Functional carbon materials addressing dendrite problems in metal batteries:surface chemistry,multi-dimensional structure engineering,and defects

Metal batteries that directly use active metals as anodes are considered as one of the most promising solutions to achieve the energy upgrade of battery technologies,while their practical application still suffers from dendrite problems.Functional carbon materials(FCMs)have demonstrated their great potential in suppressing metal dendrites benefitting from the multiple merits such as chemical tunability and capability of multi-dimensional structure assembly.Here,we initiate a review to present the recent progress in employing FCMs to deal with dendrite problems.It focuses on the surface chemistry and multi-dimensional carbon material engineering,which systematically overcomes the problems through diverse methods,such as reinforcing desolvation,improving interface compatibility,homogenizing electric field,buffering volume expansion and lattice mismatch.In addition,we also refine the long-standing debate about whether surface defects in FCMs are beneficial to suppress the metal dendrites or not,especially in the non-aqueous electrolyte regime.Finally,the remaining challenges for utilizing FCMs to suppress metal dendrites and the possible solutions are proposed to guide the future development.

An All‑In‑One Multifunctional Touch Sensor with Carbon‑Based Gradient Resistance Elements

Human–machine interactions using deep-learning methods are important in the research of virtual reality,augmented reality,and metaverse.Such research remains challenging as current interactive sensing interfaces for single-point or multipoint touch input are trapped by massive crossover electrodes,signal crosstalk,propagation delay,and demanding configuration requirements.Here,an all-inone multipoint touch sensor(AIOM touch sensor)with only two electrodes is reported.The AIOM touch sensor is efficiently constructed by gradient resistance elements,which can highly adapt to diverse application-dependent configurations.Combined with deep learning method,the AIOM touch sensor can be utilized to recognize,learn,and memorize human–machine interactions.A biometric verification system is built based on the AIOM touch sensor,which achieves a high identification accuracy of over 98%and offers a promising hybrid cyber security against password leaking.Diversiform human–machine interactions,including freely playing piano music and programmatically controlling a drone,demonstrate the high stability,rapid response time,and excellent spatiotemporally dynamic resolution of the AIOM touch sensor,which will promote significant development of interactive sensing interfaces between fingertips and virtual objects.

Synergistic interaction between redox-active electrolytes and functionalized carbon in increasing the performance of electric double-layer capacitors

The increasing demand of high-performance supercapacitors has aroused great interest in developing specific capacitance and energy density. Active carbon （AC） has attracted much attention as a promising electrode material for electric double-layer capacitors （EDLCs）. Here, a facile strategy has been employed to fabricate high-performance EDLCs using the surface-oxygen functionalized active carbon （FAC） as an electrode and 2 M KOH with K3Fe（CN）6 as an electrolyte. In this system, K3Fe（CN）6 was used as a redox additive to enhance the performance of EDLCs. A 38.5% increase in specific capacitance （207.7 F g-1） was achieved compared with the KOH electrolyte without adding K3Fe（CN）G （152.9 F g-1）, due to the synergistic effects between oxygenic functional groups and redox electrolyte. These findings provide an alternative route to improve the performance of EDLCs, which are promising candidates for the broad applications of high-performance supercapacitors.