CE of poly(amidoamine) succinamic acid dendrimers using a poly(vinyl alcohol)‐coated capillary

Desai, Ankur; Shi, Xiangyang; Baker, James R.

doi:10.1002/elps.200700454

Cited by 12 publications

(7 citation statements)

References 38 publications

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“…Wilcoxon et al (2000) have shown that hard nanoparticle Au nanoclusters are as monodisperse as 99.9% pure (C 60 ). Soft nanoparticle dendrimers are routinely produced as high as generation = 6–8 with polydispersities ranging from 1.011 to 1.201 (Islam et al 2005a; b; Desai et al 2008). …”

Section: Proposed Nanoelement Categories and Criteriamentioning

confidence: 99%

In quest of a systematic framework for unifying and defining nanoscience

2009

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This article proposes a systematic framework for unifying and defining nanoscience based on historic first principles and step logic that led to a “central paradigm” (i.e., unifying framework) for traditional elemental/small-molecule chemistry. As such, a Nanomaterials classification roadmap is proposed, which divides all nanomatter into Category I: discrete, well-defined and Category II: statistical, undefined nanoparticles. We consider only Category I, well-defined nanoparticles which are >90% monodisperse as a function of Critical Nanoscale Design Parameters (CNDPs) defined according to: (a) size, (b) shape, (c) surface chemistry, (d) flexibility, and (e) elemental composition. Classified as either hard (H) (i.e., inorganic-based) or soft (S) (i.e., organic-based) categories, these nanoparticles were found to manifest pervasive atom mimicry features that included: (1) a dominance of zero-dimensional (0D) core–shell nanoarchitectures, (2) the ability to self-assemble or chemically bond as discrete, quantized nanounits, and (3) exhibited well-defined nanoscale valencies and stoichiometries reminiscent of atom-based elements. These discrete nanoparticle categories are referred to as hard or soft particle nanoelements. Many examples describing chemical bonding/assembly of these nanoelements have been reported in the literature. We refer to these hard:hard (H-n:H-n), soft:soft (S-n:S-n), or hard:soft (H-n:S-n) nanoelement combinations as nanocompounds. Due to their quantized features, many nanoelement and nanocompound categories are reported to exhibit well-defined nanoperiodic property patterns. These periodic property patterns are dependent on their quantized nanofeatures (CNDPs) and dramatically influence intrinsic physicochemical properties (i.e., melting points, reactivity/self-assembly, sterics, and nanoencapsulation), as well as important functional/performance properties (i.e., magnetic, photonic, electronic, and toxicologic properties). We propose this perspective as a modest first step toward more clearly defining synthetic nanochemistry as well as providing a systematic framework for unifying nanoscience. With further progress, one should anticipate the evolution of future nanoperiodic table(s) suitable for predicting important risk/benefit boundaries in the field of nanoscience.Electronic supplementary materialThe online version of this article (doi:10.1007/s11051-009-9632-z) contains supplementary material, which is available to authorized users.

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Section: Proposed Nanoelement Categories and Criteriamentioning

confidence: 99%

In quest of a systematic framework for unifying and defining nanoscience

2009

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“…If a Gaussian distribution of surface functionalization is assumed, the present results suggest, based on peak areas, that fractions 3, 4, and 5 contain dendrimer conjugates with larger biotin coverage, and fractions 1 and 2 contain biotinylated conjugates with a lower degree of functionalization. These results illustrate the enhanced potential of UPLC to assess generational defect levels as well as degree of dendrimer surface modification in greater detail than has been possible by HPLC analyses or other chromatographic methods such as CE [31][32][33]50]. Current methods utilized to determine the degree of functionality such as NMR and matrix assisted laser desorption/ionization-time of flight (MALDI-TOF) only provide an estimated average number of surface functional moieties.…”

Section: Resultsmentioning

confidence: 85%

Improved Methodology for Monitoring Poly(amidoamine) Dendrimers Surface Transformations and Product Quality by Ultra Performance Liquid Chromatography

Cason

Oehrle

Fabré

et al. 2008

Journal of Nanomaterials

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Ultra performance liquid chromatography (UPLC) analysis was utilized for the first time as a methodology for monitoring poly(amidoamine) (PAMAM) dendrimer surface transformations and product quality. Results were compared to high-performance liquid chromatography (HPLC) and were found to provide a vastly improved analytical method for the characterization of dendrimer polydispersity and variance in a typical surface modification. The application of UPLC increased the average number of theoretical plates by a factor of 7 and reduced retention times of analytes by 36%, while improving the resolution capability to discriminate surface variances in dendrimers. The new UPLC procedures were used to monitor surface modification of [core: ethylenediamine]; (G = 4);dendri-poly(amidoamine)-(NH2)64(i.e., [EDA]; (G4);dendri-PAMAM-(NH2)64) to produce biotinylated dendrimer conjugates. The enhanced sensitivity and efficiency of the UPLC analyses allowed resolution of biotin substituent levels and a better characterization of the targeted dendrimer conjugates compared to traditional HPLC methodology.

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“…Wilcoxon et al (2000) have shown that hard nanoparticle Au nanoclusters are as monodisperse as 99.9% pure (C 60 ). Soft nanoparticle dendrimers are routinely produced as high as generation = 6-8 with polydispersities ranging from 1.011 to 1.201 (Islam et al 2005a;Desai et al 2008). …”

Section: Nanoelement Criteriamentioning

confidence: 99%