Recent advances in lattice thermal conductivity calculation using machine-learning interatomic potentials

Machine learning approach for the prediction and optimization of thermal transport properties

(2021) Yulou Ouyang et al.   Frontiers of Physics

First‐Principles Multiscale Modeling of Mechanical Properties in Graphene/Borophene Heterostructures Empowered by Machine‐Learning Interatomic Potentials

(2021) Bohayra Mortazavi et al.   ADVANCED MATERIALS

Ultrahigh thermal conductivity and strength in direct-gap semiconducting graphene-like BC6N: A first-principles and classical investigation

(2021) Bohayra Mortazavi   CARBON

Machine learning-based predictive modeling of contact heat transfer

(2021) Anh Tuan Vu et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Mechanical behaviors of titanium nitride and carbide MXenes: A molecular dynamics study

(2021) S. Milad Hatam-Lee et al.   APPLIED SURFACE SCIENCE

Thermo-mechanical properties of nitrogenated holey graphene (C2N): A comparison of machine-learning-based and classical interatomic potentials

(2021) Saeed Arabha et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Lattice-dynamics-based descriptors for interfacial heat transfer across two-dimensional carbon-based nanostructures

(2021) S. Milad Hatam-Lee et al.   JOURNAL OF APPLIED PHYSICS

Quenching Thermal Transport in Aperiodic Superlattices: A Molecular Dynamics and Machine Learning Study

(2020) Pranay Chakraborty et al.   ACS Applied Materials & Interfaces

Thermal boundary conductance between high thermal conductivity boron arsenide and silicon

(2020) Zhiyong Wei et al.   JOURNAL OF APPLIED PHYSICS

Performance and Cost Assessment of Machine Learning Interatomic Potentials

(2020) Yunxing Zuo et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Thermal conductivity of graphene polymorphs and compounds: From C3N to graphdiyne lattices

(2020) S. Milad Hatam-Lee et al.   CARBON

Engineered Porous Borophene with Tunable Anisotropic Properties

(2020) S. Arabha et al.   COMPOSITES PART B-ENGINEERING

Machine learning for heat transfer correlations

(2020) Beomjin Kwon et al.   INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER

Neural network potential from bispectrum components: A case study on crystalline silicon

(2020) Howard Yanxon et al.   JOURNAL OF CHEMICAL PHYSICS

Machine-Learning-Optimized Aperiodic Superlattice Minimizes Coherent Phonon Heat Conduction

(2020) Run Hu et al.   Physical Review X

Nanoporous C3N4, C3N5 and C3N6 nanosheets; novel strong semiconductors with low thermal conductivities and appealing optical/electronic properties

(2020) Bohayra Mortazavi et al.   CARBON

Machine learning prediction of thermal transport in porous media with physics-based descriptors

(2020) Han Wei et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Exploring phononic properties of two-dimensional materials using machine learning interatomic potentials

(2020) Bohayra Mortazavi et al.   Applied Materials Today

Accelerating first-principles estimation of thermal conductivity by machine-learning interatomic potentials: A MTP/ShengBTE solution

(2020) Bohayra Mortazavi et al.   COMPUTER PHYSICS COMMUNICATIONS

Tuning shear mechanical properties and tensile strength anisotropy of monolayer black phosphorene: A molecular dynamics study

(2020) S. Milad Hatam-Lee et al.   Materials Today Communications

Thermal conductivity of MoS2 monolayers from molecular dynamics simulations

(2019) Aravind Krishnamoorthy et al.   AIP Advances

Understanding the thermal conductivity of Diamond/Copper Composite by first-principles calculations

(2019) Liang Chen et al.   CARBON

SIMPLE-NN: An efficient package for training and executing neural-network interatomic potentials

(2019) Kyuhyun Lee et al.   COMPUTER PHYSICS COMMUNICATIONS

Thermal transport in silicene nanotubes: Effects of length, grain boundary and strain

(2019) Maryam Khalkhali et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Parallel Multistream Training of High-Dimensional Neural Network Potentials

(2019) Andreas Singraber et al.   Journal of Chemical Theory and Computation

Thermal conductivity of single-layer MoS2(1−x)Se2x alloys from molecular dynamics simulations with a machine-learning-based interatomic potential

(2019) Xiaokun Gu et al.   COMPUTATIONAL MATERIALS SCIENCE

Applying a machine learning interatomic potential to unravel the effects of local lattice distortion on the elastic properties of multi-principal element alloys

(2019) Mehdi Jafary-Zadeh et al.   JOURNAL OF ALLOYS AND COMPOUNDS

Machine learning models for the lattice thermal conductivity prediction of inorganic materials

(2019) Lihua Chen et al.   COMPUTATIONAL MATERIALS SCIENCE

Lattice dynamics simulation using machine learning interatomic potentials

(2019) V.V. Ladygin et al.   COMPUTATIONAL MATERIALS SCIENCE

Machine learning maximized Anderson localization of phonons in aperiodic superlattices

(2019) Prabudhya Roy Chowdhury et al.   Nano Energy

High-Throughput Continuous Production of Shear-Exfoliated 2D Layered Materials using Compressible Flows

(2018) Reza Rizvi et al.   ADVANCED MATERIALS

Novel two-dimensional diamond like carbon nitrides with extraordinary elasticity and thermal conductivity

(2018) Yuan Dong et al.   CARBON

On the diversity in the thermal transport properties of graphene: A first-principles-benchmark study testing different exchange-correlation functionals

(2018) Guangzhao Qin et al.   COMPUTATIONAL MATERIALS SCIENCE

DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics

(2018) Han Wang et al.   COMPUTER PHYSICS COMMUNICATIONS

First-principle phonon thermal transport in graphene: Effects of exchange-correlation and type of pseudopotential

(2018) Armin Taheri et al.   JOURNAL OF APPLIED PHYSICS

Extending the accuracy of the SNAP interatomic potential form

(2018) Mitchell A. Wood et al.   JOURNAL OF CHEMICAL PHYSICS

First-principles study of intrinsic phononic thermal transport in monolayer C 3 N

(2018) Yan Gao et al.   PHYSICA E-LOW-DIMENSIONAL SYSTEMS & NANOSTRUCTURES

Achieving DFT accuracy with a machine-learning interatomic potential: Thermomechanics and defects in bcc ferromagnetic iron

(2018) Daniele Dragoni et al.   PHYSICAL REVIEW MATERIALS

Predicting the effective thermal conductivities of composite materials and porous media by machine learning methods

(2018) Han Wei et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Width dependent intrinsic thermal conductivity of suspended monolayer graphene

(2017) Haidong Wang et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Anomalous strain effect on the thermal conductivity of borophene: a reactive molecular dynamics study

(2017) Bohayra Mortazavi et al.   PHYSICA E-LOW-DIMENSIONAL SYSTEMS & NANOSTRUCTURES

Synthesis and chemistry of elemental 2D materials

(2017) Andrew J. Mannix et al.   Nature Reviews Chemistry

Ror2 signaling regulates Golgi structure and transport through IFT20 for tumor invasiveness

(2017) Michiru Nishita et al.   Scientific Reports

First-Principles Prediction of Ultralow Lattice Thermal Conductivity of Dumbbell Silicene: A Comparison with Low-Buckled Silicene

(2016) Bo Peng et al.   ACS Applied Materials & Interfaces

An implementation of artificial neural-network potentials for atomistic materials simulations: Performance for TiO 2

(2016) Nongnuch Artrith et al.   COMPUTATIONAL MATERIALS SCIENCE

Amp : A modular approach to machine learning in atomistic simulations

(2016) Alireza Khorshidi et al.   COMPUTER PHYSICS COMMUNICATIONS

Thermal conductivity of bulk and monolayer MoS2

(2016) Appala Naidu Gandi et al.   EPL

Moment Tensor Potentials: A Class of Systematically Improvable Interatomic Potentials

(2016) Alexander V. Shapeev   MULTISCALE MODELING & SIMULATION

First-principles study of thermal transport in nitrogenated holey graphene

(2016) Tao Ouyang et al.   NANOTECHNOLOGY

First-principles study of thermal properties of borophene

(2016) Hongyi Sun et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

2D materials advances: from large scale synthesis and controlled heterostructures to improved characterization techniques, defects and applications

(2016) Zhong Lin et al.   2D Materials

A general-purpose machine learning framework for predicting properties of inorganic materials

(2016) Logan Ward et al.   npj Computational Materials

Two-Dimensional Nanomaterials for Biomedical Applications: Emerging Trends and Future Prospects

(2015) David Chimene et al.   ADVANCED MATERIALS

Effect of exchange–correlation on first-principles-driven lattice thermal conductivity predictions of crystalline silicon

(2015) Ankit Jain et al.   COMPUTATIONAL MATERIALS SCIENCE

Constructing high-dimensional neural network potentials: A tutorial review

(2015) Jörg Behler   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Gaussian approximation potentials: A brief tutorial introduction

(2015) Albert P. Bartók et al.   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

First-principles prediction of phononic thermal conductivity of silicene: A comparison with graphene

(2015) Xiaokun Gu et al.   JOURNAL OF APPLIED PHYSICS

Direction dependent thermal conductivity of monolayer phosphorene: Parameterization of Stillinger-Weber potential and molecular dynamics study

(2015) Wen Xu et al.   JOURNAL OF APPLIED PHYSICS

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

(2015) A.P. Thompson et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Thermal Transport Mechanisms in Carbon Nanotube-Nanofluids Identified From Molecular Dynamics Simulations

(2015) Jonathan W. Lee et al.   JOURNAL OF HEAT TRANSFER-TRANSACTIONS OF THE ASME

Thermal conductivity of a two-dimensional phosphorene sheet: a comparative study with graphene

(2015) Yang Hong et al.   Nanoscale

Two-dimensional materials and their prospects in transistor electronics

(2015) F. Schwierz et al.   Nanoscale

High thermoelectric performance in two-dimensional graphyne sheets predicted by first-principles calculations

(2015) Xiaojian Tan et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Measuring the thermal conductivity of residue-free suspended graphene bridge using null point scanning thermal microscopy

(2014) Kichul Yoon et al.   CARBON

ShengBTE: A solver of the Boltzmann transport equation for phonons

(2014) Wu Li et al.   COMPUTER PHYSICS COMMUNICATIONS

Representing potential energy surfaces by high-dimensional neural network potentials

(2014) J Behler   JOURNAL OF PHYSICS-CONDENSED MATTER

Thermal Conductivity of Graphene and Graphite: Collective Excitations and Mean Free Paths

(2014) Giorgia Fugallo et al.   NANO LETTERS

Two-dimensional material nanophotonics

(2014) Fengnian Xia et al.   Nature Photonics

Phonon thermal transport in strained and unstrained graphene from first principles

(2014) L. Lindsay et al.   PHYSICAL REVIEW B

Length-dependent thermal conductivity in suspended single-layer graphene

(2014) Xiangfan Xu et al.   Nature Communications

Tuning the thermal conductivity of silicene with tensile strain and isotopic doping: A molecular dynamics study

(2013) Qing-Xiang Pei et al.   JOURNAL OF APPLIED PHYSICS

High-Field Electrical and Thermal Transport in Suspended Graphene

(2013) Vincent E. Dorgan et al.   NANO LETTERS

First-Principles Determination of Ultrahigh Thermal Conductivity of Boron Arsenide: A Competitor for Diamond?

(2013) L. Lindsay et al.   PHYSICAL REVIEW LETTERS

Accelerating materials property predictions using machine learning

(2013) Ghanshyam Pilania et al.   Scientific Reports

High-dimensional neural-network potentials for multicomponent systems: Applications to zinc oxide

(2011) Nongnuch Artrith et al.   PHYSICAL REVIEW B

Thermal conductivity of suspended pristine graphene measured by Raman spectroscopy

(2011) Jae-Ung Lee et al.   PHYSICAL REVIEW B

Thermal conductivity of interfacial layers in nanofluids

(2011) Zhi Liang et al.   PHYSICAL REVIEW E

Nitrogen doping and curvature effects on thermal conductivity of graphene: A non-equilibrium molecular dynamics study

(2011) Bohayra Mortazavi et al.   SOLID STATE COMMUNICATIONS

Thermal conductivity of graphene ribbons from equilibrium molecular dynamics: Effect of ribbon width, edge roughness, and hydrogen termination

(2010) William J. Evans et al.   APPLIED PHYSICS LETTERS

Dimensional crossover of thermal transport in few-layer graphene

(2010) Suchismita Ghosh et al.   NATURE MATERIALS

Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons

(2010) Albert P. Bartók et al.   PHYSICAL REVIEW LETTERS

QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials

(2009) Paolo Giannozzi et al.   JOURNAL OF PHYSICS-CONDENSED MATTER

Extremely high thermal conductivity of graphene: Prospects for thermal management applications in nanoelectronic circuits

(2008) S. Ghosh et al.   APPLIED PHYSICS LETTERS

Study for the particle's scale effect on some thermophysical properties of nanofluids by a simplified molecular dynamics method

(2008) Wen-Qiang Lu et al.   ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS