In Situ Changes in Mechanical Properties Based on Gas Saturation Inside Pressure Vessels.

In previous studies, difficulties were encountered in measuring changes within high-pressure vessels owing to limitations such as sensor connectors and sensor failures under high-pressure conditions. In addition, polymer-gas mixtures experience instantaneous gas desorption upon exiting high-pressure vessels owing to pressure differentials, leading to measurement errors. In this study, a device using magnetic sensors was developed to measure the real-time changes in gas-saturated polymers inside pressure vessels. Experiments on polymethyl methacrylate gas adsorption were conducted with parameters including pressure at 5 MPa and temperatures ranging from -20 to 40 °C for 60 and 180 min. It was observed that at -20 °C, the maximum magnetic field force density and deflection were 391.53 µT and 5.83 mm, respectively, whereas at 40 °C, deflection did not occur, with a value of 321.79 µT. Based on gas saturation experiments, a new model for deflection in high-pressure atmospheres is proposed. Additionally, an ANSYS analysis was conducted to predict the changes in Young's modulus based on gas saturation. In previous studies, mechanical properties were measured outside the pressure vessel, resulting in an error due to a pressure difference, while the proposed method is characterized by the ability to directly measure polymer behavior according to gas saturation in high-pressure vessels using a magnetic sensor in real time. Therefore, it is possible to predict polymer behavior, making it easy to control variables in high-pressure polymer processes.

Solid-State Surface Patterning on Polymer Using the Microcellular Foaming Process.

This study proposes a novel process that integrates the molding and patterning of solid-state polymers with the force generated from the volume expansion of the microcellular-foaming process (MCP) and the softening of solid-state polymers due to gas adsorption. The batch-foaming process, which is one of the MCPs, is a useful process that can cause thermal, acoustic, and electrical characteristic changes in polymer materials. However, its development is limited due to low productivity. A pattern was imprinted on the surface using a polymer gas mixture with a 3D-printed polymer mold. The process was controlled with changing weight gain by controlling saturation time. A scanning electron microscope (SEM) and confocal laser scanning microscopy were used to obtain the results. The maximum depth could be formed in the same manner as the mold geometry (sample depth: 208.7 µm; mold depth: 200 µm). Furthermore, the same pattern could be imprinted as a layer thickness of 3D printing (sample pattern gap and mold layer gap: 0.4 mm), and surface roughness was increased according to increase in the foaming ratio. This process can be used as a novel method to expand the limited applications of the batch-foaming process considering that MCPs can impart various high-value-added characteristics to polymers.

Modeling and Experiment for the Diffusion Coefficient of Subcritical Carbon Dioxide in Poly(methyl methacrylate) to Predict Gas Sorption and Desorption.

Several researchers have investigated the phenomenon of polymer-gas mixtures, and a few have proposed diffusion coefficient values instead of a diffusion coefficient model. There is a paucity of studies focused on the continuous change in the diffusion coefficient corresponding to the overall pressure and temperature range of the mixture. In this study, the gas sorption and desorption experiments of poly(methyl methacrylate) (PMMA) were conducted via solid-state batch foaming, and the weight change was measured using the gravimetric method with a magnetic balance. The control parameters were temperature, which ranged from 290 to 370 K, and pressure, which ranged from 2 to 5 MPa in the subcritical regime. Based on the experimental data, the diffusion coefficient of the PMMA was calculated using Fick's law. After calculating the diffusion coefficient in the range of the experiment, the diffusion coefficient model was employed using the least-squares method. Subsequently, the model was validated by comparing the obtained results with those in the literature, and the overall trend was found to be consistent. Therefore, it was confirmed that there were slight differences between the diffusion coefficient obtained using only Fick's equation and the value using by a different method.

Mechanical Properties of Biocomposites Using Polypropylene and Sesame Oil Cake.

Sesame oil cakes (SOC) produced during sesame oil production can be classified as plant residues. This study aims to use SOC as a composite material for injection molding. A biocomposite containing polypropylene (PP) and SOC, namely PP/SOC, was developed and its mechanical properties were evaluated. PP/SOC is largely divided into Homo-PP/SOC (HPS) based on Homo-PP and Block-PP/SOC (BPS) based on block-PP. The specimens containing 0-50 wt% SOC were prepared through extrusion and injection molding. As a result of the evaluation, SOC acted as a reinforcement in the matrix, and HPS and BPS showed improved flexural modulus by 36.4% and 37.3% compared to the neat PP, respectively. Tensile strength, on the other hand, decreased by 58% and 55.1%, respectively. To analyze the cause of this, cross-section observation was conducted through scanning electron microscope (SEM), and phase separation and voids were confirmed to be the cause of this. Impact strength of PP/SOC tended to vary depending on the type of matrix. HPS increased by 30.9% compared to neat PP, and BPS decreased by 25%. This tendency difference appears to be the result of SOC inhibiting crystallization of PP, and it has been confirmed through x ray diffraction (XRD) and differential scanning calorimetry (DSC) analysis. Moreover, PP/SOC can be manufactured at a low cost and is environmentally friendly because it utilizes SOC, a plant residue. It can also be applied to commercial products, such as food packaging, owing to its good moldability and improved mechanical properties.

Learning analytics dashboards for adaptive support in face-to-face collaborative argumentation.

Despite the potential of learning analytics for personalized learning, it is seldom used to support collaborative learning particularly in face-to-face (F2F) learning contexts. This study uses learning analytics to develop a dashboard system that provides adaptive support for F2F collaborative argumentation (FCA). This study developed two dashboards for students and instructors, which enabled students to monitor their FCA process through adaptive feedback and helped the instructor provide adaptive support at the right time. The effectiveness of the dashboards was examined in a university class with 88 students (56 females, 32 males) for 4 weeks. The dashboards significantly improved the FCA process and outcomes, encouraging students to actively participate in FCA and create high-quality arguments. Students had a positive attitude toward the dashboard and perceived it as useful and easy to use. These findings indicate the usefulness of learning analytics dashboards in improving collaborative learning through adaptive feedback and support. Suggestions are provided on how to design dashboards for adaptive support in F2F learning contexts using learning analytics.

Effective virtual patient simulators for medical communication training: A systematic review.

CONTEXT: Despite the growing use of virtual patients (VPs) in medical education, few studies have explored the features and effectiveness of VP-based medical communication skills training. We undertook a systematic review to summarise the design and evaluation of VP-based medical communication skills training systems in order to identify features of successful cases. METHODS: Following PRISMA guidelines, we searched four databases for studies published between 2006 and 2018. Using a refined classification scheme, we extracted data on instructional design (scenario and instructional intervention), technological design (modality and interaction), and evaluation (user experience, learning effectiveness and evaluator). We assessed the quality of studies using the Medical Education Research Study Quality Instrument (MERSQI) and the QualSyst standard assessment criteria. RESULTS: A total of 14 studies were included for review. Of these, 85.7% (n = 12) were quantitative and 71.4% (n = 10) involved undergraduate students. The most common VP training scenario was history taking followed by the delivery of bad news. Diverse instructional interventions, including tutorials, learning activities, and feedback, were embedded in the VPs. The first-person perspective animated within-screen size VP was a popular technological feature. Most evaluations concerned the reality of simulation (for user experience) and skill in expressing empathy (as a learning outcome). Of the eight comparative studies, half reported significant attitude or skill improvements in the VP group. The distinct features of VPs shown to be effective were well-designed instructional interventions (eg, a pre-activity with a protocol-informed tutorial), and post-activity (eg, debrief or reflection), scaffolding and human feedback, but not system feedback. CONCLUSIONS: Evidence-based VP training can enable students to gain communication skills in a safe and affordable learning environment. Elaborate technology alone cannot guarantee effective learning, but evidence-based instructional interventions can facilitate its optimal use and bring about better learning outcomes.