A lithium-sulfur (Li-S) battery is regarded as the most promising candidate for next generation energy storage systems, because of its high theoretical specific capacity (1675 mA h g) and specific energy (2500 W h kg), as well as the abundance, low cost and environmental benignity of sulfur. However, the soluble polysulfides LiS (4 ≤ x ≤ 8) produced during the discharge process can cause the so-called "shuttle effect" and lead to low coulombic efficiency and rapid capacity fading of the batteries, which seriously restrict their practical application. Using porous materials as hosts to immobilize the polysulfides is proved to be an effective strategy. In this article, a dual functional cage-like metal-organic framework (Cu-MOF), Cu-TDPAT, combining the Lewis basic sites from the nitrogen atoms of the ligand HTDPAT with the Lewis acidic sites from Cu(ii) open metal sites (OMSs), was employed as the sulfur host in a Li-S battery for lithium ions and polysulfide anions (S). In addition, the size of nano-Cu-TDPAT was also optimized by microwave synthesis to reduce the internal resistance of the batteries. The electrochemical test results showed that the optimized Cu-TDPAT material can efficiently confine the polysulfides within the MOF, and the resultant porous S@Cu-TDPAT composite cathode material with the size of 100 nm shows good cycling performance with a reversible capacity of about 745 mA h g at 1C (1C = 1675 mA g) after 500 cycles, to the best of our knowledge, which is higher than those of all reported S@MOF cathode materials. The DFT calculation and XPS data indicate that the good cycling performance mainly results from the dual functional binding sites (that is, Lewis acid and base sites) in nanoporous Cu-TDPAT, providing the comprehensive and robust interaction with the polysulfides to overcome their dissolution and diffusion into the electrolyte. Clearly, our work provides a good example of designing MOFs with suitable interaction sites for the polysulfides to achieve S@MOF cathode materials with excellent cycling performance by multiple synergistic effects between nanoporous host MOFs and the polysulfides.

Carbon nanofibers were grown on flexible polyimide substrates using an ion-beam sputtering technique. Field emission measurement showed a fairly low threshold voltage of 1.5V∕μm with a current density of 1μA∕cm2. The field enhancement factor was determined to be 4400. The emitter showed resilience when exploited as a high voltage electron source for x-ray generation. The x-ray generated by the flexible emitter is capable of delivering fine images of biological samples with superior sharpness, resolution, and contrast.

Lithium-ion batteries are widely applied in many fields. It is important for predicting battery life (RUL). It is randomly discharged that the lithium-ion battery under random conditions. The experiment of constant current discharge cannot simulate the discharge state under working conditions. Based on the data collection of the NASA dataset, the DGWO-ELM algorithm is proposed to predict lithium-ion battery. The DGWO-ELM is composed of Extreme Learning Machine (ELM), Grey Wolf Optimization (GWO), and Differential Evolution (DE) for the purpose of improving the accuracy of prediction. The algorithm uses GWO algorithm to optimize the weight and threshold of ELM and improves the three deficiencies in the GWO algorithm. The DGWO-ELM algorithm is proved preferably than ELM predictor improved by particle swarm optimization (PSO-ELM) and SVM predictor improved by Grey Wolf Optimization (GWO-SVM). The algorithm is verified by NASA's lithium-ion battery constant current discharge data, and then used to predict the RUL of the lithium-ion battery in a random discharge environment. The results show that the DGWO-ELM performs well on improving the accuracy of prediction.

Lithium–sulfur (Li–S) batteries have been regarded as one of the most promising candidates for the next-generation energy storage devices, attributed to their rather high theoretical energy density. However, affected by the shuttle effect and slow redox kinetics of lithium polysulfides (LiPSs), the application of the Li–S batteries is seriously hampered. Herein, novel thorn-like carbon nanofibers combined with molybdenum nitride nanosheets (denoted as MoN@CNFs) were well designed as a modified separator coating for Li–S batteries to restrain the shuttle effect and strengthen the redox kinetics of LiPSs. The conductive carbon nanofibers provided fast electronic transport, and the decorated MoN nanosheets possessed strong affinity to sulfur species, which could effectively anchor LiPSs, boost their redox reaction as an electrocatalyst,accelerate the reversible soluble/insoluble phase conversion process, and greatly increase the efficiency of active substance utilization. As a result, the Li–S batteries with the separators modified by MoN@CNFs exhibited outstanding rate performance, stable cycling capacity, and improved reaction kinetics, which delivered a high initial capacity of 1074 mA h g–1 at 0.2 C and sustained a capacity of 531 mA h g–1 after 500 cycles at 2 C, with only 0.055% capacity fade per cycle.

This work provided insight into the mechanism of the reversible conversion of LiPSs and the construction of ultra-stable Li–S batteries.