Fibercuit: Prototyping High-Resolution Flexible and Kirigami Circuits with a Fiber Laser Engraver
August 17, 2022 Β· Declared Dead Β· π ACM Symposium on User Interface Software and Technology
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Zeyu Yan, Anup Sathya, Sahra Yusuf, Jyh-Ming Lien, Huaishu Peng
arXiv ID
2208.08502
Category
cs.HC: Human-Computer Interaction
Citations
30
Venue
ACM Symposium on User Interface Software and Technology
Last Checked
3 months ago
Abstract
Prototyping compact devices with unique form factors often requires the PCB manufacturing process to be outsourced, which can be expensive and time-consuming. In this paper, we present Fibercuit, a set of rapid prototyping techniques to fabricate high-resolution, flexible circuits on-demand using a fiber laser engraver. We showcase techniques that can laser cut copper-based composites to form fine-pitch conductive traces, laser fold copper substrates that can form kirigami structures, and laser solder surface-mount electrical components using off-the-shelf soldering pastes. Combined with our software pipeline, an end user can design and fabricate flexible circuits which are dual-layer and three-dimensional, thereby exhibiting a wide range of form factors. We demonstrate Fibercuit by showcasing a set of examples, including a custom dice, flex cables, custom end-stop switches, electromagnetic coils, LED earrings and a circuit in the form of kirigami crane.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted