Controlled Fabrication of Metallic MoO2 Nanosheets towards High-Performance p-Type 2D Transistors.

Two-dimensional (2D) semiconducting transition metal dichalcogenides (TMDCs) are extensively employed as channel materials in advanced electronic devices. The electrical contacts between electrodes and 2D semiconductors play a crucial role in the development of high-performance transistors. While numerous strategies for electrode interface engineering have been proposed to enhance the performance of n-type 2D transistors, upgrading p-type ones in a similar manner remains a challenge. In this work, significant improvements in a p-type WSe2 transistor are demonstrated by utilizing metallic MoO2 nanosheets as the electrode contact, which are controllably fabricated through physical vapor deposition and subsequent annealing. The MoO2 nanosheets exhibit an exceptional electrical conductivity of 8.4 × 104 S m‒1 and a breakdown current density of 3.3 × 106 A cm‒2. The work function of MoO2 nanosheets is determined to be ≈5.1 eV, making them suitable for contacting p-type 2D semiconductors. Employing MoO2 nanosheets as the electrode contact in WSe2 transistors results in a notable increase in the field-effect mobility to 92.0 cm2 V‒1 s‒1, which is one order of magnitude higher than the counterpart devices with conventional electrodes. This study not only introduces an intriguing 2D metal oxide to improve the electrical contact in p-type 2D transistors, but also offers an effective approach to fabricating all-2D devices.

The roles of rare and abundant microbial species in the primary succession of biological soil crusts are differentiated in metal tailings ponds with different states.

Tailings ponds formed by long-term accumulation of mineral processing waste have become a global environmental problem. Even worse, tailings ponds are often simply abandoned or landfilled after they cease to be used. This allows pollution to persist and continue to spread in the environment. The significance of primary succession mediated by biological soil crusts for tailings pond remediation has been illustrated by previous studies. However, the process of primary succession may not be the same at different stages during the lifetime of tailings ponds. Therefore, we investigated the environmental differences and the successional characteristics of microbial communities in the primary successional stage of tailings ponds at three different states. The results showed that the primary succession process positively changed the environment of tailings ponds in any state of tailings ponds. The primary successional stage determined the environmental quality more than the state of the tailings pond. In the recently abandoned tailings ponds, abundant species were more subjected to heavy metal stress, while rare species were mainly limited by nutrient content. We found that as the succession progressed, rare species gradually acquired their own community space and became more responsive to environmental stresses. Rare species played an important role in microbial keystone species groups.

Habitat-specific environmental factors regulate the spatial variability of biological soil crust microbial communities on the Qinghai-Tibet Plateau.

Biological soil crusts (BSCs) are an important biological component of the soil surface, covering approximately 12 % of the Earth's land surface. Although BSCs are closely related to habitats, the microbial diversity and spatial variability of BSCs in different ecosystems are still unclear, especially on the Qinghai-Tibet Plateau (QTP), where climate is changeable and habitats are complex. Here, we investigated the diversity, assembly processes, spatial distribution pattern and driving factors of prokaryotic and eukaryotic microbial communities in BSCs in four habitats on the QTP. It was found that habitat-specific environmental factors regulated the composition, diversity and spatial variability of BSC microbial communities. Soil organic carbon and soil water content were the most important factors (R2 = 0.9024, P = 0.001; R2 = 0.8004, P = 0.001) affecting the spatial differences in prokaryotes and eukaryotes, respectively. Under the specific climate of the QTP, the spatial pattern of microbial communities in BSCs was controlled by precipitation rather than temperature. In addition, ecological processes further explained the effects of habitat specificity, and environmental filtering explained microbial community differences better than dispersal limitation. The results of the neutral community model and the normalized stochastic ratio index revealed that the assembly of prokaryotic communities was determined by deterministic processes at the regional scale, and at the local scale, the assembly process was mainly determined by habitat type, while the assembly of eukaryotic communities was determined by stochastic processes at both the regional and local scales. This study provided a scientific reference for the prediction of BSC distribution and resource conservation under future climate change scenarios.

Soil microbe-mediated carbon and nitrogen cycling during primary succession of biological soil crusts in tailings ponds.

Tailings ponds resulting from mining operations have led to serious environmental hazards, and their bioremediation is an area of ongoing exploration. Primary succession represents the starting point of biotic community establishment and development, with soil carbon and nitrogen cycling being critical to this process. To investigate the soil microbial-mediated carbon and nitrogen cycling patterns accompanying primary succession, we selected three types of tailings ponds as study areas and set up sampling sites for different stages of primary succession. The results showed that primary succession promoted microbe-mediated carbon and nitrogen cycling. It also led to improvements in soil nutrient availability and enzyme activity. In primary succession, the main pathways of carbon cycling are 3HP and rTCA, and nitrogen cycling is nitrate assimilation. In the early stages, microbes mediated more anaerobic and microaerobic processes. As succession proceeded, the pattern of microbial contributions to the carbon and nitrogen cycles changed. As succession proceeds, the functional metabolic potential of the carbon cycle gradually rises, while the nitrogen cycle shows a dramatic increase after the accumulation of autotrophic biomass. In addition, we found a positive coupling pattern between the carbon and nitrogen cycles. These findings support the optimization of bioremediation strategies for tailings ponds.

Gradient rise in seepage pollution levels in tailings ponds shapes closer linkages between phytoplankton and bacteria.

A large number of tailings ponds formed by slag accumulation have become serious environmental hazards. Spatially high potential energy and long-term accumulation may result in gradient-changing seepage pollution. The assemblages of phytoplankton and bacteria are widely used as assessment indicators. In this study, we investigate the changes in phytoplankton and bacterial assemblages in tailing pollution. The results showed that there are temporal and spatial variabilities in seepage pollution. The abundance and diversity of phytoplankton and bacteria decreased with increasing pollution. However, Synedra acus (diatom) and Polynucleobacter (bacteria) were positively correlated with pollution levels (r = 0.37, P < 0.05; r = 0.24, P < 0.05). Heavy metals are the main contributors to bacterial changes (16.46%), while nutrients are for algae (13.24%). Tailings pond pollution reduced the number of phytoplankton and bacterial linkages. However, more pollution broke the originally independent modules of phytoplankton and bacteria, and they produced more positive correlations (79.39%; 87.68%). Microcystis sp. and Limnobacter were the key nodes of the co-occurrence network in the polluted areas. Exploring the interactions between bacteria and phytoplankton within different pollution levels could provide insights into biological interaction patterns and the bioremediation of tailings ponds.

Insights into the spatiotemporal differences in tailings seepage pollution by assessing the diversity and metabolic functions of the soil microbial community.

The formation of tailings ponds depends on the long-term accumulation of tailing and high terrain. Its seepage pollution characteristics may have gradient variations on spatiotemporal scales. Used three nearby metal tailings ponds with different service times, we aimed to reveal seepage pollution trends on spatiotemporal scales and the response of soil microbial community. The results showed that the degree of seepage pollution was negatively correlated with the distance from the tailings pond on the spatial scale, while the seepage pollution showed higher levels in tailings ponds with longer service times on the temporal scale (RI = 248.04-2109.85). The pollution effect of seepage persisted after the tailings pond was discontinued (RI = 226.72). Soil microbial diversity increased with spatial scale expansion. The proportion of Actinomyces gradually increased and Proteobacteria decreased. Cr (r = 0.21) and Fe (r = 0.22) contributed more to the microbial community changes. Functional predictions showed that pathways related to signal transduction and energy metabolism were more abundant in the tailings pond. In contaminated areas, the proportion of nitrate respiration and cellulolysis functional communities had decreased, and some potentially pathogenic human taxa had accumulated. These results emphasized that there was pollution accumulation on temporal scale and pollution dispersion on spatial scale around tailings ponds, and the response of the microbial community further illustrated these trends.

TOF-Based Fast Self-Positioning Algorithm for UWB Mobile Base Stations.

To solve the problem of heavy workload and high cost when acquiring the position of Ultra-Wideband (UWB) mobile base stations in sports fields, a fast self-positioning algorithm for UWB mobile base stations algorithm based on Time of Flight (TOF) is proposed. First, according to the layout of the base stations in the sports field, the local coordinate system is determined, and an equation based on the ranging information between the base stations is established; the Least Square method is used to calculate the coordinates of each base station, and the Newton Iteration method is used to converge the positioning results. Then the origin and propagation law of positioning error, as well as the method of reducing the positioning error are analyzed. The simulation data and experimental results show that the average positioning accuracy of the mobile base station is within 0.05 m, which meets the expected accuracy of the base station position measurement. Compared with traditional manual measurement methods, base station self-positioning can effectively save deployment time and reduce workload.