Polymer nanocomposites having a high filler content: synthesis, structures, properties, and applications
The recent development of nanoscale fillers, such as carbon nanotubes, graphene, and
nanocellulose, allows the functionality of polymer nanocomposites to be controlled and …
nanocellulose, allows the functionality of polymer nanocomposites to be controlled and …
Recent advances and remaining challenges for polymeric nanocomposites in healthcare applications
Remarkable advancements in material technologies have accelerated the use of many new
materials and their hybrids and composites in diverse applications. Among such available …
materials and their hybrids and composites in diverse applications. Among such available …
Deep learning model to predict complex stress and strain fields in hierarchical composites
Materials-by-design is a paradigm to develop previously unknown high-performance
materials. However, finding materials with superior properties is often computationally or …
materials. However, finding materials with superior properties is often computationally or …
[HTML][HTML] Bioinspired hierarchical composite design using machine learning: simulation, additive manufacturing, and experiment
Biomimicry, adapting and implementing nature's designs provides an adequate first-order
solution to achieving superior mechanical properties. However, the design space is too vast …
solution to achieving superior mechanical properties. However, the design space is too vast …
De novo composite design based on machine learning algorithm
Composites are widely used to create tunable materials to achieve superior mechanical
properties. Brittle materials fail catastrophically in the presence of cracks. Incorporating …
properties. Brittle materials fail catastrophically in the presence of cracks. Incorporating …
Machine learning for composite materials
Machine learning (ML) has been perceived as a promising tool for the design and discovery
of novel materials for a broad range of applications. In this prospective paper, we summarize …
of novel materials for a broad range of applications. In this prospective paper, we summarize …
End-to-end deep learning method to predict complete strain and stress tensors for complex hierarchical composite microstructures
Due to the high demand for materials with superior mechanical properties and diverse
functions, designing composite materials is an integral part in materials development …
functions, designing composite materials is an integral part in materials development …
Prediction and optimization of mechanical properties of composites using convolutional neural networks
In this paper, we develop a convolutional neural network model to predict the mechanical
properties of a two-dimensional checkerboard composite quantitatively. The checkerboard …
properties of a two-dimensional checkerboard composite quantitatively. The checkerboard …
Integration of stiff graphene and tough silk for the design and fabrication of versatile electronic materials
The production of structural and functional materials with enhanced mechanical properties
through the integration of soft and hard components is a common approach to Nature's …
through the integration of soft and hard components is a common approach to Nature's …
Machine learning for accelerating the design process of double-double composite structures
Current composite design processes go through expensive numerical simulations that can
quantitatively describe the detailed complex stress state embedded in the laminate structure …
quantitatively describe the detailed complex stress state embedded in the laminate structure …