Characterization of Copper Covetic Bulk and Films: Copper with High Carbon Content

Incorporation of carbon nanostructures in metals is desirable to combine the strongly bonded electrons in the metal and the free electrons in carbon nanostructures that give rise to high ampacity and high conductivity, respectively. Carbon in copper has the potential to impact industries such as: building construction, power generation and transmission, and microelectronics. This thesis focuses on the structure and properties of bulk and thin films of a new material, Cu covetic, that contains carbon in concentrations up to 16 at.%. X-ray photoelectron spectroscopy (XPS) shows C 1s peak with both sp2 and sp3 bonded C measuring up to 3.5 wt.% (16 at.%). High resolution transmission electron microscopy and electron diffraction of bulk covetic samples show a modulated structure of ≈ 1.6 nm along several crystallographic directions in regions that have high C content suggesting that the carbon incorporates into the copper lattice forming a network. Electron energy loss spectra (EELS) from covetics reveal that the level of graphitization from the source material, activated carbon, is maintained in the covetic structure. Bulk Cu covetics have a slight increase in the lattice constant, as well as <111> texturing, or possibly a different structure, compared to pure Cu. Density functional theory calculations predict bonding between C and Cu at the edges and defects of graphene sheets. The electrical resistivity of bulk covetics first increases and then decreases with increasing C content. Cu covetic films were deposited using e-beam and pulsed laser deposition (PLD) at different temperatures. No copper oxide or any allotropes of carbon are present in the films. The e-beam films show enhanced electrical and optical properties when compared to pure Cu films of the same thickness even though no carbon was detected by XPS or EELS. They also have slightly higher ampacity than Cu metal films. EELS analysis of the C-K-edge in the PLD films indicate that graphitic carbon is transferred from the bulk into the films with uniform carbon distribution. PLD films exhibit flatter and higher transmittance curves and sheet resistance two orders of magnitude lower than e-beam films leading to a high figure of merit as transparent conductors.

Sparse Signal Representation in Digital and Biological Systems

Theories of sparse signal representation, wherein a signal is decomposed as the sum of a small number of constituent elements, play increasing roles in both mathematical signal processing and neuroscience. This happens despite the differences between signal models in the two domains. After reviewing preliminary material on sparse signal models, I use work on compressed sensing for the electron tomography of biological structures as a target for exploring the efficacy of sparse signal reconstruction in a challenging application domain. My research in this area addresses a topic of keen interest to the biological microscopy community, and has resulted in the development of tomographic reconstruction software which is competitive with the state of the art in its field. Moving from the linear signal domain into the nonlinear dynamics of neural encoding, I explain the sparse coding hypothesis in neuroscience and its relationship with olfaction in locusts. I implement a numerical ODE model of the activity of neural populations responsible for sparse odor coding in locusts as part of a project involving offset spiking in the Kenyon cells. I also explain the validation procedures we have devised to help assess the model's similarity to the biology. The thesis concludes with the development of a new, simplified model of locust olfactory network activity, which seeks with some success to explain statistical properties of the sparse coding processes carried out in the network.