Switchable biomaterials for wastewater treatment
Notice bibliographique
Résumé
The development of novel switchable biomaterials has gained significant attention due to their potential in wastewater treatment, offering sustainable and cost-effective solutions for contaminant removal. This thesis presents a comprehensive review of the diverse applications of switchable biomaterials, including chitosan, polylactic acid (PLA), cellulose, biochar, rubber, resin, and crude fibers. These materials exhibit stimulus-responsive functionalities that facilitate recyclability and pollutant recovery, making them promising candidates for environmental remediation. Despite substantial advancements, challenges such as stability, recyclability, and performance optimization remain. Future research should focus on improving these aspects while exploring novel hybrid materials to enhance their applicability in real-world scenarios. Based on the research gaps identified by the literature review, the thesis work further focuses on the development and optimization of a spiropyran-assisted cellulose aerogel (CNF-SP) aerogel with UV-induced switchable wettability, and the evaluation of its performance as an effective sorbent for oil spill cleanup. Beyond oil spill remediation, the switchable properties of the aerogel hold great potential for broader wastewater treatment applications, particularly in selectively adsorbing hydrophobic and hydrophilic contaminants. The aerogel initially exhibited strong hydrophobicity (124°) and showed UV-induced switchable wettability due to the photo-response structure of spiropyran. Upon UV irradiation, the hydrophobicity of the aerogel could be switched to hydrophilicity (31°), while visible light irradiation could restore its hydrophobicity. The three-dimensional (3D) porous structure of the CNF-SP aerogel combined with the hydrophobic properties of spiropyranol led to its great oil adsorption performance (27-30 g/g of oil adsorption ratio). To systematically optimize the material, the central composite design (CCD) was applied, as it allows for efficient exploration of the interaction effects among multiple factors. The raw materials, including carboxymethyl cellulose, carboxyethyl spiropyran, polyvinyl alcohol, and nano zinc oxide, were specifically chosen due to their roles in enhancing mechanical stability, responsiveness, and adsorption capacity. The optimized CNF-SP aerogel demonstrated a high oil sorption efficiency, particularly in acid and cold environments. Moreover, the switchable function indicated that the aerogel exhibited reusability and renewability, with the added benefit of UV-induced oil recovery. However, potential limitations, such as the scalability of the synthesis process and real-world deployment challenges, remain key concerns that require further investigation. Through the development of the CNF-SP aerogel, this thesis directly addresses challenges in oil spill remediation by offering a material capable of adapting to diverse environmental conditions while ensuring high oil adsorption efficiency and sustainability. The study underscores the transformative potential of switchable biomaterials in mitigating the environmental impact of water pollution, reaffirming their role as a critical advancement in the field of wastewater treatment.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».