Elaboration and Physico-Chemical Characterization of the Gibbsite Li(OH)3 Hybrid Material

The compatibilization of raw bentonite (bent) with a polymer matrix of polypropylene (PP) can improve the performance of the material in terms of thermal and mechanical properties. In this study, two kinds of untreated bentonite, bentonite-Maghnia (bent-m) and bentonite-Mostaganem (bent-M), that differ in the proportion of Al2O3 and in the particle size distribution were coupled to typical maleic anhydride grafted polypropylene PP-MA. Stearic Acid (SA) and L-leucine Amino Acid (AA) were selected as new coupling modifiers at a 5/5 ratio of bentonite/coupling agent. All PP/bent composites were prepared by melt mixing at 190°C. Morphological observation revealed a good dispersion of bentonite into the PP matrix in the presence of AA, SA, and PP-MA. Mechanical properties showed an increase in stiffness as bent-m or bent-M were associated with AA. For instance, PP/bent-m/AA composite underwent an improvement of about 13% in Young’s modulus as compared to neat PP. On the other hand, the addition of SA into bent-m maintained stiffness and tensile strength at an acceptable level. An increase of around 40°C and 37% in the decomposition temperature and elongation at break was respectively observed for the PP/bent-m/SA composite. All coupled composites showed high degradation temperatures.

Section: G Thermogravimetric Analysis (Tga)mentioning

confidence: 99%

Preparation of Polypropylene/Bentonite Composites of Enhanced Thermal and Mechanical Properties using L-leucine and Stearic Acid as Coupling Agents

Mohammedi

Zoukrami

Haddaoui

2021

Influence of Membrane Type on Some Electrical Properties of a Single Microbial Fuel Cell

Bouzidi

Otmani

Doufnoune

et al. 2022

The effects of different parameters on the electric output of air-cathode microbial fuel cells were investigated in this work. The single microbial fuel cell was equipped by modifying Proton Exchange Membranes (PEM). Two membrane types were prepared: first by using the combination of Poly Vinyl Alcohol (PVA) with Polystyrene Sulfonate (PSSNa), while the second membrane was elaborated by mixing Poly Vinyl Chloride (PVC) with Methyl Tri-Octyl Ammonium (MTOA) chloride. The PEMs were incorporated into the air-cathode to form a Membrane Electrode Assembly (MEA) to promote electricity generation. PVA/PSSNa and PVC-MTOA membranes were synthesized by solution casting method. Fourier Transform Infrared Spectroscopy (FTIR), Ultraviolet (UV) Visible spectroscopy, Scanning Electronique Microscope (SEM), Differential Scanning Calorimetry (DSC), and water Contact Angle (CA) were used as characterization techniques to explore the membrane structure and properties. The performance and the electric capacity of the microbial fuel cell in real time were operated using an external resistance of 5kΩ. Impedance and resistance capacity were determined using the polarization method. It was found that the internal resistance of the PVA/PSSNa and PVC-MTOA membranes were 50 and 350Ω respectively. The voltage values at open circuit of the cells using PVA/PSSNa and PVC-MTOA membranes were 600mV and 150mV respectively. The values of power, current, and power density, are quite interesting. Cells with PVA/PSSNa and PVC-MTOA membranes gave values of 18.24 and 9.64mW.cm-2 respectively.

Design and Simulation of a Microcantilever Sensor for Precise Detection of Volatile Organic Compounds

Pancheti,

Shanmugaraja,

Srinivas

2024

This study presents the coating of a thin film of conducting polymer on a silicon cantilever sensor. The mechanical changes in the coated microcantilever, a bimaterial, were investigated when various volatile substances, such as methanol, ethanol, acetone, propanol, dichloroethane, and toluene were added. The results showed that the coated microcantilever is much more sensitive than the uncoated one. The maximum sensitivity observed was 40.14 kHz/ppm, demonstrating a 33.8% improvement over existing systems. Findings revealed that the maximum sensitivity achieved with the proposed sensor was 83%, and the overall improvement was 6.41%. The sensors' responses were found to be reversible, sensible, fast, and proportional to the volatile concentration.