Advanced Electrical Conductors (CNT, Graphene, and Metal-based) -- US-based candidates with work authorization only.

We are seeking a highly motivated postdoctoral researcher with expertise in nanomaterials synthesis, characterization, and electrical thermal characterization. The position is for one year, with the option to extend for another year. This interdisciplinary position combines two exciting projects:

• Metal-Graphene Ultraconductors: Develop scalable processes for ultraconductor metals (metal enhanced graphene conductors) with higher electrical and thermal conductivity than base metals.
• CNT-based Ultraconductors: Investigate carbon nanotube (CNT) based yarns with unprecedented electrical conductivity via advanced processing and intercalation methods.

Please apply to this postdoc position by filling out this form: https://forms.gle/c3hdif2xjoHYS84z8

Influence of gas pressure on the effective thermal conductivity of ceramic breeder pebble beds

https://doi.org/10.1016/j.fusengdes.2017.03.073

In this work, the role of gas pressure is examined in thermal transport through granular materials. This is of particular relevance for proposed fusion reactors, where a breeder blanket, under neutron irradiation, comprising lithium ceramic pebbles, is a key element of the design. The strcuture of a pebble bed, the materials used, the pressure of the gas all combine here to yield a thermo mechanical loading as discussed in this paper. Part of a larger project in the thermo-mechanics of energy materials.

Abstract

Lithium ceramics have been considered as tritium breeder materials in many proposed designs of fusion breeding blankets. Heat generated in breeder pebble beds due to nuclear breeding reaction must be removed by means of actively cooled plates while generated tritiums is recovered by purge gas slowly flowing through beds. Therefore, the effective thermal conductivity of pebble beds that is one of the governing parameters determining heat transport phenomenon needs to be addressed with respect to mechanical status of beds and purge gas pressure. In this study, a numerical framework combining finite element simulation and a semi-empirical correlation of gas gap conduction is proposed to predict the effective thermal conductivity. The purge gas pressure is found to vary the effective thermal conductivity, in particular with the presence of various sized gaps in pebble beds. Random packing of pebble beds is taken into account by an approximated correlation considering the packing factor and coordination number of pebble beds. The model prediction is compared with experimental observation from different sources showing a quantitative agreement with the measurement.