材料基因组工程理念下植物酚类AIE荧光纳米材料的高效定制

Fluorescent nanomaterials are widely used and environmentally friendly make them superior. Phenolic compounds have fluorescence and can assemble into green, high performance fluorescent nanomaterials via aggregation-induced emission (AIE). Based on the concept of materials genome engineering, this study intends to calculate optimal quantitative structure-activity relationship model between chemical structures and fluorescence properties using common vegetable phenolic compounds. AIE fluorescent nanomaterials will be obtained by self-assembly under different conditions, the intrinsic mechanism between phenolic compounds structure, self-assembly conditions, microstructure and fluorescence properties will be revealed. The map relational database will be built on vegetable phenolic chemical structures (intrinsic gene characteristics), self-assembly conditions & product morphology (external gene characteristics), and fluorescent nanomaterials properties. According to the database, chemical structure will be designed, synthesis and modification will be oriented, and self-assembly will be done under beneficial conditions. Therefore, rapid screening and efficient editable preparation of vegetable phenols fluorescent nanomaterials will be realized and effects of different environments and conditions on properties of fluorescent nanomaterials will be analyzed. The possible application scope and application prospects of the green new materials will be explored. This study will not only be helpful to editable preparation of fluorescent nanomaterials efficiently but also provide a new way for high value utilization of vegetable phenols.

荧光纳米材料应用广泛，环境友好使其更优越。植物酚类物质具有荧光性质，通过聚集诱导发光（AIE）作用可获得绿色高性能荧光纳米材料。本研究基于材料基因组工程理念，拟以常见植物酚类化合物为原料，计算结构与荧光性质最佳定量构效关系。在不同条件下通过超分子自组装获得植物酚类AIE荧光纳米材料，揭示化合物结构、自组装条件、产物微观形态与荧光性能之间的内在关联机制，构建植物酚类化合物结构（内在基因特征）、自组装条件和产物形态等（外在基因特征）与荧光纳米材料性能映射关系数据库。以数据库为指导，根据需要优化设计植物酚类及衍生物化学结构，定向合成与修饰，在优选条件下自组装，从而实现快速筛选、高效定制植物酚类荧光纳米材料，并分析不同使用环境和条件对各荧光纳米材料性能的影响，探索该绿色新材料可能的应用范围及应用前景。该研究将不仅有助于高效定制植物酚类荧光纳米材料，还为植物酚类高值化利用提供新途径，具有重要意义。

研究收集了厚朴酚、槲皮素、绿原酸等共计33种天然酚类化合物，通过CODESSA 软件计算确定了植物酚类化合物结构与荧光量子效率的最佳定量构效关系模型。选择在自然界分布广泛的槲皮素为代表化合物，通过超分子自组装促进聚集诱导荧光增强（AIE）、水热碳化促进荧光红移等调控荧光特性，研究其在生物成像、促进植物光合作用等方面的应用。选择在自然界储量较大、基本结构单元荧光量子效率较高、但尚未得到高附加值利用的落叶松树皮多酚为原料，通过复合、掺杂、金属离子络合等方法对其荧光性能进行调控。此外还对富含酚羟基的绿原酸、紫胶红色素等在超分子自组装作用下构建 AIE 纳米材料，并探索了在离子检测、荧光传感器等方面的应用。

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