Composite material

Summary

A composite material (also called a composition material or shortened to composite, which is the common name) is a material which is produced from two or more constituent materials. These constituent materials have notably dissimilar chemical or physical properties and are merged to create a material with properties unlike the individual elements. Within the finished structure, the individual elements remain separate and distinct, distinguishing composites from mixtures and solid solutions. Typical engineered composite materials include: *Reinforced concrete and masonry *Composite wood such as plywood *Reinforced plastics, such as fibre-reinforced polymer or fiberglass *Ceramic matrix composites (composite ceramic and metal matrices) *Metal matrix composites *and other advanced composite materials There are various reasons where new material can be favoured. Typical examples include materials which are less expensive, lighter, stronger or more durable when compared with common materia

Official source

https://en.wikipedia.org/wiki/Composite_material

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related publications (100)

Related publications

Related people (221)

Related people

Related units (78)

Related units

Related concepts (135)

Related concepts

Related courses (153)

Related courses

Related lectures (439)

Related lectures

Drops: Controlled crystallization of organic crystals and their use as matrix materials for encapsulation of volatiles

Aysu Ceren Okur

Encapsulation techniques open up new possibilities to control the kinetics and location of the release of active ingredients. Despite the progresses achieved to obtain a better control over the dimensions and composition of the capsules, the encapsulation of volatile substances is still challenging, even though it is of high relevance especially for the cosmetic industries. One way of encapsulating volatile substances is by kinetically arresting these molecules in a matrix which has a low permeability. A group of materials that likely is well-suited to generate such matrices is composed of small molecules capable of forming crystals.In this thesis, we will investigate the influence of the processing of composites containing small biocompatible organic molecules that serve as matrices with volatile active ingredients on the structure and permeability of the resulting particles. In particular, we will investigate the possibility to use organic salt crystals as matrix materials. Particles of well-defined sizes and compositions will be produced in double emulsions where the influence of the formation kinetics and confinements on the structure and permeability of the particles will be investigated. In addition, we will produce amorphous particles by kinetically suppressing the crystallization reaction using a microfluidic spray-drier. This will be achieved by co-spray-drying the active ingredient with the matrix material. We will investigate the effect of the drying speed and reactant composition on the structure and composition of the resulting particles and relate that to the release kinetics of the active ingredient. In addition, we will crystallize the amorphous composite particles and investigate the influence of the structure on the distribution of the actives within the matrix and its permeability. This project is done in collaboration with Firmenich who has all the infrastructure to quantify the release kinetics of volatile active ingredients.

EPFL2022

In situ simultaneous strain and temperature measurement of adaptive composite materials using a fiber Bragg grating based sensor

SPIE2005

, ,

Permeability of fibrous microstructures is a key material property for predicting the mold fill times and resin flow path during composite manufacturing. In this work, we report an efficient approach to predict the permeability of 3D microstructures from deep learning based permeability predictions of 2D cross-sections combined via a circuit analogy. After validating the network’s predictions in 2D and extending it to 3D, we investigate its capabilities for handling images of various sizes obtained from virtual and real microstructures. More than 90% of 2D predictions is within ± 30% of their counterparts obtained via flow simulations, similarly for 3D transverse permeability predictions, while in 3D case computational time is reduced from several thousands of seconds to less than 10 s. This work provides a robust and efficient framework for characterizing the permeability of fibrous microstructures and paves the way for extending this capability to estimate the permeability of fabric mesostructures.

2022

Drops: Controlled crystallization of organic crystals and their use as matrix materials for encapsulation of volatiles

Aysu Ceren Okur

EPFL2022