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The rational design of recognitive polymeric networks for sensing applications.

机译:用于传感应用的可识别聚合物网络的合理设计。

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Testosterone recognitive networks were synthesized with varying feed crosslinking percentages and length of the bi-functional crosslinking agent to analyze the effect of changing structural parameters on template binding properties such as affinity, selectivity, capacity, and diffusional transport. The crosslinking percentage of the crosslinking monomer ethylene glycol dimethacrylate was varied from 50% to 90% and associated networks experienced a 2 fold increase in capacity and a 4 fold increase in affinity with the equilibrium association constants, Ka, ranging from 0.32 +/- 0.02 x 10 4 M-1 to 1.3 +/- 0.1 x 104 M -1, respectively. The higher concentration of crosslinking monomer increased the crosslinking points available for inter-chain stabilization creating an increased number of stable cavities for template association. However, by increasing the length of the crosslinking agent and increasing the feed crosslinking percentage from 77% crosslinked poly(methacrylic acid- co-ethylene glycol dimethacrylate) (poly(MAA-co-EGDMA)) to 50% crosslinked poly(methacrylic acid-co-poly(ethylene glycol)200 dimethacrylate) (poly(MAA-co-PEG200DMA)), the mesh size of the network increased resulting in an increased template diffusion coefficient from (2.83 +/- 0.06) x 109 cm2/s to (4.3 +/- 0.06) x 109 cm2/s, respectively, which is approximately a 40% faster template diffussional transport. A 77% crosslinked poly (MAA-co-PEG200DMA) recognitive network had an association constant of (0.20 +/- 0.05) x 104 M -1 and bound (0.72 +/- 0.04) x 10-2 mmol testosterone/g dry polymer, which was less by 6 and 3 fold, respectively, compared to a similarly crosslinked poly(MAA-co-EGDMA) recognitive network. Structural manipulation of the macromolecular architecture illustrates the programmability of recognitive networks for specific template binding parameters and diffusional transport, which may lead to enhanced imprinted sensor materials and successful integration onto sensor platforms.
机译:合成具有不同进料交联百分比和双功能交联剂长度的睾丸激素识别网络,以分析改变结构参数对模板结合性能(如亲和力,选择性,容量和扩散运输)的影响。交联单体乙二醇二甲基丙烯酸酯的交联百分比在50%至90%之间变化,并且相关网络的容量与平衡缔合常数Ka的亲和力增加2倍,亲和力增加4倍,范围为0.32 +/- 0.02 x 10 4 M-1至1.3 +/- 0.1 x 104 M -1。较高浓度的交联单体增加了可用于链间稳定的交联点,从而增加了用于模板缔合的稳定腔的数量。但是,通过增加交联剂的长度并将进料交联百分比从77%交联的聚(甲基丙烯酸-乙二醇二甲基丙烯酸酯)(聚(MAA-co-EGDMA))提高到50%交联的聚(甲基丙烯酸-共聚(乙二醇)200二甲基丙烯酸酯)(聚(MAA-co-PEG200DMA)),网络的网眼尺寸增加,导致模板扩散系数从(2.83 +/- 0.06)x 109 cm2 / s增加到(分别为4.3 +/- 0.06)x 109 cm2 / s,这大约是模板扩散速度的40%。一个77%交联的聚(MAA-co-PEG200DMA)识别网络具有(0.20 +/- 0.05)x 104 M -1的缔合常数和结合(0.72 +/- 0.04)x 10-2 mmol睾丸酮/克干聚合物与类似的交联聚(MAA-co-EGDMA)识别网络相比,分别减少了6倍和3倍。大分子体系结构的结构操作说明了识别网络针对特定模板结合参数和扩散传输的可编程性,这可能会导致印迹传感器材料的印迹增强并成功集成到传感器平台上。

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