Abstract:In this paper, the influence of the molecular structure of polylactide (PLA)-characterised by its molar mass and content of D-lactide isomer-on the molecular ordering and α'-α form transition during fibre manufacturing by the wet spinning method is described. Fibres were studied by wide-angle X-ray diffraction (WAXD) and differential scanning calorimetry (DSC). Additionally, the physical and mechanical properties of the fibres were determined. This study also examines the preliminary molecular ordering and crystallisation of PLA fibres at various draw ratios. The performed experiments clearly show the dependence of the molecular ordering of PLA on the molar mass and D-lactide content during the wet spinning process. The fibres manufactured from PLA with the lowest content of D-lactide and the lowest molar mass were characterised by a higher tendency for crystallisation and a higher possibility to undergo the disorder-to-order phase transition (α' to α form). The structural changes in PLA explain the observed changes in the physical and mechanical properties of the obtained fibres.
We evaluated a solvent vapor-sensitive, non-woven fabric made from a biodegradable, poly(lactic acid) (PLA) polymer loaded with multi-walled carbon nanotubes. The sensory properties of the fabric were obtained by optimizing the process parameters for manufacturing the melt-blown, non-woven fabric composed of 98% PLA 4060D (Nature Works) and 2% multi-walled carbon nanotubes (Nanocyl®). The diffusion of polar and non-polar solvent molecules influenced the electron flow between the separated carbon nanotubes in percolation paths built into the PLA, resulting in an increase of the resistance of the melt-blown, non-woven fabrics. The statistically significant differences between the mean values of electrical resistance before and after the influence of the tested solvent vapors were achieved for the non-woven fabrics manufactured at high air velocity and low extruder screw speed, taking the values of 30 m3/h and 20 rpm, respectively. The results obtained for the non-woven fabric manufactured in the optimal conditions show that methanol vapor response has the lowest amplitude of 15%, whereas for benzene, acetone and toluene sensitivity reaches values of 60%, 40%, and 35%, respectively. The values of the relative resistance amplitude correspond with Flory–Huggins interaction parameters κPLA\benzene < κPLA\acetone < κPLA\toluene < κPLA\methanol.
The main aim of this research was to detail the use of melt-blown technology to manufacture a temperature-sensitive nonwoven fabric. The sensor properties of the fabric were achieved by application of the optimal composition of immiscible polymer blends loaded with multiwall carbon nanotubes (MWCNTs). As the sensing phase, a dispersion of MWCNTs in poly(e-caprolactone) (PCL) was used. The sensing phase was blended with a matrix made of polypropylene (PP). Three different polymer compositions were subjected to the melt-blowing process, changing the proportion of the matrix polymer to the dispersed phase to the range of 50-70% and changing the MWCNTs content to be between 1.2 and 2%. The selection of technological parameters was based on the thermal characteristics of the polymers used. Nonwoven fabrics made of these composites were characterized by measuring their electrical properties as a function of external stimuli. In particular, their responses to cycle changing of temperature in a range of 20-80 C were monitored. The 70%PP/28.8%/1.2%MWCNT nonwoven fabrics were observed to show the best sensitivity to changes in temperature between 50 and 60 C.
This qualitative study investigated the experience of a cohort of students exposed consecutively to two substantially different environments in their General Chemistry Laboratory programme. To this end, the first semester in a traditional expository programme was followed by a semester in a cooperative, problem-based, multi-week format. The focus on the experience of a change in the laboratory format is complementary understanding to that from participants exposed to a single format. This work used a phenomenological approach for the reduction, analysis, and interpretation of data gathered from semi-structured student interviews. Through deep analysis, five researchers distilled an outcome space with three fundamental features: (1) ten vectors of change that served as lens to analyse the phenomenon; (2) participants' ability to accurately characterise and differentiate the two instructional environments; and (3) an overarching descriptor that argues that a transition from mindless behaviour to mindful engagement subsumed the experience of a change in the laboratory environment. This outcome space is independent of participants' instructional style preferences. Findings from this work inform the design of laboratory experiences furthering the potential realisation of experimental education at the same time when they extend understanding of learning in the chemistry laboratory.
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