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Record W4400735701 · doi:10.1099/mic.0.001475

A novel closed-loop biotechnology for recovery of cobalt from a lithium-ion battery active cathode material

2024· article· en· W4400735701 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMicrobiology · 2024
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsLaurentian UniversityCentre for Excellence in Mining Innovation
FundersEuropean Regional Development FundEngineering and Physical Sciences Research CouncilBangor UniversityCoventry UniversityFaraday Institution
KeywordsCobaltCathodeBattery (electricity)Lithium (medication)IonLithium-ion batteryClosed loopChemistryMaterials scienceInorganic chemistryBiologyPhysicsEngineeringOrganic chemistryThermodynamicsPower (physics)Physical chemistry

Abstract

fetched live from OpenAlex

In recent years, the demand for lithium-ion batteries (LIBs) has been increasing rapidly. Conventional recycling strategies (based on pyro- and hydrometallurgy) are damaging for the environment and more sustainable methods need to be developed. Bioleaching is a promising environmentally friendly approach that uses microorganisms to solubilize metals. However, a bioleaching-based technology has not yet been applied to recover valuable metals from waste LIBs on an industrial scale. A series of experiments was performed to improve metal recovery rates from an active cathode material (LiCoO 2 ; LCO). (i) Direct bioleaching of ≤0.5 % LCO with two prokaryotic acidophilic consortia achieved >80 % Co and 90 % Li extraction. Significantly lower metal recovery rates were obtained at 30 °C than at 45 °C. (ii) In contrast, during direct bioleaching of 3 % LCO with consortia adapted to elevated LCO levels, the 30 °C consortium performed significantly better than the 45 °C consortium, solubilizing 73 and 93 % of the Co and Li, respectively, during one-step bioleaching, and 83 and 99 % of the Co and Li, respectively, during a two-step process. (iii) The adapted 30°C consortium was used for indirect leaching in a low-waste closed-loop system (with 10 % LCO). The process involved generation of sulfuric acid in an acid-generating bioreactor (AGB), 2–3 week leaching of LCO with the biogenic acid (pH 0.9), selective precipitation of Co as hydroxide, and recirculation of the metal-free liquor back into the AGB. In total, 58.2 % Co and 100 % Li were solubilized in seven phases, and >99.9 % of the dissolved Co was recovered after each phase as a high-purity Co hydroxide. Additionally, Co nanoparticles were generated from the obtained Co-rich leachates, using Desulfovibrio alaskensis , and Co electrowinning was optimized as an alternative recovery technique, yielding high recovery rates (91.1 and 73.6% on carbon felt and roughened steel, respectively) from bioleachates that contained significantly lower Co concentrations than industrial hydrometallurgical liquors. The closed-loop system was highly dominated by the mixotrophic archaeon Ferroplasma and sulfur-oxidizing bacteria Acidithiobacillus caldus and Acidithiobacillus thiooxidans . The developed system achieved high metal recovery rates and provided high-purity solid products suitable for a battery supply chain, while minimizing waste production and the inhibitory effects of elevated concentrations of dissolved metals on the leaching prokaryotes. The system is suitable for scale-up applications and has the potential to be adapted to different battery chemistries.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.244
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it