[HTML][HTML] Recent advances in thermal-conductive insulating polymer composites with various fillers

Q Chen, K Yang, Y Feng, L Liang, M Chi… - Composites Part A …, 2024 - Elsevier
Abstract Development of polymer-based composites with excellent thermal conductivity and
electrical insulation properties is a hot research topic, because more and more electrical …

Emerging materials intelligence ecosystems propelled by machine learning

R Batra, L Song, R Ramprasad - Nature Reviews Materials, 2021 - nature.com
The age of cognitive computing and artificial intelligence (AI) is just dawning. Inspired by its
successes and promises, several AI ecosystems are blossoming, many of them within the …

Data‐Driven Materials Innovation and Applications

Z Wang, Z Sun, H Yin, X Liu, J Wang, H Zhao… - Advanced …, 2022 - Wiley Online Library
Owing to the rapid developments to improve the accuracy and efficiency of both
experimental and computational investigative methodologies, the massive amounts of data …

Machine-learning and high-throughput studies for high-entropy materials

EW Huang, WJ Lee, SS Singh, P Kumar, CY Lee… - Materials Science and …, 2022 - Elsevier
The combination of multiple-principal element materials, known as high-entropy materials
(HEMs), expands the multi-dimensional compositional space to gigantic stoichiometry. It is …

Predicting lattice thermal conductivity via machine learning: a mini review

Y Luo, M Li, H Yuan, H Liu, Y Fang - NPJ Computational Materials, 2023 - nature.com
Over the past few decades, molecular dynamics simulations and first-principles calculations
have become two major approaches to predict the lattice thermal conductivity (κ L), which …

A novel technique based on the improved firefly algorithm coupled with extreme learning machine (ELM-IFF) for predicting the thermal conductivity of soil

N Kardani, A Bardhan, P Samui, M Nazem… - Engineering with …, 2022 - Springer
Thermal conductivity is a specific thermal property of soil which controls the exchange of
thermal energy. If predicted accurately, the thermal conductivity of soil has a significant effect …

Data-augmented modeling for yield strength of refractory high entropy alloys: A bayesian approach

B Vela, D Khatamsaz, C Acemi, I Karaman, R Arróyave - Acta Materialia, 2023 - Elsevier
Refractory high entropy alloys (RHEAs) have gained significant attention in recent years as
potential replacements for Ni-based superalloys in gas turbine applications. Improving their …

Charting lattice thermal conductivity for inorganic crystals and discovering rare earth chalcogenides for thermoelectrics

T Zhu, R He, S Gong, T **e, P Gorai… - Energy & …, 2021 - pubs.rsc.org
Thermoelectric power generation represents a promising approach to utilize waste heat. The
most effective thermoelectric materials exhibit low thermal conductivity κ. However, less than …

Predicting the thermal conductivity of soils using integrated approach of ANN and PSO with adaptive and time-varying acceleration coefficients

N Kardani, A Bardhan, P Samui, M Nazem… - International Journal of …, 2022 - Elsevier
This study aims to propose hybrid adaptive neuro swarm intelligence (HANSI) techniques for
predicting the thermal conductivity of unsaturated soils. The novel contribution is made by …

Unveiling thermal stresses in RETaO4 (RE= Nd, Sm, Eu, Gd, Tb, Dy, Ho and Er) by first-principles calculations and finite element simulations

M Gan, X Chong, T Lu, C Yang, W Yu, SL Shang… - Acta Materialia, 2024 - Elsevier
Thermal stress (σ) plays a critical role in regulating the stability and durability of thermal
barrier coatings (TBCs) during service. However, its measurements are limited due to …