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This study investigates the production of graphene-enhanced polyethylene terephthalate glycol (G-PETG) components using fused deposition modeling (FDM) and evaluates their mechanical properties, contributing to the advancement of additive manufacturing. Trials demonstrated notable improvements in mechanical performance, with optimal printing parameters identified using the Spice Logic Analytical Hierarchy Process (AHP). The effectiveness of this methodology is further compared with the Fuzzy Analytic Hierarchy Process (FAHP) combined with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The study revealed significant enhancements, with the ultimate tensile strength (UTS) reaching 69.1 MPa, an average Young’s modulus of 735.6 MPa, and an ultimate compressive strength (UCS) of 85.3 MPa. These findings provide valuable insights into optimizing techniques for improving the mechanical performance of G-PETG components, advancing material applications in various industries.

The objective of this study is to prepare a bio-based and light-weight electromagnetic interference (EMI) shielding material in the range of 8–12 GHz. Organic castor oil-based polyurethane (PU) foam was synthesized by the mechanical stirrer mixing process, whereas absorption and hydrothermal reduction processes have been used to reinforce the multi-walled carbon nanotube (MWCNT), cupric oxide (CuO) and bamboo charcoal (BC) nanoparticles in the organic PU foam. The EMI shielding properties of the PU foam composite were tested using a vector analyzer test setup. Identification of the structural property of the nanocomposite was analyzed using field-emission scanning electron microscopy images. The density of the organic PU foam composite reinforced with nanoparticles was calculated with the help of mass and volume. Response surface methodology has been used to systematically design and analyze the experiments of EMI shielding effectiveness (EMI SE) and the physical properties of the reinforced foam. Using the EMI SE experimental results, mathematical models were developed to forecast the results and validate them with error estimation. An optimization study has revealed that 0.75 wt.% of MWCNT, 1.5 wt.% of CuO, and 1.5 wt.% of BC are the optimum parameters with 0.063750 g/cm 3 density for obtaining the maximum EMI SE.

Water scarcity and clean drinking water remain a global challenge, particularly in remote and off-grid areas. Solar stills offer a low-cost, sustainable method for water purification. However, its low productivity and low efficiency are the major concerns for using it for large-scale applications. It provides low productivity because the evaporation and condensation rates in conventional solar stills (CSS) are limited by low heat transfer efficiency and large thermal losses. Wick materials increase surface area and heat transfer by dispersing water into a thin layer, which increases productivity and evaporation. Due to this, the proposed study aims to improve the performance of the inclined solar still (ISS) using different uncoated wick materials such as Flannel Cloth, Cotton Cloth, Coconut Coir mat, Jute, and Polypropylene materials. The performance enhancement without coating approach was used to avoid the additional cost, complexity, and maintenance associated with surface treatments or advanced material modifications in solar stills. Wick materials were used over the absorber plate without any coatings and compared with conventional ISS. Among the tested materials, the coconut coir mat provides the best performance. ISS with coconut coir provides water productivity of 4323 ml, whereas conventional ISS provides only 3303 ml. This water productivity of ISS with coir is 30.88% higher than that of conventional ISS. The average energy and exergy of ISS with coconut coir are 43.46% and 2.53%, which shows 62.40% and 86.02% higher energy and exergy efficiency compared to conventional ISS. The economic study gives the distilled water cost of $0.0131 for ISS with coconut coir, and this water production cost is 28.24% less compared to conventional ISS.

As noise pollution intensifies in urban areas, the need for sustainable and effective sound-reducing porous materials becomes increasingly critical. This research addresses that need by developing gypsum-based composites enhanced with vermiculite and recycled rigid polyurethane (RPU) powder, using a blend-press-sinter methodology. Gypsum-based composites were chosen for their cost-effectiveness, recyclability, structural stability, and sound-absorbing properties, all with minimal environmental impact. This approach supports the circular economy by repurposing waste materials. High-resolution scanning electron microscopy (HR-SEM) and Fourier transform infrared spectroscopy (FTIR) were employed to analyze the size, structure, uniformity, and presence of organic and inorganic compounds. Using response surface methodology (RSM) for optimization, the ideal formulation for the noise reduction coefficient (NRC) was identified, with an optimal mix of 5.3 wt% vermiculite and 6.5 wt% RPU, achieving an NRC value of 0.3628. Acoustic simulations using COMSOL Multiphysics, guided by the Johnson-Allard model, demonstrated that the optimized composite effectively reduced sound pressure levels by 17 to 58 dB across the 200 to 2000 Hz frequency range. These findings underscore the composite’s potential for room acoustics applications. By incorporating recycled and natural materials, this approach not only enhances acoustic performance but also promotes sustainable material practices.

The accumulation of polyurethane (PU) waste presents a critical environmental challenge due to the inefficiencies of traditional disposal methods like landfilling and incineration. This study introduces a sustainable approach by repurposing 99.89% pure rigid polyurethane foam granules (~ 150 µm) as fillers (5 wt.%) in bio-epoxy composites, complemented with 99.89% pure vermiculite particles (~ 10 µm) at varying concentrations (2–10 wt.%). Comprehensive characterization techniques, including high-resolution scanning electron microscopy (HR-SEM) and Fourier transform infrared spectroscopy (FTIR), were employed to evaluate the composites’ mechanical, thermal, electrical, acoustic, and electromagnetic interference (EMI) shielding properties. The study specifically measured EMI shielding effectiveness in the frequency range of 8–12 GHz. Among the formulations, sample S5 exhibited superior mechanical performance, with tensile strength (10.47 N/mm2), impact strength (0.006 kJ/cm2), and flexural strength (46.80 N/mm2). EMI analysis revealed a dielectric constant of 1.111 and shielding effectiveness of -35.24 dB, while sample S3 achieved optimal acoustic absorption (NRC 0.295). Thermal assessments showed the lowest thermal conductivity (0.141 W/mK) and a reduced burning rate (6.8 mm/min) for S5. These results highlight the viability of recycled PU foam-based composites in minimizing plastic waste and advancing net-zero carbon emission goals. Potential applications include battery enclosures, engine bay insulation, and cabin soundproofing in electric vehicles. This work establishes the novelty of integrating recycled materials into bio-epoxy matrices to address environmental challenges and create high-performance composites.

3D printing is a growing technology being incorporated into almost every industry. Although it has obvious advantages, such as precision and less fabrication time, it has many shortcomings. Although several attempts were made to monitor the errors, many have not been able to thoroughly address them, like stringing, over-extrusion, layer shifting, and overheating. This paper proposes a study using machine learning to identify the optimal process parameters such as infill structure and density, material (ABS, PLA, Nylon, PVA, and PETG), wall and layer thickness, count, and temperature. The result thus obtained was used to train a machine learning algorithm. Four different network architectures (CNN, Resnet152, MobileNet, and Inception V3) were used to build the algorithm. The algorithm was able to predict the parameters for a given requirement. It was also able to detect any errors. The algorithm was trained to pause the print immediately in case of a mistake. Upon comparison, it was found that the algorithm built with Inception V3 achieved the best accuracy of 97%. The applications include saving the material from being wasted due to print time errors in the manufacturing industry.

In aerospace applications, most of the components are made of composite materials due to the high strength-to-weight ratio. However, those composite structures are poor in sound absorption; for instance, payload fairing used in the launch vehicle system experiences broadband noise. Tuned Helmholtz resonator (HR) is being used to control few dominant low frequencies, and other frequency is left untreated. In this study, the acoustic mode of the rectangular cavity has been suppressed by a novel design of integrated passive elements (IPEs), which comprises a Helmholtz resonator, micro-perforated panel, and polyurethane foam. The proposed design reduces the noise level in Low-Mid-High frequencies, which is more efficient than passive elements used to control a single target frequency. The integrated passive components fabricated using the 3D printing technique are tested experimentally in an impedance tube to quantify the sound absorption coefficient, and the results are compared with the theoretical result. Further, the study presents a simplified approach for numerical simulation of fabricated samples coupled to a rectangular cavity system, which is validated experimentally. The overall sound pressure level (OSPL) results of the proposed design achieve 4–6 dB noise level reduction in 1 / 3 r d octave frequency band.

The novelty of this research lies in the successful fabrication of a 3D-printed honeycomb structure filled with nanofillers for acoustic properties, utilizing an impedance tube setup in accordance with ASTM standard E 1050-12. The Creality Ender-3, a 3D printer, was used for printing the honeycomb structures, and polylactic acid (PLA) material was employed for their construction. The organic, inorganic, and polymeric compounds within the composites were identified using fourier transformation infrared (FTIR) spectroscopy. The structure and homogeneity of the samples were examined using a field emission scanning electron microscope (FESEM). To determine the sound absorption coefficient of the 3D printed honeycomb structure, numerous samples were systematically developed using central composite design (CCD) and analysed using response surface methodology (RSM). The RSM mathematical model was established to predict the optimum values of each factor and noise reduction coefficient (NRC). The optimum values for an NRC of 0.377 were found to be 1.116 wt% carbon black, 1.025 wt% aluminium powder, and 3.151 mm distance between parallel edges. Overall, the results demonstrate that a 3D-printed honeycomb structure filled with nanofillers is an excellent material that can be utilized in various fields, including defence and aviation, where lightweight and acoustic properties are of great importance. [Display omitted]

Day by day gadgets are taking an irreplaceable role in our life. Humans are now depending on electronic gadgets. This increased usage and utility of these electronic gadgets increased the radiation; hence, it is important to research materials for better absorption of these radiations. In this research work, we are developing an electromagnetic interference shielding material. We used polyurethane foam (PU foam), an insulating material that has been filled with nanofillers Polyaniline (PANi), Zinc Oxide (ZnO), and MWCNT. The PU foam used was castor oil-based instead of going with petroleum-based. This work aims to achieve a potential material for electromagnetic interference shielding and sensing material that should be bio-degradable at a low price. The samples were fabricated using the taguchi method in the design of the experiment. This helps to reduce time consumption and provides more accurate results. Once the samples were fabricated, it was subjected to morphological study SEM and EDAX. EMI and conductivity were also carried out. The EMI experiment was done using setup model N5230A PNA-L. The conductivity test is done. GRA relational statistics was utilized to find the interrelation between the two output responses in the taguchi. The experiment concludes that the samples synthesized with 2 wt% of PANi, 300 rpm mixing rotation, and 10 min. Sonication time, provide the best conductivity of 900 S m −1 and EMI SE of 34.38 dB. The best result for conductivity is for sample 8. The maximum conductivity value is 900 S m −1 . The lightweight flexible conductive foams can be used in the application of biosensors.

Today, most commercial polyols used to make polyurethane (PU) foam are produced from petrochemicals. A renewable resource, castor oil (CO), was employed in this study to alleviate concerns about environmental contamination. This study intends to fabricate a bio-based and low-density EMI-defending material for communication, aerospace, electronics, and military appliances. The mechanical stirrer produces the flexible bio-based polyurethane foam and combines it with nanoparticles using absorption and hydrothermal reduction processes. The nanoparticles used in this research are graphite nanoplates (GNP), zirconium oxide (ZrO2), and bamboo charcoal (BC). Following fabrication, the samples underwent EMI testing using an EMI test setup with model number N5230A PNA-L. The EMI experimental results were compared with computational simulation using COMSOL Multiphysics 5.4 and an optimization tool using response surface methodology. A statistical design of the experimental approach is used to design and evaluate the experiments systematically. An experimental study reveals that a 0.3 weight percentage of GNP, a 0.3 weight percentage of ZrO2, and a 2.5 weight percentage of BC depict a maximum EMI SE of 28.03 dB in the 8–12 GHz frequency band.