From drug molecules to thermoset shape memory polymers: a machine learning approach
Ultraviolet (UV)-curable thermoset shape memory polymers (TSMPs) with high recovery
stress but mild glass transition temperature (T g) are highly desired for 3D/4D printing …
stress but mild glass transition temperature (T g) are highly desired for 3D/4D printing …
Deep learning for predicting the thermomechanical behavior of shape memory polymers
Thermomechanical constitutive modeling is essential for shape memory polymers (SMPs) to
be used in engineering structures and devices. However, the classical method of deriving …
be used in engineering structures and devices. However, the classical method of deriving …
Artificial Neural Network Modeling in the Presence of Uncertainty for Predicting Hydrogenation Degree in Continuous Nitrile Butadiene Rubber Processing
The transition from batch to continuous production in the catalytic hydrogenation of nitrile
butadiene rubber (NBR) into hydrogenated NBR (HNBR) marks a significant advance for …
butadiene rubber (NBR) into hydrogenated NBR (HNBR) marks a significant advance for …
[图书][B] Machine Learning Assisted Discovery of Shape Memory Polymers and Their Thermomechanical Modeling
C Yan - 2022 - search.proquest.com
As a new class of smart materials, shape memory polymer (SMP) is gaining great attention
in both academia and industry. One challenge is that the chemical space is huge, while the …
in both academia and industry. One challenge is that the chemical space is huge, while the …