Mechanistic Study of Arsenate Adsorption onto Different Amorphous Grades of Titanium (Hydr)Oxides Impregnated into a Point-of-Use Activated Carbon Block
Bibliographic record
Abstract
Millions of households still rely on drinking water from private wells or municipal systems with arsenic levels approaching or exceeding regulatory limits. Arsenic is a potent carcinogen, and there is no safe level of it in drinking water. Point-of-use (POU) treatment systems are a promising option to mitigate arsenic exposure. However, the most commonly used POU technology, an activated carbon block filter, is ineffective at removing arsenic. Our study aimed to explore the potential of impregnating carbon blocks with amorphous titanium (hydr)oxide (THO) to improve arsenic removal without introducing titanium (Ti) into the treated water. Four synthesis methods achieved 8–16 wt % Ti-loading within the carbon block with a 58–97% amorphous THO content. The THO-modified carbon block could adsorb both oxidation states of arsenic (arsenate and arsenite) in batch or column tests. Modified carbon block with higher Ti and amorphous content always led to better arsenate removal, achieving arsenic loadings up to 31 mg As/mg Ti after 70,000 bed volumes in continuous-flow tests. Impregnating carbon block with amorphous THO consistently outperformed impregnation using crystalline TiO 2 . The best-performing system (TTIP-EtOH carbon block) was an amorphous THO derived using titanium isopropoxide, ethanol, and acetic acid via the sol–gel technique, aged at 80 °C for 18 h and dried overnight at 60 °C. Comparable pore-size distribution and surface area of the impregnated carbon blocks suggested that chemical properties play a more crucial role than physical and textural properties in removing arsenate via the amorphous Ti-impregnated carbon block. Freundlich isotherms indicated energetically favorable adsorption for amorphous chemically synthesized adsorbents. The mass transport coefficients for the amorphous TTIP-EtOH carbon block were fitted using a pore-surface diffusion model, resulting in D surface = 3.1 × 10 –12 and D pore = 3.2 × 10 –6 cm 2 /s. Impregnating the carbon block with THO enabled effective arsenic removal from water without adversely affecting the pressure drop across the unit or the carbon block’s ability to remove polar organic chemical pollutants efficiently.
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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 | 0.000 | 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 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".