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Nowadays, fuel cells (FCs) attracted a great deal of attention due to their many applications and advantages: Higher efficiency than diesel or gas engines, less pollution than fossil fuels, no using fuels such as oil and gas and reducing economic dependence on fossil fuel producing countries and easy maintenance are the advantages of FCs. However, the obstacles encountered FCs commercialization’s are mainly expensive electrocatalyst materials such as platinum (Pt), it’s poisoning by intermediates like as CO and sluggish electrooxidation kinetics of fuels. For this reasons, in order to minimize the amount of Pt and accordingly total cost of FCs and also decreasing the poisoning effects, Pt particles are deposited on/in different conductive supports. Herein we investigated the effect of carbon nanoparticles (CNPs) and reduced graphene oxide (RGO) nanosheets on the carbon-ceramic electrode (CCE) as support for Pt nanoparticles (PtNPs) toward formic acid electro-oxidation. PtNPs were successfully deposited on the CNPs and RGO with electrochemical method. The fabricated nanocomposites were characterized by the field emission scanning electron microscopy, energy-dispersive X-ray and X-ray powder diffraction spectroscopy. The electrocatalytic activities of the prepared electrocatalysts for oxidation of formic acid were investigated in 0.1 M H 2 SO 4 solution by electrochemical techniques including cyclic voltammetry (CV) and chronoamperometry (CA). The results of the experiments revealed that the PtNPs on the CNPs, PtNPs/CNPs/CCE, shows more electrocatalytic activity than the RGO nanosheets support. This high electrocatalytic efficiency of the PtNPs/CNPs/CCE can be attributed to large specific surface area and unique structure of CNPs that is being used as support. The influence of some experimental agents on the electrocatalytic activity of the PtNPs/CNPs/CCE was investigated and the optimal conditions were suggested. The present investigation reveals that the PtNPs/CNPs/CCE is a promising electrocatalyst for the formic acid electro-oxidation reaction in FCs. Graphic Abstract Preparation and electrocatalytic performance of carbon support and alone PtNPs toward oxidation of formic acid.

Cu 2 SnS 3 quantum dots (QDs) were employed to create colorimetric and chemiluminometric probes for the detection of acetamiprid. We demonstrated that the chemiluminescence (CL) signal of the luminol-hydrogen peroxide system, as well as the absorbance of the oxidation product of TMB with H 2 O 2 , was enhanced by the catalytic effect of Cu 2 SnS 3 QDs. Additionally, the enhanced signals from both probes (CL intensity and absorbance) were diminished upon the addition of acetamiprid to the reaction mixture owing to the decrease in the generation of reactive oxygen species (ROS) via the interaction of hydroxyl radicals with cyanide groups of acetamiprid during the reactions. Based on these findings, we developed a colorimetric sensor for acetamiprid with both spectrophotometer-based and smartphone-based detections (with detection limits of 3.6 nM and 14.2 nM, respectively), alongside a CL sensor with a detection limit of 2.7 nM. The sensors were employed for analyzing food and water samples, yielding satisfactory results. These probes combine the advantages of both techniques, including a low limit of detection and rapid response time of CL, as well as the simplicity, cost-effectiveness, and portable nature of smartphone-based colorimetry that also allows for in-field visual detection. Graphical Abstract

Cu.sub.2SnS.sub.3 quantum dots (QDs) were employed to create colorimetric and chemiluminometric probes for the detection of acetamiprid. We demonstrated that the chemiluminescence (CL) signal of the luminol-hydrogen peroxide system, as well as the absorbance of the oxidation product of TMB with H.sub.2O.sub.2, was enhanced by the catalytic effect of Cu.sub.2SnS.sub.3 QDs. Additionally, the enhanced signals from both probes (CL intensity and absorbance) were diminished upon the addition of acetamiprid to the reaction mixture owing to the decrease in the generation of reactive oxygen species (ROS) via the interaction of hydroxyl radicals with cyanide groups of acetamiprid during the reactions. Based on these findings, we developed a colorimetric sensor for acetamiprid with both spectrophotometer-based and smartphone-based detections (with detection limits of 3.6 nM and 14.2 nM, respectively), alongside a CL sensor with a detection limit of 2.7 nM. The sensors were employed for analyzing food and water samples, yielding satisfactory results. These probes combine the advantages of both techniques, including a low limit of detection and rapid response time of CL, as well as the simplicity, cost-effectiveness, and portable nature of smartphone-based colorimetry that also allows for in-field visual detection. Graphical

Cu SnS quantum dots (QDs) were employed to create colorimetric and chemiluminometric probes for the detection of acetamiprid. We demonstrated that the chemiluminescence (CL) signal of the luminol-hydrogen peroxide system, as well as the absorbance of the oxidation product of TMB with H O , was enhanced by the catalytic effect of Cu SnS QDs. Additionally, the enhanced signals from both probes (CL intensity and absorbance) were diminished upon the addition of acetamiprid to the reaction mixture owing to the decrease in the generation of reactive oxygen species (ROS) via the interaction of hydroxyl radicals with cyanide groups of acetamiprid during the reactions. Based on these findings, we developed a colorimetric sensor for acetamiprid with both spectrophotometer-based and smartphone-based detections (with detection limits of 3.6 nM and 14.2 nM, respectively), alongside a CL sensor with a detection limit of 2.7 nM. The sensors were employed for analyzing food and water samples, yielding satisfactory results. These probes combine the advantages of both techniques, including a low limit of detection and rapid response time of CL, as well as the simplicity, cost-effectiveness, and portable nature of smartphone-based colorimetry that also allows for in-field visual detection.