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Landslides caused by earthquakes bring about dramatic changes in soil erodibility. In order to understand the change characteristics of soil erodibility during a vegetation restoration period after the 5.12 Wenchuan earthquake, a non-landslide area, landslide area, and transition area in Leigu Town, Beichuan County were selected as research areas. Field soil sampling, geostatistics, and spatial interpolation were used to explore the spatiotemporal changes in soil physicochemical properties and soil erodibility during a natural restoration in 2013 (5 years after the earthquake) and in 2022 (14 years after the earthquake). The results showed that the comprehensive soil erodibility index (CSEI) was mainly composed of five soil factors, which were soil pH, soil total nitrogen (TN), mean weight diameter of soil aggregates (MWD), fractal dimension of soil water stable aggregates (D), and soil erodibility (Kepic). The CSEI of the landslide area was slightly lower than that of the non-landslide area. The CSEI was gradually increasing during the process of natural restoration after earthquake. From 2013 to 2022, the increase rates of the CSEI were 6.9%, 10.0%, and 41.5% for the landslide area, non-landslide area, and transition area, respectively. Along attitude segments, the spatial distribution of soil erodibility in 2022 is more uniform than that in 2013. The higher value of CSEI was located in the upper part of research areas. The spatial distribution of the CSEI in 2013 and 2022 appeared as a moderate autocorrelation. The variable ranges of CSEI in 2013 and 2022 were about 20 m. In the early stage of vegetation restoration, soil and water conservation engineering was recommended in the landslide area. [ABSTRACT FROM AUTHOR]

The graphene oxide (GO) membrane holds great promise in desalination and green energy fields due to its naturally occurring nanochannels, which provide significant advantages in gas and ion filtration. In this study, the sizes and distributions of nanopore/channels in GO membranes and the relationship of GO flakes size and membrane thickness are explored by molecular dynamics simulations. Our results demonstrate that the size of GO flakes influences the distribution of nanopore sizes in GO membranes, while it almost has no influence on the total nanopore area in membranes with the same thickness. Additionally, our findings confirm that the total nanopore area of the GO membranes decreases exponentially as the membrane thickness increases, which is consistent with experimental observations. To expand the range of nanopore size regulation, we developed a columnar-array substrate model to create GO membranes customized for specific filtration functions, such as virus filtration. Our findings provide physical insights into the rational design of functional membranes for energy and environmental applications and offer theoretical guidance and technical support for the practical application of GO membranes in separation and filtration. [ABSTRACT FROM AUTHOR]

Titanium matrix composites (TMCs) with excellent mechanical properties, reinforced by graphene, is deemed the lightweight and high strength structural materials. In this study, TC11 titanium alloy powder and graphene nanosheets (GNPs) were used as raw materials, and the composite powder with good uniformity and fluidity was obtained through non-interventional homogeneous mixing by a planetary mixer. The microstructure and mechanical properties of the GNPs-TC11 composites and TC11 alloy were compared. The results showed that the microstructure of TC11 and the composites was acicular martensite α' phase under the process parameters of 280 W laser power, 1200 mm/s scanning speed, and 0.1 mm hatch spacing. The GNPs in addition, in the composites, reduced the acicular martensite particle size and expanded the proportion of low-angle grain boundaries. The tensile strength and percentage elongation after the fracture of the TC11 titanium alloy were 1265 MPa and 4.3%, respectively. Because of addition of the GNPs, the strength and percentage elongation after the fracture of the composite increased to 1384 MPa and 8.1%, respectively, at a GNPs mass content of 0.2%. The enhancement of mechanical properties can be attributed to grain refinement, dislocation strengthening, Orowan strengthening, and load transfer strengthening. [ABSTRACT FROM AUTHOR]

Titanium is a commonly used material in aviation, aerospace, and military applications, due to the outstanding mechanical properties of titanium and its alloys. However, its relatively low thermal conductivity restricts its extended usage. The use of graphene as a filler shows great potential for the enhancement of thermal conductivity in titanium-based metal-matrix composites (MMCs). We used classical molecular dynamics (MD) simulation methods to explore the thermal conductance at the titanium–graphene (Ti/Gr) interface for its thermal boundary conductance, which plays an important role in the thermal properties of Ti-based MMCs. The effects of system size, layer number, temperature, and strain were considered. The results show that the thermal boundary conductance (TBC) decreases with an increasing layer number and reaches a plateau at n = 5. TBC falls under tensile strain and, in turn, it grows with compressive strain. The variation of TBC is explained qualitatively by the interfacial atomic vibration coupling factor. Our findings also provide insights into ways to optimize future thermal management based on Ti-based MMCs materials. [ABSTRACT FROM AUTHOR]

Soil respiration (Rs) is seldom analyzed using remotely sensed data because satellite technology has difficulty monitoring various respiratory processes in the soil. We investigated the potential of remote sensing data products to estimate Rs, including land surface temperature (LST) and spectral vegetation indices from the Moderate Resolution Imaging Spectroradiometer (MODIS), using a nine-year (2007–2015) field measurement dataset of Rs and soil temperature (Ts) at five forest sites at the eastern Loess Plateau, China. The results indicate that soil temperature is the primary factor influencing the seasonal variation of Rs at the five sites. The accuracy of the model based on the observed data is not significantly different from the model based on MODIS-derived nighttime LST values. There was a significant difference with the model based on MODIS-derived daytime LST values. Therefore, nighttime LST was the optimum LST for estimation of Rs. The normalized difference vegetation index (NDVI) consistently exhibited a stronger correlation with Rs when compared to the green edge chlorophyll index and enhanced vegetation index. Further analysis showed that adding the NDVI into the model considering only Ts or nighttime LST could significantly improve the simulation accuracy of Rs. The models depending on nighttime LST and NDVI showed comparable accuracy with the models based on the in situ Ts and NDVI. These results suggest that models based entirely on remote sensing data from MODIS have the potential to estimate Rs at the cold temperate coniferous forest sites. The performance of the model in other vegetation types or regions has also been proved. Our conclusions further confirmed that it is feasible for large-scale estimates of Rs by means of MODIS data in temperate coniferous forest ecosystems. [ABSTRACT FROM AUTHOR]

Soil respiration (Rs) in high-altitude areas are normally sensitive to varying climatic conditions. The objective of this research was mainly to explore temporal variations in Rs rates and the corresponding controlling factors for the establishment of appropriate fitting models in a sub-alpine meadow of north China. The data was obtained through field measuring and extraction of the Moderate Resolution Imaging Spectroradiometer (MODIS) in the geographical unit of the study site over the period of 2007 to 2015. The main results were as follows: (1) seasonal variations in Rs rates, soil temperature (Ts), land surface temperature (LST), and normalized difference vegetation index (NDVI) all produced symmetrical bell type patterns, while soil moisture (Ms) showed a fluctuating pattern, (2) a Ts-exponential model could greatly capture seasonal variations of Rs rates in the study site, reflecting the role of temperature as a dominant driving factor in determining Rs temporal variations in alpine meadow areas, (3) there was no significant difference between the performing indicators evaluating the proposed Ts-exponential model and the LST-exponential model. This indicated great potential for applying remote sensing products to estimate seasonal Rs rates and 4) seasonal variations in Rs rates towards temperature sensitivity (Q10) showed a concave curve and dramatically decreased as the temperature increased from −1 to 11 °C. Overall, the results indicated that attention to significant effects of climatic conditions on Rs, particularly in areas of low temperature, should be warranted. Also, applicability of remote sensing products for estimating Rs was reflected and demonstrated. [ABSTRACT FROM AUTHOR]