Integrated electrocoagulation-flotation of microalgae to produce Mg-laden microalgal biochar for seeding struvite crystallization
Bibliographic record
Abstract
Abstract Developing sustainable materials for recovering and recycling nutrients from wastewater is critically needed for nutrients such as phosphorus that have a diminishing supply. Struvite crystallization is emerging as a promising strategy for phosphorus recovery which can be enhanced with seeding through microalgal biochar. The main bottleneck of using microalgae is its high harvesting cost. In this study, an integrated electrocoagulation-flotation (ECF) process is used to recover and at the same time modify the algal surface with magnesium anode and inert carbon cathode. Harvesting efficiency of 98% was achieved with 40.78 mA cm −2 , 0.5 cm inter-electrode distance and energy consumption of 4.03 kWh kg −1 in 15 min. The harvested microalgae were pyrolyzed to obtain a yield of 52.90% Mg-laden microalgal biochar. Simultaneously, surface impregnation of 28% magnesium was attained as confirmed by Scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS). Phosphorus recovery and struvite yield of 93.70% and 2.66 g L −1 , respectively, were obtained from dosing 1.50 g L −1 Mg-laden microalgal biochar. Comparison of physicochemical characteristics of residual supernatant after microalgal harvesting and struvite recovery showed that the combined use of both the residuals can serve as a sustainable growth medium for microalgae. The overall operating cost of the integrated process was found to be 2.48 USD kg −1 with a total energy consumption of 10.76 kWh kg −1 , which was found to be lower than conventional harvesting unit processes such as centrifugation and filtration. This novel approach can help attaining a circular bioeconomy by encompassing nutrient recovery and waste management in an integrated process.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 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".