Seung-Cheol Lee

Role of Oxygen during Methane Oxidation on Pd $_{1}$ /PdO $_{1}$ @CeO $_{2}$ Surface: A Combined Density Functional Theory, Microkinetic, and Machine Learning Approach

Shalini Tomar, Hojin Jeong, Joon Hwan Choi +2

This work explores the role of oxygen in industrial methane oxidation. Oxygen, a well-known oxidizing agent, drives CH $_{4}$ conversion to CO $_{2}$ and H $_{2}$ O. We report how oxygen inf…

Mechanistic Insights into Complete Methane Oxidation on Single-Atom Pd Supported by SSZ-13 Zeolite: A First-Principles Study

Anuroopa Behatha, Shalini Tomar, Hojin Jeong +3

Complete catalytic oxidation of methane is an effective strategy for greenhouse gas mitigation and clean energy conversion; yet, ensuring both high catalytic activity and stability…

Quantum Simulations of Battery Electrolytes with VQE-qEOM and SQD: Active-Space Design, Dissociation, and Excited States of LiPF $_{6}$ , NaPF $_{6}$ , and FSI Salts

Sk Mujaffar Hossain, Seung-Cheol Lee, Satadeep Bhattacharjee

Accurate prediction of excited states in battery electrolytes is central to understanding photostability, oxidative stability, and degradation. We employ hybrid quantum-classical a…

Testing the spin-bath view of self-attention: A Hamiltonian analysis of GPT-2 Transformer

Satadeep Bhattacharjee, Seung-Cheol Lee

The recently proposed physics-based framework by Huo and Johnson~\cite{huo2024capturing} models the attention mechanism of Large Language Models (LLMs) as an interacting two-body s…

Tunable Thermal Expansion in Functionalized 2D Boron Nitride: A First-Principles Investigation

Sk Mujaffar Hossain, Dobin Kim, Jaehyun Park +2

This study investigates the thermal expansion coefficient of two-dimensional (2D) functionalized boron nitride (f-BN) materials using first-principles density functional theory (DF…

Multi-site mixing and entropy stabilization of CsPbI $_{3}$ with potential application in photovoltaics

Namitha Anna Koshi, Krishnamohan Thekkepat, Doh-Kwon Lee +2

Metal halide perovskite solar cells have achieved dramatic improvements in their power conversion efficiency in the recent past. Since compositional engineering plays an important…

Integrating Density Functional Theory with Deep Neural Networks for Accurate Voltage Prediction in Alkali-Metal-Ion Battery Materials

Sk Mujaffar Hossain, Namitha Anna Koshi, Seung-Cheol Lee +2

Accurate prediction of the voltage of battery materials plays a pivotal role in the advancement of energy storage technologies and the rational design of high-performance cathode m…

Local Symmetry Breaking in Skyrmion-Hosting Centrosymmetric Hexagonal Compounds

Anupam K. Singh, Krishna K. Dubey, Parul Devi +10

Dzyaloshinskii-Moriya interaction (DMI) plays a crucial role in stabilizing the exotic topologically stable skyrmion spin textures in the noncentrosymmetric crystals. The recent di…

Enhancement of spin Hall angle by an order of magnitude via Cu intercalation in MoS $_{2}$ /CoFeB heterostructures

Abhisek Mishra, Pritam Das, Rupalipriyadarsini Chhatoi +7

Transition metal dichalcogenides (TMDs) are a novel class of quantum materials with significant potential in spintronics, optoelectronics, valleytronics, and opto-valleytronics. TM…

Origin of unexpected weak Gilbert damping in the LSMO/Pt bilayer system

Pritam Das, Pushpendra Gupta, Seung-Cheol Lee +2

This study presents a first-principles and semiclassical analysis of the puzzling observation that a La $_{0.7}$ Sr $_{0.3}$ MnO $_{3}$ (LSMO) thin film exhibits larger Gilbert damping th…

Magnetization dynamics in skyrmions due to high-speed carrier injections from Dirac half-metals

Satadeep Bhattacharjee, Seung-Cheol Lee

Recent developments in the magnetization dynamics in spin textures, particularly skyrmions, offer promising new directions for magnetic storage technologies and spintronics. Skyrmi…

Controlling Moisture for Enhanced Ozone Decomposition: A Study of Water Effects on CeO $_{2}$ Surfaces and Catalytic Activity

Suchitra Gupta, Joon Hwan Choi, Hojin Jeong +2

This study investigates the catalytic degradation of ground-level ozone on low-index stoichiometric and reduced CeO $_{2}$ surfaces using first-principles calculations. The presence o…

cond-mat.mtrl-sci2024★ 1 cited

Tuning the Electronic and Magnetic Properties of Double Transition Metal MCrCT $_{2}$ (M = Ti, Mo) Janus MXenes for Enhanced Spintronics and Nanoelectronics

Swetarekha Ram, Namitha Anna Koshi, Seung-Cheol Lee +1

Janus MXenes, a new category of two-dimensional (2D) materials, shows promising potential for advances in optoelectronics, spintronics and nanoelectronics. Our theoretical investig…

A Hybrid Machine Learning Framework for Predicting Hydrogen Storage Capacities in Metal Hydrides: Unsupervised Feature Learning with Deep Neural Networks

Satadeep Bhattacharjee, Pritam Das, Swetarekha Ram +1

In this study, we present a sophisticated hybrid machine-learning framework that significantly improves the accuracy of predicting hydrogen storage capacities in metal hydrides. Th…

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

Robin Bajaj, Seung-Cheol Lee, H. R. Krishnamurthy +2

Magnetization dynamics in magnetic materials are well described by the modified semiclassical Landau-Lifshitz-Gilbert (LLG) equation, which includes the magnetic damping $α$ and th…

Customizing PBE Exchange-Correlation functionals: A comprehensive approach for band gap prediction in diverse semiconductors

Satadeep Bhattacharjee, Namitha Anna Koshi, Seung-Cheol Lee

Accurate band gap prediction in semiconductors is crucial for materials science and semiconductor technology advancements. This paper extends the Perdew-Burke-Ernzerhof (PBE) funct…

cond-mat.mtrl-sci2023★ 9 cited

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

Satadeep Bhattacharjee, Swetarekha Ram, Seung-Cheol Lee

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 Red…

CrysMMNet: Multimodal Representation for Crystal Property Prediction

Kishalay Das, Pawan Goyal, Seung-Cheol Lee +2

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 modal…

Combining first-principles modeling and symbolic regression for designing efficient single-atom catalysts in Oxygen Evolution Reaction on Mo $_{2}$ CO $_{2}$ MXenes

Swetarekha Ram, Gwan Hyun Choi, Albert S. Lee +2

In this study, we address the significant challenge of overcoming limitations in catalytic efficiency for the oxygen evolution reaction (OER). The current linear scaling relationsh…