Multiscale structured polymers have been considered as a promising category of functional materials with unique properties. We combined rapid prototyping and gas foaming technologies to fabricate multiscale functional materials of superior mechanical and thermal insulation properties. Through scanning electron microscope based morphological characterization, formation of multiscale porous structure with nanoscale cellular pores was confirmed. Improvement in mechanical strength is attributed to rearrangement of crystals within CO₂ saturated grid sample. It is also shown that a post-foaming temperature higher than the glass transition temperature deteriorates mechanical strength, providing process guidelines. Thermal decomposition of filament material sets the upper limit of temperature for 3D printed features, characterized by simultaneous differential scanning calorimetry and thermogravimetric analysis. Porosity of the fabricated 3D structured polylactic acid (PLA) foam is controllable by suitable tuning of foaming conditions. The fabricated multiscale 3D structures have potential for thermal insulation applications with lightweight and reasonable mechanical strength.

In this study, a single paragraph of acrylonitrile-butadiene-styrene (ABS)/recycled polyethylene terephthalate (R-PET) polymeric foams is prepared using CO₂ as a blowing agent. First, the sorption kinetics of subcritical and supercritical CO₂ are first studied at saturation temperatures from −20 to 40 °C and a pressure of 10 MPa, in order to estimate the diffusion coefficient and the sorption amount. As the sorption temperature increases, the diffusion coefficient of CO₂ increases while the sorption amount decreases. Then, a series of two-step solid-state foaming experiments are conducted. In this process, a specimen is saturated with liquid CO₂ and foamed by dipping the sample in a high-temperature medium at 60 to 120 °C. The effects of foaming temperature and depressurization rate on the morphology and structure of ABS/R-PET microcellular foams are examined. The mean cell size and the variation of the cell size distribution increases as the foaming temperature and the depressurization rate increases.

A partially foamed lattice structure based on synthetic polymers was considered as a functionally graded materials due to their unique properties. In this study, a copolymer is manufactured to be porous functional materials by physical foaming technology, using carbon dioxide. Through morphological characterization, using scanning electron microscope, we identified a potential to fabricate partially foamed structures with micropores. We showed that variation of post-foaming temperature can tune the pore size distribution in the range of 0.9 to 30 μm. Thermal data of the foam grid from differential scanning calorimeter showed some shifts in glass transition, cold crystallization, and melting points. Mechanical strength and thermal conductivity were also measured to find rationale of thermal insulation with tunable mechanical strength and to elucidate the actual 3D lattice foam of a copolymer.

Energy consumption modeling has evolved along with building technology. Modeling techniques can be largely classified into white box, gray box, and black box. In this study, the thermal behavior characteristics of building components were identified through time-series data analysis using LSTM neural networks. Sensors were installed inside and outside the test room to measure physical quantities. As a result of calculating the overall heat transfer coefficient according to the international standard ISO 9869-1, the U value of the multi-window with antireflection coating was 1.84 W/(m²∙K). To understand the thermal behavior of multiple windows, we constructed a neural network using an LSTM architecture and used the measured data-set to predict and evaluate the heat flux through deep learning. From the measurement data, a wavelet transform was used to extract features and to find appropriate control time-step intervals. Performance was evaluated according to multistep measurement intervals using the error metric method. The multistep time interval for control monitoring is preferably no more than 240 s. In addition, multivariate analysis with several input variables was performed. In particular, the thermal behavior of building components can be analyzed through heat flux and temperature measurements in the transient state of physical properties of pre-installed building components, which were difficult to access with conventional steady-state measurement methods.