To tackle the insulation challenges present in packaging medium-voltage silicon carbide power devices, we developed a package design for a 20-kV silicon carbide diode. This design incorporates a nonlinear resistive polymer-nanoparticle composite to boost insulation without compromising thermal performance. Employing a "sandwich" structure, where diodes are connected between direct-bonded copper substrates, our approach minimizes parasitic inductance (<4.5 nH) through a wire-bond-less design. According to thermal simulations, this configuration leads to a junction temperature reduction up to 53.5 oC. The submodule configuration not only cuts the total deformation by a factor of three but also enhances both reliability and manufacturability. By coating the electrode triple points with the resistive composite, electric field stress is diminished. Experimental tests indicated a 96% rise in the partial discharge inception voltage of substrates, increasing from 15.6 kV to 30.6 kV. For validation, scaled-down packages equipped with silicon carbide diodes exceeding 16 kV were fabricated and put through rigorous testing.

The efficiency and power density of power conversion systems can be greatly improved by utilizing gallium nitride high-electron-mobility transistors (GaN HEMTs) due to their ultra-low on-resistances and switching energy losses. However, the wide adoption of these transistors is hindered by the challenges of packaging them within power modules to minimize parasitic inductances and maximize heat extraction. To address these challenges, in this article a packaging concept is proposed and experimentally validated for a 650 V/150 A commercial GaN HEMT in a half-bridge module with double-sided cooling (DSC). The module contains two devices sandwiched between two direct-bond copper substrates and connected face-to-face through a third direct-bond-copper interposer. Compared to a traditional wire-bond package layout, this design results in a module footprint that is at least two times smaller. Additionally, decoupling capacitors are included between the two substrates to reduce the power loop inductance to 2.087 nH. The implementation of DSC in this package reduces the junction-to-case thermal resistance of the module to 0.079°C/W. This packaging technique is a significant step toward overcoming the packaging challenges associated with GaN HEMTs and increasing their widespread use in power conversion systems.

This study investigates the modulation effects of varying infill densities and phase angles on the radiation attenuation properties of three 3D-printed polymers: acrylonitrile butadiene styrene (ABS), polylactic acid (PLA), and thermoplastic polyurethane (TPU). Using the EpiXS software for radiation attenuation calculations, the study assessed the linear attenuation coefficients (LACs) of the materials under different infill densities (30%, 50%, 70%, 90%, and 100%) and phase angles (0°, 30°, 45°, 60°, and 90°) for radiation in the 1–100 keV energy range, which corresponds to the X-ray spectrum. TPU demonstrated the highest attenuation values, with a baseline coefficient of 20.199 cm⁻¹ at 30% infill density, followed by PLA at 18.835 cm⁻¹, and ABS at 13.073 cm⁻¹. Statistical analysis via the Kruskal–Wallis test confirmed that infill density significantly impacts attenuation, while phase angle exhibited no significant effect, with p-values exceeding 0.05 across all materials. TPU showed the highest sensitivity to infill density, with a slope of 1.1194, compared to 0.7257 for ABS and 0.9251 for PLA, making TPU the most suitable candidate for radiation protection applications, particularly in applications where flexibility and high attenuation are required. The findings support the potential of 3D printing to produce customized, cost-effective radiation protection gear for medical and industrial applications. Future work can further optimize material designs by exploring more complex infill geometries and testing under broader radiation spectra.

This study explores the development of lattice-based panels for satellite applications using Direct Metal Laser Sintering and aimed to optimize lightweight, high-strength structures suitable for CubeSat deployment. Three lattice configurations namely Body-Centered Cubic, Octet, and Gyroid were evaluated. While Gyroid lattices exhibited the highest compressive strength at 13,825.8 N, the BCC lattice was selected for the final design due to superior manufacturability and weight reduction potential. The final optimized panel weighed 185.7 g, achieving an 11.4% reduction from the initial rib-type design and a 65.2% reduction from a solid panel. Finite Element Analysis and mechanical testing confirmed that the fabricated structures met the necessary mechanical requirements for aerospace launch conditions.

Additive Manufacturing (AM) process parameters significantly influence the thermal, mechanical, and surface roughness properties of printed parts. While experimental characterization is highly accurate, it is often excessively time-consuming and costly, hindering the development of scalable predictive models. This study adopts a Materials Informatics approach to curate a multi-sourced benchmarking dataset comprising 543 entries for ABS, PLA, and TPU filaments, integrating data from web-scraping (WSDS), literature (LDDS), and manufacturer technical datasheets (MTDS). Data cleaning included outlier detection via Tukey’s fences and the evaluation of imputation strategies, with K-Nearest Neighbors (KNN) consistently outperforming simple mean/median methods. We evaluated three regression models, Random Forest (RF), Ridge Regression (RR), and Support Vector Regression (SVR), using a nested cross-validation pipeline to predict tensile strength, elongation, and surface roughness. The results reveal significant data gaps in existing literature, with missingness exceeding 60% for critical parameters like fan speed and wall thickness. While the Random Forest model achieved high predictive accuracy for bulk mechanical properties, specifically a test-set R2 of 0.995 for PLA elongation, all models struggled with surface roughness, often yielding negative R2 values. This suggests that current process descriptors are insufficient to capture the stochastic nature of surface morphology. This work provides a foundational benchmarking dataset for the research community and highlights the necessity for stricter data mining protocols and more sophisticated feature engineering to achieve reliable predictive quality in material extrusion (MEX) polymers.

This study investigates the modulation effects of varying infill densities and phase angles on the radiation attenuation properties of three 3D-printed polymers: acrylonitrile butadiene styrene (ABS), polylactic acid (PLA), and thermoplastic polyurethane (TPU). Using the EpiXS software for radiation attenuation simulations, the study assessed the linear attenuation coefficients (LAC) of the materials under different infill densities (30%, 50%, 70%, 90%, and 100%) and phase angles (0°, 30°, 45°, 60°, and 90°) for radiation in the 1-100 keV energy range, which corresponds to the X-ray spectrum. TPU demonstrated the highest attenuation values, with a baseline coefficient of 20.199 cm⁻¹ at 30% infill density, followed by PLA at 18.835 cm⁻¹, and ABS at 13.073 cm⁻¹. Statistical analysis via the Kruskal-Wallis test confirmed that infill density significantly impacts attenuation, while phase angle exhibited no significant effect, with p-values exceeding 0.05 across all materials. TPU showed the highest sensitivity to infill density, with a slope of 1.1194, compared to 0.7257 for ABS and 0.9251 for PLA, making TPU the most suitable candidate for radiation shielding applications, particularly in applications where flexibility and high attenuation are required. The findings support the potential of 3D printing to produce customized, cost-effective radiation protection gear for medical and industrial applications. Future work can further optimize material designs by exploring more complex infill geometries and testing under broader radiation spectra.