Glycine-derived nitrogen-doped ordered mesoporous carbons with a bimodal mesopore size distribution for supercapacitors and oxygen reduction
Source abstract
Abstract
Nitrogen-doped carbon materials are promising for electrochemical energy storage and conversion. Dopant control and pore engineering play important roles in improving their performance. We have synthesized nitrogen-doped ordered mesoporous carbons (N-OMCs) with a bimodal mesopore size distribution using a solvent-free nanocasting method. The simplest amino acid (glycine, Gly) was used as the only carbon precursor and ordered mesoporous silica SBA-15 as the hard template. The confined pyrolysis of Gly in SBA-15 leads to efficient carbonization, nitrogen doping and an interesting structure. The N-OMCs have high surface areas (923–1374 m2·g−1), large pore volumes (1.32–2.21 cm3·g−1), a bimodal distribution of mesopore sizes (4.8 and 6.2–20 nm) and high nitrogen contents (3.66%–12.23%). The effects of the Gly/SBA-15 mass ratio (1–3) and carbonization temperature (700–1000 °C) on the physicochemical properties of the N-OMCs were studied. When used as electrode materials the N-OMCs have a high performance in supercapacitors. A typical sample has a large specific capacitance of 298 F·g−1, a good rate capability (70% retention at 30 A·g−1) and high stability. The different capacitances and rate capabilities of the N-OMCs are discussed by correlating them with their physicochemical properties. A balance of surface area, degree of graphitization, nitrogen doping, and an open mesoporous structure is essential to achieve the best performance. The N-OMCs also have a good performance in the electrocatalytic oxygen reduction reaction. A typical sample has a high onset of 0.92 V, a high half-wave potential of 0.83 V and a large limiting current density of 5.06 mA·cm−2.
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Research context
OpenAlex topics: Supercapacitor Materials and Fabrication · Electrocatalysts for Energy Conversion · Mesoporous Materials and Catalysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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