Journal of Quantitative Spectroscopy & Radiative Transfer最新文献

The interaction of the light carrying orbital angular momentum (OAM) with a single spherical particle is explored using a commercial multi-physics simulation platform. The scattering of light with wavelength of 0.532 µm from an ice particle is presented. The research focuses on studying the light-matter interface within an observation volume of radius 10 times the wavelength (5.32 µm) and present near-field magnitude and phase of the scattered field. We place the particle at the various locations of a Gaussian beam, as well as move it to through the vortex and annulus of the light that carries OAM with topological charges of 1, 2 and 3. The numerical solutions showcase the variations of the scattering field complex values and provide a valuable insight in the field behaviour near and inside the particle for different illumination. We show two and three-dimensional scattering field magnitude and phase spatial distributions and their correlations.

We report a novel algorithm for generating optimized look-up tables suitable for rapid evaluation of various light scattering parameters and other hard-to-evaluate functions. Our method uses a stochastic algorithm to minimize the number of look-up table points needed while achieving high accuracy and speed. As an example, we present a general Mie scattering look-up table applicable to a large range of size parameters (0.02 < x < 200) and most materials (organics, inorganics, minerals, metals etc.) with real and imaginary parts of the refractive index ranging from 0.2 to 5 and 0 to 5, respectively. The look-up table is up to 3500 times faster than evaluating the Mie analytical expressions (in Matlab). This method opens up new possibilities in detection algorithm development (e.g. large synthetic datasets for machine learning), inverse problems and all other problems where a large number of Mie scattering coefficients needs to be rapidly evaluated. Furthermore, this method is applicable to other, related scattering problems. For example, we also present look-up tables for scattering efficiencies for spheres on various substrates.

A specific method, combining some ingredients of the well-known DDA and PDI approaches, has been developed in our group since many years to calculate the absorption cross-sections of carbonaceous nanoparticles based on their atomistic details. This method, here named the Dynamic Atomic Dipole Interaction (DADI) model, requires the knowledge of the position and frequency-dependent polarizability of each atom constituting the nanoparticles. While the atomic positions can be quite easily obtained, for example as the results of molecular dynamics simulations, obtaining the frequency-dependent atomic polarizabilities is a trickier task. Here, a fitting procedure, named the reverse-DADI method, has been applied to calculate the frequency-dependent atomic polarizability values for carbon and hydrogen atoms involved in aromatic cycles or in aliphatic chains, on the basis of frequency-dependent molecular polarizabilities of various PAH and alkane molecules, calculated with the TD-DFT theory, in the UV–Visible range. Then, using these frequency-dependent atomic polarizabilities as input parameters in the DADI model has been shown to lead to an accurate representation of the absorption cross-sections of various PAH and alkane molecules with respect to the corresponding values obtained at the TD-DFT level, with however the great advantage of a much shorter time of calculations. Furthermore, these results are indications of a good transferability of the frequency-dependent atomic polarizability values obtained here to any C or H atom of any PAH or alkane molecule. This opens the way for building large databases of optical properties for carbonaceous species of atmospheric or astrophysical interests.

A “super-mirror” having ultrahigh infrared reflectance is achieved by an optimized photonic contrast grating metasurface. Finding ways to achieve this exceptional performance can be enabled by implementing global optimization and machine learning elements, such as Bayesian optimization and genetic algorithm. Here, we acquired an optimized grating design made of high-index germanium, which excites resonances that result in ultralow emittance at certain wavelengths. Our optimizations assisted in the discovery of hybridized coupling of Fabry-Pérot modes and guided modes in a monolithic microscale multilayered coating. We demonstrate constraints in the given geometric variable ranges improves the overall performance of algorithms. We also show the enhanced performance of a deep learning Feedforward Neural Network, which is implemented as the inverse design using the network trained with dataset obtained from Bayesian optimization and Genetic Algorithm approaches. The performance of the Feedforward Neural Network-assisted design produced normal emissivity difference by only +3.5 %, with lower sensitivity to grating dimensional parameter variations. The improvement is achieved by predicting and better understanding of the optical physics of resonant gratings. The proposed few-layer grating coating can be applied to space components, enclosures, and vessels to suppress thermal radiative heat loss.

Mueller matrices relate the Stokes parameters of the incident and emerging light, providing useful information about the radiative properties and other characteristics of the medium. Determining all elements of the 4 × 4 Mueller matrix requires complete polarimetry, which is often challenging to perform. Partial polarimetry, on the other hand, uses simpler optical components in generating and/or analyzing states of polarization, thereby measuring only a subset of the Mueller matrix. However, it may determine the full Mueller matrix under specific symmetry conditions. The present study develops a symmetry classification scheme to categorize the Mueller matrix of materials. It is shown that the symmetry of the Mueller matrix is directly determined from the information of symmetries of the sample's optical properties. Numerical calculations of various measurement scenarios, structures, and materials (with or without Lorentz reciprocity) are carried out to validate the methodology. This study offers an insightful understanding of Mueller matrix symmetry and practical guidance for simplified ellipsometry measurements.

Quantifying the interaction of atmospheric aerosols with incoming solar radiation remains a challenge owing to the limitations associated with measuring aerosol optical properties. This study investigates how the distribution of aerosol properties, whether columnar or vertical, affects the aerosol radiative forcing (ARF) and heating rates (HRs) across different atmospheric layers under cloud-free conditions in the shortwave region. We also assess the atmospheric parameters, namely, pressure, temperature, water vapour density, and ozone density, from in-situ measurements, reanalysis data, and a standard tropical atmosphere to understand their impact on ARF and HR estimates across seasons. Our findings show that aerosol absorption is highest during monsoon, while it is lowest in the winter. Significant atmospheric warming due to aerosols resulted from the substantial cooling at the surface. Columnar properties of aerosols measured at limited or multiple wavelengths yield similar ARF and HR estimates, provided spectral dependency is considered using the Angstrom exponent across seasons. However, the vertical profiles of aerosol extinction, together with a constant single scattering albedo (SSA) along the atmospheric column versus an actual SSA profile, led to notable differences in ARF and HRs, specifically in pre-monsoon and monsoon periods. Free tropospheric aerosol absorption is underestimated when using columnar properties compared to vertical distribution, while boundary layer absorption is overestimated (> 10 Wm^-2). The heterogeneity in aerosol types across atmospheric layers significantly influenced aerosol absorption, highlighting the importance of accurate vertical distribution information. HR profiles obtained with vertical distribution reflect the structure of aerosol extinction, whereas those estimated with columnar properties result in smoother profiles that fail to capture altitude gradients. Aerosol-induced HRs are higher within the boundary layer and free troposphere in the monsoon season for all scenarios of defined aerosol properties. These findings underscore the need for actual vertical profile measurements of aerosol properties to quantify aerosol radiation interaction.

The increasing demand for efficient yet nonpolluting energy conversion technologies require the photovoltaic (PV) systems to have fine-tuned optical responses and suppressed thermalization. PV cells that are based on Silicon are commonly patterned via lithography and etching techniques to implement micro/nanoscale surface components to reduce their reflectance on a wide spectrum while enhancing their absorption of energies around and higher than its bandgap. In this way, the power output increases while increases in cell temperature (e.g., thermalization) is also expected. In this work, a nanopatterned Si PV cell is designed and optimized evaluating different surface nanostructures to suppress the reflectance only in the vicinity of Si bandgap energy, so the power output can be improved and the thermalization can be suppressed simultaneously. Two- and three-dimensional, periodic structures are simulated by finite-difference time-domain method and optimized via parameter sweep optimization technique. A figure of merit (FOM) is developed to compare the in-band and out-of-band front side reflectance. The results revealed that rectangular gratings provided higher FOM, thus better selectivity compared to triangular ones. Similarly, square prism nanostructures demonstrate better selectivity compared to pyramid structures. Rigorous correlation analyses revealed that the selectivity is more strongly correlated with the height than the width. It is demonstrated that with optimized square prism nanostructures, 20 % increase of the absorption of useful radiation is accompanied by a thermalization that is limited to 15 %. With pattern optimization, it is shown that the electrical power output can be improved without producing substantial increase in the cooling load of solar cells.

Monitoring the evolution of the anthropogenic light emissions is a priority task in light pollution research. Among the complementary approaches that can be adopted to achieve this goal stand out those based on measuring the direct radiance of the sources at ground level or from low Earth orbit satellites, and on measuring the scattered radiance (known as artificial night sky brightness or skyglow) using networks of ground-based sensors. The terrestrial atmosphere is a variable medium interposed between the sources and the measuring instruments, and the fluctuation of its optical parameters sets a lower limit for the actual source emission changes that can be confidently detected. In this paper we analyze the effect of the fluctuations of the molecular and aerosol optical depths. It is shown that for reliably detecting changes in the anthropogenic light emissions of order ∼1 % per year, the inter-annual variability of the annual means of these atmospheric parameters in the measurement datasets must be carefully controlled or efficiently corrected for.

We introduce the Quantization Monte Carlo method to solve thermal radiative transport equations with possibly several collision regimes, ranging from few collisions to massive number of collisions per time unit. For each particle in a given simulation cell, the proposed method advances the time by replacing many collisions with sampling directly from the escape distribution of the particle. In order to perform the sampling, for each triplet of parameters (opacity, remaining time, initial position in the cell) on a parameter grid, the escape distribution is precomputed offline and only the quantiles are retained. The online computation samples only from this quantized (i.e., discrete) version by choosing a parameter triplet on the grid (close to actual particle’s parameters) and returning at random one quantile from the precomputed set of quantiles for that parameter. We first check numerically that the escape laws depend smoothly on the parameters and then implement the procedure on a benchmark with good results.

Four spectra of formaldehyde in natural isotopic abundance in the 3700–5200 cm^-1 region were recorded at low temperature 160–166 K at Synchrotron SOLEIL for various pressures. Line positions and intensities were retrieved by non-linear least-squares curve-fitting procedures in the range 3700–4450 cm^-1 and analyzed using ab initio based effective Hamiltonian and line intensities computed using new ab initio dipole moment surface. A new measured line list contains positions and intensities for 6177 features. Refined parameters of effective Hamiltonian were fitted to all assigned line positions with the RMS deviations of 0.001 cm^-1. Updated line lists include intensity values based on ab initio variational calculations which were subsequently empirically optimized. Comparison of our theoretical simulation with previously available data as well as with high-resolution and low-resolution experimental spectra are reported.