Materials discovery and properties prediction in thermal transport via materials informatics: a mini-review

Abstract

There has been an increasing demand for materials with special thermal properties, whereas experimental discovery is high-cost and time-consuming. The emerging discipline `Materials Informatics' is an effective approach that can accelerate materials development by combining material science and big data technique. Recently materials informatics has been applied to the design of novel materials such as thermal interface materials for heat-dissipation, and thermoelectric materials for power generation. This mini-review summarized the research progress on the applications of materials informatics for the thermal transport properties prediction and discovery of materials with special thermal properties, including optimal thermal conductivity, interfacial thermal conductance and thermoelectricity efficiency. In addition, some perspectives are given for the outlook of materials informatics in the field of thermal transport.

References in corpus (15)

• Energy Dissipation and Transport in Nanoscale Devices
• Thermal Properties of Isotopically Engineered Graphene
• Length-dependent thermal conductivity in suspended single-layer graphene
• Thermal Conductivity of Polymers and Their Nanocomposites
• Discovery of low thermal conductivity compounds with first-principles anharmonic lattice dynamics calculations and Bayesian optimization
• Representation of compounds for machine-learning prediction of physical properties
• Nanophononic metamaterial: Thermal conductivity reduction by local resonance
• Finding unprecedentedly low-thermal-conductivity half-Heusler semiconductors via high-throughput materials modeling
• A recommendation engine for suggesting unexpected thermoelectric chemistries
• Designing nanostructures for interfacial phonon transport via Bayesian optimization
• Nano-Cross-Junction Effect on Phonon Transport in Silicon-Nanowire-Cages
• High-throughput exploration of alloying as design strategy for thermoelectrics
• Generalized two-temperature model for coupled phonons
• Enhancing thermoelectric figure-of-merit by low-dimensional electrical transport in phonon-glass crystals
• The adjustable thermal resistor by reversibly folding a graphene sheet

Cited by in corpus (12)

• Lattice Thermal Conductivity Prediction using Symbolic Regression and Machine Learning
• Maximization and Minimization of Interfacial Thermal Conductance by Modulating the Mass Distribution of Interlayer
• Cross interface model for the thermal transport across interface between overlapped boron nitride nanoribbons
• Machine learning for predicting ultralow thermal conductivity and high ZT in complex thermoelectric materials
• Dissimilar thermal transport properties in $\kappa$-Ga${}_2$O${}_3$ and $\beta$-Ga${}_2$O${}_3$ revealed by machine-learning homogeneous nonequilibrium molecular dynamics simulations
• An interpretable formula for lattice thermal conductivity of crystals
• Reduction of interfacial thermal resistance of overlapped graphene by bonding carbon chains
• Machine learning enables robust prediction of thermal boundary conductance of 2D substrate interfaces
• Kolmogorov-Arnold Neural Networks for High-Entropy Alloys Design
• Data-driven reconstruction of spectral conductivity and chemical potential from thermoelectric transport data
• Thermal conductivity of molybdenum disulfide nanotube from molecular dynamics simulations
• Thermal conductivity of one-dimensional carbon-boron nitride van der Waals heterostructure: A molecular dynamics study