Abstract The ability to manufacture highly intricate designs is one of the key advantages of 3D printing. Achieving high dimensional accuracy requires precise, often time‐consuming calibration of the process parameters. Computerized feedback control systems for 3D printing enable sensing and real‐time adaptation and optimization of these parameters at every stage of the print, but multiple challenges remain with sensor embedment and measurement accuracy. In contrast to these active control approaches, here, the authors harness frontal polymerization (FP) to rapidly cure extruded filament in tandem with the printing process. A temperature gradient present along the filament, which is dependent on the printing parameters, can impose control over this exothermic reaction. Experiments and theory reveal a self‐regulative mechanism between filament temperature and cure kinetics that allows the frontal cure speed to autonomously match the print speed. This self‐regulative printing process rapidly adapts to changes in print speed and environmental conditions to produce complex, high‐fidelity structures and freestanding architectures spanning up to 100 mm, greatly expanding the capabilities of direct ink writing (DIW).
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Towards a study protocol: A data-driven workflow to identify error sources in direct ink write mechatronics
Using Direct Ink Write (DIW) technology in a rapid and large-scale production requires reliable quality control for printed parts. Data streams generated during printing, such as print mechatronics, are massive and diverse which impedes extracting insights. In our study protocol approach, we developed a data-driven workflow to understand the behavior of sensor-measured X- and Y- axes positional errors with process parameters, such as print velocity and velocity control. We uncovered patterns showing that instantaneous changes in the velocity, when the build platform accelerates and decelerates, largely influence the positional errors, especially in the X- axis due to the hardware architecture. Since DIW systems share similar mechatronic inputs and outputs, our study protocol approach is broadly applicable and scalable across multiple systems.
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- Award ID(s):
- 2052776
- PAR ID:
- 10518361
- Publisher / Repository:
- SpringerLink
- Date Published:
- Journal Name:
- MRS Advances
- ISSN:
- 2059-8521
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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