| Literature DB >> 28774086 |
Karmani Murugan1, Yahya E Choonara2, Pradeep Kumar3, Lisa C du Toit4, Viness Pillay5.
Abstract
Neogeometric copper nanoparticles (CuNPs) have various applications yet its synthesis still proves to be challenging with regards to self-assembly and uniformity control. This study aimed to synthesize shape-specific CuNPs in the biomedical application of ascertaining skin permeation and retention of the CuNPs as a drug delivery system. The approach to the shape design involved the dual control of two surfactants to direct the shape organisation of the nanoparticles (NPs) while an interesting aspect of the study showed the competitive adsorption of the surfactants onto the nanocrystal facets to direct facet growth. The resulting copper nanoparticles were characterised using X-ray diffraction (XRD) and electron diffraction spectra analysis (EDS) for elemental and crystalline analysis. Thermogravimetric Analysis (TGA) identified the degradation of the surfactant coat and the synthesis of a novel copper-polymer complex and extensive transmission electron microscopy (TEM) was conducted to determine the nanoparticle morphology. Epidermal skin tissue served as the model for permeation studies of five idealistic nano-geometries and investigated its application in drug delivery with regards to cellular internalisation and transbarrier transport of the geometric CuNPs. A mechanistic consideration for shape control is discussed.Entities:
Keywords: copper; drug delivery; geometric structure; nanocrystals; nanoparticles; self-assembly; transdermal
Year: 2016 PMID: 28774086 PMCID: PMC5456976 DOI: 10.3390/ma9120966
Source DB: PubMed Journal: Materials (Basel) ISSN: 1996-1944 Impact factor: 3.623
Surfactant variations corresponding to physicochemical characteristics of synthesized CuNPs, Data presented are mean ± SE of three experiments performed in duplicate. * p ≤ 0.05.
| Formulation | [CTAB] (M) | [SDS] (M) | Yield (%) | Geometrical Structures | Size of Nanostructures (nm) | Figure |
|---|---|---|---|---|---|---|
| S1 a | 0.00 | 0.000 | 81.0 | Spheres | 90 ± 9 | 2a |
| S2 b | 0.01 | 0.087 | 83.6 | Combination | Shape dependent | 2b |
| S3 b | 0.01 | 0.100 | 85.0 | Spheres and rods | Shape dependent | 2c |
| S4 a | 0.02 | 0.000 | 86.0 | Rods | 150 × 20 | 2d |
| S5 a | 0.02 | 0.087 | 89.8 | Cubes | 200 × 200 ± 13 | 2e |
| S6 a | 0.02 | 0.100 | 90.5 | Pyramids | 100 ± 12 | 2f |
| S7 b | 0.03 | 0.000 | 87.0 | Irregular spheres | 300 ± 11 | 2g |
| S8 b | 0.03 | 0.087 | 92.2 | Combination | Shape dependent | 2h |
| S9 b | 0.03 | 0.100 | 96.2 | Combination | Shape dependent | 2i |
| S10 b | 0.04 | 0.000 | 89.7 | Irregular spheres | 500 ± 8 | 2j |
| S11 b | 0.04 | 0.087 | 96.8 | Irregular spheres | 200–250 ± 10 | 2k |
| S12 a | 0.04 | 0.100 | 97.1 | Spheres | 5 ± 3 | 2l |
a Sample with ideal, homogenous nano-geometries; b Sample with irregular or combination geometries. CuNPs: copper nanoparticles; CTAB: cetyltrimethylammonium bromide; SE: standard error; SDS: sodium dodecyl sulphate.
Figure 1(a) Sample S1, Spherical nanoparticles (90 nm); (b) Sample S2, Combination of spheres and rods; (c) Sample S3, Combination spheres and rods with predominant rods; (d) Sample S4, Rod-like nanoparticles; (e) Sample S5, Cubic-shaped nanoparticles; (f) Sample S6, Pyramidal nanoparticles; (g) Sample S7, Irregular spherical particles; (h) Sample S8, Combination of neogeometrical nanoparticles; (i) Sample S9, Combination of neogeometrical nanoparticles at reduced size range; (j) Sample S10, Irregular nanospheres; (k) Sample S11, Spherical nanoparticles (250–300 nm); and (l) Sample S12, Spherical nanoparticles (10 nm).
Figure 2Schematic of growth of homogenous shapes according to surfactant variation: (a) Growth of a rod structure from the decahedral precursor; (b) tetrahedral precursor geometry; (c) polyhedral precursor geometry; and (d) cuboctahedral precursor geometry growing from the (100) and (111) planes. CTAB: cetyltrimethylammonium bromide; SDS: sodium dodecyl sulphate.
Zeta potential data collated from all CuNPs samples.
| Formulation | [CTAB] | [SDS] | Zeta Potential (mV) |
|---|---|---|---|
| S1 | 0.00 | 0.000 | −28.3 |
| S2 | 0.01 | 0.087 | −19.9 |
| S3 | 0.01 | 0.100 | −25.7 |
| S4 | 0.02 | 0.000 | 26.9 |
| S5 | 0.02 | 0.087 | −30.3 |
| S6 | 0.02 | 0.100 | −21.3 |
| S7 | 0.03 | 0.000 | 27.1 |
| S8 | 0.03 | 0.087 | −6.75 |
| S9 | 0.03 | 0.100 | −34.5 |
| S10 | 0.04 | 0.000 | 33.1 |
| S11 | 0.04 | 0.087 | −18.4 |
| S12 | 0.04 | 0.100 | 16.7 |
Figure 3Fourier-Transform Infrared (FTIR) spectra of: (a) ascorbic acid; (b) Sample S1; (c) CTAB; (d) SDS; (e) Sample S4; and (f) Sample S5.
Figure 4Thermogravimetric Analysis (TGA) curves of: (a) Sample S1 showing degradation of reducing agent (highlighted area in red); and (b) Sample S2 showing degradation of surfactants on the NP surface (highlighted area in red).
Figure 5Ex vivo permeation profiles of geometric copper nanoparticles through excised BALB/c mice dermal tissue (n = 3).
Copper nanoparticle flux and associated permeability coefficients for the geometric copper nanoparticles through excised BALB/c mice dermal tissue (n = 3).
| Formulation | Geometrical Structure | Flux, JS, (mg·cm−2·hr−1) | CuNPs Retained in Dermal Tissue (mg) |
|---|---|---|---|
| S1 | Spheres (90 nm) | 4.20 × 10−2 | 0.09 |
| S4 | Rods | 3.61 × 10−2 | 0.14 |
| S5 | Cubes | 3.75 × 10−2 | 0.34 |
| S6 | Pyramids | 2.66 × 10−2 | 0.28 |
| S12 | Spheres (5 nm) | 5.88 × 10−2 | 0.11 |