AIMC Topic: Polymers

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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...

Frontiers in nonviral delivery of small molecule and genetic drugs, driven by polymer chemistry and machine learning for materials informatics.

Chemical communications (Cambridge, England)
Materials informatics (MI) has immense potential to accelerate the pace of innovation and new product development in biotechnology. Close collaborations between skilled physical and life scientists with data scientists are being established in pursui...

Recent Advances and Challenges in Enzymatic Depolymerization and Recycling of PET Wastes.

Chembiochem : a European journal of chemical biology
Poly (ethylene terephthalate) (PET) is one of the most commonly used plastics in daily life and various industries. Enzymatic depolymerization and recycling of post-consumer PET (pc-PET) provides a promising strategy for the sustainable circular econ...

Simultaneous Sensing and Actuating Capabilities of a Triple-Layer Biomimetic Muscle for Soft Robotics.

Sensors (Basel, Switzerland)
This work presents the fabrication and characterization of a triple-layered biomimetic muscle constituted by polypyrrole (PPy)-dodecylbenzenesulfonate (DBS)/adhesive tape/PPy-DBS demonstrating simultaneous sensing and actuation capabilities. The musc...

Classification of helical polymers with deep-learning language models.

Journal of structural biology
Many macromolecules in biological systems exist in the form of helical polymers. However, the inherent polymorphism and heterogeneity of samples complicate the reconstruction of helical polymers from cryo-EM images. Currently, available 2D classifica...

Identification of Water-Soluble Polymers through Machine Learning of Fluorescence Signals from Multiple Peptide Sensors.

ACS applied bio materials
Recently, there has been growing concern about the discharge of water-soluble polymers (especially synthetic polymers) into the environment. Therefore, the identification of water-soluble polymers in water samples is becoming increasingly crucial. In...

Multimodal Three-Dimensional Printing for Micro-Modulation of Scaffold Stiffness Through Machine Learning.

Tissue engineering. Part A
The ability to precisely control a scaffold's microstructure and geometry with light-based three-dimensional (3D) printing has been widely demonstrated. However, the modulation of scaffold's mechanical properties through prescribed printing parameter...

Artificial intelligence and the analysis of cryo-EM data provide structural insight into the molecular mechanisms underlying LN-lamininopathies.

Scientific reports
Laminins (Lm) are major components of basement membranes (BM), which polymerize to form a planar lattice on cell surface. Genetic alternations of Lm affect their oligomerization patterns and lead to failures in BM assembly manifesting in a group of h...

CEGAT: A CNN and enhanced-GAT based on key sample selection strategy for hyperspectral image classification.

Neural networks : the official journal of the International Neural Network Society
In recent years, the application of convolutional neural networks (CNNs) and graph convolutional networks (GCNs) in hyperspectral image classification (HSIC) has achieved remarkable results. However, the limited label samples are still a major challe...

Automatically Predicting Material Properties with Microscopic Images: Polymer Miscibility as an Example.

Journal of chemical information and modeling
Many material properties are manifested in the morphological appearance and characterized using microscopic images, such as scanning electron microscopy (SEM). Polymer miscibility is a key physical quantity of polymer materials and is commonly and in...