arXiv subjects

John C. Thomas

Publications and source records attributed to John C. Thomas.

8 recordsLinked to original sources

arXiv2025

First principles and scanning tunneling spectroscopical evidences for thermodynamically stable "on-top" sulfur divacancy in monolayer WS$_{2}$

Chalcogen vacancies in monolayer transition metal dichalcogenides (TMDs), such as WS$_{2}$, play a crucial role in various applications ranging from optoelectronics and catalysis to quantum information science (QIS), making their identification and control essential. This study focuses on WS$_{2}$ single vacancy and vacancy pairs. Using first principles computations, we investigate their thermodynamic stabilities and electronic structures. We identify an "on-top" divacancy configuration where two vacancies sit on top of each other to be the only energetically stable complex with a binding energy of 160 meV. We compute a small difference in electronic structure with a shift of the unoccupied state by 140 meV for the divacancy complex and observe electronic state shift during Scanning Tunneling Spectroscopy of a series of vacancy in WS$_2$ providing spectroscopical evidence for the presence of this defect.

cond-mat.mtrl-sci↗

arXiv2025

Graphene-driven correlated electronic states in one dimensional defects within WS$_2$

Tomonaga-Luttinger liquid (TLL) behavior in one-dimensional systems has been predicted and shown to occur at semiconductor-to-metal transitions within two-dimensional materials. Reports of one-dimensional defects hosting a Fermi liquid or a TLL have suggested a dependence on the underlying substrate, however, unveiling the physical details of electronic contributions from the substrate require cross-correlative investigation. Here, we study TLL formation within defectively engineered WS$_2$ atop graphene, where band structure and the atomic environment is visualized with nano angle-resolved photoelectron spectroscopy, scanning tunneling microscopy and spectroscopy, and non-contact atomic force microscopy. Correlations between the local density of states and electronic band dispersion elucidated the electron transfer from graphene into a TLL hosted by one-dimensional metal (1DM) defects. It appears that the vertical heterostructure with graphene and the induced charge transfer from graphene into the 1DM is critical for the formation of a TLL.

cond-mat.mtrl-sci↗

arXiv2024

A substitutional quantum defect in WS$_2$ discovered by high-throughput computational screening and fabricated by site-selective STM manipulation

Point defects in two-dimensional materials are of key interest for quantum information science. However, the space of possible defects is immense, making the identification of high-performance quantum defects extremely challenging. Here, we perform high-throughput (HT) first-principles computational screening to search for promising quantum defects within WS$_2$, which present localized levels in the band gap that can lead to bright optical transitions in the visible or telecom regime. Our computed database spans more than 700 charged defects formed through substitution on the tungsten or sulfur site. We found that sulfur substitutions enable the most promising quantum defects. We computationally identify the neutral cobalt substitution to sulfur (Co$_{\rm S}^{0}$) as very promising and fabricate it with scanning tunneling microscopy (STM). The Co$_{\rm S}^{0}$ electronic structure measured by STM agrees with first principles and showcases an attractive new quantum defect. Our work shows how HT computational screening and novel defect synthesis routes can be combined to design new quantum defects.

cond-mat.mtrl-sci↗

arXiv2023

Chemo-mechanics in alloy phase stability

We describe a first-principles statistical mechanics method to calculate the free energies of crystalline alloys that depend on temperature, composition, and strain. The approach relies on an extension of the alloy cluster expansion to include an explicit dependence on homogeneous strain in addition to site occupation variables that track the degree of chemical ordering. The method is applied to the Si-Ge binary alloy and is used to calculate free energies that describe phase stability under arbitrary epitaxial constraints. We find that while the incoherent phase diagram (in which coexisting phases are not affected by coherency constraints) hosts a miscibility gap, coherent phase equilibrium predicts ordering and negative enthalpies of mixing. Instead of chemical instability, the chemo-mechanical free energy exhibits instabilities along directions that couple the composition of the alloy with a volumetric strain order parameter. This has fundamental implications for phase field models of spinodal decomposition as it indicates the importance of gradient energy coefficients that couple gradients in composition with gradients in strain.

cond-mat.mtrl-sci↗

arXiv2023

CASM Monte Carlo: Calculations of the thermodynamic and kinetic properties of complex multicomponent crystals

Monte Carlo techniques play a central role in statistical mechanics approaches for connecting macroscopic thermodynamic and kinetic properties to the electronic structure of a material. This paper describes the implementation of Monte Carlo techniques for the study multicomponent crystalline materials within the Clusters Approach to Statistical Mechanics (CASM) software suite, and demonstrates their use in model systems to calculate free energies and kinetic coefficients, study phase transitions, and construct first-principles based phase diagrams. Many crystal structures are complex, with multiple sublattices occupied by differing sets of chemical species, along with the presence of vacancies or interstitial species. This imposes constraints on concentration variables, the form of thermodynamic potentials, and the values of kinetic transport coefficients. The framework used by CASM to formulate thermodynamic potentials and kinetic transport coefficients accounting for arbitrarily complex crystal structures is presented and demonstrated with examples applying it to crystal systems of increasing complexity. Additionally, a new software package is introduced, casm-flow, which helps automate the setup, submission, management, and analysis of Monte Carlo simulations performed using CASM.

cond-mat.mtrl-sci↗

arXiv2023

Direct visualization of the charge transfer in Graphene/$α$-RuCl$_3$ heterostructure

We investigate the electronic properties of a graphene and $α$-ruthenium trichloride (hereafter RuCl$_3$) heterostructure, using a combination of experimental and theoretical techniques. RuCl$_3$ is a Mott insulator and a Kitaev material, and its combination with graphene has gained increasing attention due to its potential applicability in novel electronic and optoelectronic devices. By using a combination of spatially resolved photoemission spectroscopy, low energy electron microscopy, and density functional theory (DFT) calculations we are able to provide a first direct visualization of the massive charge transfer from graphene to RuCl$_3$, which can modify the electronic properties of both materials, leading to novel electronic phenomena at their interface. The electronic band structure is compared to DFT calculations that confirm the occurrence of a Mott transition for RuCl$_3$. Finally, a measurement of spatially resolved work function allows for a direct estimate of the interface dipole between graphene and RuCl$_3$. The strong coupling between graphene and RuCl$_3$ could lead to new ways of manipulating electronic properties of two-dimensional lateral heterojunction. Understanding the electronic properties of this structure is pivotal for designing next generation low-power opto-electronics devices.

cond-mat.mtrl-sci↗

arXiv2022

Autonomous Investigations over WS$_2$ and Au{111} with Scanning Probe Microscopy

Individual atomic defects in 2D materials impact their macroscopic functionality. Correlating the interplay is challenging, however, intelligent hyperspectral scanning tunneling spectroscopy (STS) mapping provides a feasible solution to this technically difficult and time consuming problem. Here, dense spectroscopic volume is collected autonomously via Gaussian process regression, where convolutional neural networks are used in tandem for spectral identification. Acquired data enable defect segmentation, and a workflow is provided for machine-driven decision making during experimentation with capability for user customization. We provide a means towards autonomous experimentation for the benefit of both enhanced reproducibility and user-accessibility. Hyperspectral investigations on WS$_2$ sulfur vacancy sites are explored, which is combined with local density of states confirmation on the Au{111} herringbone reconstruction. Chalcogen vacancies, pristine WS$_2$, Au face-centered cubic, and Au hexagonal close packed regions are examined and detected by machine learning methods to demonstrate the potential of artificial intelligence for hyperspectral STS mapping.

cond-mat.mtrl-sci↗

arXiv2019

Machine learning the DFT potential energy surface for inorganic halide perovskite CsPbBr$_3$

Structural phase transitions as a function of temperature dictate the structure--functionality relationships in many technologically important materials. Harmonic Hamiltonians have proven successful in predicting the vibrational properties of many materials. However, they are inadequate for modeling structural phase transitions in crystals with potential energy surfaces that are either strongly anharmonic or no\ n-convex with respect to collective atomic displacements or homogeneous strains. In this paper we develop a framework to express highly anharmonic first-principles potential energy surfaces as polynomials of collective cluster deformati\ ons. We further adapt the approach to a nonlinear extension of the cluster expansion formalism through the use of an artificial neural net model. The machine learning models are trained on a large database of first-principles calculations and are shown to reproduce the potential energy surface with l\ ow error.

cond-mat.mtrl-sci↗