FerroX

FerroX is a massively parallel, 3D phase-field simulation framework for modeling ferroelectric materials based scalable logic devices. We self-consistently solve the time-dependent Ginzburg Landau (TDGL) equation for ferroelectric polarization, Poisson's equation for electric potential, and semiconductor charge equation for carrier densities in semiconductor regions. The algorithm is implemented using Exascale Computing Project software framework, AMReX, which provides effective scalability on manycore and GPU-based supercomputing architectures. The code can be used for simulations of ferroelectric domain-wall induced negative capacitance (NC) effect in Metal-Ferroelectric-Insulator-Metal (MFIM) and Metal-Ferroelectric-Insulator-Semiconductor-Metal (MFISM) devices.

Getting Help

Our community is here to help. Please report installation problems or general questions about the code in the github Issues tab above.

Installation

Download AMReX Repository

git clone git@github.com:AMReX-Codes/amrex.git

Download FerroX Repository

git clone git@github.com:AMReX-Microelectronics/FerroX.git

Build

Make sure that the AMReX and FerroX are cloned in the same location in their filesystem. Navigate to the Exec folder of FerroX and execute make -j 4

Running FerroX

Example input scripts are located in Examples directory.

Simple Testcase

You can run the following to simulate a MFIM heterostructure with a 5 nm HZO as the ferroelectric layer and 4 nm alumina as the dielectric layer under zero applied voltage:

For MPI+OMP build

mpirun -n 4 ./main3d.gnu.MPI.OMP.ex Examples/inputs_mfim_Noeb

For MPI+CUDA build

mpirun -n 4 ./main3d.gnu.MPI.CUDA.ex Examples/inputs_mfim_Noeb

Visualization and Data Analysis

Refer to the following link for several visualization tools that can be used for AMReX plotfiles.

Visualization

Data Analysis in Python using yt

You can extract the data in numpy array format using yt (you can refer to this for installation and usage of yt. After you have installed yt, you can do something as follows, for example, to get variable 'Pz' (z-component of polarization)

import yt
ds = yt.load('./plt00001000/') # for data at time step 1000
ad0 = ds.covering_grid(level=0, left_edge=ds.domain_left_edge, dims=ds.domain_dimensions)
P_array = ad0['Pz'].to_ndarray()

Publications

1. P. Kumar, M. Hoffmann, A. Nonaka, S. Salahuddin, and Z. Yao, 3D ferroelectric phase field simulations of polycrystalline multi-phase hafnia and zirconia based ultra-thin films, submitted for publication. arxiv
2. P. Kumar, A. Nonaka, R. Jambunathan, G. Pahwa, S. Salahuddin, and Z. Yao, FerroX: A GPU-accelerated, 3D Phase-Field Simulation Framework for Modeling Ferroelectric Devices, Computer Physics Communications, 108757, 2023. link