Skip to main content

A package for LPC3D mesoscopic simulations

Project description

LPC3D

A code to do mesoscopic simulations of ions diffusing in carbon particles and of full supercapacitors.

This code is developed in the context of the MultiXscale project.

This code was written by El Hassane Lahrar and Céline Merlet, with contributions from Rudolf Weber, and was used in one published work:

"Investigating the effect of particle size distribution and complex exchange dynamics on NMR spectra of ions diffusing in disordered porous carbons through a mesoscopic model", Faraday Discuss., Advance article, https://pubs.rsc.org/en/Content/ArticleLanding/2024/FD/D4FD00082J

Here, a manual and example input files are provided.

Compared to the previous version of the program, written in C and serial (https://github.com/cmerlet/LPC3D-C-serial), this code is written using pystencils (https://pypi.org/project/pystencils/) - is parallel - and can use CPU and GPU.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

lpc3d-0.1.2.tar.gz (12.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

lpc3d-0.1.2-py3-none-any.whl (12.5 kB view details)

Uploaded Python 3

File details

Details for the file lpc3d-0.1.2.tar.gz.

File metadata

  • Download URL: lpc3d-0.1.2.tar.gz
  • Upload date:
  • Size: 12.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.8.10

File hashes

Hashes for lpc3d-0.1.2.tar.gz
Algorithm Hash digest
SHA256 ca7e0236192fef009954bf0969594480e6fff30a01e439cbb7799e2d31dc72d3
MD5 f359428079401672196bb4735da0ed80
BLAKE2b-256 ed69dd3e4c3b4d84fef89791d392304f4acd715a21758d3d3bd1a5a9d1133503

See more details on using hashes here.

File details

Details for the file lpc3d-0.1.2-py3-none-any.whl.

File metadata

  • Download URL: lpc3d-0.1.2-py3-none-any.whl
  • Upload date:
  • Size: 12.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.8.10

File hashes

Hashes for lpc3d-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 a3290a51372738b77c0be38433fd3e50a41300a5ec7cf0259282ee854897099e
MD5 0a05b1293c007d3b67de1a483acc2a0a
BLAKE2b-256 1897c82e2db50141fa7a3af394a9697455707ebed5c56cb52223b7aba30370f9

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page