journal article·2018-08

Multi-component MWCNT/NG/EP-based bipolar plates with enhanced mechanical and electrical characteristics fabricated by compression moulding

Majid Niaz Akhtar, Abu Bakar Sulong, A. Umer, Ammar Bin Yousaf, Muhammad Azhar Khan

Ceramics International· Volume 44· Issue 12
Publisher page

Abstract

Abstract In this work, multi-walled carbon nanotubes (MWCNTs), natural graphite (NG) and epoxy (EP) were used to fabricate bipolar plates by the compression moulding technique. The mechanical and thermal behaviours of the as-developed material were investigated in terms of the effects of temperature on the morphological, mechanical and electrical properties. It was observed that the flexural strength of the MWCNT/NG/EP composite decreased with increasing temperature. The highest flexural strength (27.05 MPa) was recorded at 25 °C. When heated to 200 °C, the flexural strength of the material decreased by up to 2.40 MPa. The shore hardness of the MWCNT/NG/EP composite decreased with increasing temperature. The highest shore hardness (69.7 HD) was recorded at a temperature of 25 °C, while the lowest shore hardness (31.3 HD) was recorded at 200 °C. The temperature-dependent through-plane and in-plane electrical conductivities of the MWCNT/NG/EP composite were also investigated, although its contact, bulk and forward resistivity values were found to decrease. The experimental results revealed that the effect of temperature on the thermal and mechanical properties of the bipolar plate material was different at different temperatures. The synergistic electrical nature of the as-designed material may be ascribed to the phenomenon of electron transfer among the channels of natural graphite and MWCNTs. The enhanced mechanical behaviour was attributed to the presence of EP in the composite material.
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Research context

OpenAlex topics: Carbon Nanotubes in Composites · Conducting polymers and applications · Advanced Sensor and Energy Harvesting Materials

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

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