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.

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.

This study investigates the modeling and experimental validation of cell morphology in microcellular-foamed polycaprolactone (PCL) using supercritical carbon dioxide (scCO₂) as the blowing agent. The microcellular foaming process (MCP) was conducted using a solid-state batch foaming process, where PCL was saturated with scCO₂ at 6 to 9 MPa and 313 K, followed by depressurization at a rate of −0.3 and −1 MPa/s. This study utilized the Sanchez–Lacombe equation of state and the Peng–Robinson–Stryjek–Vera equation of state to model the solubility and density of the PCL-CO₂ mixture. Classical nucleation theory was modified and combined with numerical analysis to predict cell density, incorporating factors such as gas absorption kinetics, the role of scCO₂ in promoting nucleation, and the impact of depressurization rate and saturation pressure on cell growth. The validity of the model was confirmed by comparing the theoretical predictions with experimental and reference data, with the cell density determined through field-emission scanning electron microscopy analysis of foamed PCL samples. This study proposes a method for predicting cell density that can be applied to various polymers, with the potential for wide-ranging applications in biomaterials and industrial settings. This research also introduces a Python-based numerical analysis tool that allows for easy calculation of solubility and cell density based on the material properties of polymers and penetrant gases, offering a practical solution for optimizing MCP conditions in different contexts.

Traditionally, the microcellular foaming process has aimed to generate uniform cell structures by applying heat uniformly to all surfaces of a polymer. Homogeneous cell distribution is known to enhance the mechanical properties and durability of the final product. However, the ability to engineer a gradient in cell density offers potential advantages for specific functional applications, such as improved sound absorption and thermal insulation. In this study, a controlled thermal gradient was introduced by heating only one side of a fully CO₂-saturated poly(methyl methacrylate) (PMMA) specimen. This approach allowed for the formation of a cell density gradient across the sample thickness. The entire process was conducted using a solid-state batch foaming technique, commonly referred to as the microcellular foaming process. A one-sided heating strategy successfully induced a spatial variation in cell morphology. Furthermore, a coalescence function was developed to account for cell merging behavior, enabling the construction of a predictive model for local cell density. The proposed model accurately captured the evolution of cell density gradients under asymmetric thermal conditions and was validated through experimental observations, demonstrating its potential for precise control over foam structure in saturated PMMA systems.

Four-dimensional (4D) printing adds the dimension of time to 3D-printed specimens, causing movement when external stimuli are applied. This movement enables applications across various fields, including the soft robotics, aerospace, apparel, and automotive industries. Traditionally, 4D printing has utilized special materials such as shape-memory polymers (SMPs) or shape-memory alloys (SMAs) to achieve this movement. This study explores a novel approach to 4D printing by applying microcellular foaming processes (MCPs) to 3D printing. This study primarily aims to design and fabricate patterned specimens using common materials, such as PLA, through 3D printing and to analyze their dynamic behavior under various foaming conditions. To demonstrate the potential applications of this technology, the degree of bending was measured by controlling the patterning and foaming conditions. The 3D-printed specimens with microcellular foaming exhibited predictable deformations owing to the asymmetric expansion caused by differential gas saturation. The results confirm that 4D printing can be realized using conventional materials without the need for smart materials and can introduce foaming processes as a new external stimulus. This study highlights the potential of combining 3D printing with microcellular foaming for advanced 4D printing applications.

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.