{"paper":{"title":"Thermal Conductivity of Suspended Graphene with Defects","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.mtrl-sci"],"primary_cat":"cond-mat.mes-hall","authors_text":"Alexander A. Balandin, Ashok Mulchandani, Denis L. Nika, Ganesh Balasubramanian, Hoda Malekpour, Pankaj Ramnani, Roger Lake, Srilok Srinivasan","submitted_at":"2016-03-16T21:30:12Z","abstract_excerpt":"We investigate the thermal conductivity of suspended graphene as a function of the density of defects, ND, introduced in a controllable way. Graphene layers are synthesized using chemical vapor deposition, transferred onto a transmission electron microscopy grid, and suspended over ~7.5-micrometer size square holes. Defects are induced by irradiation of graphene with the low-energy electron beam (20 keV) and quantified by the Raman D-to-G peak intensity ratio. As the defect density changes from 2.0x10^10 cm-2 to 1.8x10^11 cm-2 the thermal conductivity decreases from ~(1.8+/-0.2)x10^3 W/mK to ~"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1603.05286","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}