Herein, we demonstrate a template directed route for the synthesis of self-supported cobalt-iron based Prussian blue analogues (PBAs). The PBAs are electrochemically transformed into layered double hydroxides to produce excellent...

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Electrochemical water oxidation requires a highly active electrocatalyst system with improved catalytic activity, high mechanical stability, and strong catalyst−support interactions. In this respect, a unique and facile method has been developed for the synthesis of ultrathin Fe−Co(OH) 2 −Co(O) x (OH) y nanosheets from self-supported Prussian blue analogues by chronoamperometric method. High electrochemical surface area, improved electronic conductivity, enhanced mechanical stability, and atomic level thickness (∼3 nm) of the selfsupported ultrathin nanosheets provided the boost for alkaline water oxidation. The ultrathin Fe−Co(OH) 2 −Co(O) x (OH) y nanosheets demonstrated 10 mA cm −2 current density at only 250 mV overpotential for alkaline water oxidation. The ultrathin nanosheets also showed 24 h continuous oxygen evolution under chronoamperometric condition without losing the initial activity.

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Rapid detection and discrimination of pathogenic bacteria for food safety, environmental pollution, medical diagnoses, and chemical and biological threats remains a considerable challenge. In the present work, we demonstrate positively charged Ag/Au bimetallic nanoparticles (Ag/Au bmNPs) as a potential surface-enhanced Raman scattering (SERS) substrate for label-free detection and discrimination of three bacteria, viz., Escherichia coli, Salmonella typhimurium, and Bacillus subtilis with excellent reproducibility. The approach relies on a priori synthesis of Ag/Au bmNPs and subsequent SERS studies on bacteria. The positive surface charge on Ag/Au bmNPs offers significant advantages of short acquisition time at very low power, high sensitivity, and a simple operating procedure without the need of very specific procedures or protocols used to capture the bacteria. The reproducible and specific intrinsic fingerprint of the cell wall and intracellular components of three bacteria obtained by label-free SERS enables precise discrimination and classification of three bacteria using multivariate analyses such as principal component analysis and canonical discriminant analysis.