arXiv (All)
open access
Molecular Implementation of the Machine-Learned Skala Exchange-Correlation Functional in CP2K through GauXC
chemical-physicscomputational-physicsdisordered-systems-and-neural-networksmaterials-sciencequantum-physics
Machine-learned exchange--correlation (XC) functionals offer a route to improve Kohn--Sham density-functional theory without incurring the cost of explicitly correlated electronic-structure methods. Their use in production simulation codes, however, requires a well-defined mapping between the learne
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Native implementation of the machine-learned Skala exchange-correlation functional in CP2K: Unified one-centre reconstruction for molecular and condensed-phase calculations#1119128
- Quantum-accurate atomistic modeling of enzyme catalysis using a machine learned potential#1011205
- Orbital-Free DFT-Assisted Machine-Learned Molecular Dynamics for Electric-Field-Driven Ionic Transport#926432
- Electronic Structure and Band-Edge Character of Ga-Substituted $α$-Al$_2$O$_3$: A First-Principles Study#793935
- Electronic Structure and Band-Edge Character of Ga-Substituted $α$-Al$_2$O$_3$: A First-Principles Study#789916
Record · ID 1128634
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive