The galvanostatic charge–discharge (GCD) behaviour of silicon (Si) is known to depend strongly on morphology, cycling conditions and electrochemical environment. One common method for analysing GCD curves is through differential capacity, but the data processing required necessarily degrades the results. Here we present a method of extracting empirical information from the delithiation step in GCD data for Si at C-rates above equilibrium conditions. We find that the function is able to quickly and accurately determine the best fit to historical half-cell data on amorphous Si nanowires and thin films, and analysis of the results reveals that the function is capable of distinguishing the capacity contributions from the Li3.5Si and Li2Si phases to the total capacity. The method can also pick up small differences in the phase behaviour of the different samples, making it a powerful technique for further analysis of Si data from the literature. The method was also used for predicting the size of the reservoir effect (the apparent amount of Li remaining in the electrode), making it a useful technique for quickly determining voltage slippage and related phenomena. This work is presented as a starting point for more in-depth empirical analysis of Si GCD data.
Developing highly efficient electrocatalysts for electrochemical CO2 reduction (ECR) to value‐added products is important for CO2 conversion and utilization technologies. In this work, a sulfur‐doped Ni−N−C catalyst is fabricated through a facile ion‐adsorption and pyrolysis treatment. The resulting Ni−NS−C catalyst exhibits higher activity in ECR to CO than S‐free Ni−N−C, yielding a current density of 20.5 mA cm−2 under −0.80 V versus a reversible hydrogen electrode (vs. RHE) and a maximum CO faradaic efficiency of nearly 100 %. It also displays excellent stability with negligible activity decay after electrocatalysis for 19 h. A combination of experimental investigations and DFT calculations demonstrates that the high activity and selectivity of ECR to CO is due to a synergistic effect of the S and Ni−NX moieties. This work provides insights for the design and synthesis of nonmetal atom‐decorated M−N−C‐based ECR electrocatalysts.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.