Presented in this dissertation are designs and characterizations of nanodevices with applications in medical science, information technology, and material design. A broad perspective is taken to facilitate unconventional problem solving and creative thinking in pursuit of producing disruptive technology. At its core, the devices presented here rely on quantum mechanical effects and nanoscale dynamics including the piezoelectric effect, ballistic transport, redox state transitions, and quantum confinement, to name a few. The focus is less on chemical synthesis and more on physical models to manipulate material properties for practical use. In addition, high dimensional materials and complex systems are keenly investigated due to their rich dynamics and indeterminacy. Specifically, Ag2S atomic switches and conductive polymers are used in information technology while facile medical devices are developed utilizing nanomaterials for their sensitive but well characterized dynamics. Here, nanotechnology is at forefront of research where the transition from the nanoscale to the mesoscale induces the creative solutions.

Recent advances towards compute-in-memory technology using topological atomic switches allowed for the predictive modeling of traffic flow and fault predicting. The presence of intrinsic nonlinear dynamics in volatile atomic switches enabled for the construction of nonlinear circuits as envisioned for volatile thermodynamic computing. A hardware implemented cognitive computing device using an atomic switch network (ASN) as the processing and memory element is capable of accomplishing tasks such as chaotic time series prediction using < 1 milliWatts of energy per prediction. Tunable volatility in the active layer within a ~10 nm junction switch is paramount and a technique to adaptively control the dynamics through iterative voltammetric control loops is presented.