arXiv subjects

Mina Yoon

Publications and source records attributed to Mina Yoon.

At least 19 recordsLinked to original sources

arXiv2026

DQAOA-GPT: AI-Accelerated Distributed Quantum Optimization for Combinatorial Problems

While combinatorial optimization problems are central to many scientific and engineering applications, their solution remains challenging due to exponentially large search spaces. Variational quantum algorithms offer a promising route for tackling such problems, yet their practical performance is limited by repeated quantum circuit evaluations and classical parameter updates. In this work, we introduce DQAOA-GPT, a hybrid framework that integrates the distributed quantum approximate optimization algorithm (DQAOA), which decomposes a large optimization problem into smaller sub-problems, with GPT-based quantum circuit generation for solving those sub-problems. Rather than relying on iterative variational optimization, the proposed approach uses a trained generative model to directly generate high-quality quantum circuits for the decomposed sub-problems. As a benchmark, we evaluate DQAOA-GPT against conventional DQAOA on dense HUBO optimization problems with up to 100 decision variables. The results demonstrate that DQAOA-GPT significantly reduces computational cost while maintaining competitive solution quality, with larger acceleration observed for larger sub-problem sizes. Although this work focuses on benchmark-scale validation, the framework provides a promising foundation for larger-scale combinatorial optimization in hybrid HPC-QC environments through increased GPU resources and parallel computing capability.

quant-ph↗

arXiv2026

Optimizing Density Functional Theory for Strain-Dependent Magnetic Properties of Monolayer MnBi$_2$Te$_4$ with Diffusion Monte Carlo

Monolayer MnBi$_{2}$Te$_{4}$ (MBT) is an intrinsically magnetic topological insulator whose magnetic response is strongly affected by strain and electron correlation. In density functional theory with an on-site Hubbard correction (DFT+$U$), however, predictions vary substantially with the choice of Hubbard $U$, making it difficult to establish a reliable strain-dependent picture of magnetism in this system. Here we use diffusion Monte Carlo (DMC) to benchmark DFT+$U$ for monolayer MBT and to determine an effective $U$ as a function of strain. We find that the predicted magnetic phase diagram depends strongly on $U$, indicating that a single fixed value is not sufficient across the strain range considered. DMC nodal optimization further shows that the optimal $U$ increases with strain magnitude and is well captured by a simple quadratic form. When this DMC-informed strain-dependent $U$ is used in PBE+$U$, the calculated Mn local moments are brought into close agreement with DMC and are improved relative to commonly used fixed-$U$ choices. These results show that, for monolayer MBT, correlation strength itself should be treated as strain dependent, and they provide a practical many-body-guided strategy for improving strain-dependent DFT+$U$ descriptions of magnetic van der Waals materials.

cond-mat.mtrl-sci↗

arXiv2025

Interpretable Graph Neural Networks for Classifying Structure and Magnetism in Delafossite Compounds

Delafossites (ABC2, where A and B are metals and C is a chalcogen) are a versatile family of quantum materials and layered oxides/chalcogenides whose properties are highly sensitive to atomic composition and stacking geometry. Their broad chemical tunability makes them an ideal platform for large-scale combinatorial exploration and high-throughput computational screening with desirable quantum properties. In this work, we employ a Concept Whitening Graph Neural Network, a gray-box AI model, to classify delafossite structures by stacking sequence and magnetic states. By aligning learned representations with human-interpretable physical concepts, this gray-box approach enables both accurate prediction and insight into the structural and chemical features driving magnetic behavior. The magnetic-ordering models achieved validation accuracies exceeding 80 percent, with a further slight uptick observed in the model incorporating the largest number of concepts. Concept alignment analysis revealed measurable learning across nine physically meaningful descriptors, with coefficients of determination ranging from approximately 0.6 for the d-shell valence-electron concepts to 0.4-0.5 for the magnetic coupling parameters. Furthermore, we mapped the concept importances onto the material graph representation, elucidating interpretable physical trends and the progression of stable concept-aligned regions across training. These results demonstrate the potential of interpretable graph-based learning to capture the underlying physics of complex materials systems and provide an interpretable framework for accelerating the discovery and understanding of delafossites and related crystalline materials.

cond-mat.mtrl-sci↗

arXiv2025

Overcoming Quantum Resistivity Scaling in Nanoscale Interconnects Using Delafossite PdCoO2

Continued scaling into the sub 7 nm regime exacerbates quantum limited resistivity in Cu interconnects. We evaluated layered PdCoO2 and explicitly benchmarked it against Cu to identify mechanisms that maintain conductivity under confinement. Using a momentum resolved relaxation time formalism derived from the conductivity tensor, we link k and energy resolved velocities, life times, and mean free paths (MFPs) to thickness dependent resistivity for films and wires. PdCoO2 exhibits quasi 2D transport with high inplane velocities and strongly anisotropic MFPs (15 nm inplane, 3 nm outofplane near EF), whereas Cu shows an isotropic 22 nm MFP. Under identical boundary conditions including a realistic 2 nm liner/diffusion barrier for Cu, PdCoO2 displays suppressed boundary scattering and a much slower resistivity increase from bulk down to sub 30 nm, preserving near bulk conductivity and remaining viable at 2 nm. Thickness trends reveal dual slope changes in PdCoO2 (35 nm and 7 nm) set by anisotropic MFPs, contrasting with the single characteristic scale of Cu (40 nm). The calculated bulk values and scaling curves track available measurements for both materials. These results establish PdCoO2 as a scalable interconnect that outperforms Cu under quantum confinement and provide a quantitative framework to screen layered conductors for next generation nanoelectronic interconnects.

cond-mat.mtrl-sci↗

arXiv2025

Reversible Modification of Rashba States in Topological Insulators at Room Temperature by Edge Functionalization

Quantum materials with novel spin textures from strong spin-orbit coupling (SOC) are essential components for a wide array of proposed spintronic devices. Topological insulators have necessary strong SOC that imposes a unique spin texture on topological states and Rashba states that arise on the boundary, but there is no established methodology to control the spin texture reversibly. Here, we demonstrate that functionalizing Bi2Se3 films by altering the step-edge termination directly changes the strength of SOC and thereby modifies the Rashba strength of 1D edge states. Scanning tunneling microscopy/spectroscopy shows that these Rashba edge states arise and subsequently vanish through the Se functionalization and reduction process of the step edges. The observations are corroborated by density functional theory calculations, which show that a subtle chemical change of edge termination fundamentally alters the underlying electronic structure. Importantly, we experimentally demonstrated fully reversible and repeatable switching of Rashba edge states across multiple cycles at room temperature. The results imply Se functionalization as a practical method to control SOC and spin texture of quantum states in topological insulators.

cond-mat.mes-hall↗

arXiv2025

Coexistence of superconductivity and topological band in a van der Waals Sn1-xInxBi2Te4 crystal

The realization of topological surface states and superconductivity within a single material platform is a crucial step toward achieving topologically nontrivial superconductivity. This can be achieved at an interface between a superconductor and a topological insulator, or within a single material that intrinsically hosts both superconductivity and topological surface states. Here we use scanning tunneling microscopy to study Sn1-xInxBi2Te4 crystals. Spectroscopic evidence reveals the coexistence of topological surface states and superconductivity on the same surface of the crystals. The Te-terminated surface exhibits a single U-shaped superconducting gap with a size of up to 311 {\mu}eV, alongside Dirac bands outside the gap. Analysis of the vortex structure and differential conductance suggests weak-coupling s-wave superconductivity. The absence of observed zero modes suggests that shifting the Fermi level closer to the Dirac point of the topological bands is necessary to realize a topological superconducting state.

cond-mat.supr-con↗

arXiv2024

Thickness-Dependent Polaron Crossover in Tellurene

Polarons, quasiparticles arising from electron-phonon coupling, are crucial in understanding material properties such as high-temperature superconductivity and colossal magnetoresistance. However, scarce studies have been performed to investigate the formation of polarons in low-dimensional materials with phonon polarity and electronic structure transitions. In this work, we studied polarons of tellurene that are composed of chiral chains of tellurium atoms. The frequency and linewidth of the A1 phonon, which becomes increasingly polar for thinner tellurene, exhibit an abrupt change when the thickness of tellurene is below 10 nm. Meanwhile, the field effect mobility of tellurene drops rapidly as the thickness is smaller than 10 nm. These phonon and transport signatures, combined with the calculated phonon polarity and band structure, suggest a crossover from large polarons for bulk tellurium to small polarons for few-layer tellurene. Effective field theory considers the phonon renormalization in the strong coupling (small polaron) regime, and semi-quantitatively reproduces the observed phonon hardening and broadening effects in few-layer tellurene. This polaron crossover stems from the quasi-1D nature of tellurene where modulation of the interchain distance reduces the dielectric screening and promotes electron-phonon coupling. Our work provides valuable insights into the influence of polarons on phononic, electronic, and structural properties in low-dimensional materials.

cond-mat.mtrl-sci↗

arXiv2024

Improved Electrical Conductivity of Copper and Nitrogen Functionalized Carbon Nanotubes

In this work, we investigate the electrical conductivity of carbon nanotubes (CNTs), with a particular focus on the effects of doping. Using a first-principles approach, we study the electronic structure, phonon dispersion, and electron-phonon scattering to understand the finite-temperature electrical transport properties in CNTs. Our study covers both prototypical metallic and semiconducting CNTs, with special emphasis on the influence of typical defects such as vacancies and the incorporation of copper or nitrogen, such as pyridinic N, pyrrolic N, graphitic N, and oxidized N. Our theoretical study shows significant improvements in the electrical conduction properties of copper-CNT composites, especially when semiconducting CNTs are functionalized with nitrogen. Doping is found to cause significant changes in the electronic density of states near the Fermi level, which affects the electrical conductivity. Calculations show that certain types of functional groups, such as N-pyrrolic, result in a ~30-fold increase in the conductivity of semiconducting CNTs compared to Cu-incorporated CNTs alone. For metallic CNTs, the conductivity is in agreement with existing experimental data, and our prediction of significant increases in conductivity with N-pyrrolic functional group is consistent with recent experimental results, demonstrating the effectiveness of doping in modifying conductivity. Our study provides valuable insight into the electronic properties of doped CNTs and contributes to the development of ultra-high conductivity CNT composites.

cond-mat.mtrl-sci↗

arXiv2024

Optimizing Density Functional Theory for Strain-Dependent Magnetic Properties of MnBi$_2$Te$_4$ with Diffusion Monte Carlo

In this study, we evaluate the predictive power of density functional theory (DFT) for the magnetic properties of MnBi$_2$Te$_4$ (MBT), an intrinsically magnetic topological insulator with potential applications in spintronics and quantum computing. Our theoretical understanding of MBT has been challenged by discrepancies between experimental results and \textit{ab initio} calculations, particularly with respect to its electronic and magnetic properties. Our results show that the magnetic phase diagram of MBT varies significantly depending on the Hubbard $U$ parameter in the DFT framework, highlighting the importance of benchmark calculations. To address these challenges, we establish an optimized Hubbard $U$ approach derived from Diffusion Monte Carlo (DMC) calculations, which directly solves the many-body Schr\"{o}dinger equation based on the stochastic process, and implement it in the DFT framework. Once the optimized $U$ value is determined as a function of strain, we apply it to achieve DMC-level accuracy within our DFT framework. This approach is instrumental in accurately describing the magnetic states of MBT and understanding the underlying mechanisms governing its magnetic properties and their dependence on external factors.

cond-mat.mtrl-sci↗

arXiv2024

Controlling structural phases of Sn through lattice engineering

Topology and superconductivity, two distinct phenomena offer unique insight into quantum properties and their applications in quantum technologies, spintronics, and sustainable energy technologies if system can be found where they coexist. Tin (Sn) plays a pivotal role here as an element due to its two structural phases, $\alpha$-Sn and $\beta$-Sn, exhibiting topological characteristics ($\alpha$-Sn) and superconductivity ($\beta$-Sn). In this study we show how precise control of $\alpha$ and $\beta$ phases of Sn thin films can be achieved by using molecular beam epitaxy grown buffer layers with systematic control over the lattice parameter. The resulting Sn films showed either $\beta$-Sn or $\alpha$-Sn phases as the lattice constant of the buffer layer was varied from 6.10 A to 6.48 A, covering the range between GaSb (closely matched to InAs) and InSb. The crystal structures of the $\alpha$- and $\beta$-Sn films were characterized by x-ray diffraction and confirmed by Raman spectroscopy and scanning transmission electron microscopy. The smooth and continuous surface morphology of the Sn films was validated using atomic force microscopy. The characteristics of $\alpha$- and $\beta$-Sn phases were further verified using electrical transport measurements by observing resistance drop near 3.7 K for superconductivity of the $\beta$-Sn phase and Shubnikov-de Haas oscillations for the $\alpha$-Sn phase. Density functional theory calculations showed that the stability of the Sn phases is highly dependent on lattice strain, with $\alpha$-Sn being more stable under tensile strain and $\beta$-Sn becoming favorable under compressive strain, which is in good agreement with experimental observations. Hence, this study sheds light on controlling Sn phases through lattice engineering, enabling innovative applications in quantum technologies and beyond.

cond-mat.mtrl-sci↗

arXiv2024

Exploring interlayer coupling in the twisted bilayer PtTe$_{2}$

We have investigated interlayer interactions in the bilayer PtTe$_{2}$ system, which influence the electronic energy bands near the Fermi levels. Our diffusion Monte Carlo (DMC) calculations for the high-symmetry bilayer stackings (AA, AB, AC) manifest distinct interlayer binding characteristics among the stacking modes by revealing significantly different interlayer separations depending on the stackings, which is critical to understanding the interlayer coupling of the twisted bilayers consisting of various local stacking arrangements. Furthermore, a comparison between the interlayer separations obtained from DMC and density functional theory (DFT) shows that meta-GGA-based vdW-DFT results agree with DMC for different layer stackings, including twisted bilayers, but only the ground-state AA stacking matches well with GGA-based DFT predictions. This underscores the importance of accurate exchange-correlation potentials even for capturing the stacking-dependent interlayer binding properties. We further show that the variability in DFT-predicted interlayer separations is responsible for the large discrepancy of band structures in the 21.79$^{\circ}$-twisted bilayer PtTe$_{2}$, affecting its classification as metallic or semiconducting. These results demonstrate the importance of obtaining a correct description of stacking-dependent interlayer coupling in modeling delicate bilayer systems at finite twists.

cond-mat.mtrl-sci↗

arXiv2024

Distance-Dependent Evolution of Electronic States in Kagome- Honeycomb Lateral Heterostructures in FeSn

In this work, we demonstrate the formation and electronic influence of lateral heterointerfaces in FeSn containing Kagome and honeycomb layers. Lateral heterostructures offer spatially resolved property control, enabling the integration of dissimilar materials and promoting phenomena not typically observed in vertical heterostructures. Using the molecular beam epitaxy technique, we achieve a controllable synthesis of lateral heterostructures in the Kagome metal FeSn. With scanning tunneling microscopy/spectroscopy in conjunction with first-principles calculations, we provide a comprehensive understanding of the bonding motif connecting the Fe3Sn-terminated Kagome and Sn2-terminated honeycomb surfaces. More importantly, we reveal a distance-dependent evolution of the electronic states in the vicinity of the heterointerfaces. This evolution is significantly influenced by the orbital character of the flat bands. Our findings suggest an approach to modulate the electronic properties of the Kagome lattice, which should be beneficial for the development of future quantum devices.

cond-mat.str-el↗

arXiv2024

The influence of Structural Dynamics in Two-Dimensional Hybrid Organic-Inorganic Perovskites on their Photoluminescence Efficiency -- Neutron scattering analysis

Two-dimensional hybrid organic-inorganic perovskites (HOIPs) have emerged as promising materials for light-emitting diode applications. In this study, by using time-of-flight neutron spectroscopy we identified and quantitatively separated the lattice vibrational and molecular rotational dynamics of two perovskites, butylammonium lead iodide (BA)$_{2}$PbI$_{4}$ and phenethyl-ammonium lead iodide (PEA)$_{2}$PbI$_{4}$. By examining the corresponding temperature dependence, we found that the lattice vibrations, as evidenced by neutron spectra, are consistent with the lattice dynamics obtained from Raman scattering. We revealed that the rotational dynamics of organic molecules in these materials tend to suppress their photoluminescence quantum yield (PLQY) while the vibrational dynamics did not show predominant correlations with the same. Additionally, we observed photoluminescence emission peak splitting for both systems, which becomes prominent above certain critical temperatures where the suppression of PLQY begins. This study suggests that the rotational motions of polarized molecules may lead to a reduction in exciton binding energy or the breaking of degeneracy in exciton binding energy levels, enhancing non-radiative recombination rates, and consequently reducing photoluminescence yield. These findings offer a deeper understanding of fundamental interactions in 2D HOIPs and could guide the design of more efficient light-emitting materials for advanced technological applications.

cond-mat.mtrl-sci↗

arXiv2023

Theoretical investigation of delafossite-Cu2ZnSnO4 as a promising photovoltaic absorber

In the quest for efficient and cost-effective photovoltaic absorber materials beyond silicon, considerable attention has been directed toward exploring alternatives. One such material, zincblende-derived Cu2ZnSnS4 (CZTS), has shown promise due to its ideal band-gap size and high absorption coefficient. However, challenges such as structural defects and secondary phase formation have hindered its development. In this study, we examine the potential of another compound Cu2ZnSnO4 (CZTO) with a similar composition to CZTS as a promising alternative. Employing ab initio density function theory (DFT) calculations in combination with an evolutionary structure prediction algorithm, we identify that the crystalline phase of the delafossite structure is the most stable among the 900 (meta)stable CZTO. Its thermodynamic stability at room temperature is also confirmed by the molecular dynamics study. Excitingly, this new phase of CZTO displays a direct band gap where the dipole-allowed transition occurs, making it a strong candidate for efficient light absorption. Furthermore, the estimation of spectroscopic limited maximum efficiency (SLME) directly demonstrates the high potential of delafossite-CZTO as a photovoltaic absorber. Our numerical results suggest that delafossite-CZTO holds another promise for future photovoltaic applications.

cond-mat.mtrl-sci↗

arXiv2023

Over 30,000-fold field enhancement of terahertz nanoresonators enabled by rapid inverse design

The rapid development of 6G communications using terahertz (THz) electromagnetic waves has created a demand for highly sensitive THz nanoresonators capable of detecting these waves. Among the potential candidates, THz nanogap loop arrays show promising characteristics but require significant computational resources for accurate simulation. This requirement arises because their unit cells are 10 times smaller than millimeter wavelengths, with nanogap regions that are 1,000,000 times smaller. To address this challenge, we propose a rapid inverse design method using physics-informed machine learning, employing double deep Q-learning with an analytical model of the THz nanogap loop array. In about 39 hours on a middle-level personal computer, our approach identifies the optimal structure through 200,000 iterations, achieving experimental electric field enhancement of 32,000 at 0.2 THz, 300 % stronger than prior results. Our analytical model-based approach significantly reduces computational resources, offering a practical alternative to numerical simulation-based inverse design

physics.optics↗

arXiv2023

Doping transition-metal atoms in graphene for atomic-scale tailoring of electronic, magnetic, and quantum topological properties

Atomic-scale fabrication is an outstanding challenge and overarching goal for the nanoscience community. The practical implementation of moving and fixing atoms to a structure is non-trivial considering that one must spatially address the positioning of single atoms, provide a stabilizing scaffold to hold structures in place, and understand the details of their chemical bonding. Free-standing graphene offers a simplified platform for the development of atomic-scale fabrication and the focused electron beam in a scanning transmission electron microscope can be used to locally induce defects and sculpt the graphene. In this scenario, the graphene forms the stabilizing scaffold and the experimental question is whether a range of dopant atoms can be attached and incorporated into the lattice using a single technique and, from a theoretical perspective, we would like to know which dopants will create technologically interesting properties. Here, we demonstrate that the electron beam can be used to selectively and precisely insert a variety of transition metal atoms into graphene with highly localized control over the doping locations. We use first-principles density functional theory calculations with direct observation of the created structures to reveal the energetics of incorporating metal atoms into graphene and their magnetic, electronic, and quantum topological properties.

cond-mat.mtrl-sci↗

arXiv2023

The role of temperature on defect diffusion and nanoscale patterning in graphene

Graphene is of great scientific interest due to a variety of unique properties such as ballistic transport, spin selectivity, the quantum hall effect, and other quantum properties. Nanopatterning and atomic scale modifications of graphene are expected to enable further control over its intrinsic properties, providing ways to tune the electronic properties through geometric and strain effects, introduce edge states and other local or extended topological defects, and sculpt circuit paths. The focused beam of a scanning transmission electron microscope (STEM) can be used to remove atoms, enabling milling, doping, and deposition. Utilization of a STEM as an atomic scale fabrication platform is increasing; however, a detailed understanding of beam-induced processes and the subsequent cascade of aftereffects is lacking. Here, we examine the electron beam effects on atomically clean graphene at a variety of temperatures ranging from 400 to 1000 C. We find that temperature plays a significant role in the milling rate and moderates competing processes of carbon adatom coalescence, graphene healing, and the diffusion (and recombination) of defects. The results of this work can be applied to a wider range of 2D materials and introduce better understanding of defect evolution in graphite and other bulk layered materials.

cond-mat.mes-hall↗

arXiv2023

Doping of Cr in Graphene Using Electron Beam Manipulation for Functional Defect Engineering

Chromium atoms in graphene have been proposed to exhibit magnetic moments and spin-selective conducting states depending on the local bonding geometry within the graphene structure, which could lead to interesting applications in spintronics. Despite this interest, there are few direct experimental reports of Cr dopants in graphene even though it is theorized to be stable. Here, we demonstrate the introduction of single Cr dopant atoms into the graphene lattice and onto graphene edges through the controlled use of a focused electron beam in a scanning transmission electron microscope. We show local control of doping locations and when coupled with targeted in situ milling during scanning of the e-beam, these strategies demonstrate an important component of the fabrication of tailored nanostructured devices in the electron microscope. The approach is validated with first principles calculations to understand synthesis pathways during fabrication and reveal the energetics and local properties of Cr atoms embedded in graphene; e.g., Cr doping can convert graphene into a magnetic and semiconducting material, which suggests Cr-doped graphene can be used as a building block for potential electronic devices and a means to construct them.

cond-mat.mtrl-sci↗