Yang Cheng,Yuan Liu,Jiguang Li,Yudong Li,Da Lei,Dezhong Li,Xincun Dou
Highly efficient detection of environmental residual potentially toxic species is of concern worldwide as their presence in an excessive amount would greatly endanger the health of human beings as well as environmental sustainability. The solvation effect is a critical factor to be considered for understanding chemical reaction progress as well as the photophysical behaviors of substances and thus is promising for visualized detection of metal ions. Herein, by applying 5-amino-1,10-phenanthroline (APT) as the optical probe, a sensing strategy was proposed based on the solvation effect modulated complexation of APT towards different metal ions to achieve the visualized discrimination of four critical ions (Cu(II), Zn(II), Cd(II), and Al(III)). How the crucial intrinsic properties of the solvent (e.g., polarity, solvent free energy, and electrostatic potential) influenced the complexation and the product emission was clarified, and the detection performances were systematically evaluated with detection limits as low as the nM level and good recognition selectivity. Furthermore, a portable sensing chip was developed with potential for highly efficient analysis in complicated scenes; thus, this strategy offers a new insight into determining multiple metal ions or other critical substances upon solvation manipulation.
Zhongfei Shang,Meimei Wang,Honghong Li,Jiahao Dong,Luyan Yang,Xincun Dou,Baiyi Zu
The exploration of efficient hazardous chemical sensing technology is of great importance to protect the environment and maintain public security. Here, a design strategy of a trimode upconversion nanoprobe was developed for H2O2 detection through establishing the inner filter effect (IFE) between the anthracene-based probes and the NaYF4:Yb/Tm/Er upconversion nanoparticles (UCNPs). The trimode nanoprobe exhibits superior H2O2 detection performance, including a low limit of detection (LOD) of 152 nM, fast response (<3 s), outstanding selectivity, and robust anti-interference ability even in the presence of 15 common interferents. Furthermore, the practical utility of this design is conclusively demonstrated through a sensing chip capable of accurately and selectively identifying H2O2 even in the presence of more than 7 types of coexisting multicolor interferents. This sensing strategy, characterized by its strong anti-interference capability even when facing extremely complex real-world samples, is expected to establish a promising framework for ultra-accurate detection of hazardous substances.
Yi Liu,Huanjiao Weng,Zhiwei Chen,Ming Zong,Shubin Fang,Zili Wang,Shaohua He,Yangming Wu,Jizhen Lin,Shangyuan Feng,Duo Lin
The Omicron variants of SARS-CoV-2 have been spreading globally and has never disappeared from our sight, indicating that its coexistence with humans has become a fact, and monitoring its evolution and spread remains a current task. Although polymerase chain reaction (PCR) is the most commonly used virus detection method, it requires labor-intensive and time-consuming procedures in a laboratory setting. Herein, a multichannel nanoplasmonic sensing chip based on surface enhanced Raman spectroscopy (SERS) was developed for detecting N and S proteins, as well as IgG and IgM, related to SARS-CoV-2 Omicron variants. Through a self-screening process, specific antibodies for on-site and rapid identification of important variants of concerns (VoCs) were obtained, and their binding was confirmed by protein structure analysis. The use of these S protein specific antibodies can accurately identify Omicron VoCs (BA. 5, BF.7，XBB.1.5) with the detection limit (LoD) at 0.16 pg/mL. Then, the proposed SERS array chip was integrated with a hand-held Raman spectrometer to successfully detect the Omicron subvariants in real saliva samples within only 20 minutes, greatly reducing the detection time of PCR. This sensing technology will provide a powerful and rapid point-of-care testing (POCT) method for virus diagnosis, subtype identification, and post infection antibody level monitoring.
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