Sulfonated Chitosan and <scp>HKUST</scp>‐1 metal organic frameworks based hybrid membranes for direct methanol fuel cell applications
Bibliographic record
Abstract
Abstract Sulfonated Chitosan and copper‐based metal–organic frameworks (Hong Kong University of Science and Technology (HKUST‐1) or Cu‐BTC or MOF‐199) based hybrid membranes are fabricated using a solution casting method for direct methanol fuel cell (DMFC) applications. The well‐defined cubic structure and sharp crystalline X‐ray diffraction pattern confirms the successful synthesis of HKUST‐1. The SEM cross‐sectional images showed that incorporated HKUST‐1 acts as a pore‐filling agent as well as creating finger‐like hydrophilic channels into the S‐Chitosan matrix. The existence of intermolecular hydrogen bonding between the COOH groups of HKUST‐1 and SO 3 H groups of S‐Chitosan enhances the membrane performances such as water uptake, ion exchange capacity, proton conductivity, and thermal stability. Specifically hybrid membrane with 0.5 wt% of HKUST‐1 showed the highest proton conductivity of 5.38 × 10 −3 and 6.19 × 10 −3 S cm −1 at 25 and 80°C respectively. Besides the S‐Chitosan‐0.5 membrane exhibited lower methanol permeability and selectivity than pristine S‐Chitosan and commercial Nafion membranes due to the small ionic size. Besides the pore reduction ability of HKUST‐1 selectively allowed protons and block the methanol permeation in the membrane matrix. Overall results indicate that the S‐Chitosan‐0.5 hybrid membrane is a suitable candidate for DMFC applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".