A novel immunosensor based on cobalt oxide nanocomposite modified single walled carbon nanohorns for the selective detection of aflatoxin B1.

We developed a novel, sensitive, and selective platform for the specific determination of aflatoxin B1 (AFB1). Single-walled carbon nanohorns decorated by a cobalt oxide composite and gold nanoparticles were created to provide facile electron transfer and improve the sensor's sensitivity. In addition, we attributed the selectivity of the proposed sensor to the specific binding property of the anti-aflatoxin B1 antibody. We clarified the specific interaction of the proposed immunosensor to AFB1 using homology modeling combined with molecular docking. In the presence of AFB1, the current signal of the modified electrode reduced; this involved specific antibody-antigen binding, including hydrophobic hydrogen bonding and pi-pi stack interactions. The new AFB1 sensor platform showed two linearity ranges of 0.01-1 ng mL-1 and 1-100 ng mL-1, with the limit of detection at 0.0019 ng mL-1. We investigated the proposed immunosensor in real samples, including peanuts, certified reference material of a peanut sample (labeled 206 µg kg-1 AFB1), corn, and chicken feed. The sensor's accuracy was 86.1-104.4% recovery, which agrees with the reference HPLC technique using paired t-test analysis. The present work shows excellent performance for AFB1 detection and could be applied for food quality control or modified to detect other mycotoxins.

Data-Driven Discovery of Graphene-Based Dual-Atom Catalysts for Hydrogen Evolution Reaction with Graph Neural Network and DFT Calculations.

The flexible tuning ability of dual-atom catalysts (DACs) makes them an ideal system for a wide range of electrochemical applications. However, the large design space of DACs and the complexity in the binding motif of electrochemical intermediates hinder the efficient determination of DAC combinations for desirable catalytic properties. A crystal graph convolutional neural network (CGCNN) was adopted for DACs to accelerate the high-throughput screening of hydrogen evolution reaction (HER) catalysts. From a pool of 435 dual-atom combinations in N-doped graphene (N6Gr), we screened out two high-performance HER catalysts (AuCo@N6Gr and NiNi@N6Gr) with excellent HER, electronic conductivity, and stability using the combination of CGCNN and density functional theory (DFT). Furthermore, comprehensive DFT studies were conducted on these two catalysts to confirm their outstanding reaction kinetics and to understand the cooperative effect between the metal pair for HER. To obtain ideal hydrogen binding in AuCo, the inert Au weakens the strong hydrogen binding of Co, while for NiNi, the two weakly binding Ni cooperate. The present protocol was able to select the two catalysts with different physical origins for HER and can be applied to other DAC catalysts, which should hasten catalyst discovery.

Detection of hazardous mercury ion using [5]helicene-based fluorescence probe with "TurnON" sensing response for practical applications.

A new fluorescence probe based on [5]helicene derivative (MT) was designed and synthesized. The chemical structure of the probe was fully characterized by NMR, mass spectrometry and X-ray crystallography. MT which is the combination of thioamide[5]helicene with Schiff base-thiophene moiety, exhibited a high selectivity to detect Hg2+ through irreversible desulfurization reaction with "TurnON" fluorescence response and large Stokes shift of 110 nm in aqueous methanol solution. The detection limit of MT was 1.2 ppb (6.0 × 10-3 µM), which is lower than the limit of Hg2+ level in drinking water, as specified by WHO (6.0 ppb) and U.S. EPA (2.0 ppb). The Hg2+ detection range of the probe was 0.07-1.6 µM with good linearity. Under UV irradiation, MT possessed the capability to detect Hg2+ in diverse context of real samples, including drinking and sea waters, vegetable tissue and brain tumor cell. In addition, MT could be used as a paper test strip for monitoring and screening of Hg2+ contamination in environment.