Investigation of Electrochemical and Hybrid Microbial Desalination Cells for Environmental Applications
Bibliographic record
Abstract
ABSTRACT\n Road salt is a global problem especially in cold countries that are focused on road safety in urbanized and big cities. On an average approximately 5 million tonnes of road salt is applied on Canadian highways annually. Road salt impacts aquatic ecosystems, bridges, buildings and corrodes metal structures. Therefore the treatment of road salt is important and needs to be studied.\nIn this study, a batch lab-scale 3-compartment electrochemical desalination cell was invented and studied to reduce NaCl(aq) (model of road salt) through the utilization of NaBH4/H2O2 redox reaction. Using of several commercial cation exchange and anion exchange membranes desalination was shown to be successful. The average road salt concentrations around City of London, ON was found to be 12 to 18 g/L, which the fuel cell was built based on. Operating in the batch regime, the CMI-7000 in combination with AMI-7001 membrane pairs assisted in the removal of sodium ions with ~98.9%; whereas; the removal of chloride ions was ~99%. Over maximum of 9-hour runtime, the total desalination rate (TDR) for NaCl was 0.70 g.L-1/hr. Other salts such as MgCl2(aq), CaCl2(aq) and KCl(aq) were desalination almost completely in the same lab-scale 3-compartment electrochemical desalination cell in the batch regime. The borohydride/peroxide cell in the batch regime has demonstrated its viability for the desalination of salt solutions.\nSecond, the 3-compartment electrochemical desalination cell at batch regime with external mixing was studied for faster desalination. It was also used to study additional five different sets of process parameters. Over maximum of approximately 7-hour runtime, the total desalination rate for NaCl was 2.4 times better for batch regime with mixing (1.65 g.L-1/hr) in comparison to static batch regime (0.70 g.L-1/hr).\nThird, a 3-compartment electrochemical desalination cell (EDC) was studied utilizing the energy from NaBH4/H2O2 redox reaction in the continuous regime. Five different sets of parameters in the continuous regime were examined. Desalination rate is fastest with continuous regime, where on average the total desalination rate for NaCl was 7.6 times better for continuous regime(5.32 g.L-1/hr) in comparison to batch regime (0.70 g.L-1/hr).\nFourth, a batch lab-scale microbial desalination cell (MDC) was studied. Its performance was compared to that in the previous work (EDC in the batch regime) to reduce the salt concentration by utilizing the energy from sodium acetate/potassium ferricyanide redox reaction. This 3-compartment sodium acetate /NaCl /potassium ferricyanide cell was effective in desalinating NaCl (modeled road salt); however, it is slower. Total Desalination Rate for EDC was 0.70 g.L1/hr; whereas, MDC’s TDR was 0.20 g.L-1/hr. This microbial desalination cell in the batch regime was advantageous because it utilizes wastewater’s energy in desalination.\nIn addition, a lab-scale hybrid Microbial Desalination Cell (MDC)/EDC was invented and studied to remove NaCl(aq) by utilizing the NaBH4/Fe2(SO4)3 redox chemical reaction in the batch regime. Preliminary runs were “offline”; whereas, “inline” test runs were explored when hybrid MDC/EDC was attached to the bioreactor. The Total Desalination Rate-* this system was 1.1 g.L-1/hr; whereas, MDC’s TDR was 0.20 g.L-1/hr. All the different studies of electrochemical and bio-electrochemical desalination cells are novel work and can be scaled-up.
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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 | 0.001 | 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".