From 1e7a4971b5a0fa26c6bf44ba01a8c04dda898515 Mon Sep 17 00:00:00 2001 From: "allcontributors[bot]" <46447321+allcontributors[bot]@users.noreply.github.com> Date: Fri, 5 Feb 2021 21:35:55 +0000 Subject: [PATCH 1/2] docs: update README.md [skip ci] --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 16ef33eff9..5937a8f59d 100644 --- a/README.md +++ b/README.md @@ -6,7 +6,7 @@ [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pybamm-team/PyBaMM/blob/master/) [![black_code_style](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black) -[![All Contributors](https://img.shields.io/badge/all_contributors-27-orange.svg?style=flat-square)](#contributors-) +[![All Contributors](https://img.shields.io/badge/all_contributors-28-orange.svg?style=flat-square)](#contributors-) PyBaMM (Python Battery Mathematical Modelling) solves physics-based electrochemical DAE models by using state-of-the-art automatic differentiation and numerical solvers. The Doyle-Fuller-Newman model can be solved in under 0.1 seconds, while the reduced-order Single Particle Model and Single Particle Model with electrolyte can be solved in just a few milliseconds. Additional physics can easily be included such as thermal effects, fast particle diffusion, 3D effects, and more. All models are implemented in a flexible manner, and a wide range of models and parameter sets (NCA, NMC, LiCoO2, ...) are available. There is also functionality to simulate any set of experimental instructions, such as CCCV or GITT, or specify drive cycles. @@ -147,6 +147,7 @@ Thanks goes to these wonderful people ([emoji key](https://allcontributors.org/d