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Materials Informatics Framework for Accelerated Discovery of High-Refractive-Index 2D Materials.

Liudmila A Klimova¹, Ivan A Kruglov¹, Georgy A Ermolaev¹

¹Emerging Technologies Research Center, XPANCEO, Internet City, Emmay Tower, Dubai, United Arab Emirates.

|January 13, 2026

Summary

We developed a physics-guided machine learning model to predict optical properties of two-dimensional (2D) materials. This accelerates the discovery of new 2D materials for photonic applications.

Keywords:

2D materials density functional theory graph neural networks machine learning framework materials informatics refractive index transition metal dichalcogenides

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Area of Science:

Materials Science
Condensed Matter Physics
Computational Materials Science

Background:

Predicting optical properties of 2D materials is vital for photonics but challenging due to theory-experiment discrepancies.
Existing methods struggle with accurate and efficient screening of novel 2D materials for specific applications.

Purpose of the Study:

To develop a physics-guided machine learning (ML) framework for accelerated screening of 2D materials.
To enable accurate prediction of optical properties for designing next-generation photonic materials.

Main Methods:

Combined first-principles density functional theory (DFT) calculations with graph neural network (GNN) models.
Integrated experimental spectroscopic validation and Cauchy-model for optical property correction.
Developed a universal method for defining 2D material thickness and corrected DFT-derived optical properties.

Main Results:

Created a database of over 1000 transition metal dichalcogenides (TMDs) monolayers and their optical properties.
Developed a ML model to accurately calculate refractive indices in the near-infrared (near-IR) region (755-1064 nm).
Validated the ML model against independent 2D materials databases, confirming structure-property correlations.

Conclusions:

The ML framework significantly accelerates the screening of 2D materials with tailored optical functionalities.
High-refractive-index materials like Bi2Te2Se show promise for enhanced field confinement in monolayer waveguides.
This approach facilitates the discovery and design of novel 2D materials for integrated photonics.