arXiv subjects

Chinonso Ugwumadu

Publications and source records attributed to Chinonso Ugwumadu.

6 recordsLinked to original sources

arXiv2026

A Defect-Free Model of Amorphous Silicon with Pristine Electronic Structure

Amorphous silicon (a-Si) is understood to be the canonical continuous random network material, ideally defined by fully fourfold coordination. Here, we show that a defect-free ('ideal') model of a-Si from machine-learning-driven molecular-dynamics simulations [L. A. M. Rosset et al., Nat. Commun. 16, 2360 (2025)], subsequently evaluated with hybrid-level density-functional theory computations, can accurately reproduce the experimentally observed electronic bandgap. We compare this model with one resulting from the Wooten-Winer-Weaire (WWW) bond-switching approach and with other recent approximants to ideal a-Si. More broadly, our work provides a platform for studies of band tails, optical properties, and transport in a-Si.

cond-mat.mtrl-sci↗

arXiv2026

Temperature dependence of electronic conductivity from ab initio thermal simulation

We present a temperature-dependent extension of the approximate electronic conductivity formula of Hindley and Mott that leverages time-averaged fluctuations of the electronic density of states obtained from ab initio molecular dynamics. By thermally averaging the square of the density of states near the Fermi level, we obtain an estimate of the temperature dependence of the conductivity. This approach termed the thermally-averaged Hindley-Mott (TAHM) method was applied to five representative systems: crystalline aluminum (c-Al), aluminum with a grain boundary (AlGB), a four-layer graphene-aluminum composite (Al-Gr), amorphous silicon (a-Si) and amorphous germanium-antimony-telluride (a-GST). The method reproduces the expected Bloch-Gruneisen decrease in conductivity for c-Al and AlGB. Generally, the reduction (increase) in conductivity for metallic (semiconducting) materials are reproduced. It captures microstructure-induced, thermally activated conduction in multilayer Al-Gr, a-Si and a-GST. Overall, the approach provides a computationally efficient link between time-dependent electronic structure and temperature-dependent transport, offering a simple and approximate tool for exploring electronic conductivity trends in complex and disordered materials.

cond-mat.mtrl-sci↗

arXiv2025

Electronic and thermal properties of the phase-change memory material, Ge2Sb2Te5, and results from spatially resolved transport calculations

We report new insights into the electronic, structural, and transport (heat and charge) properties of the phase-change memory material Ge2Sb2Te5. Using realistic structural models of Konstantinou et. al. [Nat. Commun. 10, 3065 (2019)], we analyze the topology, electronic states, and lattice dynamics with density functional methods, including hybrid-functional calculations and machine-learned interatomic potentials. The Kohn-Sham orbitals near the Fermi level display a strong electron-phonon coupling, and exhibit large energy fluctuations at room temperature. The conduction tail states exhibit larger phonon-induced fluctuations than the valence tail states. To resolve transport at the atomic scale, we employ space-projected electronic conductivity and site-projected thermal conductivity methods. Local analysis of heat transport highlights the role of filamentary networks dominated by Te, with Sb and Ge making progressively smaller contributions.

cond-mat.mtrl-sci↗

arXiv2025

New models of clean and hydrogenated amorphous silicon surfaces

We present new atomistic models of amorphous silicon (a-Si) and hydrogenated amorphous silicon (a-Si:H) surfaces. The a-Si model included 4096 atoms and was obtained using local orbital density functional theory. By analyzing a slab model (periodic in two dimensions with a slab about 44 Å thick), we observed a strong correlation between surface structure and surface charge density, which might be compared to STM experiments. Hydrogen atoms added near the under-coordinated surface atoms passivate dangling bonds and induce structural rearrangements. We analyze the electronic structure, including the localization of the states, and note resonant mixing between bulk and surface defect structures. We also compute the classical normal modes of the hydrogenated a-Si and compare them to experiments where possible. Our work is a step toward understanding the meaning of ``surface reconstruction" for a noncrystalline material.

cond-mat.mtrl-sci↗

arXiv2023

Understanding defects in amorphous silicon with million-atom simulations and machine learning

The structure of amorphous silicon is widely thought of as a fourfold-connected random network, and yet it is defective atoms, with fewer or more than four bonds, that make it particularly interesting. Despite many attempts to explain such "dangling-bond" and "floating-bond" defects, respectively, a unified understanding is still missing. Here, we show that atomistic machine-learning methods can reveal the complex structural and energetic landscape of defects in amorphous silicon. We study an ultra-large-scale, quantum-accurate structural model containing a million atoms, and more than ten thousand defects, allowing reliable defect-related statistics to be obtained. We combine structural descriptors and machine-learned local atomic energies to develop a universal classification of the different types of defects in amorphous silicon. The results suggest a revision of the established floating-bond model by showing that fivefold-coordinated atoms in amorphous silicon exhibit a wide range of local environments, and it is shown that fivefold (but not threefold) coordination defects tend to cluster together. Our study provides new insights into one of the most widely studied amorphous solids, and has general implications for modelling and understanding defects in disordered materials beyond silicon alone.

cond-mat.mtrl-sci↗

arXiv2022

Ab initio simulation of amorphous graphite

A disorder-order transition from amorphous carbon (aC) to layered amorphous graphene (LAG) has been predicted using ab-initio methods. Amorphous carbon at densities close to the graphitic density show a strong proclivity to layer in NVT simulations near 3000K . Our calculations have shown that graphitization is strongly dependent on the simulation temperature and is not observed under 2500K. The origin of such a disorder-order transition has been studied using various structural analyses. Each layer of LAG is a layer of amorphous graphene (aG) including pentagons and heptagons in addition to hexagons and the planes are separated by about 3.2A. LAG obtained from the NVT simulations were highly stable. The electronic charge density, especially for the pi and pi$^*$ states, was computed with the Hyed-Scuseria-Ernzerhof (HSE) hybrid functional and compared with crystalline graphite (cG). The impact of structural disorder has been studied in detail, especially the consequences of disorder to electronic transport.

cond-mat.mtrl-sci↗