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WOS: 000314706300003 ; PubMed ID: 23390578 ; We propose a hybrid nano-structuring scheme for tailoring thermal and thermoelectric transport properties of graphene nanoribbons. Geometrical structuring and isotope cluster engineering are the elements that constitute the proposed scheme. Using first-principles based force constants and Hamiltonians, we show that the thermal conductance of graphene nanoribbons can be reduced by 98.8% at room temperature and the thermoelectric figure of merit, ZT, can be as high as 3.25 at T = 800 K. The proposed scheme relies on a recently developed bottom-up fabrication method, which is proven to be feasible for synthesizing graphene nanoribbons with an atomic precision. ; German Research Foundation (DFG) [SPP-1386, CU44/11-1]; German Excellence Initiative via the Cluster of Excellence "Center for Advancing Electronics Dresden" (cfAED) [EXC 1056]; European Union (ERDF); Free State of Saxony via TP A2 ("MolFunc"/"MolDiagnosik") of the Cluster of Excellence "European Center for Emerging Materials and Processes Dresden" (ECEMP); Danish Council for Independent Research (DFF); NSF [DMR 0844082]; Scientific and Technological Research Council of Turkey (TUBITAK); Ministry of Education, Science and Technology through the National Research Foundation of Korea [R31-10100] ; We would like to acknowledge the support by the priority program Nanostructured Thermoelectrics (SPP-1386) of the German Research Foundation (DFG) (Contract No. CU44/11-1), the German Excellence Initiative via the Cluster of Excellence EXC 1056 "Center for Advancing Electronics Dresden" (cfAED), the European Union (ERDF) and the Free State of Saxony via TP A2 ("MolFunc"/"MolDiagnosik") of the Cluster of Excellence "European Center for Emerging Materials and Processes Dresden" (ECEMP). H. S. acknowledges funding from the Danish Council for Independent Research (DFF). C. S. and T. C. acknowledge support from NSF (DMR 0844082) to International Institute of Materials for Energy Conversion at Texas A&M University. The parts of computations are carried out at the facilities of Laboratory of Computational Engineering of Nanomaterials also supported by ARO, ONR, and DOE grants. We also would like to thank for generous time allocation made for this project by the Supercomputing Center of Texas A&M University. C. S. acknowledges the support from The Scientific and Technological Research Council of Turkey (TUBITAK) to his research at Anadolu University. G. C. further acknowledges the World Class University program funded by the Ministry of Education, Science and Technology through the National Research Foundation of Korea (R31-10100). The Center for Information Services and High Performance Computing (ZIH) at the TU-Dresden is also acknowledged.