In Case You Missed It
Additive Manufacturing
“Ultrafast Laser Direct Writing of Highly Conductive Copper Micropatterns”
Authors: S.Y. Xue, et al.
Abstract: Copper (Cu) interconnects are fundamental to advanced optoelectronic systems. Femtosecond laser direct writing (FsLDW) employing particle-free Cu ion inks provides a compelling “cold processing” approach; however, it frequently results in porous, high-resistivity structures caused by disordered grain growth and solvent-induced micro-explosions. Here, the authors report a high-precision FsLDW strategy utilizing a specifically formulated metal-organic complex ink. By decreasing the reduction energy barrier and regulating crystallization via a composite amine complex, combined with a pre-baking step to suppress micro-explosions, the authors achieve Cu micropatterns with a highly dense surface morphology under ambient conditions. The resulting structures demonstrate a minimum resistivity of 9.34μΩ·cm (approximately 5.5 times that of bulk Cu) while maintaining sub-10μm linewidths. Moreover, this method exhibits broad processing adaptability and substrate compatibility, facilitating reliable metallization on flexible substrates, macroscopic wafers and curved surfaces. The fabricated Cu interconnects function as stable signal and power transmission pathways within a fully FsLDW-patterned UV photodetector. This study establishes a practical route for deploying high-performance conductive networks in advanced electronic systems. (Opto-Electronic Manufacturing, vol. 1, article 260002, 2026, https://doi.org/10.29026/oem.2026.260002)
Flexible/Wearable Electronics
“Programmable Spinning of Integrated Circuit Fibers”
Authors: Fengqiang Sun, et all.
Abstract: Textiles based on electronic fibers can be used to integrate sensing, processing, and feedback into a single wearable platform. However, embedding circuit-level functionality directly into fibers remains challenging due to poor fiber utilization and unstable interconnects. Here the authors report a programmable microfluidic spinning process to fabricate integrated circuit fibers. The approach combines conductive layers with different functional layers to create distinct modules capable of electron–photon conversion, electron–electron conversion, electron–ion carrier conversion and electro-quasistatic modulation. By arranging and integrating these modules during microfluidic spinning, customizable circuits within a single fiber can be built. The fibers can then be woven, sewn and arranged into textiles and can withstand repeated deformation and washing. The authors use the approach to create electroluminescent fibers for light emission, resistor and capacitor fibers for analog signal processing, organic electrochemical transistor fibers for digital logic operations, and electro-quasistatic fibers for touchless sensing and control. (Nature Electronics, Oct. 2026, https://www.nature.com/articles/s41928-026-01712-2)
Inspection
“CDA-YOLO: An Improved YOLOv11 Model for PCB Defect Detection”
Authors: Anlong Yuan and Jingmin Li
Abstract: Printed circuit boards (PCBs) are fundamental to modern electronic systems, and their manufacturing quality directly determines the performance and reliability of the final product. However, existing YOLO‑based defect detection models still face critical challenges, including high miss rates for tiny defects and frequent false positives caused by complex background textures. To address these issues, the authors propose CDA‑YOLO, an enhanced YOLOv11 framework incorporating three key innovations. First, a Cross-level Bidirectional Feature Pyramid Network (CBiFPN) is designed, which effectively alleviates the loss of fine-grained details of small targets as features propagate through deep layers. Second, a lightweight Dual-Scale Convolution module (DualScaleConv) is proposed, which employs a parallel branch structure to simultaneously capture local details and global contextual information. Finally, a parameter-free average attention mechanism (PfAAM) is integrated into the C3k2 module to enhance the feature response in defect-related regions and suppress background noise. Experimental results demonstrate that the proposed model achieves competitive performance on the PCB defect dataset, with mAP@0.5 reaching 96.1% and mAP@0.5:0.95 reaching 56%, corresponding to improvements of 2.8% and 3.4% over the baseline YOLOv11, respectively. These results validate that CDA-YOLO offers an efficient and robust solution for industrial-grade PCB defect detection. (Scientific Reports, Oct. 19, 2026, https://doi.org/10.1038/s41598-026-74471-x)
Power Electronics
“A 98.8%-Efficient, Thermally-Optimized 48V-to-12V DC–DC Converter for High-Power Data Centers”
Authors: Ziqian Zhang
Abstract: This work presents the design of a 48V-to-12V high-power DC–DC converter based on a resonant switched-capacitor topology. By employing zero-current switching (ZCS) control, the prototype achieves a peak efficiency of 98.8% and a full-load efficiency of 96.1% under a 70 A load condition. To address the stringent power delivery requirements in data center high-performance computing (HPC) applications, particular emphasis is placed on optimizing PCB stack-up and via structures. A comparative study of different substrate designs demonstrates that an optimized multilayer PCB architecture improves the conversion efficiency by an additional 1.5%, while reducing the temperature rise of key power devices by 9.6 °C. Experimental validation confirms that the proposed design not only achieves ultra-high conversion efficiency but also significantly enhances thermal performance. The converter consistently maintains excellent electrical characteristics and thermal stability across a wide load range, meeting the requirements of modern data center power systems for high efficiency, high power density and high reliability. (Frontiers in Electronics, vol. 7, article 1697781, Apr. 15, 2026, https://www.frontiersin.org/journals/electronics/articles/10.3389/felec.2026.1697781/full)End of article content