Comparative Effects of Hydrazine and Thermal Reduction Methods on Electromagnetic Interference Shielding Characteristics in Foamed Titanium Carbonitride MXene Films
Bibliographic record
Abstract
Abstract The urgent need for the development of micro‐thin shields against electromagnetic interference (EMI) has sparked interest in MXene materials owing to their metallic electrical conductivity and ease of film processing. Meanwhile, postprocessing treatments can potentially exert profound impacts on their shielding effectiveness (SE). This work comprehensively compares two reduction methods, hydrazine versus thermal, to fabricate foamed titanium carbonitride (Ti 3 CNT x ) MXene films for efficient EMI shielding. Upon treatment of ≈ 100 µm‐thick MXene films, gaseous transformations of oxygen‐containing surface groups induce highly porous structures (up to ≈ 74.0% porosity). The controlled application of hydrazine and heat allows precise regulation of the reduction processes, enabling tailored control over the morphology, thickness, chemistry, and electrical properties of the MXene films. Accordingly, the EMI SE values are theoretically and experimentally determined. The treated MXene films exhibit significantly enhanced SE values compared to the pristine MXene film (≈ 52.2 dB), with ≈ 38% and ≈ 83% maximum improvements for the hydrazine and heat‐treated samples, respectively. Particularly, heat treatment is more effective in terms of this enhancement such that an SE of 118.4 dB is achieved at 14.3 GHz, unprecedented for synthetic materials. Overall, the findings of this work hold significant practical implications for advancing high‐performance, non‐metallic EMI shielding 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 | 0.001 | 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".