Characterisation and optimisation of biosorption of metals by dealginated seaweed.
Bibliographic record
Abstract
The ability of dealginated seaweed, a waste material derived from the commercial processing of seaweed for alginate production, to remove cadmium, lead, nickel, copper, chromium, silver, aluminium and gold from solution was determined. Metal sorption was found to be rapid (90% removal within 5 minutes), achieving a residual concentration of 0.9 mg L[-1] after 1 h contact time from an initial solution concentration of 10 mg L[-1]. The binding of metal by dealginate was found to be pH dependent, optimal sorption occurring at around pH 6-8 for cadmium, lead, nickel, copper and chromium and pH 3-4 for aluminium and gold respectively, suggesting an ion exchange mechanism. Determination of a molar ratio in the displacement of calcium by cadmium on dealginate supported the presence of an ion-exchange relationship, since the displacement of approximately 1 mol of calcium by 1 mol of cadmium was observed.The sorption data was best fitted in the ion exchange approximation as opposed to the Langmuir model. The binding capacities were found to be 1.2, 0.5, 1.6, 0.8, 1.2, 0.4, 0.9 and 0.4 mmol g-1 for cadmium, lead, nickel, copper, chromium, silver, aluminium and gold respectively. The ion exchange constants were calculated to be 3.3 x 10[-6], 4.1 x 10[-6], 6.2 x 10[-6], 1.8 x 10[-6], 2.3 x 10[-6], 2.4 x 10[-7],8 x 10[-10] for cadmium, lead, nickel, copper, chromium, silver and aluminium. The values of the capacities and ion exchange constants showed affinity of the biosorbent to specific metals. The identification of the binding sites on the surface of dealginated seaweed was investigated by a number of techniques. Potentiometric titration revealed three distinct pKa values, the first having a similar value to carboxyl groups, the second being comparable with that of saturated thiols and amines and the third similar to sulphonate groups. Esterification of the dealginate resulted in the subsequent reduction in metal sorption, indicating that carboxyl groups are largely responsible for sorption except in the case of aluminium and gold, where 40-60% of the metal remained in solution after modification of the surface. Evidence of the FT-IR spectra confirmed the presence of carboxyl groups in untreated dealginate, while the number of carboxyl groups was markedly reduced in the esterified sample.The occurrence of other mechanisms apart from ion exchange was suggested by the FT-IR spectrum for aluminium and gold. ESEM images of the surface of dealginated seaweed showed the algae cell structure still present in large areas. X-ray maps revealed the presence of silver, aluminium and gold associated with sulphur atoms on the dealginate surface. EXAFS results showed that cadmium, lead, copper and silver were bound to the dealginate through oxygen atoms, possibly from carboxylate groups. Evidence of gold reduction from Au (III) to Au(l) and Au(O) was also confirmed by the bond distance calculated for this metal.Methods for the on-line preconcentration of cadmium, chromium, copper and lead and chemical speciation of Cr[3+] and CrO[4][2-] using a microcolumn packed with dealginated seaweed were developed. Effective column capacities were 4.0, 8.7, 9.4 and 8.5 mumol L[-1] for cadmium, chromium, copper and lead, respectively. The application of the method was extended to the determination of zinc, cobalt, mercury, scandium, strontium, vanadium, arsenic, selenium, manganese and antimony. The analytical procedures developed for metal preconcentration and chromium speciation were validated by analyses of two Lake Ontario reference materials, TMDA 51.2 and TMDA 54.2 and a synthetic seawater sample. The findings of this study demonstrated that the sorption of metal by dealginate is mainly due to an ion-exchange mechanism. The binding capacities of the biosorbent for the elements studied were adequate for trace analysis and the use of dealginate was shown to be a cheaper alternative to synthetic resins.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".