Electrically Conductive Ni-P Nanoporous Membrane Reactors for Electrochemical Reductive Dechlorination of Organic Pollutants
Bibliographic record
Abstract
Transition-metal phosphides (TMPs) are emerging electrocatalysts for both hydrogen evolution and the conversion of reactants/contaminants by various electrochemical reactions. TMPs are promising catalysts because they are earth abundant, have high electrical conductivity, and have high chemical stability. In this seminal work, a low-priced nickel phosphorus (Ni-P) ultrafiltration membrane was fabricated and used for electrochemical reductive dechlorination of chlorophenols. Amorphous Ni-P nanoparticles were grown on an ultrafiltration poly(ether sulfone) (PES) membrane via electroless deposition. The prepared Ni-P membrane was used as a cathode for electrochemical reductive dechlorination of 2-chlorophenol (2-CP) in flow-through mode. It was observed that a dechlorination efficiency of 42.7%, a reaction rate constant of 1.621 min –1, and a Faradaic efficiency of 24.5% were achieved at an optimized cathodic potential of −2.50 V. The dechlorination was primarily attributed to the partial positively charged Ni δ+ on the Ni-P membrane surface, which facilitated atomic H* evolution by forming reactive Ni–H* bonds for dechlorination. Additionally, doping P atoms in Ni retarded the deactivation of electrocatalytic Ni sites. This work demonstrates that the cost-effective Ni-P membrane electrocatalyst is a promising technology to degrade chlorinated compounds with applications to industrial wastewaters and landfill leachates.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".