Physicochemical, solar thermal and mechanical properties of hydrothermally treated and carbonized corncob
Bibliographic record
Abstract
Converting biomass waste materials to porous carbon for solar thermal evaporation represents a new approach to both energy and environmental sustainability. In this work, the agricultural biomass residue corncob was hydrothermally-treated at 200 °C for 4 h and further carbonized at 600 °C for 2 h in Ar to produce porous carbon. Morphological examination on the obtained carbon material was performed using scanning electron microscopy (SEM). Thermogravimetric analysis (TGA) of the derived carbon was conducted to determine the temperature-dependent weight change. The corncob-generated carbon showed the porous microstructure with a BET surface area of 2.9299 m²/g. The single point adsorption total pore volume of pores less than 0.9384 nm width at P/P o = 0.01 is 0.000097 cm³/g and the single point desorption total pore volume of pores less than 20.7391 nm width at P/P o = 0.9 is 0.006376 cm³/g. The adsorption average pore diameter is 0.1318 nm, and the desorption average pore diameter is 8.7044 nm. Solar thermal evaporation tests were performed by setting both pristine corncob and carbonized corncob in seawater fetched from Salton Sea, Southern California, USA. Weight loss of seawater under sunlight was recorded each 15 min to obtain the time dependent water evaporation plot and calculate the solar water evaporation rate. The solar thermal evaporation rate for the pristine corncob was found to be 1.91 kg/(m 2 ∙h). The corncob derived hydrochar carbon reached a much higher solar thermal evaporation rate of 4.48 kg/m 2 ∙h. It is concluded that carbonized corncob is effective in harvesting solar energy for brine concentration and clean water generation. The unique advantages of the carbonized corn cob include higher solar thermal evaporation rate, better pore structure, and lower cost than many other materials. In addition, mechanical property testing results were also obtained under compression and torsion conditions.
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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 | 0.001 | 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) | 0.001 | 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".