UC Riverside

This dissertation investigated the electronic transport properties of diamond and diamond-on-graphene heterostructures. I obtained three main results during the course of my studies, one regarding the electronic transport in polycrystalline diamond films, and two regarding its potential device applications. First, I observed dissipative quantum tunneling in lowly boron-doped polycrystalline diamond by collapse of current-voltage characteristics onto a single curve, exhibiting universal scaling behavior. One of our main outcomes was the observation of a quasi-classical to quantum transition of the transport behavior of localized charge carriers within a series of quantum wells. Within our experiment, quantum mechanical tunneling was mediated by a composite quasiparticle, consisting of an instanton and anti-instanton, referred to as the bounce solution within this quantum field theoretical tunneling model. Second, I realized the first diamond-on-graphene barristor, which exhibits an optimal operation behavior between room temperature and 100◦ C. At room temperature the tunability of the Schottky barrier is the largest, but with increasing temperature the tunability degrades and is eventually lost. At 100◦ C the diode characteristics of the diamond-graphene interface is most clearly pronounced. My work layed out the first steps towards high temperature diamond and graphene based electronics for high power switching applications. Third, I fabricated the first diamond-based memristor which acts as an inorganic synapse. My diamond-based memristive inorganic synapse showed effects of a psychological human memory model with filtering, learning, remembering and forgetting of incoming signals. Spike-timing dependent plasticity in our inorganic synapse displayed the frequency dependent effect on learning. Last but not least, I observed that my inorganic synapse mimicks a refractory period commonly observed when neurons fire off action potentials between neuron cells. My diamond-based memristor has potential device applications in neuromorphic computing for novel non-traditional computer architectures for in-memory information processing.