Greatly Enhanced Electromagnetic Interference Shielding Effectiveness and Mechanical Properties of Polyaniline-Grafted Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub> MXene–PVDF Composites
Bibliographic record
Abstract
Nowadays, evolutions in wireless telecommunication industries, such as the emergence of complex 5G technology, occur together with massive development in portable electronics and wireless systems. This positive progress has come at the expense of significant electromagnetic interference (EMI) pollution, which requires the development of highly efficient shielding materials with low EM reflection. The manipulation of MXene surface functional groups and, subsequently, incorporation into engineered polymer matrices provide mechanisms to improve the electromechanical performance of conductive polymer composites (CPCs) and create a safe EM environment. Herein, Ti 3 C 2 T x MXene nanoflakes were first synthesized and then, taking advantage of their abundant surface functional groups, polyaniline (PA) nanofibers were grafted onto the MXene surface via oxidant-free oxidative polymerization at two different MXene to monomer ratios. The electrical conductivity, EMI shielding effectiveness (SE), and mechanical properties of poly (vinylidene fluoride) (PVDF)-based CPCs at different nanomaterial loadings were then thoroughly investigated. A very low percolation threshold of 1.8 vol % and outstanding electrical conductivities of 0.23, 0.195, and 0.17 S/cm were obtained at 6.9 vol % loading for PVDF–MXene, PVDF–MX 2 AN 1, and PVDF–MX 1 AN 1, respectively. Compared to the pristine MXene composite, surface modification significantly enhanced the EMI SE of the PVDF–MX 2 AN 1 and PVDF–MX 1 AN 1 composites by 19.6 and 32.7%, respectively. The remarkable EMI SE enhancement of the modified nanoflakes was attributed to (i) the intercalation of PA nanofibers between MXene layers, resulting in better nanoflake exfoliation, (ii) a large amount of dipole and interfacial polarization dissipation by constructing capacitor-like structures between nanoflakes and polymer chains, and (iii) augmented EMI attenuation via conducting PA nanofibers. The surface modification of the MXene nanoflakes also enhanced the interfacial interactions between PVDF chains and nanoflakes, which resulted in an improved Young’s modulus of the PVDF matrix by about 67 and 46% at 6.9 vol % loading for PVDF–MX 2 AN 1 and PVDF–MX 1 AN 1 composites, respectively.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".