The main goal of this research is to study the development of crystalline morphology and compare it to various mechanical properties of microfibrillar composites (MFCs) based on polypropylene (PP) and poly(ethylene terephthalate) (PET), by adding a functional compatibilizer and a non-functional rubber in two different steps in the processing sequence. The MFCs were prepared at a weight ratio of 80/20 PP/PET by twin screw extrusion followed by cold drawing and injection moulding. The non-functionalized polyolefin-based elastomer (POE) and the functional compatibilizer (i.e., POE grafted with maleic anhydride (POE--MA)) were added in a fixed weight percentage at two stages: during extrusion or during injection moulding. The morphology observations showed differences in crystalline structure, and the PP spherulite size was reduced in all MFCs due to the presence of PET fibrils. Their relationship with the mechanical performances of the composite was studied by tensile and impact tests. Adding the functional compatibilizer during extrusions showed better mechanical properties compared to MFCs. Overall, a clear relationship was identified between processing, structure and properties.
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http://dx.doi.org/10.3390/polym10030291 | DOI Listing |
Sci Rep
December 2024
Department of Physics, Indian Institute of Technology, Patna, 801106, Bihar, India.
A highly effective method for creating a supramolecular metallogel of Ni(II) ions (NiA-TA) has been developed in our work. This approach uses benzene-1,3,5-tricarboxylic acid as a low molecular weight gelator (LMWG) in DMF solvent. Rheological studies assessed the mechanical properties of the Ni(II)-metallogel, revealing its angular frequency response and thixotropic behaviour.
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December 2024
School of Electrical Engineering, Aalto University, P.O. Box 15500, Aalto, FI-00076, Finland.
Engineering plastics are finding widespread applications across a broad temperature spectrum, with additive manufacturing (AM) having now become commonplace for producing aerospace-grade components from polymers. However, there is limited data available on the behavior of plastic AM parts exposed to elevated temperatures. This study focuses on investigating the tensile strength, tensile modulus and Poisson's ratio of parts manufactured using fused filament fabrication (FFF) and polyetheretherketone (PEEK) plastics doped with two additives: short carbon fibers (SCFs) and multi-wall carbon nanotubes (MWCNTs).
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December 2024
School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan, China.
The dolomite dust-emulsified asphalt composite (DAC) with excellent mechanical properties was successfully prepared using alkali activation. The effects of different alkali concentrations and emulsified asphalt contents on the mechanical properties of the materials were studied. And the micro-mechanisms of its mechanical performance changes were analyzed through SEM and XRD characterization.
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December 2024
Department of Mechanical Engineering, Sejong University, Seoul, Republic of Korea.
Nonthermal plasma has been extensively utilized in various biomedical fields, including surface engineering of medical implants to enhance their biocompatibility and osseointegration. To ensure robustness and cost effectiveness for commercial viability, stable and effective plasma is required, which can be achieved by reducing gas pressure in a controlled volume. Here, we explored the impact of reduced gas pressure on plasma properties, surface characteristics of plasma-treated implants, and subsequent biological outcomes.
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December 2024
School of Civil & Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Per- and polyfluoroalkyl substances (PFASs) have recently garnered considerable concerns regarding their impacts on human and ecological health. Despite the important roles of polyamide membranes in remediating PFASs-contaminated water, the governing factors influencing PFAS transport across these membranes remain elusive. In this study, we investigate PFAS rejection by polyamide membranes using two machine learning (ML) models, namely XGBoost and multimodal transformer models.
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