Active Layer Thickness Research Articles

Accelerating Laser Powder Bed Fusion: The Influence of Roller-Spreading Speed on Powder Spreading Performance

The powder spreading process is a fundamental element within the laser powder bed fusion (PBF-LP) framework given its pivotal role in configuring the powder bed. This configuration significantly influences subsequent processing steps and ultimately determines the quality of the final manufactured part. This research paper presents a comprehensive analysis of the impacts of varying spreading speeds, which are enabled by different roller configurations, on powder distribution in PBF-LP. By utilizing extensive Discrete Element Method (DEM) modelling, we systematically examine how spreading speed affects vital parameters within the spreading process, including packing density, mass fraction, and actual layer thickness. Our exploration of various roller configurations has revealed that increasing spreading speed generally decreases packing density and layer thickness for non-rotating, counter-rotating, and forward-rotating rollers with low clockwise rotational speeds (sub-rolling) due to powder dragging. However, a forward-rotating roller with a high clockwise rotational speed (super-rolling) balances momentum transfer, enhancing packing density and layer thickness while increasing surface roughness. This configuration significantly improves the uniformity and density of the powder bed, providing a technique to accelerate the spreading process while maintaining and not reducing packing density. Furthermore, this configuration offers crucial insights into optimizing additive manufacturing processes by considering the complex relationships between spreading speed, roller configuration, and powder spreading quality.

Permafrost Degradation Induces the Abrupt Changes of Vegetation NDVI in the Northern Hemisphere

AbstractPermafrost, widely distributed in the Northern Hemisphere, plays a vital role in regulating heat and moisture cycles within ecosystems. In the last four decades, due to global warming, permafrost degradation has accelerated significantly in high latitudes and altitudes. However, the impact of permafrost degradation on vegetation remains poorly understood to date. Based on active layer thickness (ALT) monitoring data, meteorological data and normalized difference vegetation index (NDVI) data, we found that most ALT‐monitored sites in the Northern Hemisphere show an increasing trend in NDVI and ALT. This suggests an overall increase in NDVI from 1980 to 2021 while permafrost degradation has been occurring. Permafrost degradation positively influences NDVI growth, with the intensity of the effects varying across land cover types and permafrost regions. Furthermore, based on Mann‐Kendall trend test, we detected abrupt changes in NDVI and environmental factors, further confirming that there is a strong consistency between the abrupt changes of ALT and NDVI, and the consistency between the abrupt change events of ALT and NDVI is stronger than that of air temperature and precipitation. These findings work toward a better comprehending of permafrost effects on vegetation growth in the context of climate change.

Improving TFT Device Performance by Changing the Thickness of the LZTO/ZTO Dual Active Layer.

The primary objective of this research paper is to explore strategies for enhancing the electrical performance of dual active layer thin film transistors (TFTs) utilizing LZTO/ZTO as the bilayer architecture. By systematically adjusting the thickness of the active layers, we achieved significant improvements in the performance of the LZTO/ZTO TFTs. An XPS analysis was performed to elucidate the impact of the varying O2 element distribution ratio within the LZTO/ZTO bilayer thin film on the TFTs performance, which was directly influenced by the modification in the active layer thickness. Furthermore, we utilized atomic force microscopy to analyze the effect of altering the active layer thickness on the surface roughness of the LZTO/ZTO bilayer film and the impact of this roughness on the TFTs electrical performance. Through the optimization of the ZTO active layer thickness, the LZTO/ZTO TFT exhibited an mobility of 10.26 cm2 V-1 s-1 and a switching current ratio of 5.7 × 107, thus highlighting the effectiveness of our approach in enhancing the electrical characteristics of the TFT device.

Formation and evolution of thermokarst landslides in the Qinghai-Tibet Plateau, China

Thermokarst landslide (TL) activity in the Qinghai-Tibet Plateau (QTP) is intensifying due to climate warming-induced permafrost degradation. However, the mechanisms driving landslide formation and evolution remain poorly understood. This study investigates the spatial distribution, annual frequency, and monthly dynamics of TLs along the Qinghai-Tibet engineering corridor (QTEC), in conjunction with in-situ temperature and rainfall observations, to elucidate the interplay between warming, permafrost degradation, and landslide activity. Through the analysis of high-resolution satellite imagery and field surveys, we identified 1298 landslides along the QTEC between 2016 and 2022, with an additional 386 landslides recorded in a typical landslide-prone sub-area. In 2016, 621 new active-layer detachments (ALDs) were identified, 1.3 times the total historical record. This surge aligned with unprecedented mean annual and August temperatures. The ALDs emerged primarily between late August and early September, coinciding with maximum thaw depth. From 2016 to 2022, 97.8 % of these ALDs evolved into retrogressive thaw slumps (RTSs), identified as active landslides. Landslides typically occur in alpine meadows at moderate altitudes and on gentle northward slopes. The thick ice layer near the permafrost table serves as the material basis for ALD occurrence. Abnormally high temperature significantly increased the active layer thickness (ALT), resulting in melting of the ice layer and formation of a thawed interlayer, which was the direct causing factor for ALD. By altering the local material, micro-topography, and thermal conditions, ALD activity significantly increases RTS susceptibility. Understanding the mechanisms of ALD formation and evolution into RTS provides a theoretical foundation for infrastructure development and disaster mitigation in extreme environments.

Opto-electronic responses of large area WSe2 layers synthesized by chemical conversion of WO3 thin films

Atomically thin tungsten diselenide (WSe2) has drawn much interest due to its remarkable optical properties and potential applications in next-generation optoelectronics and energy harvesting devices. High-quality, wafer-scale synthesis of such two-dimensional (2D) semiconductors is necessary for their practical applications. Chemical vapor deposition (CVD) is a promising method for synthesizing large-area thin films of 2D materials where the constituent elements are of widely different vapor pressure. Herein, we demonstrate large-area synthesis of the 2H phase of WSe2 with a precise control over the 2D film thickness. The first step of this process is the deposition of tungsten trioxide (WO3) films of a well-defined thickness by thermal evaporation over large areas. The subsequent selenization of these films in an atmospheric pressure CVD reactor, yields high-quality uniform films of WSe2. The quality of these films is ascertained by measuring their characteristic Raman active vibrational modes and layer thickness dependent optical absorption and photoluminescence. The photoconductivity (PC) of these films has been measured with 405, 532 and 915 nm laser excitation. We note an increase in the PC of the films with their thickness. The best photoresponsivity and detectivity obtained are 11.3 mA/W and 1.42 × 108 Jones respectively. These results are promising to create photo-transistor arrays over large areas using such WO3 processed films.

Employing automated electrical resistivity tomography for detecting short- and long-term changes in permafrost and active-layer dynamics in the maritime Antarctic

Abstract. Repeated electrical resistivity tomography (ERT) surveys can substantially advance the understanding of spatial and temporal freeze–thaw dynamics in remote regions, such as Antarctica, where the evolution of permafrost has been poorly investigated. To enable time-lapse ERT surveys in Antarctica, an automated ERT (A-ERT) system is required, as regular site visits are not feasible. In this context, we developed a robust A-ERT prototype and installed it at the Crater Lake CALM-S site on Deception Island, Antarctica, to collect quasi-continuous ERT measurements. We developed an automated data processing workflow to efficiently filter and invert the A-ERT datasets and extract the key information required for a detailed investigation of permafrost and active-layer dynamics. In this paper, we report on the results of two complete year-round A-ERT datasets collected in 2010 and 2019 at the Crater Lake CALM-S site and compare them with available climate and borehole data. The A-ERT profile has a length of 9.5 m with an electrode spacing of 0.5 m, enabling a maximum investigation depth of approximately 2 m. Our detailed investigation of the A-ERT data and inverted results shows that the A-ERT system can detect the active-layer freezing and thawing events with high temporal resolution. The resistivity of the permafrost zone in 2019 is very similar to the values found in 2010, suggesting the stability of the permafrost over almost 1 decade at this site. The evolution of thaw depth exhibits a similar pattern in both years, with the active-layer thickness fluctuating between 0.20–0.35 m. However, a slight thinning of the active layer is evident in early 2019, compared to the equivalent period in 2010. These findings show that A-ERT datasets, combined with the new processing workflow that we developed, are an effective tool for studying permafrost and active-layer dynamics with very high resolution and minimal environmental disturbance. The ability of the A-ERT setup to monitor the spatiotemporal progression of thaw depth in two dimensions, and potentially in three dimensions, and to detect brief surficial refreezing and thawing of the active layer reveals the significance of the automatic ERT monitoring system to record continuous resistivity changes. An A-ERT monitoring setup with a longer profile length can investigate greater depths, offering effective monitoring at sites where boreholes are costly and invasive techniques are unsuitable. This shows that the A-ERT setup described in this paper can be a significant addition to the Global Terrestrial Network for Permafrost (GTN-P) and the Circumpolar Active Layer Monitoring (CALM) networks to further investigate the impact of fast-changing climate and extreme meteorological events on the upper soil horizons and to work towards establishing an early warning system for the consequences of climate change.

Spatial Distribution of Thaw Depth in Palsas Estimated From Optical Unoccupied Aerial Systems Data

ABSTRACTMaximum seasonal thaw depth, referred to as active layer thickness (ALT), is one of the key parameters used to monitor permafrost conditions. ALT maps based on interpolation of point measurements or derived from coarse or moderate spatial resolution satellite data often hide small‐scale spatial variations in thaw depth resulting from differences in surface characteristics and microtopography. To model and predict changes in hydrological and biogeochemical processes in permafrost areas accurately, high‐resolution remote sensing‐based estimations of ALT are needed. Therefore, we applied random forest (RF) regression on a set of topographical and spectral vegetation indices derived from optical unoccupied aerial systems data, Landsat 8 land surface temperature (LST) data, and field measurements to estimate thaw depths in palsas at three mires in north‐west Finland. We also analyzed differences in thaw depths between mires located at different elevations, between dome and plateau‐shaped palsas, and between different vegetation and surface cover classes. The RF models resulted in root mean square errors from 2.4 to 5.7 cm between predicted and observed thaw depths and the R2 values of 0.57–0.96. Height from the surrounding fen surface and LST were the most important variables in thaw depth models, although high‐accuracy results were also achieved without LST. The mean thaw depths did not differ between the sites with lowest and highest elevation, whereas the thaw depths were significantly deeper in dome‐shaped palsas compared to plateaus. The thaw depths were significantly different between vegetation cover classes only on plateau‐shaped palsas. The results indicate the high impact of the topography on the palsa thaw depth, thus highlighting the importance of accurate elevation models in spatial modeling of palsa ALT. The methodology presented in this study can be applied to other permafrost regions where field measurements of ALT are accompanied with high‐resolution topographical and multispectral data.

Summer heat wave in 2022 led to rapid warming of permafrost in the central Qinghai-Tibet Plateau

Extreme events with increasing frequency and intensity are significantly affecting the permafrost environment. Analysis using the ERA5-Land reanalysis data revealed that the permafrost region of the central Qinghai-Tibet Plateau (QTP) experienced the summer heat wave in 2022. Four active layer sites experienced maximum active layer thicknesses (ALT) in 2022 (mean: 207.7 cm), which was 20% higher than the mean ALT during 2000–2021 (mean: 175.9 cm). The mean annual ground temperature (MAGT) observed in 2022 was also the highest, exceeding the average of the previous years by 10%. The contribution fraction of heat wave to the seasonal thaw depth of active layer was quantified using Stefan model with ranging from 6.6% to 13.6%, and the maximum contribution fraction occurs in 2022. These findings are helpful to better understand the impact processes of extreme events on the active layer and permafrost.

Enhancing Specific Detectivity and Device Stability in Vacuum-Deposited Organic Photodetectors Utilizing Nonfullerene Acceptors.

Organic photodetector (OPD) studies have undergone a revolutionary transformation by introducing nonfullerene acceptors (NFAs), which provide substantial benefits such as tunable band gaps and enhanced absorption in the visible spectrum. Vacuum-processed small-molecule-based OPD devices are presented in this study by utilizing a blend of boron subphthalocyanine (SubPc) and chlorinated subphthalocyanine (Cl6SubPc) as the active layer. Four different active layer thicknesses are further investigated to understand the intrinsic phenomena, unveiling the suppression of dark current density while maintaining photoexcitation and charge separation efficiency. Experimental results reveal that, at an applied bias of -3 V, the 50-nm-thick active layer achieves a remarkably low dark current density of 1.002 nA cm-2 alongside a high external quantum efficiency (EQE) of 52.932% and a responsivity of 0.226 A W-1. These impressive performance metrics lead to a specific detectivity of 1.263 × 1013 Jones. Furthermore, the findings offer new insights into intrinsic phenomena within the bulk heterojunction (BHJ), such as thermally generated current and exciton quenching. This integration is potentially well-heeled to revolutionize display technology by combining high-sensitivity photodetection, offering new possibilities for novel display panels with sensing applications.

Advances in InSAR Analysis of Permafrost Terrain

ABSTRACTDifferential interferometric synthetic aperture radar (InSAR) is a remote sensing technique for measuring surface displacements with precision down to millimeters, most commonly from satellites. In permafrost landscapes, InSAR measurements can provide valuable information on geomorphic processes and hazards, including thaw subsidence and frost heave, thermokarst, and permafrost creep. We first review recent progress in InSAR data availability, InSAR processing and uncertainty analysis methods relevant to permafrost studies. These technical advances have contributed to our understanding of surface deformation in flat and sloping terrain in polar and mountainous regions. We emphasize two emerging trends. First, InSAR increasingly enables insight into the mechanisms, controls, and drivers of permafrost landscape dynamics on subseasonal to decadal time scales. Second, InSAR observations in conjunction with models enable novel ways to infer subsurface parameters, such as near‐surface ground ice content and active layer thickness. We anticipate that in the coming decade, InSAR will mature into a widely used operational tool for monitoring, modeling, and planning across rapidly changing permafrost landscapes.

Enhancing light absorption in ultra-thin perovskite solar cells using plasmonic gold nanoparticle clusters

Perovskite solar cells with ultra-thin absorber layers offer potential cost savings in manufacturing, but their reduced thickness can limit light absorption and efficiency. This work explores using plasmonic gold nanoparticles as a light-trapping strategy to compensate for lower absorption in ultra-thin perovskite devices. Numerical simulations investigate embedding 25 nm radius gold nanoparticles within the 200 nm thick perovskite active layer to boost optical absorption through near-field enhancement and light scattering effects. The solar cell structure incorporating these plasmonic nanoparticles achieves a substantially higher short-circuit current density of 23.10 mA cm−2 compared to 18.70 mA cm−2 for a reference cell without nanoparticles. This study provides design approaches for realizing high-efficiency yet cost-effective ultra-thin perovskite photovoltaics by harnessing plasmonic light-trapping techniques. The results display methodologies to improve photon absorption and power conversion in thin-film perovskite devices through strategic nanoparticle integration.

Carboxyl-functionalized polyimide for polar/non-polar organic solvent separation by pervaporation

The separation of azeotropic organic-organic mixtures is critical in the chemical and petrochemical sectors and membrane technology is one of the most successful and sustainable ways to achieve it. A significant challenge is to find materials with the adequate permselectivity for the demanding operational conditions. We propose a carboxyl-functionalized polyimide for pervaporation and separation of polar and non-polar organic azeotropic mixtures with high industrial relevance, such as methanol-toluene, methanol/methyl tert-butyl ether, and ethanol-cyclohexane. Both flat dense films and hollow fibers were investigated. The fabrication as hollow fibers enabled the flux increase by reducing the active layer thickness from 40 to 0.3 μm, while keeping the separation factors nearly unchanged. For methanol/toluene mixtures, by using hollow fibers, the separation factor was around 140, with a flux of 0.54 kg m−2 h−1. For methanol/methyl tert-butyl ether, the separation factor was around 3100 with a flux of 0.14 kg m−2 h−1. For ethanol/cyclohexane, the separation factor was 406 with a flux of 0.24 kg m−2 h−1. The pervaporation performance is a result of a combination of the membrane adequate hydrophilicity and robust mechanical stability, demonstrating their potential application for separating alcohols from organic mixtures.

High-precision estimation of pan-Arctic soil surface temperature from MODIS LST by incorporating multiple environment factors and monthly-based modeling

Global warming has shown an “Arctic amplification effect” in recent decades, leading to pronounced changes in pan-Arctic soil surface temperature (SST). SST plays a direct role in energy exchange between soil and atmosphere and serves as an indicator of the land–atmosphere energy balance. Remote sensing land surface temperature (LST) data is able to indicate near-surface temperature, but influences from environment factors, such as vegetation and snow, can introduce biases between LST and SST. In this study, the importances of five environment factors (vegetation, snow, surface soil composition, topography, and solar radiation) to monthly mean SST estimation from MODIS LST in pan-Arctic were analyzed. Then a method for pan-Arctic monthly mean SST estimation from MODIS LST by incorporating these environment factors and monthly-based modeling based on random forest (RF) algorithm was proposed. The results reveal that all the selected environment factors contribute to monthly-based modeling, with vegetation exerting the greatest importance from May to October and snow in March and April. The root mean square error (RMSE) of pan-Arctic monthly SST estimated by the proposed method from 2003 to 2022 ranges from 0.89 to 1.88 °C, which is a 42.95–––53.35 % reduction compared to the widely used season-based multivariate linear regression (MLR) models based solely on LST (RMSE between 1.56 and 4.03 °C). The accuracy is notably improved in areas with lower and no vegetation (grassy woodlands, grasslands, permanent wetlands, and barrens) in the cold season (September to the following April), and in higher vegetation (forests) areas in the warm season (May to August). The proposed method can contribute to producing high-precision monthly mean SST data from LST, estimating permafrost extent and active layer thickness, and understanding the land–atmosphere energy balance in pan-Arctic.

Investigation of BGaN Layer in Photodetector Structure

This study involves the design and simulation of a BGaN/GaN/ZnO/Al2O3 photodetector for UV/BLUE light with two different boron concentrations: 5% and 20%. The proposed photodetector structure exhibits an internal optical gain of 3.867 × 104 at 10 V and a wavelength of 250 nm for x = 0.05. Moreover, a gain of 1.006 × 104 at the same voltage and wavelength was obtained for a 20% boron concentration under an incidence of 0.01 × 104 cm2/W. A photocurrent peak of 0.31 mA at a wavelength of 0.455 µm, corresponding to an energy of 2.73 eV, was achieved for x = 0.05, which makes it a promising candidate for optoelectronic devices, such as light-emitting diodes (LEDs). A maximum photocurrent of 0.54 mA in the long-range deep UV range between 100 and 250 nm was obtained for x = 0.2. Based on the simulated spectral response, increasing the band gap (EG) improves the optical absorption, and higher absorption rates were found at x = 0.2 in the UV area. However, we also considered the impact of the BGaN active layer thickness on dark current and photocurrent at room temperature. Additionally, we studied the effect of temperature on current under illumination.

Toward long-term monitoring of regional permafrost thaw with satellite interferometric synthetic aperture radar

Abstract. Active-layer thickness (ALT) is estimated for a study area in northern Alaska's continuous-permafrost zone using satellite data from Sentinel-1 (radar) and ICESat-2 (lidar) for the period 2017 to 2022. Synthetic aperture radar (SAR) interferograms were generated using the Short Baseline Subset (SBAS) approach. Displacement time series over the thaw season (June–September) are fit well with a linear model (root mean square error (RMSE) scatter is less than 7 mm) and show maximum seasonal subsidence of 20–60 mm. ICESat-2 products were used to validate the interferometric synthetic aperture radar (InSAR) displacement time series. ALT was estimated from measured subsidence using a widely used model exploiting the volume difference between ice and water, reaching a maximum depth in our study area of 1.5 m. Estimated ALT is in good agreement with in situ and other remotely sensed data but is sensitive to assumed thaw season onset, indicating the need for reliable surface temperature data. Our results suggest the feasibility of long-term permafrost monitoring with satellite InSAR. However, the C-band (∼55 mm center wavelength) Sentinel radar is sensitive to vegetation cover and, in our studies, was not successful for similar monitoring in the heavily treed discontinuous-permafrost zone of central Alaska.

The surface deformation of permafrost and active layer thickness in the upper reaches of the Black River basin, revealed by InSAR observations and independent component analysis

The Heihe River Basin, located in the northeastern part of the Qinghai-Tibetan Plateau, is part of the perennial permafrost belt of the Qilian Mountains. Recent observations indicate ongoing permafrost degradation in this region. This study utilizes data from 255 observations provided by Sentinel-1 satellites, MODIS Land Surface Temperature, SMAP-L4 soil moisture data, GNSS measurements, and in situ measurement. We introduced Variational Bayesian independent Component Analysis (VB-ICA) in multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) processing to investigate the spatial-temporal characteristics of surface deformation and permafrost active layer thickness (ALT) variations. The analysis demonstrates strong agreement with borehole data and offers improvements over traditional methodologies. The maximum value of ALT in the basin is found to be 5.7 m. VB-ICA effectively delineates seasonal deformations related to the freeze-thaw cycles, with a peak seasonal deformation amplitude of 60 mm. Moreover, the seasonal permafrost's lower boundary reaches an elevation of 3700 m, revealing that permafrost is experiencing widespread degradation and associated soil erosion in the high elevation region of The Heihe River Basin. The paper also explores the efficacy of reference point selection and baseline network establishment for employing the InSAR method in monitoring freeze-thaw deformations. The study underscores the InSAR method's adaptability and its importance for interpreting permafrost deformation and related parameters.

High-temperature planar asymmetric ceramic membranes: Effect of the Pt amount and dispersion on the H2 separation performance

This work investigates for the first time the effect of Pt catalyst amount and dispersion on hydrogen permeation performances of BaCe0.65Zr0.20Y0.15O3−δ–Gd0.2Ce0.8O2−δ (BCZY–GDC) composite planar Cer-Cer membranes with asymmetrical architecture, aiming to maximize the ratio between the permeated hydrogen and the metal content. To boost the hydrogen separation reactions, Pt must be deposited on both the dense and porous sides of the membrane. Moreover, the complex architecture of the porous layer can be used to disperse Pt particles providing a good interaction with the membrane. To fulfil this aim BCZY-GDC membranes composed of a 20 μm thick active dense layer and a 600 μm thick, porous support were produced by tape casting and impregnated with different amounts of platinum. Hydrogen permeation properties were thoroughly investigated examining the composition of the feed and the sweep gasses, temperature, stream humidification, catalyst amount and nature of the dispersion media. The effect of Pt-catalysed hydrogen permeation and water splitting reaction at the permeate side was investigated and discussed. It was found that using an optimal amount of Pt solution to activate the porous side of the membranes is paramount to increase hydrogen permeation in the whole operating temperature range while keeping low the amount of noble metal catalyst. Moreover, the selection of a proper solvent with good interaction with the membrane allows the obtainment of smaller Pt nanoparticles resulting in higher permeation. The best performances in terms of hydrogen permeation (0.74 and 1.29 mL min−1 cm−2 at 750 °C using a feed stream with respectively 50 % and 80 % of H2 in He) were obtained using an acetone-based solution for depositing 1.5 mg cm−2 of Pt at the porous side. This work suggests that the metal deposition plays a non-trivial role in the hydrogen separation process and should be fully evaluated to increase the final performance while cutting down the cost of the Pt catalyst and therefore, of the final device.

Enhancing Blue Polymer Light-Emitting Diode Performance by Optimizing the Layer Thickness and the Insertion of a Hole-Transporting Layer.

Polymer light-emitting diodes (PLEDs) hold immense promise for energy-efficient lighting and full-color display technologies. In particular, blue PLEDs play a pivotal role in achieving color balance and reducing energy consumption. The optimization of layer thickness in these devices is critical for enhancing their efficiency. PLED layer thickness control impacts exciton recombination probability, charge transport efficiency, and optical resonance, influencing light emission properties. However, experimental variations in layer thickness are complex and costly. This study employed simulations to explore the impact of layer thickness variations on the optical and electrical properties of blue light-emitting diodes. Comparing the simulation results with experimental data achieves valuable insights for optimizing the device's performance. Our findings revealed that controlling the insertion of a layer that works as a hole-transporting and electron-blocking layer (EBL) could greatly enhance the performance of PLEDs. In addition, changing the active layer thickness could optimize device performance. The obtained results in this work contribute to the development of advanced PLED technology and organic light-emitting diodes (OLEDs).

SILAR deposition and characterization of ZnO films for numerical investigation as electron transport layer in solar cells

The SILAR method of thin film deposition has attracted the scientific community over the years due to its easiness, low cost, availability of room temperature deposition, and more over due to the variation in properties of thin films available by varying deposition parameters.This work is carried out in a way to comprehensively compare two ZnO thin film samples prepared from precursor media with Zinc Acetate (S1) and Zinc Chloride(S2) salts deposited by SILAR method in Perovskite Solar cell applications. The XRD, FTIR, Raman, FESEM, and UV-Visible analysis were carried out for identifying the structural, morphological, and optical quality of these samples. The role of these samples as Electron Transport Layer (ETL) in Perovskite Solar cell were identified using General purpose PhotoVoltaic Device model (GPVDM) simulation software which is well adapted for studying Solar cell architecture. It provided the output Solar cell parameters like Jsc, Voc, FF, PCE, etc and by varying the active layer and Hole Transport Layer (HTL) thicknesses, the optimized efficiency of devices with samples S1 and S2 were obtained as 21.88% and 21.96%.The results showed that SILAR-synthesized ZnO thin films could be potential candidates for ETL applications in Perovskite Solar cells.

Thermokarst landslides susceptibility evaluation across the permafrost region of the central Qinghai-Tibet Plateau: Integrating a machine learning model with InSAR technology

Thermokarst landslides (TLs), which are made up of retrogressive thaw slumps (RTSs) and active-layer detachments slides (ALDSs), are quickly increasing in the central Qinghai-Tibet Plateau (QTP) permafrost area. TLs induce many environmental problems and threaten the safety of infrastructure. A landslide susceptibility map is crucial to prevent the negative impacts of these landslides. However, traditional thermokarst landslides susceptibility (TLS) evaluations do not consider real-time surface deformation information. Therefore, we propose a novel method that integrates a conventional machine learning model with ground surface deformation. Nine influencing factors, including slope, normalized difference vegetation index, elevation, precipitation, thawing degree days, soil content, active layer thickness, water content, and vegetation type were selected based on the q-index detector, and support vector machine was employed to obtain an initial model (IM). We obtained surface deformation in the study area using the enhanced Small Baseline Subset (SBAS) method. The accuracy of the InSAR results was validated through comparison with data from two field monitoring cross-sections. Subsequently, we established an integrated model (ITM) by combining the initial model with surface deformation using the contribution matrix, and confirmed the fusion model’s higher rationality and accuracy through comparison with the IM. Furthermore, we examined the impact of the quadtree segmentation method on atmospheric correction and validated the TLS results obtained using the ITM with high-resolution optical remote sensing imagery from GF6. Finally, the influencing factors and distribution characteristics of TLS was analyzed, and the results indicated that climatic conditions are the primary factors affecting the distribution of TLS.