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Carbonized and activated wood scraps are appealing scaffolds to host active materials for supercapacitors, which can realize the waste into treasure. However, the active material loaded on the inner wall...

The global digital elevation model (DEM) is important for various scientific applications. With the recently released TanDEM-X 90-m DEM and AW3D30 version 2.2, the open global or near-global coverage DEM datasets have been further expanded. However, the quality of these DEMs has not yet been fully characterized, especially in the application for regional scale studies. In this study, we assess the quality of five freely available global DEM datasets (SRTM-1 DEM, SRTM-3 DEM, ASTER GDEM2, AW3D30 DEM and TanDEM-X 90-m DEM) and one 30-m resampled TanDEM-X DEM (hereafter called TDX30) over the south-central Chinese province of Hunan. Then, the newly-released high precision ICESat-2 (Ice, Cloud, and land Elevation Satellite-2) altimetry points are introduced to evaluate the accuracy of these DEMs. Results show that the SRTM1 DEM offers the best quality with a Root Mean Square Error (RMSE) of 8.0 m, and ASTER GDEM2 has the worst quality with the RMSE of 10.1 m. We also compared the vertical accuracies of these DEMs with respect to different terrain morphological characteristics (e.g., elevation, slope and aspect) and land cover types. It reveals that the DEM accuracy decreases when the terrain elevation and slope value increase, whereas no relationship was found between DEM error and terrain aspect. Furthermore, the results show that the accuracy increases as the land cover type changes from vegetated to non-vegetated. Overall, the SRTM1 DEM, with high spatial resolution and high vertical accuracy, is currently the most promising dataset among these DEMs and it could, therefore, be utilized for the studies and applications requiring accurate DEMs.

As a naturally ordered porous material, wood has many unique advantages in the field of energy storage. After carbonization, it can be directly loaded with active materials to form a self-supporting electrode material without a conductive agent and binder. Here, carbon nanotube (CNT) arrays are grown in wood tracheids by chemical vapor deposition, and nickel–cobalt sulfide (NCS) nanosheets are deposited on CNTs by electrochemical deposition to build self-supporting electrodes. CNTs are similar to the inflorescence axis to distribute nutrients, which is an excellent passage for electron transportation; NCS nanosheets, similar to Sophora flowers, exhibit better electrochemical properties after compounding with CNTs. The composite electrode based on NCS and CNTs in a carbonized wood slice (CWS) achieves an excellent specific capacity of 8.62 F cm–2 at 5 mA cm–2. The all-solid-state hybrid supercapacitor assembled with NCS/CNT@CWS as the cathode and CNT@CWS as the anode expresses a high specific capacitance of 0.85 F cm–2 at 5 mA cm–2, and the capacitance is retained at 92.86% even after 10,000 cycles.