Search Results (159)

In this work, a comprehensive theoretical investigation is carried out to explore the electronic and spectroscopic properties of selected diatomic molecular ions MgRb⁺ and SrRb⁺. Using high-level ab initio calculations based on a pseudopotential approach, along with large Gaussian basis sets and full valence configuration interaction (FCI), we accurately determine adiabatic potential energy curves, spectroscopic constants, transition dipole moments (TDMs), and permanent electric dipole moments (PDMs). To deepen our understanding of these systems, we calculate radiative lifetimes for vibrational levels in both ground and low-lying excited electronic states. This includes evaluating spontaneous and stimulated emission rates, as well as the effects of blackbody radiation. We also compute Franck–Condon factors and analyze photoassociation processes for both ions. Furthermore, to explore low-energy collisional dynamics, we investigate elastic scattering in the first excited states (2¹Σ⁺) describing the collision between the Ra atom and Mg⁺ or Sr⁺ ions. Our findings provide detailed insights into the theoretical electronic structure of these molecular ions, paving the way for future experimental studies in the field of cold and ultracold molecular ion physics. Full article

Measuring the emissivity of an infrared radiant sample with high accuracy is important. Previous studies reported on the multi- or two-temperature calibration methods, which used a reference blackbody (or blackbodies) to eliminate the background radiation, and assumed that the background radiation was independent of temperature. However, in practical measurements, this assumption does not hold. To solve the above problems, this study proposes a modified two-temperature calibration method and facility. The two temperature points are set in a certain small interval based on the proposed calculation method; based on the indication of the approximation that the emissivities of the sample and the background radiations remain the same at these two temperatures, the emissivities can be calculated with measurement signals at these two temperatures, and a reference blackbody is not needed. An experimental facility was built up and three samples with emissivities around 0.100, 0.500, and 0.900 were measured in (8~14) μm. The relative expanded uncertainties were 9.6%, 4.0%, and 1.5% at 60 °C, respectively, and 8.8%, 5.8%, and 1.2% at 85 °C (k = 2), respectively. The experimental results showed consistency with the results obtained using other methods, indicating the effectiveness of the developed method. The developed method might be suitable for samples whose emissivities are temperature insensitive. Full article

High-resolution numerical weather prediction requires accurate cloud microphysical initial conditions to enhance forecasting capabilities for high-impact severe weather events such as convective storms. This study integrated Fengyun-2 (FY-2) geostationary satellite data (equivalent blackbody temperature and total cloud cover) and next-generation 3D weather radar reflectivity from the China Meteorological Administration (CMA) to construct cloud microphysical initial fields and evaluate their impact on the CMA-MESO 3 km regional model. An analysis of the catastrophic rainfall event in Henan on 20 July 2021, and a 92-day continuous experiment (May–July 2024) revealed that assimilating cloud microphysical variables significantly improved precipitation forecasting: the equitable threat scores (ETSs) for 1 h forecasts of light, moderate, and heavy rain increased from 0.083, 0.043, and 0.007 to 0.41, 0.36, and 0.217, respectively, with average hourly ETS improvements of 21–71% for 2–6 h forecasts and increases in ETSs for light, moderate, and heavy rain of 7.5%, 9.8%, and 24.9% at 7–12 h, with limited improvement beyond 12 h. Furthermore, the root mean square error (RMSE) of the 2 m temperature forecasts decreased across all 1–72 h lead times, with a 4.2% reduction during the 1–9 h period, while the geopotential height RMSE reductions reached 5.8%, 3.3%, and 2.0% at 24, 48, and 72 h, respectively. Additionally, synchronized enhancements were observed in 10 m wind prediction accuracy. These findings underscore the critical role of cloud microphysical initialization in advancing mesoscale numerical weather prediction systems. Full article

The Flexible Combined Imager (FCI), developed as the next-generation imager for the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Meteosat Third Generation (MTG) satellite series, represents a significant advancement over its predecessor, SEVIRI, on the Meteosat Second Generation (MSG) satellites. FCI offers more spectral bands, higher spatial resolution, and faster imaging capabilities, supporting a wide range of applications in weather forecasting, climate monitoring, and environmental analysis. On 13 January 2024, the FCI onboard MTG-I1 (renamed Meteosat-12 in December 2024) experienced a critical anomaly involving the failure of its onboard Calibration and Obturation Mechanism (COM). As a result, the use of the COM was discontinued to preserve operational safety, leaving the instrument dependent on alternative calibration methods. This loss of onboard calibration presents immediate challenges, particularly for the infrared channels, including image artifacts (e.g., striping), reduced radiometric accuracy, and diminished stability. To address these issues, EUMETSAT implemented an external calibration approach leveraging algorithms from the Global Space-based Inter-Calibration System (GSICS). The inter-calibration algorithm transfers stable and accurate calibration from the Infrared Atmospheric Sounding Interferometer (IASI) hyperspectral instrument aboard Metop-B and Metop-C satellites to FCI’s infrared channels daily, ensuring continued data quality. Comparisons with Cross-track Infrared Sounder (CrIS) data from NOAA-20 and NOAA-21 satellites using a similar algorithm is then used to validate the radiometric performance of the calibration. This confirms that the external calibration method effectively compensates for the absence of onboard blackbody calibration for the infrared channels. For the visible and near-infrared channels, slower degradation rates and pre-anomaly calibration ensure continued accuracy, with vicarious calibration expected to become the primary source. This adaptive calibration strategy introduces a novel paradigm for in-flight calibration of geostationary instruments and offers valuable insights for satellite missions lacking onboard calibration devices. This paper details the COM anomaly, the external calibration process, and the broader implications for future geostationary satellite missions. Full article

This study addresses the challenges of high-power consumption and complexity in conventional infrared (IR) gas sensors by integrating metamaterials and gold coatings into IR radiation sources to reduce radiation loss. In addition, emitter design optimization and material selection were employed to minimize conduction loss. Our metasurface exhibited superior performance, achieving a narrower full width at half maximum at 4197 and 3950 nm, resulting in more confined emission spectral ranges. This focused emission reduced energy waste at unnecessary wavelengths, improving efficiency compared to traditional blackbody emitters. At 300 °C, the device consumed only 6.8 mW, while maintaining temperature uniformity and a fast response time. This enhancement is promising for the operation of such sensors in IoT networks with ultra-low power consumption and at suitably low costs for widespread demands in high-technology farming. Full article

Multispectral imaging technology holds significant promise in the field of thermal imaging applications, primarily due to its unique ability to provide comprehensive two-dimensional spectral data distributions without the need for any form of scanning. This paper focuses on the development of an accessible basic design concept and a method for estimating temperature maps using a four-channel spectral imaging system. The research examines key design considerations and establishes a workflow for data correction and processing. It involves preliminary camera calibration procedures, which are essential for accurately assessing and compensating for the characteristic properties of optical elements and image sensors. The developed method is validated through testing using a blackbody source, demonstrating a mean relative temperature error of 1%. Practical application of the method is demonstrated through temperature mapping of a tungsten lamp filament. Experiments demonstrated the capability of the developed multispectral camera to detect and visualize non-uniform temperature distributions and localized temperature deviations with sufficient spatial resolution. Full article

The reflectance (R) of linear and circular micro-gratings on c-plane sapphire Al₂O₃ ablated by a femtosecond (fs) laser were spectrally characterised for thermal emission $\propto (1-R)$ in the mid-to-far infrared (IR) spectral range. An IR camera was used to determine the blackbody radiation temperature from laser-patterned regions, which showed (3–6)% larger emissivity dependent on the grating pattern. The azimuthal emission curve closely followed the Lambertian angular profile $\propto cos{\theta }_a$ at the 7.5–13 μm emission band. The back-side ablation method on transparent substrates was employed to prevent debris formation during energy deposition as it applies a forward pressure of >0.3 GPa to the debris and molten skin layer. The back-side ablation maximises energy deposition at the exit interface where the transition occurs from the high-to-low refractive index. Phononic absorption in the Reststrahlen region 20–30 μm can be tailored with the fs laser inscription of sensor structures/gratings. Full article

Predicting the solar flux density distribution formed by heliostats in a concentrated solar tower power (CSP) plant is important for the optimization and stable operation of a CSP plant. However, the high temperature and blackbody attribute of the receiver makes direct measurement of the concentrated solar irradiance distribution a difficult task. To address this issue, indirect methods have been proposed. Nevertheless, these methods are either costly or not accurate enough. This study proposes a ray tracing-assisted deep learning method for the prediction of the concentrated solar flux density distribution formed by a heliostat. Namely, a generative adversarial neural network (GAN) model using Monte Carlo ray tracing results as the input was built for the prediction of solar flux density distribution concentrated by a heliostat. Experiments showed that the predicted solar flux density distributions were highly consistent with the concentrated solar spots on the Lambertian target formed by the same heliostat. This ray tracing-assisted deep learning method can be extended to other heliostats in the CSP plant and pave the way for the prediction of the solar flux density distribution concentrated by the whole heliostat field in a CSP plant. Full article

LED solar simulators currently face limitations in their spectral simulation capabilities, especially in terms of accurately incorporating AM0G and AM1.5G solar spectra. To this end, this study introduced a framework for an LED solar spectrum simulation algorithm that considers both AM0G and AM1.5G. This study examined the principle of solar spectrum discretization and reconstruction, established a foundation for analyzing the quality of solar spectrum reconstruction, and developed a non-dominated sorting genetic algorithm II (NSGA-II)-assisted long short-term memory (LSTM)-based solar spectrum simulation strategy. This strategy integrates a multi-objective genetic algorithm to generate training datasets and a neural network for solar spectrum simulation. A dataset generation method using the NSGA-II algorithm was implemented, which leveraged the 6500 K standard blackbody spectral curve, the spectral curve offset coefficients, and the spectral distributions of various narrowband LEDs. An LSTM-based neural network for solar spectrum simulation was developed, with the RMSE serving as the evaluation function. The analysis and selection of 29 narrowband LEDs produced 5000 solar spectrum simulation training datasets. The trained LSTM model achieved spectral matching accuracies within ±10.5% and ±9.3% for AM0G and AM1.5G, respectively, meeting the A+ level simulation standard for solar spectrum reconstruction considering AM0G and AM1.5G. These findings provide a theoretical foundation and technical advancements for high-precision solar spectrum reconstruction, which has practical implications for improving the efficiency and accuracy of solar energy systems, as well as supporting further research on solar spectrum utilization, and is expected to influence the development of more efficient solar simulators. Full article

A near-minimal instance of optical cooling is experimentally presented, wherein the internal-state entropy of a single atom is reduced more than twofold by illuminating it with broadband, incoherent light. Since the rate of optical pumping by a thermal state increases monotonically with its temperature, the cooling power in this scenario increases with higher thermal occupation, an example of a phenomenon known as cooling by heating. In contrast to optical pumping using coherent, narrow-band laser light, here, we perform the same task with fiber-coupled, broadband sunlight, the brightest laboratory-accessible source of continuous blackbody radiation. Full article

Silicon photodetectors are well developed, with the advantage of their low cost and easy fabrication. However, due to the semiconductor band gap limitation, their detection wavelength is limited in the visible and near-infrared ranges. To broaden the detection wavelength, we stacked a mercury telluride (HgTe) colloidal quantum dot (CQD) photodiode and a silicon PIN photodiode in series. This detector shows response spectra ranging from visible to short-wave infrared (430 nm to 2800 nm) at room temperature. At zero bias, the total photocurrents are 112.5 μA and 1.24 μA, with a tungsten lamp and a blackbody serving as light sources, respectively. The response speed can reach 1.65 μs, with the calculated detectivities of the visible wavelength D* = 1.01 × 10¹¹ Jones, and that of the short-wave infrared being D* = 2.66 × 10¹⁰ Jones at room temperature. At the same time, with a homemade trans-impedance amplifier (TIA) circuit, we demonstrate the device application for figuring out the amplified voltage of the VIS, SWIR, and the VIS-SWIR stacked layers. Full article

With the advancement of non-classical light sources such as single-photon and entangled-photon sources, innovative microscopy based on quantum principles has been proposed for traditional microscopy. This paper introduces the experimental demonstration of a quantum polarization microscopic technique that incorporates a quantum-entangled photon source. Although the point that employs the variation in polarization angle due to reflection or transmission at the sample is similar to classical polarization microscopy, the method for constructing the image contrast is significantly different. The image contrast is constructed by the coincidence count of signal and idler photons. In the case that the coincidence count is recorded from both the signal and idler photons, the photon statistics resemble a thermal state, similar to the blackbody radiation, but with a significantly higher peak intensity in the second-order autocorrelation function at zero delay that is derived from the coincidence count, while, when the coincidence count is taken from either the signal or idler photon only, although the photon state exhibits a thermal state again, the photon statistics become more dispersive and result in a lower peak intensity of the autocorrelation function. These different thermal states can be switched by slightly changing the photon polarization, which is suddenly aroused within a narrow range of the analyzer angle. The autocorrelation function g²(0) at the thermal state exhibits a sensitivity that is three times higher compared to the classical coincidence count rate, and this concept can be effectively utilized to enhance the contrast of the image. One of the key achievements of our proposed method is ensuring a low power of illumination (in the order of Pico-joules) for constructing the image. In addition, the robustness without any precise setup is also favorable for practical use. This polarization microscopic technique can provide a superior imaging technique compared to the classical method, opening a new frontier for research in material sciences, biology, and other fields requiring high-resolution imaging. Full article

It is vital to measure combustion temperature to define combustion models accurately. For single fuel particles in powder-fueled ramjets, their size distribution ranges from submicron to submillimeter, and their burn time is short to millisecond order. Moreover, the radiation intensity of different types of fuel particles significantly oscillated with several orders of magnitude. Current temperature measurement technology is facing this challenge. This paper proposes a highly spatiotemporal resolved pyrometry to measure the combustion temperature of fuel particles by coupling single-point photomultiplier tube (PMT)-based and two-dimensional complementary metal oxide semiconductor (CMOS)-based photoelectric devices. Both the offline calibration by blackbody furnace and online calibration by standard lamp confirmed the measurement accuracy of the pyrometry. Then, the pyrometry was used to measure the combustion temperature of fuel particles including micro-Al, nano-Al, micro-Mg, nano-B, and micro-B₄C. The temperature evolution and distribution of burning fuel particles were complementarily obtained, especially the interfacial flame temperature near the particle surface. Based on the obtained combustion temperature, the combustion characteristics and the energy release efficiencies among these fuels were evaluated and compared in detail, which are helpful to recognize, in depth, the combustion behavior and reveal the combustion mechanism of fuel particles in powder-fueled ramjets. Full article

In this study, we investigate the properties of a thin accretion disk around a static spherically symmetric black hole in 4D Einstein–Gauss–Bonnet gravity, with an additional coupling constant, $\alpha$, appearing in the spacetime metric. Using the Novikov–Thorne accretion disk model, we examine the thermal properties of the disk, finding that increasing $\alpha$ reduces the energy, angular momentum, and effective potential of a test particle orbiting the black hole. We demonstrate that $\alpha$ can mimic the spin of a Kerr black hole in general relativity up to $a\simeq$ 0.23 M for the maximum value of $\alpha$. Our analysis of the thermal radiation flux shows that larger $\alpha$ values increase the flux and shift its maximum towards the central black hole, while far from the black hole, the solution recovers the Schwarzschild limit. The impact of $\alpha$ on the radiative efficiency of the disk is weak but can slightly alter it. Assuming black-body radiation, we observe that the disk’s temperature peaks near its inner edge and is higher for larger $\alpha$ values. Lastly, the electromagnetic spectra reveal that the disk’s luminosity is lower in Einstein–Gauss–Bonnet gravity compared to general relativity, with the peak luminosity shifting toward higher frequencies, corresponding to the soft X-ray band as $\alpha$ increases. Full article

To obtain accurate blackbody temperature, emissivity, and waveband measurements, an energy-domain infrared nonuniformity method based on unsupervised learning is proposed. This method exploits the inherent physical correlation within the calibration dataset and sets the average predicted energy-domain value of the same blackbody temperature as the learning goal. Then, the coefficients of the model are learned without theoretical radiance labels by leveraging clustering-based unsupervised learning methodologies. Finally, several experiments are performed on a mid-wave infrared system. The results show that the trained correction network is uniform and produces stable outputs when the integration time and attenuator change within the optimal dynamic range. The maximum change in the image corrected using the proposed algorithm was 1.29%. Full article