Nano- and Microscale Design of Electrically Conductive Bacterial Cellulose/PEDOT Cryogels for Electromagnetic Interference Shielding
Bibliographic record
Abstract
Exploiting conductive biobased polymer nanocomposites for electromagnetic interference (EMI) shielding is a rapidly evolving research area. In this study, we systematically fine-tune the nano- and microstructural features of bacterial cellulose (BC) modified with poly(3,4-ethylenedioxythiophene) (PEDOT) for EMI shielding applications. First, to investigate the effect of nanostructure, PEDOT is incorporated into the BC matrix using two methods: chemical vapor polymerization (CVP) and in situ polymerization. The CVP method produces more uniform and denser BC-PEDOT nanocomposites, resulting in cryogels with higher electrical conductivity and total EMI shielding effectiveness (SE T ) (52 ± 2 S/m, 37 dB) compared to those of the in situ polymerized BC-PEDOT cryogels (7 ± 1.5 S/m, 27 dB). The cryogels’ microstructure is then adjusted to control the EMI shielding mechanisms by applying different drying methods: freeze-drying, air-drying, and hybrid freeze- and air-drying. Our results indicate that the more energy-efficient air-drying method enhances the reflection-dominant EMI shielding mechanism, with a slight increase in total shielding effectiveness. The drying conditions also affect the final mechanical properties of the samples. Overall, this study demonstrates that BC-PEDOT nanocomposites are excellent candidates for EMI shielding applications.
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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 | 0.000 | 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".