journal article·2022-06

Development of nitrogen-decorated carbon dots (NCDs) thermally conductive film for windows application

Ronn Goei, Frankie Ting Feng Tan, Amanda Jiamin Ong, Daniel Mandler, Alfred Iing Yoong Tok

Carbon Letters· Volume 32· Issue 4
Publisher page

Abstract

A thermally conductive film can be used to laterally conduct heat along the surface of glass windows, toward its edges where a heat sink could be located, thereby reducing temperature differential between the inside and outside surfaces of the window and thus lowering cross-sectional conductive heat transfer. This technique can offer optimized thermal energy management to modern buildings without the weight and cost of double- or triple-glazed window panels. In this work, a thermally conductive film was developed using carbon dots with inherently high thermal conductivity. Nitrogen atoms were then added to the carbon dots structure to intensify high-frequency phonon that would result in higher lateral thermal conductivity. The nitrogen-decorated carbon dots (NCDs) were prepared by a simple hydrothermal synthesis of citric acid with the addition of ethylenediamine as the N source. The NCDs were added to a cellulose-based solution and drop-casted onto FTO glass resulting in a transparent, laterally thermally conductive film, that also blocks ultraviolet (UV) and high-intensity blue light radiation. The visible-light transmission of the NCDs’ film was found to be up to 65%, comparable to the commercial solar films. The lateral thermal conductivity of the NCDs’ film increases with increasing N content up to an optimum level, suggesting the role of N to “concentrate’ the high-frequency phonons responsible for effective lateral thermal conductivity of the films.
Source: expertdata · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Carbon and Quantum Dots Applications · Thermal Radiation and Cooling Technologies · Aerogels and thermal insulation

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

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