Large discrete resistance jump at grain boundary in copper nanowire.

Copper is the current interconnect metal of choice in integrated circuits. As interconnect dimensions decrease, the resistivity of copper increases dramatically because of electron scattering from surfaces, impurities, and grain boundaries (GBs) and threatens to stymie continued device scaling. Lacking direct measurements of individual scattering sources, understanding of the relative importance of these scattering mechanisms has largely relied on semiempirical modeling. Here we present the first ever attempt to measure and calculate individual GB resistances in copper nanowires with a one-to-one correspondence to the GB structure. Large resistance jumps are directly measured at the random GBs with a value far greater than at coincidence GBs and first-principles calculations. The high resistivity of the random GB appears to be intrinsic, arising from the scaling of electron mean free path with the size of the lattice relaxation region. The striking impact of random GB scattering adds vital information for understanding nanoscale conductors.

Micro-differential thermal analysis detection of adsorbed explosive molecules using microfabricated bridges.

Although micromechanical sensors enable chemical vapor sensing with unprecedented sensitivity using variations in mass and stress, obtaining chemical selectivity using the micromechanical response still remains as a crucial challenge. Chemoselectivity in vapor detection using immobilized selective layers that rely on weak chemical interactions provides only partial selectivity. Here we show that the very low thermal mass of micromechanical sensors can be used to produce unique responses that can be used for achieving chemical selectivity without losing sensitivity or reversibility. We demonstrate that this method is capable of differentiating explosive vapors from nonexplosives and is additionally capable of differentiating individual explosive vapors such as trinitrotoluene, pentaerythritol tetranitrate, and cyclotrimethylenetrinitromine. This method, based on a microfabricated bridge with a programmable heating rate, produces unique and reproducible thermal response patterns within 50 ms that are characteristic to classes of adsorbed explosive molecules. We demonstrate that this micro-differential thermal analysis technique can selectively detect explosives, providing a method for fast direct detection with a limit of detection of 600x10(-12) g.