Fused deposition modeling of functional nanohybrids: a transformative approach to sustainable water purification
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.
Bibliographic record
Abstract
Fused Deposition Modeling (FDM) has revolutionized the production of customized polymer-based components across industries. The integration of nanohybrid (NH) materials into polymer matrices has led to notable improvements in mechanical strength (up to 60 MPa), thermal stability (20–40 °C increase in degradation temperature), and adsorption efficiency (up to 210 mg/g for Pb²⁺ removal). This review analyzes the synergy between FDM and nanotechnology for creating multifunctional, sustainable polymers designed for wastewater treatment applications. NH-enhanced composites such as TiO₂–PLA and GO–PBS have demonstrated over 95% dye degradation and >99% antibacterial activity, offering potential for scalable 3D-printed filters, catalytic reactors, and membranes. Furthermore, Multi-Criteria Decision-Making (MCDM) frameworks, including Analytic Hierarchy Process (AHP) and TOPSIS, are discussed as tools to select optimal material combinations balancing performance, cost, and environmental safety. The review outlines a roadmap for translating laboratory-scale NH–FDM innovations into real-world environmental solutions, emphasizing sustainability, safety, and long-term functionality in advanced water treatment 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 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 it