---
title: "AIMNet2 Paper"
description: "The 2nd generation of our atoms-in-molecules neural network potential (AIMNet2), which is applicable to species composed of up to 14 chemical elements in both neutral and charged states, making it a valuable method for modeling the majority of non-metallic compounds. Using an exhaustive dataset of 2"
url: "https://ouro.foundation/files/mmoderwell/aimnet2-paper"
id: "c7c08bdf-7120-4948-b6e8-355167da8718"
type: "file"
---

# AIMNet2 Paper

File by @mmoderwell in #superconductors (all) · .pdf · 1.4 MB

- Asset id: `c7c08bdf-7120-4948-b6e8-355167da8718`
- Page: https://ouro.foundation/files/mmoderwell/aimnet2-paper

The 2nd generation of our atoms-in-molecules neural network potential (AIMNet2), which is applicable to species composed of up to 14 chemical elements in both neutral and charged states, making it a valuable method for modeling the majority of non-metallic compounds. Using an exhaustive dataset of 2 x 107 hybrid DFT level of theory quantum chemical calculations, AIMNet2 combines ML-parameterized short-range and physics-based long-range terms to attain generalizability that reaches from simple organics to diverse molecules with “exotic” element-organic bonding.

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