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This study investigates the fabrication and characterization of heat-responsive PLA/PU/MXene shape memory polymer blend nanocomposites with varying PLA content (10, 20, 30, and 50%) and a fixed MXene content of 0.5 wt.%. The results indicate significant improvements in mechanical properties, with the 50% PLA/PU/MXene blend showing a 300% increase in ultimate tensile strength and a 90% decrease in % elongation compared to pure PU. Additionally, the 50% blend exhibited a 400% increase in flexural strength. Microstructural analysis revealed dispersed pores and sea–island morphology in pure PU and the 50% PLA/PU/MXene blend. Thermal analysis using DSC showed an increase in crystallinity from 33% (pure PU) to 45% for the 50% PLA/PU/MXene blend, indicating enhanced crystalline domains due to the semi-crystalline nature of PLA and MXene's influence on molecular ordering. TGA demonstrated a significant improvement in thermal stability, with the onset temperature rising from 185 °C (pure PU) to 212 °C and the degradation temperature increasing from 370 °C to 425 °C for the 50% blend, attributed to the rigid structure of PLA and MXene's stabilizing effect. Shape memory testing revealed that the 30% PLA/PU/MXene blend achieved the best shape fixity and recovery with optimal performance, whereas higher PLA content diminished shape memory behavior. [ABSTRACT FROM AUTHOR]

This research article proposes a new method for an enhanced Flexible Manufacturing System (FMS) using a combination of smart methods. These methods use a set of three technologies of Industry 4.0, namely Artificial Intelligence (AI), Digital Twin (DT), and Wi-Fi-based indoor localization. The combination tackles the problem of asset tracking through Wi-Fi localization using machine-learning algorithms. The methodology utilizes the extensive "UJIIndoorLoc" dataset which consists of data from multiple floors and over 520 Wi-Fi access points. To achieve ultimate efficiency, the current study experimented with a range of machine-learning algorithms. The algorithms include Support Vector Machines (SVM), Random Forests (RF), Decision Trees, K-Nearest Neighbors (KNN) and Convolutional Neural Networks (CNN). To further optimize, we also used three optimizers: ADAM, SDG, and RMSPROP. Among the lot, the KNN model showed superior performance in localization accuracy. It achieved a mean coordinate error (MCE) between 1.2 and 2.8 m and a 100% building rate. Furthermore, the CNN combined with the ADAM optimizer produced the best results, with a mean squared error of 0.83. The framework also utilized a deep reinforcement learning algorithm. This enables an Automated Guided Vehicle (AGV) to successfully navigate and avoid both static and mobile obstacles in a controlled laboratory setting. A cost-efficient, adaptive, and resilient solution for real-time tracking of assets is achieved through the proposed framework. The combination of Wi-Fi fingerprinting, deep learning for localization, and Digital Twin technology allows for remote monitoring, management, and optimization of manufacturing operations. [ABSTRACT FROM AUTHOR]

Dimethylformamide (DMF), a polar solvent, is commonly used for preparing graphene/epoxy nanocomposites. While previous research has commonly predominantly highlighted the improvement in physio-mechanical properties of these nanocomposites, the effect of DMF on processing and its direct influence on the final characteristics of MXene/epoxy nanocomposites have not been investigated. This unexplored link between DMF dosage, MXene concentrations, and the final composite properties presents an exciting direction for future research. In this study, a fixed dosage of DMF was used with varying MXene concentrations to fabricate the nanocomposites. To assess the reliability of DMF dosage on the characteristics of the fabricated nanocomposites, various evaluation techniques were employed, including dispersion evaluation, mechanical tests, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), scanning electron microscopy (SEM), electromagnetic interference (EMI) shielding, and surface roughness measurements. The research outcomes revealed that as MXene concentration increased, the characteristics of the MXene/epoxy nanocomposites, improved across the board, indicating their potential for use in energy storage applications. [ABSTRACT FROM AUTHOR]

In this research, an ESC tester machine was built by utilising a fracture mechanics approach. The machine consists of critical components such as an aluminium frame, 3D printed pulley and bracket, DC motor, Arduino microcontroller, and fasteners. The test was performed by securing an acrylic sample using a hook fixed to bracket on the base of the frame and integrated load cell with Arduino microcontroller board. Digital camera was used to capture images with Image J processing software to measure the transient damage area and macro-crack length development at each test condition. The results suggested that the applied load can influence the fracture toughness values. At 55N, the fracture toughness for the acrylic was 1.9 MPa.m1/2. Increasing the load to 65N, the fracture toughness dropped by 60% to 0.7 MPa.m1/2. The minimum fracture toughness was observed at 85N load; a 91% reduction was recorded. Maximum damage area of 89 mm2 was recorded for sample tested at 55N while minimum damage area was at 85N load, where only 31.81 mm2 area was calculated. It can be concluded that this newly built machine can be used to perform fracture toughness test on polymeric materials under environmental stress cracking (ESC) condition. [ABSTRACT FROM AUTHOR]

In this research, an ESC tester machine was built by utilising a fracture mechanics approach. The machine consists of critical components such as an aluminium frame, 3D printed pulley and bracket, DC motor, Arduino microcontroller, and fasteners. The test was performed by securing an acrylic sample using a hook fixed to bracket on the base of the frame and integrated load cell with Arduino microcontroller board. Digital camera was used to capture images with Image J processing software to measure the transient damage area and macro-crack length development at each test condition. The results suggested that the applied load can influence the fracture toughness values. At 55N, the fracture toughness for the acrylic was 1.9 MPa.m1/2. Increasing the load to 65N, the fracture toughness dropped by 60% to 0.7 MPa.m1/2. The minimum fracture toughness was observed at 85N load; a 91% reduction was recorded. Maximum damage area of 89 mm² was recorded for sample tested at 55N while minimum damage area was at 85N load, where only 31.81 mm² area was calculated. It can be concluded that this newly built machine can be used to perform fracture toughness test on polymeric materials under environmental stress cracking (ESC) condition. [ABSTRACT FROM AUTHOR]

The synergistic effects of halloysite nanotubes (HNTs) and carbon nanotubes (CNTs) on the mechanical properties of epoxy nanocomposites were investigated. The addition of hybrid nanofillers (0.5 wt% HNTs–0.5 wt% CNTs) has significantly increased the storage modulus, flexural strength, tensile strength, fracture toughness (K1C), critical strain energy release rate (G1C), and microhardness of the nanocomposites. The tensile strength and Young's modulus increased up to approximately 45% and 49%, respectively. The flexural strength and modulus increased up to approximately 46% and 17%, respectively. K1C, G1C, and microhardness recorded improvements of up to approximately 125%, 134%, and 11%, respectively. The formation of a large number of microcracks (emanated radially) and the increase in fracture surface area (due to crack deflection) were the major toughening mechanisms in the hybrid nanocomposites. SEM images revealed that the hybrid nanofillers were uniformly dispersed in the epoxy matrix and the fracture surface was coarser than that of neat epoxy, suggesting a semi-ductile fracture. This study has shown that the synergistic effects of HNTs–CNTs hybrid nanocomposites at low content (0.5 wt% HNTs–0.5 wt% CNTs) have significantly enhanced the mechanical properties of epoxy nanocomposites. [ABSTRACT FROM AUTHOR]

Halloysite nanotubes (HNTs)-polyester nanocomposites with four different concentrations were produced using solution casting technique and the biodegradation effect of short-term seawater exposure (120 h) was studied. Monolithic polyester was observed to have the highest seawater absorption with 1.37%. At 0.3 wt % HNTs reinforcement, the seawater absorption dropped significantly to the lowest value of 0.77% due to increase of liquid diffusion path. For samples tested in dry conditions, the Tg, storage modulus, tensile properties and flexural properties were improved. The highest improvement of Tg was from 79.3 to 82.4 °C (increase 3.1 °C) in the case of 0.3 wt % HNTs. This can be associated with the exfoliated HNTs particles, which restrict the mobility of polymer chains and thus raised the Tg. After seawater exposure, the Tg, storage modulus, tensile properties and flexural properties of polyester and its nanocomposites were decreased. The Young's modulus of 0.3 wt % HNTs-polyester dropped 20% while monolithic polyester dropped up to 24% compared to their values in dry condition. Apart from that, 29% flexural modulus reduction was observed, which was 18% higher than monolithic polyester. In contrast, fracture toughness and surface roughness increased due to plasticization effect. The presence of various microbial communities caused gradual biodegradation on the microstructure of the polyester matrix as also evidently shown by SEM images. [ABSTRACT FROM AUTHOR]

DMF is one the most commonly-used solvents for preparing graphene nanocomposites. Various processing variables for DMF are being used for the preparation of epoxy/graphene nanocomposites. Whilst the emphasis of all of these reported studies are on the improvements in mechanical, and other properties, of the epoxy/graphene nanocomposites, there is no study investigating how DMF affects the processing and how it is associated with the final properties of the nanocomposites. In this work, different dosages of DMF have been used to prepare nanocomposites. Mechanical testing, X-ray diffraction (XRD), dynamic mechanical analysis (DMA), thermogravimetric analysis (TGA), and scanning electron microscopy (SEM) have been used to analyze the effectiveness of DMF dosage on the properties of processed nanocomposites. Larger dosages of DMF are not always ideal for dispersing graphene as it promotes reaggregation of graphene during the processing. [ABSTRACT FROM AUTHOR]

The degradation of mechanical properties in halloysite nanoclay–polyester nanocomposites was studied after an exposure of 24 h in diluted methanol system by clamping test specimens across steel templates. The glass transition temperature (Tg) and storage modulus increased steadily with the increase of halloysite nanoclays before and after diluted methanol exposure. The addition of nano-fillers was found to reduce liquid uptake by 0.6% in case of 1 wt% reinforcement compared to monolithic polyester. The mechanical properties of polyester-based nanocomposites were found to decrease as a result of diluted methanol absorption. After diluted methanol exposure, the maximum microhardness, tensile, flexural and impact toughness values were observed at 1 wt% of halloysite nanoclay. The microhardness increased from 203 to 294 HV (45% increase). The Young’s modulus increased from 0.49 to 0.83 GPa (70% increase) and the tensile strength increased from 23 to 27 MPa (17.4% increase). The impact toughness increased from 0.19 to 0.54 kJ/m2 in diluted methanol system (184% increase). Surprisingly, the fracture toughness of all types of nanocomposites was found to increase after exposing to diluted methanol due to plasticization effect. Scanning electron microscope images of the fractured surfaces of tensile specimens revealed that the methanol increased the ductility of the matrix and reduced the mechanical properties of the nanocomposites. [ABSTRACT FROM AUTHOR]

The influence of short-term water absorption on the mechanical properties of halloysite nanotubes-multi layer graphene reinforced polyester hybrid nanocomposites has been investigated. The addition of nano-fillers significantly increased the flexural strength, tensile strength, and impact strength in dry and wet conditions. After short-term water exposure, the maximum microhardness, tensile, flexural and impact toughness values were observed at 0.1 wt % multi-layer graphene (MLG). The microhardness increased up to 50.3%, tensile strength increased up to 40% and flexural strength increased up to 44%. Compared to dry samples, the fracture toughness and surface roughness of all types of produced nanocomposites were increased that may be attributed to the plasticization effect. Scanning electron microscopy revealed that the main failure mechanism is caused by the weakening of the nano-filler-matrix interface induced by water absorption. It was further observed that synergistic effects were not effective at a concentration of 0.1 wt % to produce considerable improvement in the mechanical properties of the produced hybrid nanocomposites. [ABSTRACT FROM AUTHOR]