One-step and controllable synthesis of active N-rich graphene nanoclusters-CNT composite via an ultrafast deflagration reaction for oxygen reduction electrocatalysis
Source abstract
Abstract
One-step and controllable synthesis of carbon-based metal-free ORR catalysts with special nitrogen (N) species via a facile method is especially attractive but still challenging. In this study, pristine carbon nanotube (CNT) is easily modified to form the graphene nanoclusters-CNT (GN-CNT) composite with rich active N species via a facile and one-step energetic material (NaN3) deflagration method for the first time. Thanks to the controllable introduction of defects/edges into the CNT structure during the ultrafast ( 5 at%) in the product, which leads to an excellent ORR performance of the prepared catalyst. An optimized GN-CNT sample is capable of achieving an excellent ORR performance with the half-wave potential of 0.84 V (300 mV positive than Pt/C) and limiting current density of − 5.5 mA·cm−2 (~ 10% higher than Pt/C). In addition, the prepared catalysts also show significant higher intrinsic catalytic activity, long-term stability and methanol tolerance than commercial Pt/C. Such an energetic material induced deflagration method may provide a rapid, one-step and controllable way to effectively modify or synthesize other N-doped functional materials which can be widely used in the field of catalysis. An ultrafast (< 1 s) and one-step deflagration strategy enabling the controllable synthesis of graphene nanoclusters-CNT composite with a high proportion of pyridinic and graphitic N (as high as ~ 85%) in the total N-doping content (5.25 at%) is reported for the first time, which shows significantly higher intrinsic ORR kinetic activity, long-term stability and methanol tolerance than commercial Pt/C.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Electrocatalysts for Energy Conversion · Advanced battery technologies research · Fuel Cells and Related Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (59)
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