Wood Bark-Based Films as Electrical Insulators with Ultralow Dielectric Constant and Loss Factor
Bibliographic record
Abstract
Dielectric polymers, particularly thermally stable synthetic types, play a crucial role in capacitors, circuit boards, insulators, and high-frequency devices. However, they also contribute significantly to electronic waste, making up approximately 20% of the 74.7 million metric tons of e-waste generated each year. Unfortunately, less than 18% of this waste is properly recycled, posing serious risks to human health and the environment. To address these challenges, we present a circular approach to fabricating biobased dielectric structures with ultralow dielectric constant and dielectric loss factor. Our method utilizes forestry residues derived from birch bark, after the extraction of high-value bioactive compounds. Specifically, we process the thermally stable, lignin-rich fibers in the residual bark through partial dissolution and cross-linking to produce “birch dielectric (BD)” films. These films exhibit exceptional dielectric properties, with dielectric constant (D k ) and loss factor (D f ) values as low as ∼1.8 and ∼0.002, respectively, outperforming or matching the requirements of modern electrical insulators, including advanced polymer blends based on polyimides. In addition to their functional performance, BD films demonstrate remarkable mechanical and thermal stability, photothermal conversion capabilities, strength retention after cycling, and biodegradability. These findings, supported by experimental data and simulation studies of intermolecular interactions, highlight the potential of BD films as a sustainable and efficient alternative to conventional dielectric materials.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".