amset

Electronic transport properties from first-principles calculations

https://github.com/hackingmaterials/amset

Science Score: 72.0%

This score indicates how likely this project is to be science-related based on various indicators:

✓
CITATION.cff file
Found CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
✓
.zenodo.json file
Found .zenodo.json file
○
DOI references
✓
Academic publication links
Links to: nature.com
✓
Committers with academic emails
5 of 13 committers (38.5%) from academic institutions
✓
Institutional organization owner
Organization hackingmaterials has institutional domain (hackingmaterials.lbl.gov)
○
JOSS paper metadata
○
Scientific vocabulary similarity
Low similarity (6.1%) to scientific vocabulary

Keywords

materials-science mobility seebeck thermoelectric transport

Keywords from Contributors

fermi-slice fermi-surface vasp cryptocurrencies graph-generation mesh computational-chemistry energy-systems chemistry physics

Last synced: 6 months ago · JSON representation ·

Repository

Electronic transport properties from first-principles calculations

Basic Info

Host: GitHub
Owner: hackingmaterials
License: other
Language: Python
Default Branch: main
Homepage: https://hackingmaterials.lbl.gov/amset/
Size: 35.5 MB

Statistics

Stars: 155
Watchers: 16
Forks: 52
Open Issues: 4
Releases: 37

Topics

materials-science mobility seebeck thermoelectric transport

Created over 9 years ago · Last pushed 6 months ago

Metadata Files

Readme License Citation

README.md

AMSET is a package for calculating electronic transport properties from first-principles calculations.

Website (including documentation): https://hackingmaterials.lbl.gov/amset/
Help/Support: https://discuss.matsci.org/c/amset
Source: https://github.com/hackingmaterials/amset

If you find AMSET useful, please consider citing our paper:

Ganose, A. M., Park, J., Faghaninia, A., Woods-Robinson, R., Persson, K. A., Jain, A. Efficient calculation of carrier scattering rates from first principles. Nat. Commun. 12, 2222 (2021)

Interested in contributing? See our contribution guidelines

Owner

Name: Hacking Materials Research Group
Login: hackingmaterials
Kind: organization
Location: Lawrence Berkeley National Lab, CA

Website: https://hackingmaterials.lbl.gov
Repositories: 22
Profile: https://github.com/hackingmaterials

Citation (CITATION.cff)

cff-version: 1.2.0
authors:
- family-names: Ganose
  given-names: Alex M.
  orcid: https://orcid.org/0000-0002-4486-3321
- family-names: Park
  given-names: Junsoo
- family-names: Faghaninia
  given-names: Alireza
- family-names: Woods-Robinson
  given-names: Rachel
- family-names: Persson
  given-names: Kristin A.
- family-names: Jain
  given-names: Anubhav
  orcid: https://orcid.org/0000-0001-5893-9967
doi: 10.1038/s41467-021-22440-5
title: 'Efficient calculation of carrier scattering rates from first principles'
message: |
  If you use AMSET in your research, please cite the following:
preferred-citation:
  authors:
  - family-names: Ganose
    given-names: Alex M.
    orcid: https://orcid.org/0000-0002-4486-3321
  - family-names: Park
    given-names: Junsoo
  - family-names: Faghaninia
    given-names: Alireza
  - family-names: Woods-Robinson
    given-names: Rachel
  - family-names: Persson
    given-names: Kristin A.
  - family-names: Jain
    given-names: Anubhav
    orcid: https://orcid.org/0000-0001-5893-9967
  title: 'Efficient calculation of carrier scattering rates from first principles'
  version: 0.4.17 # replace with whatever version you use
  date-published: 2021-04-13
  doi: 10.1038/s41467-021-22440-5
  url: https://www.nature.com/articles/s41467-021-22440-5
  issn: 2041-1723
  journal: Nature Communications
  pages: 2222
  volume: 12
  year: 2021
  type: article

GitHub Events

Total

Create event: 43
Release event: 1
Issues event: 5
Watch event: 21
Delete event: 40
Issue comment event: 15
Push event: 74
Pull request review event: 43
Pull request event: 86
Fork event: 5

Last Year

Create event: 43
Release event: 1
Issues event: 5
Watch event: 21
Delete event: 40
Issue comment event: 15
Push event: 74
Pull request review event: 43
Pull request event: 86
Fork event: 5

Committers

Last synced: about 2 years ago

All Time

Total Commits: 3,451
Total Committers: 13
Avg Commits per committer: 265.462
Development Distribution Score (DDS): 0.642

Past Year

Commits: 98
Committers: 2
Avg Commits per committer: 49.0
Development Distribution Score (DDS): 0.347

Top Committers

Name	Email	Commits
Alex Ganose	a**e@g**m	1,234
Alireza	a**a@w**u	1,087
Alireza	a**a@g**m	440
dependabot[bot]	4****]	367
dependabot-preview[bot]	2****]	252
Jason Frost	j**t@l**v	25
Jason Frost	j**t@s**u	23
Francesco Ricci	f**i@g**m	14
Alex Dunn	a**n@l**v	4
Kieran B. Spooner	3****r	2
Anubhav Jain	a**n@l**v	1
Anubhav Jain	a**r@g**m	1
Zhenzhu Li	l****l	1

Committer Domains (Top 20 + Academic)

lbl.gov: 3 stanford.edu: 1 wustl.edu: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 8
Total pull requests: 343
Average time to close issues: 22 days
Average time to close pull requests: 12 days
Total issue authors: 8
Total pull request authors: 8
Average comments per issue: 1.5
Average comments per pull request: 0.24
Merged pull requests: 258
Bot issues: 0
Bot pull requests: 329

Past Year

Issues: 2
Pull requests: 76
Average time to close issues: 30 days
Average time to close pull requests: 10 days
Issue authors: 2
Pull request authors: 4
Average comments per issue: 0.5
Average comments per pull request: 0.16
Merged pull requests: 64
Bot issues: 0
Bot pull requests: 70

View more stats

Top Authors

Issue Authors

antonf-ekb (1)
Li-HX580 (1)
thienbinh92 (1)
mvnayagam (1)
github-actions[bot] (1)
janosh (1)
sayeneBB (1)
dependabot[bot] (1)
Hemumurari (1)
liuzh1206 (1)
nickwangplus1s (1)

Pull Request Authors

dependabot[bot] (342)
github-actions[bot] (12)
utf (6)
Shiva-sslg (4)
Grimenes (3)
dg981001 (2)
e-kwsm (1)
dependabot-preview[bot] (1)

Top Labels

Issue Labels

dependencies (2) python (1)

Pull Request Labels

dependencies (355) python (330) github_actions (12)

Packages

Total packages: 2
Total downloads:
- pypi 449 last-month

Total dependent packages: 1
(may contain duplicates)
Total dependent repositories: 1
(may contain duplicates)
Total versions: 46
Total maintainers: 1

pypi.org: amset

AMSET is a tool to calculate carrier transport properties from ab initio calculation data

Homepage: https://github.com/hackingmaterials/amset
Documentation: https://amset.readthedocs.io/
License: modified BSD
Latest release: 0.5.1
published 8 months ago

Versions: 36
Dependent Packages: 1
Dependent Repositories: 1
Downloads: 449 Last month

Rankings

Dependent packages count: 4.8%

Forks count: 6.4%

Stargazers count: 6.8%

Downloads: 9.3%

Average: 9.7%

Dependent repos count: 21.5%

Maintainers (1)

alexganose

Last synced: 6 months ago

conda-forge.org: amset

AMSET is a package for calculating electronic transport properties from first-principles calculations.

Homepage: https://github.com/hackingmaterials/amset
License: BSD-3-Clause
Latest release: 0.4.18
published over 3 years ago

Versions: 10
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Forks count: 28.2%

Stargazers count: 32.5%

Dependent repos count: 34.0%

Average: 36.5%

Dependent packages count: 51.2%

Last synced: 6 months ago

Dependencies

.github/workflows/docs.yml actions

actions/cache v3 composite
actions/checkout v3 composite
actions/setup-python v4 composite
peaceiris/actions-gh-pages v3 composite

.github/workflows/pre-commit.yml actions

actions/checkout v3 composite
actions/setup-python v4 composite
peter-evans/create-pull-request v4 composite

.github/workflows/release.yml actions

actions/cache v3 composite
actions/checkout v3 composite
actions/create-release v1 composite
actions/setup-python v4 composite
pypa/gh-action-pypi-publish master composite

.github/workflows/tests.yml actions

actions/cache v3 composite
actions/checkout v3 composite
actions/setup-python v4 composite

requirements.txt pypi

BoltzTraP2 ==22.6.1
click ==8.1.3
h5py ==3.7.0
interpolation ==2.2.4
matplotlib ==3.6.2
memory_profiler ==0.60.0
monty ==2022.9.9
numba ==0.56.4
pyFFTW ==0.13.0
pymatgen ==2022.10.22
scipy ==1.9.3
spglib ==2.0.2
sumo ==2.3.5
tabulate ==0.9.0
tqdm ==4.64.1

setup.py pypi

BoltzTraP2 *
click *
h5py *
interpolation *
matplotlib *
memory_profiler *
monty *
numba *
pyFFTW *
pymatgen >=2022.0.16
scipy *
spglib *
sumo *
tabulate *
tqdm *