (BC) aerosol plays a significant role in the atmosphere, influencing climate through its interactions with radiation, such as scattering and absorbing. The accurate determination of the single‐scattering properties of BC, including the extinction efficiency, the single‐scattering albedo, the asymmetry factor and six phase matrix elements, is crucial for understanding its radiation effects. In this study, we developed a comprehensive model for BC particles that incorporates complex morphological characteristics and the mixing of BC with other hygroscopic aerosols. We established a database of single‐scattering properties for these models using the invariant imbedding T‐matrix method. However, the large storage space required by this database (over 20 GB) makes it impractical for widespread applications. Therefore, we employed a deep learning method to compress the storage consumption. Two deep neural networks (DNNs) were trained using the database, enabling the prediction of all single‐scattering properties. Remarkably, the performance of the DNNs was excellent, with a coefficient of determination greater than 0.99 for all single‐scattering properties, as determined through statistical assessment. These DNN models hold great potential for various atmospheric radiation and remote sensing studies in the future. Key Points: A flexible model of partially and fully encapsulated fractal black carbon particles was developedA database of single‐scattering properties of encapsulated fractal black carbon particles was constructedTwo deep neural networks were obtained, offering a flexible approach to calculating the optical properties of black carbon aerosols [ABSTRACT FROM AUTHOR]

Active thermal radiation control of an object requires adaptive and flexible strategies to cope with emissivity engineering and its temperature dependence. On the other hand, the concept of digital coding allows a high degree of freedom in manipulating the interacting physical quantities based on local discretized features. Learning from this idea, this study put forward the manipulation of spatial infrared emission based on tungsten (W)‐doped VO2 films toward thermal coding. Here, 1‐bit coding worksheets created by low‐emissivity, that is, code '0′, and high‐emissivity, that is, code '1′, shift with materials metal‐insulator phase transition to encode emissive information in the temperature domain. It is shown experimentally that this concept has marked implications on thermal radiation control at Mid‐infrared, among which are as follows: digital anti‐counterfeiting by in‐plane spatial coding of a group of VO2 thin films with various W‐doping density and infrared camouflage by out‐of‐plane spatial coding of them. With a W‐doping gradient of 0%, 0.8%, and 1.7%, the three‐phase transition points in the temperature domain, that is, 72, 63, and 45 °C, give a remarkable modulation range of 27 °C. These phenomena pave the way for new classes of emissivity engineering for more accurate, flexible, and adaptive thermal radiation control. [ABSTRACT FROM AUTHOR]

In the current operational four‐dimensional variational (4DVar) data assimilation (DA) system of the Global Forecast System developed by the China Meteorology Administration (CMA‐GFS), all microwave observation data in cloud and precipitation regions are discarded during pre‐processing. This study implemented a Pseudo All‐Sky DA (referred to as PAS‐DA hereafter) subsystem in the operational cycle version of the CMA‐GFS (CMA‐GFS v3.2). The term "pseudo" in this study indicates that the Jacobians of brightness temperature with respect to hydrometeors from the adjoint radiative transfer model were temporarily neglected. Specifically, a liquid hydrometeor sensitive channel (23.8 GHz V pol.) of the MicroWave Radiation Imager on the platform of FengYun‐3D (FY3D‐MWRI) was selected to assess the impact of the all‐sky assimilation approach using the PAS‐DA subsystem. In the observation error model, we proposed a new cumulative distribution function (CDF) bias correction method for the cloud proxy in consideration of large discrepancies between the probability density functions (PDFs) of the observed‐cloud‐proxy and simulated‐cloud‐proxy (known as "cloud bias"). Results of single‐observation experiments justified that the present PAS‐DA subsystem could extend analysis increments to cloud regions, meanwhile correcting the errors of humidity analysis according to the mislocation of cloud distributions. In addition, the forecast experiments that were run for 1 month of the 6 hr PAS‐DA cycle in July and August 2021 demonstrate obvious superiority of the PAS‐DA over the current operational clear‐sky DA cycle: (a) root‐mean‐square errors (RMSEs) of humidity analysis were reduced by about 10% in the tropics, (b) significant improvements in humidity forecasts could be sustained for 96 hr and (c) many other forecast scores in the tropics and Southern Hemisphere also benefit from the PAS‐DA approach. Therefore, the PAS‐DA could be used for all‐sky assimilation studies and particularly for understanding how the all‐sky assimilation approach works, although the PAS‐DA serves as a transition scheme from the clear‐sky to "true" all‐sky DA. [ABSTRACT FROM AUTHOR]

Purpose: Ankylosing spondylitis (AS) is a chronic inflammatory disease of the axial spine; however, the quantitative detection of inflammation in AS remains a challenge in clinical settings. We aimed to investigate the feasibility of using a specific P2X7R-targeting 18F-labeled tracer [18F]GSK1482160 for positron emission tomography (PET) imaging and the quantification of AS. Methods: The radioligand [18F]GSK1482160 was obtained based on nucleophilic aliphatic substitution. Dynamic [18F]GSK1482160 and [18F]FDG micro-PET/CT imaging were performed on AS mice (n = 8) and age-matched controls (n = 8). Tracer kinetics modeling was performed using Logan's graphical arterial input function analysis to quantify the in vivo expression of P2X7R. The post-PET tissues were collected for hematoxylin–eosin (H&E), immunohistochemical (IHC), and immunofluorescence (IF) staining. Results: [18F]GSK1482160 PET/CT imaging revealed that the specific binding in the ankle joint and sacroiliac joint (SIJ) of the AS at 8 weeks group (BPNDankle−AS−8W (non-displaceable binding potential of the ankle) 3.931 ± 0.74; BPNDSIJ−AS−8W (BPBD of the SIJ) 4.225 ± 0.84) were significantly higher than the controls at 8 weeks group (BPNDankle−Ctr−8W 0.325 ± 0.15, BPNDSJJ−Ctr−8W 0.319 ± 0.17) respectively, and the AS at 14 weeks group (BPNDankle−AS−14W 12.212 ± 2.25; BPNDSJJ−AS−14W 13.389 ± 3.60) were significantly higher than the controls at 14 weeks group (BPNDankle−Ctr−14W 0.204 ± 0.16, BPNDSJJ−Ctr−14W 0.655 ± 0.35) respectively. The four groups had no significant difference in the [18F]FDG uptake of ankle and SIJ. IHC and IF staining revealed that the overexpression of P2X7R was colocalized with activated macrophages from the ankle synovium and spinal endplate in mice with AS, indicating that quantification of P2X7R may contribute to the understanding of the pathogenesis of inflammation in human AS. Conclusion: This study developed a novel P2X7R-targeting PET tracer [18F]GSK1482160 to detect the expression of P2X7R in AS mouse models and provided powerful non-invasive PET imaging and quantification for AS. [ABSTRACT FROM AUTHOR]

The development of proton, oxygen‐ion, and electron mixed conducting materials, known as triple‐conduction materials, as cathodes for proton‐conducting solid oxide fuel cells (H‐SOFCs) is highly desired because they can increase fuel cell performance by extending the reaction active area. Although oxygen‐ion and electron conductions can be measured directly, proton conduction in these oxides is usually estimated indirectly. Because of the instability of cathode materials in a reducing environment, direct measurement of proton conduction in cathode oxide is difficult. The La0.8Sr0.2Sc0.5Fe0.5O3–δ (LSSF) cathode material is proposed for H‐SOFCs in this study, which can survive in an H2‐containing atmosphere, allowing measurement of proton conduction in LSSF by hydrogen permeation technology. Furthermore, LSSF is discovered to be a unique proton and electron mixed‐conductive material with limited oxygen diffusion capability that is specifically designed for H‐SOFCs. The LSSF is an appealing cathode choice for H‐SOFCs due to its outstanding CO2 tolerance and matched thermal expansion coefficient, producing a record‐high performance of 2032 mW cm−2 at 700°C and good long‐term stability under operational conditions. The current study reveals that a new type of proton–electron mixed conducting cathode can provide promising performance for H‐SOFCs, opening the way for developing high‐performance cathodes. [ABSTRACT FROM AUTHOR]

Mineral dust particles are typically nonspherical and inhomogeneous; however, they are often simplified as homogeneous spherical particles for retrieving the refractive indices from laboratory measurements of scattering and absorption coefficients. This study theoretically investigated uncertainties in refractive indices and corresponding optical properties resulting from this simplification at various sizes within the wavelength range of 355 to 1064 nm. Different numerical experiments were conducted under both ideal and realistic scenarios, taking into account instrumental bias in the realistic scenarios. In the numerical experiments, the inhomogeneous super-spheroid models were considered as the dust samples, while the homogeneous super-spheroid models and sphere models were used to retrieve the refractive indices. Under the ideal scenario, the look-up tables for the homogeneous super-spheroid models satisfactorily covered the measurements at any size and wavelength, while those for the sphere models failed when considering large sizes. Under the realistic scenario, both the homogeneous super-spheroid models and sphere models were ineffective for large sizes due to discrepancies in size distribution resulting from the measurements using an optical particle counter. Nevertheless, it was possible to retrieve the imaginary parts of the refractive indices based solely on the absorption coefficients. The imaginary parts obtained from the sphere models were generally consistent with those from the super-spheroid models under ideal conditions, while the former was significantly smaller than the latter under the realistic conditions. In addition, the retrieved imaginary parts were found to be size-dependent, which could be attributed to the inherent limitations of homogeneous models in characterizing inhomogeneous particles. Results showed that the uncertainties in the imaginary part and single scattering albedo should be smaller than 0.002 (0.0007) and 0.03 (0.01), respectively, under conditions of high (low) absorption. The sphere models tended to overestimate the asymmetry factor. The uncertainty in the asymmetry factor exhibited a significant variation, reaching up to 0.04 or even larger. Nonetheless, the uncertainties in the phase matrices resulting from the uncertainties in refractive indices were generally acceptable within a specific model. [ABSTRACT FROM AUTHOR]