RRAM devices have been subjected to intense research efforts and are proposed for nonvolatile memory and neuromorphic applications. In this paper we describe a multiscale modeling platform connecting the microscopic properties of the resistive switching material to the electrical characteristics and operation of RRAM devices. The platform allows self-consistently modeling the charge and ion transport and the material structural modifications occurring during RRAM operations and reliability, i.e., conductive filament creation and partial disruption. It allows describing the electrical behavior (current, forming, switching, cycling, reliability tests) of RRAM devices in static and transient conditions and their dependence on external conditions (e.g., temperature). Thanks to the kinetic Monte Carlo approach, the inherent variability of physical processes is properly accounted for. Simulation results can be used both to investigate material properties (including atomic defect distributions) and to optimize stack and bias pulses for optimum device performances and reliability.
Multiscale modeling of oxide RRAM devices for memory applications: from material properties to device performance / Larcher, Luca; Padovani, Andrea. - In: JOURNAL OF COMPUTATIONAL ELECTRONICS. - ISSN 1569-8025. - 16:4(2017), pp. 1077-1084. [10.1007/s10825-017-1095-3]
Multiscale modeling of oxide RRAM devices for memory applications: from material properties to device performance
Larcher, Luca;Padovani, Andrea
2017
Abstract
RRAM devices have been subjected to intense research efforts and are proposed for nonvolatile memory and neuromorphic applications. In this paper we describe a multiscale modeling platform connecting the microscopic properties of the resistive switching material to the electrical characteristics and operation of RRAM devices. The platform allows self-consistently modeling the charge and ion transport and the material structural modifications occurring during RRAM operations and reliability, i.e., conductive filament creation and partial disruption. It allows describing the electrical behavior (current, forming, switching, cycling, reliability tests) of RRAM devices in static and transient conditions and their dependence on external conditions (e.g., temperature). Thanks to the kinetic Monte Carlo approach, the inherent variability of physical processes is properly accounted for. Simulation results can be used both to investigate material properties (including atomic defect distributions) and to optimize stack and bias pulses for optimum device performances and reliability.Pubblicazioni consigliate
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