Multi-resistance states and neural learning with perovskite nickelates

Habituation behavior, which can be defined as decrement in response to repeated stimuli, is a fundamental form of non-associative learning observed among all living systems, from human beings with central nervous system to single-cell organism without a brain. We present realization of similar behavior in a quantum perovskite nickelate system via dynamical modulation of electron localization. This is achieved by weak anchoring of hydrogen to interstitial sites in the perovskite accompanied by charge transfer into the e_g orbitals of Ni. The electron transfer from hydrogen creates a strongly correlated Ni²⁺ state that is insulating with a gap of nearly 3 eV for one electron/unit cell doping level. Since the dopant is weakly bound and quite mobile, we can create varying levels of volatility. Hence, a range of resistance states can be temporally controlled. This behavior can be modeled by exponential relaxations and the resulted plasticity can be incorporated into neural learning algorithms. We find that incorporating controlled memory loss enhances learning by forgetting non-critical information. The studies suggest that control of strong correlations in complex oxides presents an opportunity for materials design in the quest for post-Moore disruptive computing vectors.