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Record W4390328128 · doi:10.1021/acs.est.3c08067

Rapid, Selective, and Chemical-Free Removal of Dissolved Silica from Water via Electrosorption: Feasibility and Mechanisms

2023· article· en· W4390328128 on OpenAlex
Wen Ma, Sohum K. Patel, Mariana Marcos−Hernández, Xiaoxiong Wang, Xuechen Zhou, Weiyi Pan, Yong-Uk Shin, D. Villagrán, Menachem Elimelech

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnvironmental Science & Technology · 2023
Typearticle
Languageen
FieldEngineering
TopicMembrane-based Ion Separation Techniques
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaBureau of ReclamationDirectorate for Engineering
KeywordsSorptionElectrodeChemical engineeringDissolved silicaAnodeMesoporous silicaWater treatmentChemistryHydroxideSelectivityInorganic chemistryMaterials scienceCatalysisAdsorptionOrganic chemistryMesoporous materialWaste management

Abstract

fetched live from OpenAlex

The unavoidable and detrimental formation of silica scale in engineered processes necessitates the urgent development of effective, economic, and sustainable strategies for dissolved silica removal from water. Herein, we demonstrate a rapid, chemical-free, and selective silica removal method using electrosorption. Specifically, we confirm the feasibility of exploiting local pH dynamics at the electrodes in flow-through electrosorption, achieved through a counterintuitive cell configuration design, to induce ionization and concomitant electrosorption of dissolved silica. In addition, to improve the feasibility of silica electrosorption under high-salinity solutions, we developed a silica-selective anode by functionalizing porous activated carbon cloths with aluminum hydroxide nanoparticles (Al(OH) 3 –p–ACC). The modification markedly enhances silica sorption capacity (2.8 vs 1.1 mg silica g anode –1 ) and reduces the specific energy consumption (13.3 vs 19.8 kWh kg silica –1 ). Notably, the modified electrode retains remarkable silica sorption capacity even in the presence of high concentrations of co-occurring ions (up to 100 mM NaCl). The mechanisms underlying the superior silica removal stability and selectivity with the Al(OH) 3 –p–ACC electrode are also elucidated, revealing a synergistic interaction involving outer-sphere and inner-sphere complexation between dissolved silica and Al(OH) 3 nanoparticles on the electrodes. Moreover, we find that effective regeneration of the electrodes may be achieved by applying a reverse potential during discharge, although complete regeneration of the modified electrodes may necessitate alternative materials or process optimization. We recommend the adoption of feedwater-specific designs for the development of future silica-selective electrodes in electrosorption capable of meeting silica removal demands across a wide range of engineered systems.

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 score0.027
Threshold uncertainty score0.483

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 studies0.0000.001
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 head0.008
GPT teacher head0.208
Teacher spread0.200 · 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