Application of Algal Biofilms for the Recovery of Rare Earth Elements from Dilute Aqueous Solution via Biosorption
Bibliographic record
Abstract
Rare earth elements are a critical resource and there is interest in meeting the growing demand by recovering them from waste sources, but conventional recovery methods are not economically feasible. One alternative is to adsorb metal ions onto microbial biomass, but the poor mechanical properties make microbial biomass difficult to implement. This thesis investigated using algal biofilms for rare earth biosorption as an improvement over suspended biomass by comparing adsorption isotherms, kinetics, selectivity, and desorption recovery between the two. Euglena mutabilis biofilms have a higher maximum lanthanum adsorption capacity than suspended Euglena (65 vs. 25 mg/g respectively). This increase was caused by the biofilm’s extracellular polymeric substance (EPS) matrix providing additional binding sites for adsorption. The EPS matrix adsorbed metal ions via an ion exchange reaction where rare earths substituted the ionic crosslinkers (e.g., Ca2+, Mg2+) and had an estimated lanthanum adsorption capacity of 360 mg/g. In a multi-rare earth system, biofilms adsorbed up to 35% more heavier rare earths from Er to Lu than suspensions due to binding sites provided by EPS. The largest adsorption capacities for the biofilm biomass were Sm, Eu, Yb, and Lu with 0.035, 0.033, 0.033, and 0.031 mmol/g respectively. The presence of calcium and magnesium did not affect adsorption onto the biofilm, but iron reduced total rare earth adsorption by up to 25% due to competitive adsorption. Recovery of rare earths via acid desorption was higher with biofilms than suspensions with 86 vs 72% recovery of lanthanum using HCl. Preferential desorption of heavier rare earths from Ho to Lu occurred at higher pH for both Euglena suspensions and biofilms. After three repeated adsorption-desorption cycles using HCl, the lanthanum adsorption capacity of biofilms increased by up to 3.8 times its initial value due to the co-desorption of other metal ions from the EPS matrix “activating” the biofilm biomass. These results demonstrate that biofilms have several advantages over suspended biomass for rare earth biosorption due to the EPS matrix. Testing in a continuous system however is necessary to fully establish the industrial potential for biofilm biosorption to recover rare earths.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".