# Research Topics computational materials physics

**Research Area/ Research Interest: computational materials physics**

**Research Paper Topics for:** Masters and PhD Thesis and publication

- Computational materials discovery for lanthanide hydrides at high pressure for high temperature superconductivity
- Modeling and simulation of microstructure in metallic systems based on multi-physics approaches
- Flexible and interpretable generalization of self-evolving computational materials framework
- Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discovery
- Progress of Physics-based Mean-field Modeling and Simulation of Steel
- Representations of molecules and materials for interpolation of quantum-mechanical simulations via machine learning
- Delocalization of dark and bright excitons in flat-band materials and the optical properties of V2O5
- Ferroelectricity coexisted with p-orbital ferromagnetism and metallicity in two-dimensional metal oxynitrides
- A physics-informed machine learning method for predicting grain structure characteristics in directed energy deposition
- Discovering plasticity models without stress data
- Screening transition metal-based polar pentagonal monolayers with large piezoelectricity and shift current
- Unexpected thermal conductivity enhancement in aperiodic superlattices discovered using active machine learning
- Author Correction: Towards prediction of ordered phases in rechargeable battery chemistry via group–subgroup transformation
- Accelerated computation of lattice thermal conductivity using neural network interatomic potentials
- Two-dimensional Stiefel-Whitney insulators in liganded Xenes
- Author Correction: Valley-filling instability and critical magnetic field for interaction-enhanced Zeeman response in doped WSe2 monolayers
- The kinetics of static recovery by dislocation climb
- Deep learning based design of porous graphene for enhanced mechanical resilience
- Changing your tune on catalytic efficiency: Tuning Cr concentration in La0. 3Sr0. 7Fe1-xCrxO3-δ perovskite as a cathode in solid oxide electrolysis cell
- Identifying the mechanistic insights into PbSeO3 decomposition, during milling, to give way to PbSe: An experimental and theoretical approach
- Fracture toughness of single layer boronitrene sheet using MD simulations
- Co Anchored B36 Cluster as a Novel Single Atom Catalyst for Removing Toxic CO Molecules: A Mechanistic First‐Principles Study
- Bridging microscopy with molecular dynamics and quantum simulations: an atomAI based pipeline
- Multiscale investigation of magnetic field distortion on surface of ferromagnetic materials caused by stress concentration for metal magnetic memory method
- Electronic structure investigation of intrinsic and extrinsic defects in LiF
- A machine learning approach to map crystal orientation by optical microscopy
- Comparison of three state-of-the-art crystal plasticity based deformation twinning models for magnesium alloys
- Relativistic domain-wall dynamics in van der Waals antiferromagnet MnPS3
- Multiscale modeling of ultrafast melting phenomena
- Computational modelling of process–structure–property–performance relationships in metal additive manufacturing: a review
- Hierarchical multi-response Gaussian processes for uncertainty analysis with multi-scale composite manufacturing simulation
- Probing the displacement damage mechanism in Si, Ge, GaAs by defects evolution analysis
- Mechanism of the motion of nanovehicles on hexagonal boron-nitride: A molecular dynamics study
- Imaging atomic-scale chemistry from fused multi-modal electron microscopy
- Machine learning of superconducting critical temperature from Eliashberg theory
- Polycrystalline morphology and mechanical strength of nanotube fibers
- High-throughput generation of potential energy surfaces for solid interfaces
- Physics makes the difference: Bayesian optimization and active learning via augmented Gaussian process
- A review on the application of lattice Boltzmann method for melting and solidification problems
- Probing the structural evolution, electronic and vibrational properties of magnesium clusters doped with two lithium atoms
- Machine learned interatomic potentials using random features
- First-principles search of hot superconductivity in La-XH ternary hydrides
- Self-supervised optimization of random material microstructures in the small-data regime
- Machine learning and materials informatics approaches in the analysis of physical properties of carbon nanotubes: a review
- Machine learned interatomic potentials using random features
- Optimization of the elastic properties of block copolymers using coarse-grained simulation and an artificial neural network
- The effect of stress on the migration of He gas bubbles under a thermal gradient in Fe by phase-field modeling
- Intriguing magnetoelectric effect in two-dimensional ferromagnetic/perovskite oxide ferroelectric heterostructure
- Dimensionality effects in high‐performance thermoelectric materials: Computational and experimental progress in energy harvesting applications
- Materials physics from microscopy: statistical and machine learning methods for tackling inverse problems
- First principles study on organic cation A-site doping in CsPbI3 perovskite
- Full spectrum optical constant interface to the Materials Project
- Homogeneous nucleation of dislocations in copper: Theory and approximate description based on molecular dynamics and artificial neural networks
- Phase diagram of a distorted kagome antiferromagnet and application to Y-kapellasite
- The N-body interatomic potential for molecular dynamics simulations of diffusion in tungsten
- Structure-mechanical property relations of nanoporous two-dimensional gallium selenide
- Prediction of grain-size transition during solidification of hypoeutectic Al-Si alloys by an improved three-dimensional sharp-interface model
- gpaw-tools–higher-level user interaction scripts for GPAW calculations and interatomic potential based structure optimization
- Mechanism of keyhole pore formation in metal additive manufacturing
- Sensitivity of the electronic and topological properties of tetradymites upon atomic mutations
- First-principles study on controlling transport gap of graphene nanoribbons using hybrid Armchair–Zigzag nanostructures
- Dislocation emission and propagation under a nano-indenter in a model high entropy alloy
- Accurate Prediction of Voltage of Battery Electrode Materials Using Attention Based Graph Neural Networks
- Design of a graphical user interface for few-shot machine learning classification of electron microscopy data
- Amphoteric behavior of component and microstructure feature on CaO-Al2O3-TiO2 ternary melt by molecular dynamics simulation
- Machine Learning as a Tool for Specific Capacity Prediction of Prospective Potassium Battery Electrodes
- Constitutive behavior predictions of mushy zone during solidification by phase field model and coupled Eulerian–Lagrangian method
- Development of a physically-informed neural network interatomic potential for tantalum
- Applied stress anisotropy effect on melting of tungsten: molecular dynamics study
- Determination of representative volume element size for a magnetorheological elastomer
- Toward autonomous materials research: Recent progress and future challenges
- Effect of loading path on grain misorientation and geometrically necessary dislocation density in polycrystalline aluminum under reciprocating shear
- Numerical modeling of dendrite growth in a steady magnetic field using the two relaxation times lattice Boltzmann-phase field model
- Modeling of stoichiometric phases in off-eutectic compositions of directional solidifying NbSi-10Ti for phase-field simulations
- Machine learning predictions of superalloy microstructure
- Exchange interaction between the high spin Co3+ states in LaCoO3
- DIMS: A tool for setting up defects and impurities CASTEP calculations
- Supervised deep learning prediction of the formation enthalpy of complex phases using a DFT database: The σ− phase as an example
- Intrinsic disorder of dangling OH-bonds in the first water layer on noble metal surfaces
- Efficiency in identification of internal structure in simulated monoatomic clusters: Comparison between common neighbor analysis and coordination …
- Molecular dynamic characteristic temperatures for predicting metallic glass forming ability
- Reactive molecular dynamics simulations of nickel-based heterometallic catalysts for hydrogen evolution in an alkaline KOH solution
- Molecular dynamics simulation on spallation of [111] Cu/Ni nano-multilayers: Voids evolution under different shock pulse duration
- Development of a plasticity-oriented interatomic potential for CrFeMnNi high entropy alloys
- Structural stability of titanate pyrochlores undergoing radiation damage
- High-order one-dimensional (1D) fermion in ferromagnetic RbFeF3
- Developing atomistic glass models using potential-free Monte Carlo method: From simple to complex structures
- ESpinS: A program for classical Monte-Carlo simulations of spin systems
- How asymmetric chirality and chain density affect chain stiffness of polymer melts
- Continuum to rarefied diffusive tortuosity factors in porous media from X-ray microtomography
- Nicholas Metropolis Award for Outstanding Doctoral Thesis Work in Computational Physics (2022): Surface processes in ion-irradiated materials from first principles
- The emancipation of flexoelectricity
- Development and evaluation of granular simulation for integrating computational thinking into computational physics courses
- Deep learning for mapping element distribution of high-entropy alloys in scanning transmission electron microscopy images
- Data-driven quest for two-dimensional non-van der Waals materials
- Ab initio calculation of electron temperature dependent electron heat capacity and electron-phonon coupling factor of noble metals
- Shock-induced spallation in single-crystalline tantalum at elevated temperatures through molecular dynamics modeling
- A reverse design model for high-performance and low-cost magnesium alloys by machine learning
- TeaNet: Universal neural network interatomic potential inspired by iterative electronic relaxations
- Towards physical insights on microstructural damage nucleation from data analytics
- Database Development and Component Design with Two-Dimensional Trusslike Microstructures
- 18 A Review of Machine
- A multi-phase-field model of topological pattern formation during electrochemical dealloying of binary alloys
- Stacking fault energy and ductility in a new zirconium alloys: A combined experimental and first-principles study
- An Atomistic-to-Microscale Computational Analysis of the Dislocation Pileup-induced Local Stresses near an Interface in Plastically Deformed Two-phase Materials
- Encoding the atomic structure for machine learning in materials science
- Study on the structures and electronic properties of double-walled silicon nanotubes (4, min)@(8, mout) under external electric field by SCC-DFTB calculations
- A Micro-macro Coupling and Physics Informed Modeling Approach for Bearing Failure with X-Ray CT Characterization
- Pattern Recognition for the Electronic Phase of Bismuth Antimony Thin Films
- Machine learning study of the magnetic ordering in 2d materials
- Interatomic Fe–Cr potential for modeling kinetics on Fe surfaces
- Piezoelectric modulus prediction using machine learning and graph neural networks
- Materials Science and Molecular Modeling
- Strain and interface energy of ellipsoidal inclusions subjected to volumetric eigenstrains: shape factors
- Uncertainty bounds for multivariate machine learning predictions on high-strain brittle fracture
- Review of Theoretical and Computational Methods for 2D Materials Exhibiting Charge Density Waves
- Effect of Fiber Waviness on Processing and Performance of Textile Composites
- Materials Design using an Active Subspace Batch Bayesian Optimization Approach
- Disordered MgB2 superconductor critical temperature modeling through regression trees
- Structure and lattice thermal conductivity of grain boundaries in silicon by using machine learning potential and molecular dynamics
- Estimating the lower-limit of fracture toughness from ideal-strength calculations
- A physics-informed variational DeepONet for predicting crack path in quasi-brittle materials
- 2D materials bridging experiments and computations for electro/photocatalysis
- Crack propagation in quasi-brittle materials by fourth-order phase-field cohesive zone model
- Effect of Sb doping on microstructure, mechanical and electronic properties of Mg2Si in Mg2Si/AZ91 composites by experimental investigation and first-principles …
- A Review on DFT+ U Scheme for Structural, Electronic, Optical and Magnetic Properties of Copper Doped ZnO Wurtzite Structure
- Formula graph self-attention network for representation-domain independent materials discovery
- Machine learning interatomic potential for high throughput screening and optimization of high-entropy alloys
- Materials and Molecular Modelling at the Exascale
- Improved Optical and Electronic Properties of Single-Layer MoS2 by Co Doping for Promising Intermediate-Band Materials
- The structural evolution and superconductivity under pressure for superconductor AFe2As2 (A = Ba, Sr)
- Prediction of the electron density of states for crystalline compounds with Atomistic Line Graph Neural Networks (ALIGNN)
- List of Faculty
- DFT insights into the adsorption mechanism of five-membered aromatic heterocycles containing N, O, or S on Fe (110) surface
- Chalcogenide Perovskites: Tantalizing Prospects, Challenging Materials
- Information is everywhere
- Computational Discovery and Investigation of New Two Dimensional Ferroelectric Materials
- Computational wave solutions of some nonlinear evolution equations
- Multi-Scale Modeling for Texture and Grain Topology of Polycrystalline Microstructures under Uncertainty
- Machine learning-enabled band gap prediction of monolayer transition metal chalcogenide alloys
- Magnetism and perfect spin filtering in pristine MgCl 2 nanoribbons modulated by edge modification
- Computational analysis of transient XMCD sum rules for laser pumped systems: When do they fail?
- Physics-informed deep learning for data-driven solutions of computational fluid dynamics
- Intermolecular and Intramolecular Friedel‐Crafts Acylation of Carboxylic Acids using Binary Ionic Liquids: An Experimental and Computational Study
- Computational tool for learning electrostatic physics through the development of a disruptive methodology
- An efficient computational framework for generating realistic 3D mesoscale concrete models using micro X-ray computed tomography images and dynamic physics …
- Density-of-states similarity descriptor for unsupervised learning from materials data
- Twin boundary migration and reactions with stacking fault tetrahedron in Cu and CoCrCuFeNi high-entropy alloy
- Generative Design of Stable Semiconductor Materials Using Deep Learning And DFT
- Computational Study of Brønsted Acidity in the Metal-Organic Framework UiO-66
- Molecular Dynamic Simulation of Zigzag Silicon Carbide Nanoribbon
- Computational spectroscopy for point defects
- Computational Exploration of a Sulfonated Polybenzimidazole Membrane for 2, 3-Butanediol/Water Separation
- Molecular dynamic simulation of uniaxial tension deformation applied to α-Fe nanowire
- CateCom: a practical data-centric approach to categorization of computational models
- Vacancy formation energies and migration barriers in multi-principal element alloys
- Halide Perovskites: Advanced Photovoltaic Materials Empowered by a Unique Bonding Mechanism
- High-efficient low-cost characterization of materials properties using domain-knowledge-guided self-supervised learning
- Quantum Computational Particle Physics: Algorithms, Resource Estimation, and Model-Building
- Artificial Neural Network Potentials for Mechanics and Fracture Dynamics of Materials
- The role of thermal fluctuations and vibrational entropy for the delta-to-alpha transition in hybrid organic-inorganic perovskites: the FAPbI3 case
- Ceramic nuclear fuel performance and the role of atomic scale simulations
- Computational Investigation of Neutron Field modified with Various Materials
- Computational Perspective on Recent Advances in Quantum Electronics: From Electron Quantum Optics to Nanoelectronic Devices and Systems
- Computational investigations of thermoelectric properties of lead telluride, magnesium silicide, and magnesium stannide under high pressure and anisotropic stress
- Extending the Capability of Classical Quantum Many-Body Methods
- 3D Grain Shape Generation in Polycrystals Using Generative Adversarial Networks
- Computational study on the adsorption of arsenic pollutants on graphene-based single-atom iron adsorbents
- Computational Approaches to Defects and Doping in Non-Ideal Semiconductors
- Verification and validation of numerical models for the materials of the lumbar spine
- Strengthening magnesium by design: integrating alloying and dynamic processing
- Experimental and computational investigation of 3, 5-di-tert-butyl-2-(((3-((2-morpholinoethyl)(pyridin-2-ylmethyl) amino) propyl) imino) methyl) phenol and related …
- Low-dimensional heterostructures for advanced electrocatalysis: an experimental and computational perspective
- Orbital Hall effect in crystals: inter-atomic versus intra-atomic contributions
- Effect of nanoindentation rate on plastic deformation in Cu thin films
- Mechanical properties and deformation mechanisms of amorphous nanoporous silicon nitride membranes via combined atomistic simulations and experiments
- Surface Magnetism in Y Co2
- Onset of metallic transition in molecular liquid hydrogen
- Janus Ga2SeTe/In2SSe heterostructures: Tunable electronic, optical, and photocatalytic properties
- Multi-Scale Structural Analysis Enhanced By Machine Learning With Applications To 3D Printed Aerospace Structures
- A physically-based computational approach for processing-microstructure-property linkage of materials additively manufactured by laser powder bed fusion
- An analytical approach to evaluate effective coefficients of 1–3 piezoelectric composites
- Evaluation of Performance of Chlorinated Polyethylene Using Wireless Network and Artificial Intelligence Technology
- Impact of impurities and time on thermoelectric performance of MgAgSb
- High temperature superconductivity in the candidate phases of solid hydrogen
- In-Situ Calibrated Digital Process Twin Models for Resource Efficient Manufacturing
- Quasi-1D electronic transport and isotropic phonon transport in the Zintl Ca5In2Sb6
- Influence of impurities and degradation on carbon fiber and amorphous carbon thermal conductivity
- The role of impurities and degradation on the thermal conductivity of carbon fiber and amorphous carbon
- Molecular Dynamics Simulations of Structural Changes for a Molten Ag54Cu1 Cluster during Cooling
- Computational evaluation of optoelectronic, thermodynamic and electron transport properties of CuYZ2 (Z= S, Se and Te) chalcogenides semiconductors
- Ephemeral data derived potentials for random structure search
- Criticality and marginal stability of the shear jamming transition of frictionless soft spheres
- On physics-informed data-driven isotropic and anisotropic constitutive models through probabilistic machine learning and space-filling sampling
- Multiscale machine-learning interatomic potentials for ferromagnetic and liquid iron
- Simulating Pitting Corrosion in AM 316L Microstructures Through Phase Field Methods and Computational Modeling
- Robust Dirac spin gapless semiconductors in a two-dimensional oxalate based organic Honeycomb-Kagome lattice
- Development, verification, and validation of comprehensive acoustic fluid‐structure interaction capabilities in an open‐source computational platform
- ImageMech: From image to particle spring network for mechanical characterization
- First principle investigations on gas molecules (CO2, CO, NO2, NO and O2) using Armchair GaN nanoribbons for nano sensor applications
- Adapting a Multi-Material ALE with AMR Method for Physics of High-Speed Material Interactions
- Understanding Catalyst Inhibition from Biogenic Impurities in Transfer Hydrogenation of a Biorenewable Platform Chemical
- Convergence analysis and validation of a discrete element model of the human lumbar spine
- Optoelectronic Properties of Mixed Iodide–Bromide Perovskites from First-Principles Computational Modeling and Experiment
- Strong Zeeman splitting in orbital-hybridized valleytronic interfaces
- A molecular dynamics study of a cascade induced irradiation creep mechanism in pure copper
- Materials for a Sustainable Microelectronics Future: Electric Field Control of Magnetism with Multiferroics
- Advances in computational intelligence of polymer composite materials: machine learning assisted modeling, analysis and design
- Dynamical and Nonstandard Computational Analysis of Heroin Epidemic Model
- Numerical Analysis of the Temperature Field during Single-pass Two-layers Laser Additive Manufacturing of Fused Silica Glass
- The phase diagrams of beryllium and magnesium oxide at megabar pressures
- Structural, electronic, and mechanical properties of Y7Ru4InGe12: a first-principle study
- Ab initio study of structural, electronic, mechanical and optical properties of the tetragonal Cs2AgBiBr6 halide double perovskite
- Analysis of the mechanical behavior of adobe walls without reinforcement through computational modelling
- Radiation Damage in High Entropy Alloys
- Role of void shape on shock responses of nanoporous metallic glasses via molecular dynamics simulation
- Computational Analysis of Strain-Induced Effects on the Dynamic Properties of C60 in Fullerite
- The Ir–OOOO–Ir Transition State and the Mechanism of the Oxygen Evolution Reaction on IrO2 (110)
- Adaptively compressed exchange in LAPW
- A non-local model for the description of twinning in polycrystalline materials in the context of infinitesimal strains: application to a magnesium alloy

# Research Topics Physics

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