From 7241a320c9e4730c7c34035cdaacf1758b05aea3 Mon Sep 17 00:00:00 2001 From: Xiao Jin Date: Fri, 1 Nov 2024 10:17:15 +0800 Subject: [PATCH] Update README.md --- README.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 73c2a57..087b861 100644 --- a/README.md +++ b/README.md @@ -72,7 +72,9 @@ M-OFDFT is a deep-learning implementation of orbital-free density functional the - [equivariant_electron_density](https://github.com/JoshRackers/equivariant_electron_density) Generate and predict molecular electron densities with Euclidean Neural Networks - [DeePDFT](https://github.com/peterbjorgensen/DeepDFT) -This is the official Implementation of the DeepDFT model for charge density prediction. +This is the official Implementation of the DeepDFT model for charge density prediction. +- [DFA_recommeder](https://github.com/hjkgrp/dfa_recommender) + System-specific density functional recommender ## Green Function - [DeepGreen](https://arxiv.org/abs/2312.14680) The many-body Green's function provides access to electronic properties beyond density functional theory level in ab inito calculations. It present proof-of-concept benchmark results for both molecules and simple periodic systems, showing that our method is able to provide accurate estimate of physical observables such as energy and density of states based on the predicted Green's function.