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Dameul Jeong

Publications and source records attributed to Dameul Jeong.

4 recordsLinked to original sources

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

Magnetic and Crystal Symmetry Effects on Spin Hall Conductivity in Altermagnets

Altermagnets, which reconcile zero net magnetization with pronounced spin splitting, offer fresh opportunities for spin-based functionalities in next-generation electronic and spintronic devices. In this paper, we explore the unconventional spin Hall conductivity (USHC) in three prototypical altermagnets -- RuO$_2$, CrSb, and MnTe -- and elucidate how distinct magnetic and crystal symmetries modulate their spin Hall responses. RuO$_2$ exhibits only trivial USHC contributions under a tilted geometry, demonstrating that symmetry projections alone can induce apparent unconventional elements. In contrast, CrSb and MnTe manifest robust, symmetry-driven USHC without structural tilts, enabled by easy-axis orientations that reduce magnetic symmetry. Through extensive first-principles calculations, we demonstrate the complementary roles of the time-reversal-even and time-reversal-odd components in determining the overall SHC. Our findings indicate that controlling the interplay between crystal and magnetic symmetry -- for instance, by epitaxial strain or doping -- can provide an experimental avenue to tune USHC magnitudes and directions in altermagnets. These results pave the way for the engineering of multifunctional spintronic devices, where enhanced coherence and robust spin transport are realized in zero-net-moment materials with easily tailored spin configurations.

cond-mat.mtrl-sci

Interfacial Magnetic Anisotropy of Iron-Adsorbed Ferroelectric Perovskites: First-Principles and Machine Learning Study

The advancement of spin-based devices as a replacement for CMOS technology demands lower spin-switching energy in ferromagnetic (FM) materials. Ferroelectric (FE) materials offer a promising avenue for influencing FM properties, yet the mechanisms driving this interplay remain inadequately understood. In this study, we investigate iron-adsorbed FE ABO$_3$ perovskites using a combination of first-principles calculations and machine learning. Our findings reveal a universal correlation between the magnetic anisotropy energy (MAE) of iron and the induced magnetic dipole moments within the BO$_2$ layer and basal oxygen atoms of ABO$_3$ at the FE/FM interface. By identifying key material descriptors and achieving high predictive accuracy, this research provides a robust framework for selecting and optimizing ABO$_3$ substrates for energy-efficient spintronic devices. These insights contribute to the rational design of novel low-power spin-based technologies.

cond-mat.mtrl-sci

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 Schrödinger 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