对致癌氨基甲酸乙酯(EC)危害的担忧驱使人们试图有效地利用,及时,直截了当,和早期食品安全预警的经济分析方法。这里,我们提出了一种新型的分子印迹聚合物Co@MOF-MIP,具有高的过氧化物酶(POD)样活性和明亮的蓝色荧光发射,为了开发一种通用的比色视觉检测方法,荧光,以及EC的光热三模态检测和逻辑门输出。简而言之,Co@MOF-MIP的POD样活性使其将H2O2分解为·OH,以氧化无色的3,3\',5,5'-四甲基联苯胺(TMB)成蓝色oxTMB,产生660nm的光热效应,并通过内部滤波器效应爆发Co@MOF-MIP的蓝色荧光,观察到减少的荧光信号以及增加的比色和660nm照射的光热信号。然而,EC可以专门填充Co@MOF-MIP的压印腔,以将催化底物TMB和H2O2从Co@MOF-MIP中阻断出来,以进一步与Co2的内部催化中心反应,导致TMB转化为oxTMB的抑制,在荧光信号增强中产生EC浓度依赖性三峰响应,比色法,和660nm照射光热信号减小。在智能手机和手持热成像仪等便携式设备的辅助下,提出了一种可视化的现场便携式三峰分析平台,用于EC的快速准确检测,比色法的低检出限为1.64、1.24和1.78μg/L。荧光,和光热模式,分别。有趣的是,这些反应性事件可以通过经典的布尔逻辑门分析进行编程,为大数据物联网监测和预警早期残留EC提供一种新颖的有希望的途径,动态,快,准确的方式,保障食品安全。
Concerns regarding the hazard of the carcinogenic ethyl carbamate (EC) have driven attempts to exploit efficient, timely, straightforward, and economic assays for warning early food safety. Here, we proposed a novel molecularly imprinted polymer Co@MOF-MIP, with a high peroxidase (POD)-like activity and a bright blue fluorescence emission, to develop a versatile visual assay for colorimetric, fluorescent, and photothermal trimodal detection and logic gate outputting of EC. Briefly, the POD-like activity of Co@MOF-MIP made it to decompose H2O2 into ·OH for oxidizing colorless 3,3\',5,5\'-tetramethylbenzidine (TMB) into a blue oxTMB, resulting in a 660 nm irradiated photothermal effect and bursting the blue fluorescence of Co@MOF-MIP via inner filter effect, observing a decreased fluorescence signal together with an increased colorimetric and 660 nm irradiated photothermal signals. However, EC could specifically fill the imprinted cavities of Co@MOF-MIP to block the catalytic substrates TMB and H2O2 out of Co@MOF-MIP for further reacting with the inside catalytic center of Co2+, resulting in the transformation suppressing of TMB into oxTMB, yielding an EC concentration-dependent trimodal responses in fluorescence signal enhancement, colorimetric, and 660 nm irradiated photothermal signal decreases. Assisted by the portable devices such as smartphones and hand-held thermal imagers, a visual onsite portable trimodal analytical platform was proposed for EC fast and accurate detection with the low detection limits of 1.64, 1.24, and 1.78 μg/L in colorimetric, fluorescent, and photothermal modes, respectively. Interestingly, these reactive events could be programmed by the classical Boolean logic gate analysis to offer a novel promising avenue for the big data Internet of Things monitoring and warning early residual EC in a more intelligent, dynamical, fast, and accurate manner, safeguarding food safety.