Graphene oxide membranes with a confined mass transfer effect for Li+/Mg2+ separation: a molecular dynamics study.

Membrane separation technology represented by graphene oxide (GO) membranes has been widely used in lithium extraction from salt lakes. It is extraordinary to study the extraction of Li+ by GO membranes from the perspective of the confined mass transfer effect. This study establishes a GO channel model with the confined mass transfer effect to closely fit the actual mass transfer process. Meanwhile, this study investigates the dynamic fluid characteristics in the separation of Li+/Mg2+ by GO membranes using molecular dynamics simulations. The results showed that the Li+/Mg2+ separation ratio is maximum at 1.0 nm layer spacing and 10% oxidation degree of the GO membrane. Water molecules form a bilayer within the channel at the appropriate interlayer channel (1 nm) and oxidation level (10%), which accelerates the ion transport rate. Furthermore, the GO oxidation group has the weakest hydrogen bonding effect on water which promotes the passage of water. Finally, the maximum separation ratio is reached due to the fact that the binding force of Li+ to water molecules in the channel is lower than that of Mg2+. The results of this study will provide theoretical consideration for the design of high-performance Li+/Mg2+ separation membranes.

Defect Engineering in GO Membranes - Tailoring Size and Oxidation Degree of Nanosheet for Enhanced Pore Channels.

Graphene Oxide (GO) membrane has been extensively applied in the field of water purification and membrane separation processes. While the solute molecule transport in GO membranes encompasses interlayer channels, edge defects, and in-plane crack-like holes, the significance of edge defects or crack-like pores in ultrathin membranes is often overlooked. In our study, we focused on the construction of short-range channel GO membranes with varied defect structures by modulating the transverse size of the porous nanosheets. GO nanosheets with different sizes were procured through high-energy γ-irradiation combined with centrifugation. Notably, the large-sized porous GO nanosheets (L-pGO) exhibit a consistent structure, and numerous in-plane defects. In contrast, the smaller counterparts (S-pGO) present a fewer in-plane defects. The performance metrics revealed that L-pGO exhibited a water flux of 849.25 L m-2 h-1 bar-1, while S-pGO demonstrated nearly 100 % dye rejection capacity. These findings underscore the potential of defect engineering as a powerful strategy to enhance the efficiency of two-dimensional membranes.

Pedestrian multiple-object tracking based on FairMOT and circle loss.

Multi-object Tracking is an important issue that has been widely investigated in computer vision. However, in practical applications, moving targets are often occluded due to complex changes in the background, which leads to frequent pedestrian ID switches in multi-object tracking. To solve the problem, we present a multi-object tracking algorithm based on FairMOT and Circle Loss. In this paper, HRNet is adopted as the baseline. Then, Polarized Self-Attention is added to HRNet-w32 to obtain weights of helpful information based on its modeling advantages. Moreover, the re-identification branch is optimized, and the Circle Loss is selected as the loss function to acquire more discriminative pedestrian features and to distinguish different pedestrians. The method proposed is assessed on the public MOT17 datasets. The experimental results show that the MOTA score achieves 69.5%, IDF1 reaches 70.0%, and the number of ID switches (IDs) decreases 636 times compared to the TraDes algorithm.