Unravelling the Synergistic Effect of Multiscale Hierarchical Material Architecture for Enhanced Urea Adsorption
Bibliographic record
Abstract
Adsorption of inert small molecules has always been challenging, and hence, these molecules are generally difficult to remove from solution. In this work, we demonstrated a significant improvement (>25 times) in the adsorption of an inert small molecule, urea, using a hierarchical material design, which remarkably outperformed the simple chemical functionalization of the substrate. To illustrate this point, we employed two-dimensional (2D) materials such as Ti 3 C 2 T x MXene as the adsorbent “substrate” which has a high potential for efficient urea removal. In particular, Cu-functionalized MXene, with Cu valency between 0 and +1 exhibited superior urea adsorption performance compared to pristine MXene. However, due to the strong van der Waals forces, MXene has a propensity to aggregate, leading to the loss of active sites for urea adsorption. To address this, cellulose nanocrystals were introduced as they have dual functionalities, namely, to prevent aggregation and preserve active sites for adsorption of urea. These nanocrystals are small, rigid, and hydrophilic, facilitating their interaction with hydrophilic groups on the MXene surface. Porous hydrogel macrobeads prepared using alginate cross-linked with calcium ions yielded a hierarchical structure with nanosized MXene-cellulose moieties distributed within the millimeter beads. Besides serving as mechanical support, the cellulose nanocrystals can be further surface-functionalized with enhanced interaction with chemical groups such as polydopamine to boost the adsorption properties. Each component in the hydrogel composite synergistically enhanced the interaction with urea and promoted adsorption. Consequently, the composite hydrogel exhibited a remarkable enhancement in urea adsorption capacity from 6.7 to 354.4 mg/g in aqueous solution, while a maximum adsorption capacity ( Q max ) of 115.1 mg/g was observed in simulated dialysate solution due to the increased surface area available for urea adsorption. The development of this hydrogel composite consisting of Cu-functionalized MXene, functionalized cellulose nanocrystals, and alginate cross-linked with calcium showcased its potential as a highly efficient and versatile material for effective urea adsorption in both aqueous and simulated dialysate solutions.
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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".