Nanocomposite beads with engineered pore architecture for improved removal of emerging contaminants from water
Bibliographic record
Abstract
• Developed adsorbent with faster adsorption rate suitable for gravitational POU device. • Improved the mechanical properties of nanocomposite beads through internal gelation. • Improved the specific surface area of the biopolymeric nanocomposite beads by 71 %. • Reduced diffusion/mass transfer resistance of the beads for improved water treatment. • Improved maximum adsorption capacity of TC by 43 % and DCF by 780 %. The rapid crosslinking process for the formation of biopolymeric beads typically limits their adsorption rates and capacities due to suboptimal pore structures and morphology. In conventional beads, the highly porous core is enclosed by a semi-permeable shell, restricting mass transfer. To address this, we engineered the pore architecture of the beads using an internal gelation (IG) process. This approach overcomes diffusion resistance barriers, and improves the environmental performance of the beads. By controlling the gelation process with CaCO 3 (IGC), which is a gas forming agent, and CaSO 4 (IGS), which controls the rate of cross-linking from within the beads, we tailored the pore architecture. We characterized the beads in terms of elemental composition, morphology, mechanical properties, and stability. The IG beads, containing only 3.5 wt% graphene oxide (GO), showed significantly faster adsorption rates—up to two orders of magnitude higher for diclofenac and twice as fast for tetracycline removal compared to externally gelled (EG) beads. IGS beads demonstrated superior adsorption capacities, with multiple-fold increases for both diclofenac and tetracycline, due to enhanced intraparticle diffusion enabled by the IG process. The exceptional performance of IGS beads is attributed to the creation of a highly porous outer shell with hierarchical linkage to the inner core, reducing diffusion resistance and maximizing the adsorption potential of GO’s sp 2 hybridized domains, without the need for chemical reduction of the nanosheets. IGC beads, with improved mechanical properties, also showed remarkable adsorption capacities comparable to IGS beads, and surpassing that of EG beads. Our technique, not material specific, can be used in any hydrogel that is made by ionic cross-linking for a broad range of applications.
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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 | 0.000 | 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) | 0.000 | 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".