Oxygen-Containing Functional Groups Regulating the Carbon/Electrolyte Interfacial Properties Toward Enhanced K Storage.

Oxygen-containing functional groups were found to effectively boost the K storage performance of carbonaceous materials, however, the mechanism behind the performance enhancement remains unclear. Herein, we report higher rate capability and better long-term cycle performance employing oxygen-doped graphite oxide (GO) as the anode material for potassium ion batteries (PIBs), compared to the raw graphite. The in situ Raman spectroscopy elucidates the adsorption-intercalation hybrid K storage mechanism, assigning the capacity enhancement to be mainly correlated with reversible K adsorption/desorption at the newly introduced oxygen sites.

Fe/FeC Embedded in N-Doped Worm-like Porous Carbon for High-Rate Catalysis in Rechargeable Zinc-Air Batteries.

Designing low-cost preparation of high-activity electrocatalysts with excellent stability is the route one must take to fully realize large-scale application implementation of zinc-air batteries. 3D nitrogen-doped nanocarbons with transition metals or their derivatives encapsulated in show promising potential in the field of non-precious metal oxygen electrocatalysis. Herein, we report a simple, economical, and large-scale production method to construct worm-like porous nitrogen-doped carbon with -grown carbon nanotubes and uniformly embedded Fe/FeC nanoparticles.

Optimized Kinetics Match and Charge Balance Toward Potassium Ion Hybrid Capacitors with Ultrahigh Energy and Power Densities.

Potassium ion hybrid capacitors (PIHCs) are of particular interest benefiting from high energy/power densities. However, challenges lie in the kinetic mismatch between battery-type anode and capacitive-type cathode, as well as the difficulty in achieving optimized charge/mass balance. These significantly sacrifice the electrochemical performance of PIHCs.

Changes of EEG phase synchronization and EOG signals along the use of steady state visually evoked potential-based brain computer interface.

Objective: The steady-state visual evoked potential (SSVEP)-based brain computer interface (BCI) has demonstrated relatively high performance with little user training, and thus becomes a popular BCI paradigm. However, due to the performance deterioration over time, its robustness and reliability appear not sufficient to allow a non-expert to use outside laboratory. It would be thus helpful to study what happens behind the decreasing tendency of the BCI performance.