Goldilocks

概要

The Goldilocks MCP server provides essential k-point generation tools for computational materials science, specifically tailored for Quantum ESPRESSO with SSSP1.3 PBEsol pseudo-potentials. It leverages advanced machine learning models (ALIGNN and Random Forest) to predict k-point distances and generate corresponding k-point grids for 3D crystalline inorganic materials. By allowing users to specify desired confidence levels, Goldilocks helps streamline the setup of Density Functional Theory (DFT) calculations, enhancing both efficiency and reliability for researchers.

主な機能

• Supports ALIGNN and Random Forest machine learning models.
• Generates k-point grids using predicted k-spacing lower bounds.
• Estimates k-point distance with specified confidence levels (0.85, 0.9, 0.95).
• 2 GitHub stars
• Designed for Quantum ESPRESSO SCF DFT calculations.
• Outputs predicted k-spacing and confidence intervals.

ユースケース

• Optimizing k-point sampling for Density Functional Theory (DFT) calculations.
• Automating k-point grid generation for high-throughput computational materials science.
• Improving efficiency and accuracy of Quantum ESPRESSO simulations.