Unveiling the Multifaceted Properties of Zn 3 MoN 4 a Nitride‐Based Compound via DFT and ML Study

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Authors: Pandit Aditya Rajnikant, S. Chellaiya Thomas Rueshwin, Shanmugam Parthiban, R.D. Eithiraj
Cited by: 0
References: 40

Abstract

ABSTRACT A theoretical investigation on the Zn 3 MoN 4 compound was carried out using WIEN2k, DFT‐based code, to calculate the electronic, optoelectronic, and thermal properties of the wurtzite‐based diamond‐like Zn 3 MoN 4 structure. This compound exhibits an orthorhombic structure with the space group Pmn2 1 . The structural, electronic, optoelectronic and thermoelectric properties were calculated within the GGA approximation. As GGA tends to underestimate the band gap, both GGA and the hybrid functional (YS‐PBE0) methods were implemented, yielding indirect band gaps of 2.062 and 3.106 eV, respectively. Band gaps predicted using Extra Trees (2.081 eV) and K‐Nearest Neighbors (2.087 eV) closely matched the DFT value of 2.06 eV for Zn 3 MoN 4 , outperforming Random Forest (1.700 eV), Gradient Boost (1.404 eV) and XGBoost (1.455 eV). From the density of states, it was observed that Mo‐ d and N‐ p orbitals have the major electronic contribution. The calculated optoelectronic properties, including dielectric constants, absorption coefficient, refractive index, reflectivity, and energy loss, suggest promising potential for optoelectronic applications. Additionally, effective mass, exciton binding energy, and exciton Bohr radius were calculated, with the effective mass of holes being greater than that of electrons, signifying holes as the major carriers. The thermoelectric properties were also investigated, including Seebeck coefficient, electrical conductivity, thermal conductivity, power factor, and figure of merit, across the temperature range 0–1000 K. The ZT values were modelled with consistent R 2 and RMSE performance for the aforementioned models.

Fields of Study & Subjects

Machine Learning in Materials Science GaN-based semiconductor devices and materials 2D Materials and Applications

Publication details

Journal / source
Advanced Theory and Simulations
Volume
9
Issue
2
Publication date
1 February 2026
Language
EN