From classical thermodynamics to phase-field method

LQ Chen, Y Zhao - Progress in Materials Science, 2022‏ - Elsevier
Phase-field method is a density-based computational method at the mesoscale for modeling
and predicting the temporal microstructure and property evolution during materials …

A review of the application of machine learning and data mining approaches in continuum materials mechanics

FE Bock, RC Aydin, CJ Cyron, N Huber… - Frontiers in …, 2019‏ - frontiersin.org
Machine learning tools represent key enablers for empowering material scientists and
engineers to accelerate the development of novel materials, processes and techniques. One …

Deep learning approaches for mining structure-property linkages in high contrast composites from simulation datasets

Z Yang, YC Yabansu, R Al-Bahrani, W Liao… - Computational Materials …, 2018‏ - Elsevier
Data-driven methods are emerging as an important toolset in the studies of multiscale,
multiphysics, materials phenomena. More specifically, data mining and machine learning …

[HTML][HTML] Machine learning and materials informatics approaches for predicting transverse mechanical properties of unidirectional CFRP composites with microvoids

M Li, H Zhang, S Li, W Zhu, Y Ke - Materials & Design, 2022‏ - Elsevier
The mechanical properties of composites are traditionally measured using numerical and
experimental approaches, which impede the innovation of materials due to the cost, time, or …

Material structure-property linkages using three-dimensional convolutional neural networks

A Cecen, H Dai, YC Yabansu, SR Kalidindi, L Song - Acta Materialia, 2018‏ - Elsevier
The core materials knowledge needed in the accelerated design, development, and
deployment of new and improved materials is most accessible when cast in the form of …

Accelerating phase-field predictions via recurrent neural networks learning the microstructure evolution in latent space

C Hu, S Martin, R Dingreville - Computer Methods in Applied Mechanics …, 2022‏ - Elsevier
The phase-field method is a popular modeling technique used to describe the dynamics of
microstructures and their physical properties at the mesoscale. However, because in these …

Progress report on phase separation in polymer solutions

F Wang, P Altschuh, L Ratke, H Zhang… - Advanced …, 2019‏ - Wiley Online Library
Polymeric porous media (PPM) are widely used as advanced materials, such as sound
dampening foams, lithium‐ion batteries, stretchable sensors, and biofilters. The functionality …

Microstructure recognition using convolutional neural networks for prediction of ionic conductivity in ceramics

R Kondo, S Yamakawa, Y Masuoka, S Tajima, R Asahi - Acta Materialia, 2017‏ - Elsevier
Convolutional neural networks (CNNs) have recently exhibited state-of-the-art performance
with respect to image recognition tasks. In the present study, we adopt CNNs to link …

Materials informatics

S Ramakrishna, TY Zhang, WC Lu, Q Qian… - Journal of Intelligent …, 2019‏ - Springer
Materials informatics employs techniques, tools, and theories drawn from the emerging
fields of data science, internet, computer science and engineering, and digital technologies …