The Drift-Diffusion package in Python (DDPy) is a Python package for drift-diffusion simulations of transport in semiconductor devices.
While first-principles calculations (Nanodcal, RESCU) provide an unparalled tool for accurate predictions of material properties based on atomic structure only, these methods are ill-suited to the simulation of large devices containing millions of atoms. To simulate large systems, using continuum models such as drift-diffusion remains the most popular approach in device engineering.
DDPy is currently available as a test version only. It contains modules for drift-diffusion calculations in one, two, and three dimensions, with the 2D implementation being the most advanced in its development.
The 2D version of DDPy includes a Poisson-Boltzmann solver for equilibrium calculations along with an implementation of the Gummel iteration method for out-of-equilibrium conditions. Calculations are performed using the Scharfetter-Gummel finite-difference discretization on a rectangular Cartesian mesh. DDPy currently supports Ohmic, artificial (non-contact) and gate (metal-oxide) boundary conditions, enabling to calculate current-voltage characteristics of, e.g., metal-oxide-semiconductor (MOS) devices.
In the long term, DDPy will seamlessly integrate with first-principles calculation tools developed by NanoAcademic Technologies (Nanodcal, RESCU), enabling to combine materials calculations and large-scale device simulations on a single platform.
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