Advanced Nano‐Fibrillated Cellulose/Modified MXene Janus Membrane for Continuous 24‐h Water‐Power Co‐Generation
Bibliographic record
Abstract
Abstract Solar‐driven evaporators have emerged as a sustainable strategy for water purification and energy harvesting. Designing advanced systems that achieve high evaporation performance, long‐term operational stability, and resistance to salt crystallization remains a significant challenge. In this study, an innovative Janus membrane is proposed that addresses these challenges, featuring a super hydrophilic cellulose nanofiber (CNF)@Hexadecyl Trimethyl Ammonium Bromide (CTAB)‐MXene layer and a superhydrophobic polytetrafluoroethylene (PTFE) layer. CTAB modification of MXene enhances its interlayer spacing and specific surface area, enabling rapid water transport and efficient solar energy absorption of the CNF@CTAB‐MXene layer. A PTFE layer is sputter‐deposited onto CNF@CTAB‐MXene layer, effectively preventing salt accumulation and membrane fouling, with plasma pre‐treatment ensuring excellent interfacial bonding between these two layers. Under 1 sun illumination, the CNF@CTAB‐MXene/PTFE Janus evaporator achieves a remarkable evaporation rate of 1.51 kg m −2 h −1 with outstanding salt resistance. The synergy between superhydrophilic and superhydrophobic layers facilitates efficient water transport while maintaining long‐term stability without performance degradation. Additionally, the evaporator generates a voltage of 343.8 mV during thermoelectric power generation, and its unique design allows electricity generation from wind energy at night. This integrated system provides an advanced and durable solution for water‐power co‐generation, offering practical benefits for off‐grid or remote regions.
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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".