A systematic study on the use of ultrasound energy for the synthesis of nickel–metal organic framework compounds
Bibliographic record
Abstract
A nickel metal-organic framework (Ni-MOF) was successfully synthesized using ultrasound irradiation. Further to this, X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FT-IR), Thermo-Gravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC) and nitrogen adsorption [i.e. Brunauer-Emmett-Teller (BET) Surface Area Analysis] techniques were used to characterize the synthesized Ni-MOF. In addition, the effect of sonication on the surface area, pore diameter and pore volume of the final product was systematically studied using Taguchi technique. The experiments ascertained that manufacturing of the Ni-MOF by means of the ultrasonic-assisted technique is feasible at a relatively shorter time compare to the conventional methods. The final product showed more uniform shape distribution and improved BET properties. The obtained results offered that the synthesized Ni-MOF samples could be used in several applications.
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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".