Search Results (45)

Pluriannual time series of fine particle concentrations suspended in the atmosphere are often lacking. Such data is necessary in evaluating the efficiency of policies aiming to improve air quality in megacities. In this work, a recently developed empirical method is applied over the megacities of Paris, Cairo, and New Delhi. The method utilizes observations of the aerosol optical depth, Angström Exponent, and atmospheric precipitable water as inputs to estimate the PM10. The modeled values validated against their respective reference measurements exhibited the best performance at daily, weekly, and monthly averages when using inputs of the AERONET. When exploiting inputs of the CAMS and MERRA-2 reanalyses, the results were found to be satisfactory with MERRA-2 on the monthly scale. This allows the reconstruction of the variability of the PM10 for the last 45 years. Analysis shows that average annual PM10 concentration has decreased from 40 to 20 µg·m⁻³ in Paris, increased from 70 to 250 µg·m⁻³ in New Delhi, and stayed relatively stable (around 100 µg·m⁻³) in Cairo. Provided that at least one year of PM10 measurements are available to calibrate the empirical method, the method herein is replicable over other megacities around the world. Full article

As semiconductor manufacturing advances into the angstrom-scale era characterized by three-dimensional integration, conventional metrology technologies face fundamental limitations regarding accuracy, speed, and non-destructiveness. Although optical spectroscopy has emerged as a prominent research focus, its application in complex manufacturing scenarios continues to confront significant technical barriers. This review establishes three concrete objectives: To categorize AI–optical spectroscopy integration paradigms spanning forward surrogate modeling, inverse prediction, physics-informed neural networks (PINNs), and multi-level architectures; to benchmark their efficacy against critical industrial metrology challenges including tool-to-tool (T2T) matching and high-aspect-ratio (HAR) structure characterization; and to identify unresolved bottlenecks for guiding next-generation intelligent semiconductor metrology. By categorically elaborating on the innovative applications of AI algorithms—such as forward surrogate models, inverse modeling techniques, physics-informed neural networks (PINNs), and multi-level network architectures—in optical spectroscopy, this work methodically assesses the implementation efficacy and limitations of each technical pathway. Through actual application case studies involving J-profiler software 5.0 and associated algorithms, this review validates the significant efficacy of AI technologies in addressing critical industrial challenges, including tool-to-tool (T2T) matching. The research demonstrates that the fusion of AI and optical spectroscopy delivers technological breakthroughs for semiconductor metrology; however, persistent challenges remain concerning data veracity, insufficient datasets, and cross-scale compatibility. Future research should prioritize enhancing model generalization capability, optimizing data acquisition and utilization strategies, and balancing algorithm real-time performance with accuracy, thereby catalyzing the transformation of semiconductor manufacturing towards an intelligence-driven advanced metrology paradigm. Full article

Aerosols are composed of suspended solid or liquid particles and interact with solar radiation through absorption, refraction, and scattering, influencing climate variability. The Ångström exponent (α) is commonly used to differentiate particle sizes, but its relationship with aerosol optical depth (AOD) and wavelength (λ) is non-linear. This relationship is modeled using higher-order polynomial expressions in this study based on the AOD data from the AErosol RObotic NETwork (AERONET). In the model, polynomial coefficients are used to effectively classify aerosol types, such as dust and biomass-burning aerosols, with a strong correlation among coefficients of the same order. Such a close correlation among the coefficients of the same polynomial order is attributed to a large variability. The coefficients of the same order exhibit a scaled relationship, where scaling factors are expressed as a function of wavelength. Full article

This study presents the longest time series of aerosol optical properties and Precipitable Water Vapor (PW) from two AERONET sites in the Indo-Gangetic Plains (IGP). Analyzing 22 years of data (2001–2022) from Kanpur and 16 years (2007–2023) from Gandhi College, the study focuses on Aerosol Optical Depth (AOD), Ångström Exponent (α), Single Scattering Albedo (SSA), and Precipitable Water Vapor (PW). Significant variability in aerosol properties is observed across monthly, seasonal, and annual scales. The highest mean AOD₅₀₀ values, coupled with higher α_440–870 during post-monsoon and winter, indicate the dominance of fine-mode aerosols. A decrease in SSA with wavelength during these seasons further highlights the absorbing nature of these fine-mode aerosols, driven by fossil fuels and biomass burning. In contrast, summer and pre-monsoon have relatively lower mean AOD₅₀₀, lowest α_440–870, and increased SSA with wavelength, suggesting the dominance of coarse-mode scattering dust aerosols. PW exhibits a seasonal cycle, reaching its peak during the monsoon due to moisture transport from the Arabian Sea and Bay of Bengal, then decreasing post-monsoon as drier conditions prevail. Long-term annual trends reveal increasing aerosol concentrations, with AOD₅₀₀ rising by 18% at Kanpur and 29% at Gandhi College, suggesting faster aerosol loading at the latter. Sub-period analysis indicates a slowdown in AOD₅₀₀ increase during 2012–2023 at Kanpur, indicating potential stabilization post-industrialization, while Gandhi College’s more pronounced AOD₅₀₀ and α_440–870 increase underscores the growing impact of fine aerosols in rural IGP areas. Kanpur shows a sustained SSA increase, though at a slower rate in recent years, indicating dominant scattering aerosols. In contrast, Gandhi College has transitioned from moderate SSA increases to declines at longer wavelengths, suggesting enhanced fine-mode absorbing aerosols. At Gandhi College, the decline in PW reduces atmospheric moisture, limiting wet scavenging and likely contributing to the rise in fine-mode aerosols, especially during the monsoon and post-monsoon seasons. Our findings highlight the evolving aerosol sources in the IGP, with Kanpur stabilizing and rural areas like Gandhi College seeing continued increases in pollution. Full article

Molecular Dynamics simulations study material structure and dynamics at the atomic level. X-ray and neutron scattering experiments probe exactly the same time- and length scales as the simulations. In order to benchmark simulations against measured scattering data, a program is required that computes scattering patterns from simulations with good single-core performance and support for parallelization. In this work, the existing program Sassena is used as a potent solution to this requirement for a range of scattering methods, covering pico- to nanosecond dynamics, as well as the structure from some Ångströms to hundreds of nanometers. In the case of nanometer-level structures, the finite size of the simulation box, which is referred to as the finite size effect, has to be factored into the computations for which a method is described and implemented into Sassena. Additionally, the single-core and parallelization performance of Sassena is investigated, and several improvements are introduced. Full article

The present study aimed to investigate atmospheric optical characteristics over the Gorky and Cheboksary Reservoirs and their multi-scale temporal variations to obtain the background characteristics and to identify events involving the transfer of absorbing aerosol to the studied region in 2022–2023. The region is located at a considerable distance (500 km) from the nearest AERONET station; therefore, previous atmospheric data were not available. As a solution, the in situ self-measured aerosol optical depth (AOD) and Angström exponent, as well as satellite products (MAIAC and CALIPSO) for MODIS data, were used. This allowed us to set background values of an AOD of 0.11 at a wavelength of 500 nm and an Angström exponent of 1.2, against their maximum values of 0.38 and 2.5, respectively. To explain these variations, the registered conditions and the microstructure of the dust aerosol over the studied region are presented. For days with background values, the analysis of the particle size distribution data did not show a predominance of any particle size. The optical properties of a smoke aerosol in an atmospheric column are described, and an analysis of the dynamics of particle size variability is presented. A comparative analysis of the optical characteristics of atmospheric aerosol over the Gorky and Cheboksary Reservoirs using in situ and MODIS products was carried out. Full article

Graphene-based laminar membranes exhibit remarkable ion sieving properties, but their monovalent ion selectivity is still low and much less than the natural ion channels. Inspired by the elementary structure/function relationships of biological ion channels embedded in biomembranes, a new strategy is proposed herein to mimic biological K⁺ channels by using the graphene laminar membrane (GLM) composed of two-dimensional (2D) angstrom(Å)-scale channels to support a simple model of semi-biomembrane, namely oil/water (O/W) interface. It is found that K⁺ is strongly preferred over Na⁺ and Li⁺ for transferring across the GLM-supported water/1,2-dichloroethane (W/DCE) interface within the same potential window (-0.1-0.6 V), although the monovalent ion selectivity of GLM under the aqueous solution is still low (K⁺/Na⁺~1.11 and K⁺/Li⁺~1.35). Moreover, the voltammetric responses corresponding to the ion transfer of NH₄⁺ observed at the GLM-supported W/DCE interface also show that NH₄⁺ can often pass through the biological K⁺ channels due to their comparable hydration–free energies and cation-π interactions. The underlying mechanism of as-observed K⁺ selective voltammetric responses is discussed and found to be consistent with the energy balance of cationic partial-dehydration (energetic costs) and cation-π interaction (energetic gains) as involved in biological K⁺ channels. Full article

The regional and global scale of aerosols in the atmosphere can be quantified using the aerosol optical depth (AOD) retrieved from satellite observations. To obtain reliable satellite AODs, conducting consistent validations and refining retrieval algorithms are crucial. AODs and Ångström exponents (AEs) measured with the aerosol robotic network (AERONET) are considered as the ground truth for satellite validations. AERONET AEs are used to collocate the wavelength of the AERONET AODs to those of the satellite AODs when there is a discordancy in their wavelengths. However, numerous validation studies have proposed different strategies by applying the AERONET AODs and AEs, and spatiotemporal collocation criteria. This study examined the impact of the wavelength and spatial collocation radius variations by comparing AODs at 550 nm derived from the geostationary ocean color imager (GOCI) with those obtained from the AERONET for the year 2016. The estimated AERONET AODs at 550 nm varied from 5.18% to 11.73% depending on the selection of AOD and AE, and the spatial collocation radii from 0 to 40 km, respectively. The longer the collocation radius and the higher the AODs, the greater the variability observed in the validation results. Overall, the selection of the spatial collocation radius had a stronger impact on the variability in the validation results obtained compared to the selection of the wavelength. The variability was also found in seasonal analysis. Therefore, it is recommended to carefully select the data wavelength and spatial collocation radius, consider seasonal effects, and provide this information when validating satellite AODs using AERONET. Full article

Ion and water transport at the Angstrom/Nano scale has always been one of the focuses of experimental and theoretical research. In particular, the surface properties of the angstrom channel and the solid-liquid interface interaction will play a decisive role in ion and water transport when the channel size is small to molecular or angstrom level. In this paper, the chemical structure and theoretical model of graphene oxide (GO) are reviewed. Moreover, the mechanical mechanism of water molecules and ions transport through the angstrom channel of GO are discussed, including the mechanism of intermolecular force at a solid/liquid/ion interface, the charge asymmetry effect and the dehydration effect. Angstrom channels, which are precisely constructed by two-dimensional (2D) materials such as GO, provide a new platform and idea for angstrom-scale transport. It provides an important reference for the understanding and cognition of fluid transport mechanism at angstrom-scale and its application in filtration, screening, seawater desalination, gas separation and so on. Full article

Hard dental tissues possess a complex hierarchical structure that is particularly evident in enamel, the most mineralised substance in the human body. Its complex and interlinked organisation at the Ångstrom (crystal lattice), nano-, micro-, and macro-scales is the result of evolutionary optimisation for mechanical and functional performance: hardness and stiffness, fracture toughness, thermal, and chemical resistance. Understanding the physical–chemical–structural relationships at each scale requires the application of appropriately sensitive and resolving probes. Synchrotron X-ray techniques offer the possibility to progress significantly beyond the capabilities of conventional laboratory instruments, i.e., X-ray diffractometers, and electron and atomic force microscopes. The last few decades have witnessed the accumulation of results obtained from X-ray scattering (diffraction), spectroscopy (including polarisation analysis), and imaging (including ptychography and tomography). The current article presents a multi-disciplinary review of nearly 40 years of discoveries and advancements, primarily pertaining to the study of enamel and its demineralisation (caries), but also linked to the investigations of other mineralised tissues such as dentine, bone, etc. The modelling approaches informed by these observations are also overviewed. The strategic aim of the present review was to identify and evaluate prospective avenues for analysing dental tissues and developing treatments and prophylaxis for improved dental health. Full article

We have simulated a series of nanoindentation experiments on nanocrystalline tungsten specimens using a combination of molecular dynamics simulations and the embedded atom method potential. The research aimed to investigate the impact of grain size on the mechanical properties of tungsten. Nanoindentation is a technique used to measure the mechanical properties of materials at a small scale. In this study, the researchers varied the grain size of the tungsten specimens, ranging from 7.9 to 10.5 nanometers. They also applied a loading rate of 3 angstroms per picosecond at a temperature of 300 Kelvin. The study found that as the grain size increased, the hardness increased, and the elastic modulus decreased. Hardness is a measure of a material’s resistance to deformation, and the elastic modulus is a measure of a material’s stiffness. The findings suggest that as the grain size of tungsten increases, the material becomes harder but less stiff. Additionally, the study explored the ways in which nanocrystalline tungsten deformed during nanoindentation. The researchers found that the deformation of the material was primarily due to dislocation activity, which is consistent with previous research on the topic. Overall, the findings of this research provide valuable insights into the mechanical properties of nanocrystalline tungsten and the ways in which the material deforms under stress. These findings could have practical applications in the development of materials for use in various industries. Full article

The translocation of specific polypeptide chains across membranes is an essential activity for all life forms. The main components of the general secretory (Sec) system of E. coli include integral membrane translocon SecYEG, peripheral ATPase SecA, and SecDF, an ancillary complex that enhances polypeptide secretion by coupling translocation to proton motive force. Atomic force microscopy (AFM), a single-molecule imaging technique, is well suited to unmask complex, asynchronous molecular activities of membrane-associated proteins including those comprising the Sec apparatus. Using AFM, the dynamic structure of membrane-external protein topography of Sec system components can be directly visualized with high spatial-temporal precision. This mini-review is focused on AFM imaging of the Sec system in near-native fluid conditions where activity can be maintained and biochemically verified. Angstrom-scale conformational changes of SecYEG are reported on 100 ms timescales in fluid lipid bilayers. The association of SecA with SecYEG, forming membrane-bound SecYEG/SecA translocases, is directly visualized. Recent work showing topographical aspects of the translocation process that vary with precursor species is also discussed. The data suggests that the Sec system does not employ a single translocation mechanism. We posit that differences in the spatial frequency distribution of hydrophobic content within precursor sequences may be a determining factor in mechanism selection. Precise AFM investigations of active translocases are poised to advance our currently vague understanding of the complicated macromolecular movements underlying protein export across membranes. Full article

Atomistic molecular dynamics (MD) and a microstructural dislocation density-based crystalline plasticity (DCP) framework were used together across time scales varying from picoseconds to nanoseconds and length scales spanning from angstroms to micrometers to model a buried copper–nickel interface subjected to high strain rates. The nucleation and evolution of defects, such as dislocations and stacking faults, as well as large inelastic strain accumulations and wave-induced stress reflections were physically represented in both approaches. Both methods showed similar qualitative behavior, such as defects originating along the impactor edges, a dominance of Shockley partial dislocations, and non-continuous dislocation distributions across the buried interface. The favorable comparison between methods justifies assumptions used in both, to model phenomena, such as the nucleation and interactions of single defects and partials with reflected tensile waves, based on MD predictions, which are consistent with the evolution of perfect and partial dislocation densities as predicted by DCP. This substantiates how the nanoscale as modeled by MD is representative of microstructural behavior as modeled by DCP. Full article

The general objective of this research was to propose a new fire risk index, specifically the Fire Risk Atlantic Forest (FIAF) index in Itatiaia National Park (PNI). The data were collected from two levels (2 and 10 m) of a micrometeorological tower, with a time series on an hourly scale, daily from 2018 to 2021. Two multiple regression models were generated for the two collection levels (FIAF 2 and 10 m) and, based on the statistical criteria and the choice of the best model, a future simulation was generated using the scenario SSP 4.5 for 2022 to 2050. The correlation matrix between the data from the FIAF and fire foci models was also analyzed. The FIAF model was compared with the traditional models already used in Brazil, such as the Angström indices, Monte Alegre Formula (FMA), and the improved Monte Alegre Formula (FMA+) models. The results showed that the FIAF model at 10 m overestimated the results observed mainly during the dry season. The FIAF 2 m model presented the highest correlation with a fire foci value greater than 0.74. In the future simulation, the years that presented the highest extreme risks were: 2025, 2035, 2041, and 2049. Thus, it is possible to state that the FIAF model at the 2 m level was the best model for predicting the degree of fire risk in the PNI. Full article

Aerosols are essential climate variables that need to be observed at a global scale to monitor the evolution of the atmospheric composition and potential climate impacts. We used the measurements performed over the May 2007–December 2019 period by a ground-based sun photometer installed at the island of La Réunion (21°S, 55°E), together with a linear regression fitting model, to assess the climatology and types of aerosols reaching this observation site located in a sparsely documented pristine area, and the forcings responsible for the variability of the observed aerosol optical depth (AOD) and related trend. The climatology of the aerosol optical depth (AOD) at 440 nm (AOD₄₄₀) and Ångström exponent between 500 and 870 nm (α) revealed that sea salts could be considered as the La Réunion AOD₄₄₀ and α baselines (0.06 ± 0.03 and 0.61 ± 0.40, respectively, from December to August), which were mainly modulated by biomass burning (BB) plumes passing over La Réunion (causing a doubling of AOD₄₄₀ and α up to 0.13 ± 0.07 and 1.06 ± 0.34, respectively, in October). This was confirmed by the retrieved aerosol volume size distributions showing that the coarse-mode (fine-mode) dominated the total volume concentration for AOD₄₄₀ lower (higher) than 0.2 with a mean radius equal to 3 μm (0.15 μm). The main contribution to the AOD₄₄₀ variability over La Réunion was evaluated to be the BB activity (67.4 ± 28.1%), followed by marine aerosols (16.3 ± 4.2%) and large-scale atmospheric structures (5.5 ± 1.7%). The calculated trend for AOD₄₄₀ equaled 0.02 ± 0.01 per decade (2.6 ± 1.3% per year). These results provide a scientific reference base for upcoming studies dedicated to the quantification of the impact of wildfire emissions on the southwestern Indian Ocean’s atmospheric composition and radiative balance. Full article