Dimensionality effects of carbon-based thermal additives for microporous adsorbents. (15th November 2015)

• Record Type: Journal Article
• Authors: Yang, Sungwoo; Kim, Hyunho; Narayanan, Shankar; McKay, Ian S.; Wang, Evelyn N.
• Is Part Of: Materials & design. Volume 85(2016:Sep.)
• Page Start: 520
• Page End: 526
• Publication Date: 2015-11-15
• Subjects: Thermal conductivity -- Microporous adsorbent -- Zeolite -- Metal organic frameworks -- Graphene -- Graphene oxide -- Carbon nanotube; Materials -- Periodicals; Engineering design -- Periodicals; Matériaux -- Périodiques; Conception technique -- Périodiques; Electronic journals; 620.11
• DOI: 10.1016/j.matdes.2015.06.166
• Languages: English
• ISSNs: 0264-1275

Abstract

Abstract: We present a systematic study of carbon nanomaterials with different geometries and thermal properties, including few-layer graphene (FLG), graphene oxide (GO), and functionalized carbon nanotubes (fCNT) as additives to enhance the thermal conductivity of microporous adsorbent materials. The dimensionality and intrinsic thermal conductivity of the additives were found to be critical for both maximizing the thermal conductivity enhancement, and minimizing the reduction in the adsorption capacity of the active materials. We demonstrated that two-dimensional (2D) FLG was the most effective thermal additive for zeolite (ZT) adsorbents due to its high thermal conductivity and preferential 2D geometry. Meanwhile, negligible enhancement was observed from one-dimensional (1D) additives such as fCNTs, which is consistent with the predictions from a modified effective medium analysis (EMA). Our work provides insights for the development of additives to enhance the thermal performance of porous materials in applications such as adsorption heat pumps, gas storage, and separation processes. Graphical abstract: Highlights: Investigated carbon nanomaterials as thermal binders with various thermal properties Determined two-dimensional few-layer graphene as the most effective thermal binder Demonstrated results consistent with predictions using effective medium analysis