AIMC Topic: Tensile Strength

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Bioinspired Super-Robust Conductive Hydrogels for Machine Learning-Assisted Tactile Perception System.

Advanced materials (Deerfield Beach, Fla.)
Conductive hydrogels have attracted significant attention due to exceptional flexibility, electrochemical property, and biocompatibility. However, the low mechanical strength can compromise their stability under high stress, making the material susce...

Modelling the effect of base component properties and processing conditions on mixture products using probabilistic, knowledge-guided neural networks.

International journal of pharmaceutics
Development of materials by mixing different base components is a widespread methodology to create materials with improved properties compared to those of its base components. However, efficient determination of the properties of mixture-based materi...

Squid-Inspired Anti-Salt Skin-Like Elastomers With Superhigh Damage Resistance for Aquatic Soft Robots.

Advanced materials (Deerfield Beach, Fla.)
Cephalopod skins evolve multiple functions in response to environmental adaptation, encompassing nonlinear mechanoreponse, damage tolerance property, and resistance to seawater. Despite tremendous progress in skin-mimicking materials, the integration...

Multifunctional Magnetic Muscles for Soft Robotics.

Nature communications
Despite recent advancements, artificial muscles have not yet been able to strike the right balance between exceptional mechanical properties and dexterous actuation abilities that are found in biological systems. Here, we present an artificial magnet...

Tensile strength analysis of additively manufactured CM 247LC alloy specimen by employing machine learning classifiers.

PloS one
Using a cutting-edge net-shape manufacturing technique called Additive Layer Manufacturing (ALM), highly complex components that are not achievable with conventional wrought and cast methods can be produced. As a result, the aerospace sector is payin...

Strain-Temperature Dual Sensor Based on Deep Learning Strategy for Human-Computer Interaction Systems.

ACS sensors
Thermoelectric (TE) hydrogels, mimicking human skin, possessing temperature and strain sensing capabilities, are well-suited for human-machine interaction interfaces and wearable devices. In this study, a TE hydrogel with high toughness and temperatu...

A study of forecasting the Nephila clavipes silk fiber's ultimate tensile strength using machine learning strategies.

Journal of the mechanical behavior of biomedical materials
Recent advancements in biomaterial research conduct artificial intelligence for predicting diverse material properties. However, research predicting the mechanical properties of biomaterial based on amino acid sequences have been notably absent. This...

Machine learning to mechanically assess 2D and 3D biomimetic electrospun scaffolds for tissue engineering applications: Between the predictability and the interpretability.

Journal of the mechanical behavior of biomedical materials
Currently, the use of autografts is the gold standard for the replacement of many damaged biological tissues. However, this practice presents disadvantages that can be mitigated through tissue-engineered implants. The aim of this study is to explore ...

Optimizing the selection of natural fibre reinforcement and polymer matrix for plastic composite using LS-SVM technique.

Chemosphere
The manufacturing sector is paying close attention to plastic matrix composites (PMCs) reinforced with natural fibres for improving their products. Due to the fact that PMC reinforced with naturally occurring fibres is more affordable and has superio...

Application of unsupervised and supervised learning to a material attribute database of tablets produced at two different granulation scales.

International journal of pharmaceutics
The purpose of this study is to demonstrate the usefulness of machine learning (ML) for analyzing a material attribute database from tablets produced at different granulation scales. High shear wet granulators (scale 30 g and 1000 g) were used and da...