Insight into the intrinsic activity of various transition metal sulfides for efficient hydrogen evolution reaction.

The electrocatalytic hydrogen evolution reaction (HER) is an efficient approach to convert sustainable energy sources into clean energy carriers, H2. Although various transition metal sulfides (TMSs) have been reported as promising alternatives to precious metal-based catalysts, the top catalyst among TMSs remains unclear as there is a dearth of high-quality studies that provide a 'fair' comparison of the performance of these TMSs synthesized and tested under the same conditions. In this work, layered transition metal sulfides (MS2: MoS2, WS2, VS2) and non-layered transition metal sulfides (MxSy: FeS2, CoSx, NiS) were obtained by a straightforward hydrothermal method, and thus a comprehensive platform was established for the comparison of the intrinsic activity of these materials in the HER. Experimental results demonstrate that layered MS2 exhibits better performance than non-layered MxSy in acidic electrolytes, while CoSx and NiS can catalyze hydrogen evolution more effectively under alkaline conditions due to structural reconfiguration. MoS2 shows the best HER performance in both acidic and alkaline electrolytes, particularly in 1 M KOH solution. This work provides guidance for the optimal design of transition metal electrocatalysts, and structural engineering strategies can be used to further enhance their catalytic activity.

A corpus of CO2 electrocatalytic reduction process extracted from the scientific literature.

The electrocatalytic CO2 reduction process has gained enormous attention for both environmental protection and chemicals production. Thereinto, the design of new electrocatalysts with high activity and selectivity can draw inspiration from the abundant scientific literature. An annotated and verified corpus made from massive literature can assist the development of natural language processing (NLP) models, which can offer insight to help guide the understanding of these underlying mechanisms. To facilitate data mining in this direction, we present a benchmark corpus of 6,086 records manually extracted from 835 electrocatalytic publications, along with an extended corpus with 145,179 records in this article. In this corpus, nine types of knowledge such as material, regulation method, product, faradaic efficiency, cell setup, electrolyte, synthesis method, current density, and voltage are provided by either annotating or extracting. Machine learning algorithms can be applied to the corpus to help scientists find new and effective electrocatalysts. Furthermore, researchers familiar with NLP can use this corpus to design domain-specific named entity recognition (NER) models.

Construction of imine-linked covalent organic framework as advanced adsorbent for the sensitive determination of chlorophenols.

Food safety is a great concern of the general public. Chlorophenols (CPs) as organic pollutant can be found in drinking water and foods, causing serious harm to human health. Herein, imine-linked covalent organic frameworks (COFs), named as TAPT-AN-COF, was synthesized by aniline modulation strategy through condensation of 1,3,5-triformylphoroglucinol and 4,4',4''-(1,3,5-Triazine-2,4,6-triyl)trianiline with aniline as modulator. The prepared TAPT-AN-COF possesses good crystallinity and regular morphology, displaying excellent adsorption capability towards CPs pollutants. Thus, the TAPT-AN-COF was used as novel adsorbent for off-line solid-phase extraction of four CPs (2-CP, 3-CP, 2,3-CPs, 2,4-CPs) from bottled water, tea drink and honey samples before high performance liquid chromatography-ultraviolet detection. Under optimal conditions, wide linear range, low detection limits and satisfactory extraction recovery were gained. The π-stacking and hydrophobic interactions between the TAPT-AN-COF and the analytes played an important role in the adsorption. The established method has a great potential in determining other hydrophobic aromatic compounds.