Literature DB >> 25692225

Nano copper oxide-incorporated mesoporous carbon composite as multimode adsorbent for selective isolation of hemoglobin.

Yang Zhang1, Li-Gang Xing, Xu-Wei Chen, Jian-Hua Wang.   

Abstract

Assembly of nano-objects with tunable size, morphology and function into integrated nanostructures is critical for the development of a novel nanosystem in adsorption, sensing and drug/gene delivery. We demonstrate herein the fabrication of ordered mesoporous carbon by assembling uniform and highly dispersed copper-oxide (CuxOy) nanoparticles into the mesopores via evaporation of solvent from the mixture of triblock copolymer, carbon source and metal nitrate hydrate. The ordered 2D hexagonal mesoporous carbon composite possesses a large surface area of 580.8 cm(2)/g, a uniform pore size of 5.4 nm, a large pore volume of 0.64 cm(3)/g and a high metal content of 3.32 wt %. The mesoporous composite exhibits excellent adsorption selectivity and high adsorption capacity to hemoglobin (Hb) under the synergistic effect of hydrophobic and metal-affinity interactions as well as size exclusion. This facilitates multimode adsorption of hemoglobin fitting Langmuir adsorption model and offers an adsorption capacity of 1666.7 mg g(-1) for hemoglobin. The mesoporous composite is used for the isolation of hemoglobin from human whole blood with high purity. It demonstrates the potential of the copper-oxide nanoparticle-embedded mesoporous carbon composite in selective isolation/removal of specific protein species from biological sample matrixes.

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Keywords:  copper-oxide nanoparticles; hemoglobin; mesoporous carbon; multimodal adsorption

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Year:  2015        PMID: 25692225     DOI: 10.1021/am508836m

Source DB:  PubMed          Journal:  ACS Appl Mater Interfaces        ISSN: 1944-8244            Impact factor:   9.229


  1 in total

1.  Synthesis of Ag nanoparticles/ordered mesoporous carbon as a highly efficient catalyst for the electroreduction of benzyl bromide.

Authors:  Zhi-Xia Zhang; Shuo Wang; Shi-Ming Li; Si-Li Shan; Huan Wang; Jia-Xing Lu
Journal:  RSC Adv       Date:  2020-01-03       Impact factor: 4.036

  1 in total

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