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Tensile Strength

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Use of machine learning in prediction of granule particle size distribution and tablet tensile strength in commercial pharmaceutical manufacturing.

International journal of pharmaceutics
In the manufacturing of pharmaceutical Oral Solid Dosage (OSD) forms, Particle Size Distribution (PSD) and Tensile Strength (TS) are common in-process tests that are controlled in order to achieve the quality targets of the end-product. The Quality b...

A Bioinspired Stress-Response Strategy for High-Speed Soft Grippers.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
The stress-response strategy is one of the nature's greatest developments, enabling animals and plants to respond quickly to environmental stimuli. One example is the stress-response strategy of the Venus flytrap, which enables such a delicate plant ...

Application of machine learning to a material library for modeling of relationships between material properties and tablet properties.

International journal of pharmaceutics
This study investigates the usefulness of machine learning for modeling complex relationships in a material library. We tested 81 types of active pharmaceutical ingredients (APIs) and their tablets to construct the library, which included the followi...

Smart surgical sutures using soft artificial muscles.

Scientific reports
Wound closure with surgical sutures is a critical challenge for flexible endoscopic surgeries. Substantial efforts have been introduced to develop functional and smart surgical sutures to either monitor wound conditions or ease the complexity of knot...

3D printing of resilient biogels for omnidirectional and exteroceptive soft actuators.

Science robotics
Soft robotics greatly benefits from nature as a source of inspiration, introducing innate means of safe interaction between robotic appliances and living organisms. In contrast, the materials involved are often nonbiodegradable or stem from nonrenewa...

A strategy to formulate data-driven constitutive models from random multiaxial experiments.

Scientific reports
We present a test technique and an accompanying computational framework to obtain data-driven, surrogate constitutive models that capture the response of isotropic, elastic-plastic materials loaded in-plane stress by combined normal and shear stresse...

A Data-Driven Approach to Predicting Tablet Properties after Accelerated Test Using Raw Material Property Database and Machine Learning.

Chemical & pharmaceutical bulletin
The purpose of this study was to develop a model for predicting tablet properties after an accelerated test and to determine whether molecular descriptors affect tablet properties. Tablets were prepared using 81 types of active pharmaceutical ingredi...

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...

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...

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 ...