Sustainability in the Metallurgical Industry: Chemically Modified Cellulose for Selective Biosorption of Gold from Mixtures of Base Metals in Chloride Media
Bibliographic record
Abstract
In an effort to develop sustainable materials and methods for the recovery and recycling of precious metals, we recently developed two different adsorbents by cross-linking pure cellulose with either epichlorohydrin or concentrated sulfuric acid and then modifying the surface with N -aminoguanidine functional groups. The adsorption behavior of these sorption materials toward Au(III) from a multicomponent mixture of Pt(IV), Pd(II), and some base-metal ions was studied in hydrochloric acid media. Both of the adsorbents exhibited outstanding selectivity toward precious metals, with a selectivity order of Au(III) ≫ Pd(II) > Pt(IV), over base metals in a wide range of acid concentrations. These materials contain a number of positive centers in HCl media that function as sorption active sites for chloroanionic species of Au(III), Pd(II), and Pt(IV). The chloroanionic species of the corresponding precious metals were thus adsorbed on these materials through anion-exchange-coupled electrostatic interaction. The sulfuric acid cross-linked material exhibited improved selectivity and greater adsorption capacity compared to the epichlorohydrin cross-linked adsorbent. As equilibrium was achieved within an hour with quantitative adsorption, the effectiveness of the sulfuric acid cross-linked material with regard to Au(III) was exemplified by the fact that 1 kg of the dry adsorbent material had a capacity to load 9.2 mol, that is, nearly 1.8 kg of Au(III). Moreover, the adsorbed Au(III) was subsequently reduced to the elemental form, yielding metallic gold particles, thereby demonstrating the considerable improvements in efficiency and effectiveness of the novel adsorbents for the recovery of gold in comparison to current commercial resins.
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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".