journal article·2019-12

Ultra-black carbon@silica core-shell aerogels with controllable electrical conductivities

Hongqiang Wang, Chen Zhang, Bin Zhou, Zhihua Zhang, Jun Shen, Ai Du

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Abstract

Ultra-black materials have attracted widespread attention from researchers because of their great value in the applications of photo-thermal conversion, the shielding of precision optical instruments, thermal detection, power generation, and pyroelectric sensors. However, at present, the ultra-black materials with excellent performance are carbon materials with high electrical conductivity. When these materials are used for shielding in precision optical instruments and some equipment with circuits, high electrical conductivity is a disadvantage. Herein, a facile route to synthesis carbon@silica (C@SiO2) aerogels with a carbon–silica core-shell structure is developed, via the chemical vapor deposition of ammonia-catalyzed tetraethoxysilane onto the skeleton of an ultra-black carbon aerogel (CA). As a result, the obtained C@SiO2 aerogels show controllable silica shell thicknesses ranging from 6.81 to 20.54 nm. Due to their dielectric and dense silica coverage, the C@SiO2-4 has a high onset of the degradation temperature of 544 °C in the air atmosphere, which is 101 °C higher than that of a CA. The C@SiO2-4 also has a controllable and ultra-low electrical conductivity of 0.021 mS mm−1, which is less than one ten thousandth of that of the CA (230 mS mm−1). Most importantly, the C@SiO2 aerogels retain a high average absorption of 98.81% across 400–2000 nm. The controllable electrical conductivity combined with high absorption and good thermal resistance makes the C@SiO2 aerogel an ideal ultra-black media to be applied in the shielding field and the precision optical instruments.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Aerogels and thermal insulation · Transition Metal Oxide Nanomaterials · Supercapacitor Materials and Fabrication

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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