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Seung-Cheol Lee

Publications and source records attributed to Seung-Cheol Lee.

At least 37 records · Page 2Linked to original sources

Calculation of Gilbert damping and magnetic moment of inertia using torque-torque correlation model within ab initio Wannier framework

Magnetization dynamics in magnetic materials are well described by the modified semiclassical Landau-Lifshitz-Gilbert (LLG) equation, which includes the magnetic damping $α$ and the magnetic moment of inertia $\mathrm{I}$ tensors as key parameters. Both parameters are material-specific and physically represent the time scales of damping of precession and nutation in magnetization dynamics. $α$ and $\mathrm{I}$ can be calculated quantum mechanically within the framework of the torque-torque correlation model. The quantities required for the calculation are torque matrix elements, the real and imaginary parts of the Green's function and its derivatives. Here, we calculate these parameters for the elemental magnets such as Fe, Co and Ni in an ab initio framework using density functional theory and Wannier functions. We also propose a method to calculate the torque matrix elements within the Wannier framework. We demonstrate the effectiveness of the method by comparing it with the experiments and the previous ab initio and empirical studies and show its potential to improve our understanding of spin dynamics and to facilitate the design of spintronic devices.

cond-mat.mtrl-sci↗

Magneto-transport in the monolayer MoS2 material system for high-performance field-effect transistor applications

Electronic transport in monolayer MoS2 is significantly constrained by several extrinsic factors despite showing good prospects as a transistor channel material. Our paper aims to unveil the underlying mechanisms of the electrical and magneto-transport in monolayer MoS2. In order to quantitatively interpret the magneto-transport behavior of monolayer MoS2 on different substrate materials, identify the underlying bottlenecks, and provide guidelines for subsequent improvements, we present a deep analysis of the magneto-transport properties in the diffusive limit. Our calculations are performed on suspended monolayer MoS2 and MoS2 on different substrate materials taking into account remote impurity and the intrinsic and extrinsic phonon scattering mechanisms. We calculate the crucial transport parameters such as the Hall mobility, the conductivity tensor elements, the Hall factor, and the magnetoresistance over a wide range of temperatures, carrier concentrations, and magnetic fields. The Hall factor being a key quantity for calculating the carrier concentration and drift mobility, we show that for suspended monolayer MoS2 at room temperature, the Hall factor value is around 1.43 for magnetic fields ranging from 0.001 to 1 Tesla, which deviates significantly from the usual value of unity. In contrast, the Hall factor for various substrates approaches the ideal value of unity and remains stable in response to the magnetic field and temperature. We also show that the MoS2 over an Al2O3 substrate is a good choice for the Hall effect detector. Moreover, the magnetoresistance increases with an increase in magnetic field strength for smaller magnetic fields before reaching saturation at higher magnetic fields. The presented theoretical model quantitatively captures the scaling of mobility and various magnetoresistance coefficients with temperature, carrier densities and magnetic fields.

cond-mat.mes-hall↗

Insights into Heterogeneous Catalysis on Surfaces with 3d Transition Metals: Spin-Dependent Chemisorption Models and Magnetic Field Effects

This article provides a review of recent developments in the field of 3d transition metal (TM) catalysts for different reactions including oxygen-based reactions such as Oxygen Reduction Reaction (ORR) and Oxygen Evolution Reaction (OER). The spin moments of 3d TMs can be exploited to influence chemical reactions, and recent advances in this area, including the theory of chemisorption based on spin-dependent d-band centers and magnetic field effects, are discussed. The article also explores the use of scaling relationships and surface magnetic moments in catalyst design, as well as the effect of magnetism on chemisorption and vice versa. In addition, recent studies on the influence of a magnetic field on the ORR and OER are presented, demonstrating the potential of ferromagnetic catalysts to enhance these reactions through spin polarization.

cond-mat.mtrl-sci↗

Chemical bonding in large systems using projected population analysis from real-space density functional theory calculations

We present an efficient and scalable computational approach for conducting projected population analysis from real-space finite-element (FE) based Kohn-Sham density functional theory calculations (DFT-FE). This work provides an important direction towards extracting chemical bonding information from large-scale DFT calculations on materials systems involving thousands of atoms while accommodating periodic, semi-periodic or fully non-periodic boundary conditions. Towards this, we derive the relevant mathematical expressions and develop efficient numerical implementation procedures that are scalable on multi-node CPU architectures to compute the projected overlap and Hamilton populations. The population analysis is accomplished by projecting either the self-consistently converged FE discretized Kohn-Sham orbitals, or the FE discretized Hamiltonian onto a subspace spanned by a localized atom-centred basis set. The proposed methods are implemented in a unified framework within DFT-FE code where the ground-state DFT calculations and the population analysis are performed on the same FE grid. We further benchmark the accuracy and performance of this approach on representative material systems involving periodic and non-periodic DFT calculations with LOBSTER, a widely used projected population analysis code. Finally, we discuss a case study demonstrating the advantages of our scalable approach to extract the quantitative chemical bonding information of hydrogen chemisorbed in large silicon nanoparticles alloyed with carbon, a candidate material for hydrogen storage.

physics.comp-ph↗

CrysMMNet: Multimodal Representation for Crystal Property Prediction

Machine Learning models have emerged as a powerful tool for fast and accurate prediction of different crystalline properties. Exiting state-of-the-art models rely on a single modality of crystal data i.e. crystal graph structure, where they construct multi-graph by establishing edges between nearby atoms in 3D space and apply GNN to learn materials representation. Thereby, they encode local chemical semantics around the atoms successfully but fail to capture important global periodic structural information like space group number, crystal symmetry, rotational information, etc, which influence different crystal properties. In this work, we leverage textual descriptions of materials to model global structural information into graph structure and learn a more robust and enriched representation of crystalline materials. To this effect, we first curate a textual dataset for crystalline material databases containing descriptions of each material. Further, we propose CrysMMNet, a simple multi-modal framework, which fuses both structural and textual representation together to generate a joint multimodal representation of crystalline materials. We conduct extensive experiments on two benchmark datasets across ten different properties to show that CrysMMNet outperforms existing state-of-the-art baseline methods with a good margin. We also observe that fusing the textual representation with crystal graph structure provides consistent improvement for all the SOTA GNN models compared to their own vanilla versions. We have shared the textual dataset, that we have curated for both the benchmark material databases, with the community for future use.

cond-mat.mtrl-sci↗

Combining first-principles modeling and symbolic regression for designing efficient single-atom catalysts in Oxygen Evolution Reaction on Mo$_2$CO$_2$ MXenes

In this study, we address the significant challenge of overcoming limitations in catalytic efficiency for the oxygen evolution reaction (OER). The current linear scaling relationships hinder the optimization of electrocatalytic performance. To tackle this issue, we investigate the potential of designing single-atom catalysts (SACs) on Mo$_2$CO$_2$ MXenes for electrochemical OER using first-principles modeling simulations. By employing the Electrochemical Step Symmetry Index (ESSI) method, we assess OER intermediates to fine-tune activity and identify the optimal SAC for Mo$_2$CO$_2$ MXenes. Our findings reveal that both Ag and Cu exhibit effectiveness as single atoms for enhancing OER activity on Mo$_2$CO$_2$ MXenes. However, among the 21 chosen transition metals (TMs) in this study, Cu stands out as the best catalyst for tweaking the overpotential ($η_{OER}$). This is due to Cu's lowest overpotential compared to other TMs, which makes it more favorable for OER performance. On the other hand, Ag is closely aligned with ESSI=$η_{OER}$, making the tuning of its overpotential more challenging. Furthermore, we employ symbolic regression analysis to identify the significant factors that exhibit a correlation with the OER overpotential. By utilizing this approach, we derive mathematical formulas for the overpotential and identify key descriptors that affect catalytic efficiency in electrochemical OER on Mo$_2$CO$_2$ MXenes. This comprehensive investigation not only sheds light on the potential of MXenes in advanced electrocatalytic processes but also highlights the prospect of improved activity and selectivity in OER applications.

cond-mat.mtrl-sci↗

Straintronics using the monolayer-Xene platform -- a comparative study

Monolayer silicene is a front runner in the 2D-Xene family, which also comprises germanene, stanene, and phosphorene, to name a few, due to its compatibility with current silicon fabrication technology. Here, we investigate the utility of 2D-Xenes for straintronics using the ab-initio density functional theory coupled with quantum transport based on the Landauer formalism. With a rigorous band structure analysis, we show the effect of strain on the K-point, and calculate the directional piezoresistances for the buckled Xenes as per their critical strain limit. Further, we compare the relevant gauge factors, and their sinusoidal dependences on the transport angle akin to silicene and graphene. The strain-insensitive transport angles corresponding to the zero gauge factors are 81 degree and 34 degree for armchair and zigzag strains, respectively, for silicene and germanene. For stanene as the strain limit is extended to 10% and notable changes in the fundamental parameters, the critical angle for stanene along armchair and zigzag directions are 69 degree and 34 degree respectively. The small values of gauge factors are attributed to their stable Dirac cones and strain-independent valley degeneracies. We also explore conductance modulation, which is quantized in nature and exhibits a similar pattern with other transport parameters against a change in strain. Based on the obtained results, we propose the buckled Xenes as an interconnect in flexible electronics and are promising candidates for various applications in straintronics.

cond-mat.mes-hall↗

Spin torques and anomalous velocity in spin textures induced by fast electron injection from topological ferromagnets: The role of gauge fields

A new method for analysing magnetization dynamics in spin textures under the influence of fast electron injection from topological ferromagnetic sources such as Dirac half metals has been proposed. These electrons, traveling at a velocity $v$ with a non-negligible value of $v/c$ (where c is the speed of light), generate a non-equilibrium magnetization density in the spin-texture region, which is related to an electric dipole moment via relativistic interactions. When this resulting dipole moment interacts with gauge fields in the spin-texture region, an effective field is created that produces spin torques. These torques, like spin-orbit torques that occur when electrons are injected from a heavy metal into a ferromagnet, can display both damping-like and anti-damping-like properties. Finally, we demonstrate that such an interaction between the dipole moment and the gauge field introduces an anomalous velocity that can contribute to transverse electrical conductivity in the spin texture in a way comparable to the topological Hall effect.

cond-mat.mes-hall↗

High-frequency complex impedance analysis of the two-dimensional semiconducting MXene-$Ti_2CO_2$

The two-dimensional compound group of MXenes, which exhibit unique optical, electrical, chemical, and mechanical properties, are an exceptional class of transition metal carbides and nitrides. In addition to traditional applications in Li-S, Li-ion batteries, conductive electrodes, hydrogen storage, and fuel cells, the low lattice thermal conductivity coupled with high electron mobility in the semiconducting oxygen-functionalized MXene-$Ti_2CO_2$ has led to the recent interests in high-performance thermoelectric and nanoelectronic devices. Apart from the above dc-transport applications, it is crucial to also understand ac-transport across them, given the growing interest in applications surrounding wireless communications and transparent conductors. In this work, we investigate using our recently developed $ab~initio$ transport model, the real and imaginary components of electron mobility and conductivity to conclusively depict carrier transport beyond the room temperature for frequency ranges upto the terahertz range. We also contrast the carrier mobility and conductivity with respect to the Drude's model to depict its inaccuracies for a meaningful comparison with experiments. Our calculations show the effect of acoustic deformation potential scattering, piezoelectric scattering, and polar optical phonon scattering mechanisms. Without relying on experimental data, our model requires inputs calculated from first principles using density functional theory. Our results set the stage for providing ab-initio based ac-transport calculations given the current research on MXenes for high frequency applications.

cond-mat.mtrl-sci↗

CrysGNN : Distilling pre-trained knowledge to enhance property prediction for crystalline materials

In recent years, graph neural network (GNN) based approaches have emerged as a powerful technique to encode complex topological structure of crystal materials in an enriched representation space. These models are often supervised in nature and using the property-specific training data, learn relationship between crystal structure and different properties like formation energy, bandgap, bulk modulus, etc. Most of these methods require a huge amount of property-tagged data to train the system which may not be available for different properties. However, there is an availability of a huge amount of crystal data with its chemical composition and structural bonds. To leverage these untapped data, this paper presents CrysGNN, a new pre-trained GNN framework for crystalline materials, which captures both node and graph level structural information of crystal graphs using a huge amount of unlabelled material data. Further, we extract distilled knowledge from CrysGNN and inject into different state of the art property predictors to enhance their property prediction accuracy. We conduct extensive experiments to show that with distilled knowledge from the pre-trained model, all the SOTA algorithms are able to outperform their own vanilla version with good margins. We also observe that the distillation process provides a significant improvement over the conventional approach of finetuning the pre-trained model. We have released the pre-trained model along with the large dataset of 800K crystal graph which we carefully curated; so that the pretrained model can be plugged into any existing and upcoming models to enhance their prediction accuracy.

cs.LG↗

Computational design of novel MAX phase alloys for potential hydrogen storage media combining first principles and cluster expansion methods

Finding a suitable material for hydrogen storage at ambient atmospheric conditions is challenging for material scientists and chemists. In this work, using a first principles based cluster expansion approach, the hydrogen storage capacity of Ti2AC (A = Al,Ti, Cr, Mn, Fe, Co, Ni, Cu, and Zn) MAX phase and its alloys were studied. We found that hydrogen is energetically stable in Ti-A layers in which the tetrahedral site consisting of one A atom and three Ti atoms is energetically more favorable for hydrogen adsorption than other sites in the Ti-A layer. Ti2CuC has the highest hydrogen adsorption energy than other Ti2AC phases. We find that 83.33% Cu doped Ti2AlxCu1-xC alloy structure is both energetically and dynamically stable and can store 3.66 wt% hydrogen at ambient atmospheric conditions, which is higher than both Ti2AlC and Ti2CuC phase. These findings indicate that the hydrogen capacity of the MAX phase can be significantly improved by doping an appropriate atom species.

cond-mat.mtrl-sci↗

Can magneto-transport properties provide insight into the functional groups in semiconducting MXenes?

The Hall scattering factor of Sc2CF2, Sc2CO2 and Sc2C(OH)2 is calculated using Rode's iterative approach by solving the Boltzmann transport equation. This is carried out in conjunction with calculations based on density functional theory. The electrical transport in Sc2CF2, Sc2CO2, and Sc2C(OH)2 is modelled by accounting for both elastic (acoustic and piezoelectric) and inelastic (polar optical phonon) scattering. Polar optical phonon (POP) scattering is the most significant mechanism in these MXenes. We observe that there is a window of carrier concentration where Hall factor acts dramatically; Sc2CF2 obtains an incredible high value of 2.49 while Sc2CO2 achieves a very small value of approximately 0.5, and Sc2C(OH)2 achieves the so called ideal value of 1. We propose in this paper that such Hall factor behaviour has significant promise in the field of surface group identification in MXenes, an issue that has long baffled researchers.

cond-mat.mtrl-sci↗

Anti-site disorder and Berry curvature driven anomalous Hall effect in spin gapless semiconducting Mn2CoAl Heusler compound

Spin gapless semiconductors exhibit a finite band gap for one spin channel and closed gap for other spin channel, emerged as a new state of magnetic materials with a great potential for spintronic applications. The first experimental evidence for the spin gapless semiconducting behavior was observed in an inverse Heusler compound Mn2CoAl. Here, we report a detailed investigation of the crystal structure and anomalous Hall effect in the Mn2CoAl using experimental and theoretical studies. The analysis of the high-resolution synchrotron x-ray diffraction data shows anti-site disorder between Mn and Al atoms within the inverse Heusler structure. The temperature-dependent resistivity shows semiconducting behavior and follows Mooijs criteria for disordered metal. Scaling behavior of the anomalous Hall resistivity suggests that the anomalous Hall effect in the Mn2CoAl is primarily governed by intrinsic mechanism due to the Berry curvature in momentum space. The experimental intrinsic anomalous Hall conductivity (AHC) is found to be 35 S/cm, which is considerably larger than the theoretically predicted value for ordered Mn2CoAl. Our first-principle calculations conclude that the anti-site disorder between Mn and Al atoms enhances the Berry curvature and hence the value of intrinsic AHC, which is in a very well agreement with the experiment.

cond-mat.mtrl-sci↗

A general rule for predicting the magnetic moment of Cobalt-based Heusler compounds using compressed sensing and density functional theory

We propose a general rule for estimating the magnetic moments of Co$ 2$(cobalt)-based Heusler alloys, especially when doped with late transition metals. We come up with a descriptor that can characterise both pure Co$_2$YZ compounds and the doped ones with the chemical formula Co$_2$Y$_{1-x}$M$_x$Z (M is the dopant) using online data for magnetic moments of Heusler alloys with Co$_2$YZ structure and compressive sensing approach. The newly proposed descriptor not only depends on the number of valence electrons of the compound also it depends on the number of unoccupied d-electrons in the doping site. A comparison of the performance of the proposed descriptor and the Slater-Pauling rule is made. Unlike the Slater-Pauling rule, which is only effective for half-metallic Heusler compounds, our machine-learning approach is more generic since it applies to any Co$_2$YZ Heusler compounds, regardless of whether they are half-metals or not. We use this new rule to estimate the magnetic moments of a few yet-to-be-discovered Heusler compounds and compare the results to density functional theory (DFT) based calculations. Finally, we use DFT and machine learning investigations to prove their stability.

cond-mat.mtrl-sci↗

A new palladium alloy with near-ideal hydrogen storage performance

Hydrogen-based fuels demand high-density storage that can operate under ambient temperatures. Pd and its alloys are the most investigated metal hydrides for hydrogen fuel cell applications. This study presented an alternative Pd alloy for hydrogen storage that can store and release hydrogen at room temperature. The surface of the most studied Pd (110) was modified with Au and Rh so that the hydrogen adsorption energy was 0.49 eV and the release temperature was 365 K. Both values are quite near to the optimum values for the adsorption energy and release temperature of a hydrogen fuel cell in real-world usage.

cond-mat.mtrl-sci↗

Surface-oxygen-passivation driven large anomalous Hall conductivity (AHC) in nitride MXenes: Can AHC be a tool to determine functional groups in 2D ferro(i)magnets?

Identifying the existence of specific functional groups in MXenes is a difficult topic that has perplexed researchers for a long time. We show in this paper that in the case of magnetic MXenes, the magneto-transport properties of the material provide an easy solution. One of the fascinating properties that MXenes offer is the realization of intrinsic ferromagnetism which is important for two-dimensional (2D) materials family. The previous reports have only made a few statements on some MXenes citing its usefulness for spintronics related applications. Here, using first-principle calculations we have examined the actual magneto-transport phenomena in MXenes family. We have considered all possible combinations of 3\textit{d} transition metals ($Ti, V, Cr$ and $Mn$) and nitride based functionalized $(O_2, F_2$ and $(OH)_2$) MXenes, $M_2NT_2$. The intrinsic anomalous Hall effect is investigated in $Cr$ and $Mn$ based MXenes as the compounds possess ground state stable ferromagnetic solutions. We demonstrate that intrinsic Anomalous Hall conductivity (AHC) can be used to identify the functional groups in MXenes. Additionally, half-metallic features of these ferromagnetic MXenes make them potential candidates for varieties of applications such as in logic and memory devices, quantum computations, spintronics etc. The maximum anomalous Hall conductivity (AHC) at Fermi energy, $E_F$, is found in case of $Mn_2NO_2$ (470 $S/cm$) which is attributed to the presence of avoided band crossing and larger density of states. Together, when considered all the studied systems, the AHC can be above 2500 $S/cm$ within $E_F \pm $ 0.25 $eV$. Our findings could be useful not only in guiding the experimentalists by considering AHC as a simple tool in determining the functional groups in 2D ferro(i)magnets, also, it could be useful in designing memory device with negligible stray fields.

cond-mat.mtrl-sci↗

Electrical and magneto transport in 2D semiconducting MXene Ti2CO2

The Hall scattering factor is formulated using Rode's iterative approach to solving the Boltzmann transport equation in such a way that it may be easily computed within the scope of ab-inito calculations. Using this method in conjunction with density functional theory based calculations, we demonstrate that the Hall scattering factor in electron-doped Ti2CO2 varies greatly with temperature and concentration, ranging from 0.2 to around 1.3 for weak magnetic fields. The electrical transport was modelled primarily using three scattering mechanisms: piezoelectric scattering, acoustic scattering, and polar optical phonons. Even though the mobility in this material is primarily limited by acoustic phonons, piezoelectric scattering also plays an important role which was not highlighted earlier.

cond-mat.mtrl-sci↗

Pressure induced isostructural phase transition in biskyrmion host hexagonal MnNiGa

Magnetic skyrmions are vortex-like spin textures, which can be manipulated by external stress or pressure via magnetoelastic effects. Here, we present the observation of isostructural phase transition in a biskyrmion host hexagonal MnNiGa at a pressure around 4 GPa using pressure-dependent synchrotron x-ray powder diffraction (XRD) data analysis. Our XRD data reveals anisotropic compression behavior with pressure with different compression rates of the a-axis in the basal plane and the c-axis in the prismatic plane. However, the hexagonal symmetry remains unchanged for pressure up to 14 GPa. Fitting of unit cell volume with pressure using a second-order Birch-Murnagan equation of state reveals that the data to fall into two distinct curves for those above and below 4 GPa. The present study contributes to the understanding of crystal structure with the application of hydrostatic pressure in the biskyrmion host MnNiGa, wherein the skyrmion textures can be manipulated by pressure due to their magnetoelastic character.

cond-mat.mtrl-sci↗