Cargando…

Facile Fabrication of Graphene Oxide Nanoribbon-Based Nanocomposite Papers with Different Oxidation Degrees and Morphologies for Tunable Fire-Warning Response

Smart fire-warning sensors based on graphene oxide (GO) nanomaterials, via monitoring their temperature-responsive resistance transition, have attracted considerable interest for several years. However, an important question remains as to whether or not different oxidation degrees of the GO network...

Descripción completa

Detalles Bibliográficos
Autores principales: Qiu, Wei-Wei, Yu, Zhi-Ran, Zhou, Ling-Yun, Lv, Ling-Yu, Chen, Heng, Tang, Long-Cheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9228757/
https://www.ncbi.nlm.nih.gov/pubmed/35745302
http://dx.doi.org/10.3390/nano12121963
Descripción
Sumario:Smart fire-warning sensors based on graphene oxide (GO) nanomaterials, via monitoring their temperature-responsive resistance transition, have attracted considerable interest for several years. However, an important question remains as to whether or not different oxidation degrees of the GO network can produce different impacts on fire-warning responses. In this study, we synthesized three types of GO nanoribbons (GONRs) with different oxidation degrees and morphologies, and thus prepared flame retardant polyethylene glycol (PEG)/GONR/montmorillonite (MMT) nanocomposite papers via a facile, solvent free, and low-temperature evaporation-induced assembly approach. The results showed that the presence of the GONRs in the PEG/MMT promoted the formation of an interconnected nacre-like layered structure, and that appropriate oxidation of the GONRs provided better reinforcing efficiency and lower creep deformation. Furthermore, the different oxidation degrees of the GONRs produced a tunable flame-detection response, and an ideal fire-warning signal in pre-combustion (e.g., 3, 18, and 33 s at 300 °C for the three PEG/GONR/MMT nanocomposite papers), superior to the previous GONR-based fire-warning materials. Clearly, this work provides a novel strategy for the design and development of smart fire-warning sensors.