Design and synthesis of thin palladium membranes on porous metal substrate for hydrogen extraction
Bibliographic record
Abstract
Membrane separation is regarded nowadays as a preferred method for production of purified hydrogen. Palladium (Pd) is an attractive membrane material due to its ability to dissociate molecular hydrogen into atoms. It is usually deposited on the porous substrate that can provide good mechanical support and reduce the thickness of the membrane for maximizing hydrogen permeability. Pd membrane used for hydrogen separation must be thin enough to increase hydrogen flux and reduce cost while remaining thick enough to retain adhesion, attrition resistance and mechanical integrity during high temperature cycles. In this paper, the progress of electroless deposition of Pd around the pore area at surface of porous stainless steel was recorded and a bridge structure that was formed during the membrane deposition around the pore area of the substrate was illustrated. After that, the porous substrate was modified using micro-or nano-size metal or metal oxide particles in order to reduce pore size in the substrate surface. The experimental results obtained from hydrogen permeation through the Pd membranes having the thickness from 400 nm to 18 μm built on both modified and original porous stainless steel substrates demonstrate that these thin membranes are solid and they can be used at the temperature of 550°C and hydrogen pressure difference of 3.447x10 5 Pa. The proposed processing will allow optimizing the design and fabrication of thin Pd membranes on different porous substrates for hydrogen separation.
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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) | 0.000 | 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 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".