What is AMMBER?
The AI-assisted Microstructure Model BuildER (AMMBER) is an ongoing project at the University of Michigan.
AMMBER_python is a utility for extracting free-energy data and formatting it for use in phase-field simulation codes.
Phase-field models, which incorporate thermodynamic and kinetic data from atomistic calculations and experiments, have become a key computational tool for understanding microstructural evolution and providing a path to control and optimize morphologies and topologies of structures from nanoscale to microscales. However, due to the complexity of interactions between multiple species, these models are difficult to parameterize. In this project, we developed algorithms and software that automate and optimize the selection of thermodynamic and kinetic parameters for phase-field simulations of microstructure evolution in multicomponent systems.
Presently, the framework consists of two modules: AMMBER_python, which is used to extract phase-field usable free energies from general data sources, and AMMBER-PRISMS-PF, which provides an open-source suite of multi-component, multi-phase-field model implementations with a simple, flexible interface for defining a system of thermodynamic and kinetic parameters.
Quick Start Guide
Install:
To install the AMMBER Python package, you can use pip. First, ensure your pip is up to date:
python -m pip install --upgrade pip
pip install ammber
Installing from Source:
If you want to install the package directly from the source code, follow these steps:
-
Clone the repository:
git clone https://github.com/UMThorntonGroup/AMMBER_python.git cd AMMBER_python
-
Upgrade
pipand install the package:python -m pip install --upgrade pip pip install .
Development Installation:
For development purposes, you can install the package in editable mode:
-
Clone the repository:
git clone https://github.com/UMThorntonGroup/AMMBER_python.git cd AMMBER_python
-
Upgrade
pipand install in editable mode:python -m pip install --upgrade pip pip install -e .
Dependencies:
AMMBER requires the following Python packages:
numpyscipypycalphad
These dependencies will be installed automatically when using pip install ammber. If you encounter issues, you can manually install them using:
pip install numpy scipy pycalphad
License:
MIT License. Please see LICENSE for details.
Links
Metadata
Release files for ammber 0.1.8
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ammber-0.1.8.tar.gz | 11.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ammber-0.1.8-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 19.8 kB
Release files / ammber-0.1.8.tar.gz
| Download URL | ammber-0.1.8.tar.gz |
|---|---|
| Size | 11.0 kB |
| Tags | Source |
|
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
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twine/6.1.0 CPython/3.13.7
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Transparency logRelease files / ammber-0.1.8-py3-none-any.whl
| Download URL | ammber-0.1.8-py3-none-any.whl |
|---|---|
| Size | 8.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Feb 18, 2026.
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