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https://github.com/barathme/hen_multiscale_lowk

Explainable Multiscale Modeling of High-Entropy Nitride Superlattices for Low-Thermal-Conductivity Coatings

https://github.com/barathme/hen_multiscale_lowk

Science Score: 44.0%

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Repository

Explainable Multiscale Modeling of High-Entropy Nitride Superlattices for Low-Thermal-Conductivity Coatings

Basic Info
  • Host: GitHub
  • Owner: barathme
  • License: mit
  • Default Branch: main
  • Size: 1.95 KB
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 1
Created 6 months ago · Last pushed 6 months ago
Metadata Files
Readme License Citation

README.md

HEN Multiscale Low-K: Data & Code

This repository contains data, code, and figures supporting the manuscript: “Explainable Multiscale Modeling of High-Entropy Nitride Superlattices for Low-Thermal-Conductivity Coatings.”

Contents

  • data/ – raw & processed datasets + metadata
  • dft_inputs/ – input files for first-principles runs (e.g., VASP)
  • ml_models/ – training scripts, SHAP analysis, saved models
  • fe_model/ – steady-state conduction model inputs & scripts
  • figures/ – high-resolution figures (1000 dpi) and editable scripts
  • docs/ – extended methodology and citation info

Quick Start

  1. Install Python 3.10+
  2. Install dependencies: bash pip install -r ml_models/requirements.txt
  3. Train & demo (uses dummy data if data/processed/dataset.csv not found): bash python ml_models/training_scripts/train_model.py
  4. SHAP summary (after training): bash python ml_models/shap_analysis/shap_summary.py
  5. 1D FE conduction demo: bash python fe_model/post_processing/calc_deltaT.py

Data

  • Place your cleaned training data at: data/processed/dataset.csv (columns example included in data/metadata/DATA_README.md).

Citation

Add Zenodo DOI badge here once generated.

License

MIT License (see LICENSE).

Owner

  • Login: barathme
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this repository, please cite it."
title: "HEN Multiscale Low-K: Data & Code"
authors:
  - family-names: "YourSurname"
    given-names: "YourName"
license: MIT
version: "1.0.0"
doi: "10.5281/zenodo.TBD"
date-released: "2025-08-23"
repository-code: "https://github.com/YOUR_USERNAME/HEN_Multiscale_LowK"

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