  In Valence Change Memory (VCM) cells, the conductance of an insulating
switching layer is reversibly modulated by creating and redistributing point
defects under an external field. Accurate simulations of the switching dynamics
of these devices can be difficult due to their typically disordered atomic
structures and inhomogeneous arrangements of defects. To address this, we
introduce an atomistic framework for modelling VCM cells. It combines a
stochastic Kinetic Monte Carlo approach for atomic rearrangement with a quantum
transport scheme, both parameterized at the ab-initio level by using inputs
from Density Functional Theory (DFT). Each of these steps operates directly on
the underlying atomic structure. The model thus directly relates the energy
landscape and electronic structure of the device to its switching
characteristics. We apply this model to simulate non-volatile switching between
high- and low-resistance states in an TiN/HfO2/Ti/TiN stack, and analyze both
the kinetics and stochasticity of the conductance transitions. We also resolve
the atomic nature of current flow resulting from the valence change mechanism,
finding that conductive paths are formed between the undercoordinated Hf atoms
neighboring oxygen vacancies. The model developed here can be applied to
different material systems to evaluate their resistive switching potential,
both for use as conventional memory cells and as neuromorphic computing
primitives.
