4D Printing of Multifunctional and Biodegradable PLA-PBAT-FeO Nanocomposites with Supreme Mechanical and Shape Memory Properties.

4D printing magneto-responsive shape memory polymers (SMPs) using biodegradable nanocomposites can overcome their low toughness and thermal resistance, and produce smart materials that can be controlled remotely without contact. This study presented the development of 3D/4D printable nanocomposites based on poly (lactic acid) (PLA)-poly (butylene adipate-co-terephthalate) (PBAT) blends and magnetite (FeO) nanoparticles. The nanocomposites are prepared by melt mixing PLA-PBAT blends with different FeO contents (10, 15, and 20 wt%) and extruded into granules for material extrusion 3D printing.

4D printing and optimization of biocompatible poly lactic acid/poly methyl methacrylate blends for enhanced shape memory and mechanical properties.

This study introduces a novel approach to 4D printing of biocompatible Poly lactic acid (PLA)/poly methyl methacrylate (PMMA) blends using Artificial Neural Network (ANN) and Response Surface Methodology (RSM). The goal is to optimize PMMA content, nozzle temperature, raster angle, and printing speed to enhance shape memory properties and mechanical strength. The materials, PLA and PMMA, are melt-blended and 4D printed using a pellet-based 3D printer.

Microencapsulation of natural products using spray drying; an overview.

Aims: This study examines microencapsulation as a method to enhance the stability of natural compounds, which typically suffer from inherent instability under environmental conditions, aiming to extend their application in the pharmaceutical industry.

Methods: We explore and compare various microencapsulation techniques, including spray drying, freeze drying, and coacervation, with a focus on spray drying due to its noted advantages.

Results: The analysis reveals that microencapsulation, especially via spray drying, significantly improves natural compounds' stability, offering varied morphologies, sizes, and efficiencies in encapsulation.

Multiphase Reconstruction of Heterogeneous Materials Using Machine Learning and Quality of Connection Function.

Establishing accurate structure-property linkages and precise phase volume accuracy in 3D microstructure reconstruction of materials remains challenging, particularly with limited samples. This paper presents an optimized method for reconstructing 3D microstructures of various materials, including isotropic and anisotropic types with two and three phases, using convolutional occupancy networks and point clouds from inner layers of the microstructure. The method emphasizes precise phase representation and compatibility with point cloud data.

3D and 4D Printing of PETG-ABS-FeO Nanocomposites with Supreme Remotely Driven Magneto-Thermal Shape-Memory Performance.

This study introduces novel PETG-ABS-FeO nanocomposites that offer impressive 3D- and 4D-printing capabilities. These nanocomposites can be remotely stimulated through the application of a temperature-induced magnetic field. A direct granule-based FDM printer equipped with a pneumatic system to control the output melt flow is utilized to print the composites.