Green nanotechnology approach for synthesis and encapsulation of gold nanoparticles from agricultural waste
Notice bibliographique
Résumé
Researchers in nanotechnology are turning towards "Nature" to provide inspiration to develop novel innovative methods for nanoparticle synthesis. Currently used chemical and physical methods of nanoparticles synthesis use toxic chemicals in their synthesis protocols. The toxic residues from these nanoparticles make them unsafe for food related applications. There is a need to develop nanoparticles using greener alternatives. Another challenging question that needs to be addressed is agricultural waste management. Merging these two problems led to the concept of creating wealth out of waste. Agricultural waste materials such as grape seeds, skin, stalk and organic waste generated during the Canadian fall season due to the fall of maple leaves and pine needles were used in this study to synthesize gold nanoparticles (AuNP). The main goal of this study is to synthesize gold nanoparticles without using toxic chemicals in the synthesis protocol making them suitable for drug/functional food delivery systems. A green nanotechnology approach was followed by using water as the solvent throughout the study. This value addition to agricultural waste has led to the yield of high value and ecofriendly gold nanoparticles. From the transmission electron microscopy (TEM) micrographs of gold nanoparticles produced using grape seeds (GSE), skin (GSK), stalk (GST) and pine needle extract, nearly spherically- shaped AuNP about 20 - 25 nm in diameter were observed. Whereas the gold nanoparticles produced using maple leaf extract produced triangular prisms. This is the first study stating the use of maple leaf extracts to potentially synthesize gold nanoparticles. As the plant matrix is a highly complex system, catechin, a polyphenolic compound present in grape seed, skin, and stalk, and in pine needles, was selected for further investigation. Gold nanoparticles were synthesized using different combinations of catechin (CAT), tannic acid (TAE), 1:1 CAT: TAE, 1:4 CAT: TAE. TEM images showed that gold nanoparticles synthesized using catechin were quasi-spherical in shape with 40 – 50 nm in size. All the gold nanoparticles produced by green synthesis method in this study were hydrophilic in nature.In order to make hybrid organic-inorganic carriers for drug delivery systems, AuNP synthesized using catechin was encapsulated in maltodextrin and beta-cyclodextrin complexes. The method adopted for encapsulation of AuNP into maltodextrin followed a top-down approach. The complex formation of AuNP into beta-cyclodextrin followed a bottom-up approach. Three different encapsulation methods such as microwave assisted encapsulation, freeze drying encapsulation and simple inclusion encapsulation for maltodextrin and molecular inclusion encapsulation for beta-cyclodextrin were studied for encapsulation of AuNP. The scanning electron microscopy (SEM) images of the AuNP encapsulated powder showed interesting morphology when comparing microwave assisted encapsulation to freeze drying encapsulation in both maltodextrin and beta-cyclodextrin. It was found from this study that organic-inorganic hybrid carriers can be developed using water following a green nanotechnology approach.
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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) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».