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From classical thermodynamics to phase-field method
Phase-field method is a density-based computational method at the mesoscale for modeling
and predicting the temporal microstructure and property evolution during materials …
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
Machine learning tools represent key enablers for empowering material scientists and
engineers to accelerate the development of novel materials, processes and techniques. One …
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
Data-driven methods are emerging as an important toolset in the studies of multiscale,
multiphysics, materials phenomena. More specifically, data mining and machine learning …
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
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 …
experimental approaches, which impede the innovation of materials due to the cost, time, or …
Material structure-property linkages using three-dimensional convolutional neural networks
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 …
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
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 …
microstructures and their physical properties at the mesoscale. However, because in these …
Progress report on phase separation in polymer solutions
Polymeric porous media (PPM) are widely used as advanced materials, such as sound
dampening foams, lithium‐ion batteries, stretchable sensors, and biofilters. The functionality …
dampening foams, lithium‐ion batteries, stretchable sensors, and biofilters. The functionality …
Microstructure recognition using convolutional neural networks for prediction of ionic conductivity in ceramics
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 …
with respect to image recognition tasks. In the present study, we adopt CNNs to link …
Materials informatics
Materials informatics employs techniques, tools, and theories drawn from the emerging
fields of data science, internet, computer science and engineering, and digital technologies …
fields of data science, internet, computer science and engineering, and digital technologies …