Encapsulating laser-induced graphene to enhance its electrical and mechanical properties
Bibliographic record
Abstract
Laser-induced graphene (LIG) has emerged as a promising material in the field of printed electronics, offering excellent electrical conductivity and versatility. Its versatility stems from multiple factors: the potential for low-cost, facile, and rapid production without toxic chemicals (unlike traditional copper traces on printed circuit boards); the ability to be fabricated on various substrates; its customizable properties and its large surface area. However, the inherent fragility of its structure poses a significant challenge, as it can be easily damaged or removed even by touching or under mechanical forces, limiting its practical applications. While a few encapsulation techniques have been explored to enhance the mechanical robustness of LIG, they often result in a significant increase in electrical resistance, diminishing its conductivity to the point where it becomes impractical for use as conductive traces in printed electronics. In this study, we present a novel and facile approach to encapsulating LIG inscribed on a Kapton substrate while preserving the LIG's remarkable electrical properties. Through a simple and cost-effective encapsulation process involving controlled pressure application, we successfully limited the increase in resistance to just 5\% of the LIG’s original value. This optimal result was achieved with an applied pressure of 80 psi using a hydraulic press. The fabricated LIG exhibited a low initial sheet resistance of approximately 2.2 $\Omega/ \text{sq}$, making it a promising candidate for applications requiring this level of resistance. Our approach offers a straightforward solution to enhancing the mechanical robustness of LIG while maintaining its desirable electrical characteristics, potentially broadening its applicability in flexible electronics and related fields. Comprehensive characterization techniques, including Raman spectroscopy and scanning electron microscopy (SEM) were employed to investigate the structural and morphological properties of the encapsulated LIG. The results obtained from these analyses validate the efficacy of our encapsulation approach in preserving the desirable properties of LIG while enhancing its mechanical durability. The findings of this research open up new avenues for the practical implementation of LIG in various electronic devices and applications where mechanical robustness and high conductivity are essential requirements, such as flexible and wearable electronics and flexible interconnects for conformable electronic systems. Future research endeavors can focus on further optimizing the encapsulation process, exploring alternative substrate materials, and investigating the potential integration of encapsulated LIG into diverse electronic systems and components.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".