Graphene-like sheets supported Fe-Co layered double hydroxides nanoflakes as an efficient electrocatalyst for both hydrogen and oxygen evolution reaction, A green investigation

Composite of a thiacalix[4]arene-copper(I) metal-organic framework and mesoporous carbon for efficient electrochemical detection of antibiotics

Abundant use of nitrofurantoin (NFT) and metronidazole (MTZ) antibiotics has led to excessive residues in the environments and humans, resulting in serious damage to the human body and ecosystem. Therefore, effective detection of NFT and MTZ is exceedingly necessary. In this regard, metal-organic frameworks (MOFs) are promising materials as electrochemical sensors. Herein, we synthesized a new two-dimensional thiacalix [4]arene-copper (I) MOF (Cu-TC4A-M). This MOF was mixed with mesoporous carbon (MC) to a give Cu-TC4A-M@MC composite. In addition, the sensors of Cu-TC4A-M@MC(2:1)/GCE and Cu-TC4A-M@MC(1:2)/GCE were achieved (GCE = glassy carbon electrode), and then were applied for effectively detecting NFT and MTZ, respectively. Markedly, the two sensors exhibited satisfactory linear detection range, anti-interference, reproducibility and stability. When they were utilized in the real samples, such as human serum, urine, tap water and lake water, satisfactory recoveries were attained. The relative standard deviations (RSDs) were in the range of 1.16 % ∼ 1.92 % for NFT and 0.95 % ∼ 2.33 % for MTZ. This work provided a new application prospect for the thiacalix [4]arene-based MOFs as promising candidate materials for NFT and MTZ detection.

Sonication strategy for anchoring single metal atom oxides (W, Cu, Co) on CeO2-rGO for boosting electrocatalytic oxygen evolution reaction

In the field of electrocatalysis, single-atomic-layer tungsten, copper, and cobalt oxide on CeO2, ethylene diamine (ED) and reduced graphene oxide (rGO) supported materials shows tremendous potential. Despite the enormous interest in single metal atom oxide (SMAO) catalysts, it is still very difficult to directly convert readily available bulk metal oxide into single atom oxide. It is crucial and tough to create high performance materials for the oxygen evolution reaction (OER) in an alkaline environment. Herein, a single tungsten, copper and cobalt atom oxide (SMAO) anchored on the CeO2 atomic layer and overall components deposited on the rGO (rGO-ED-CeO2-WCuCo) is prepared through a one-pot sonication technique. The presence of SMAO is identified by high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) imaging. The electrocatalytic performance of final rGO-ED-CeO2-WCuCo-30 nanocomposite for the OER in 1 M KOH electrolyte is evidenced by providing low overpotential of 283 mV at 10 mA cm-2. The Tafel slope for OER using rGO-ED-CeO2-WCuCo-30 electrocatalysts is 57.03 mV dec-1. The electrocatalytic activity of rGO-ED-CeO2-WCuCo-30 nanocomposites for OER was noticeably increased when compared to bare CeO2 nanorods (401 mV), rGO-ED-CeO2-WCo-30 (345 mV), rGO-ED-CeO2-WCu-30 (340 mV) and rGO-ED-CeO2-WCuCo-20 (321 mV) samples.

Heterogeneous catalysis mediated by light, electricity and enzyme via machine learning: Paradigms, applications and prospects

Energy crisis and environmental pollution have become the bottleneck of human sustainable development. Therefore, there is an urgent need to develop new catalysts for energy production and environmental remediation. Due to the high cost caused by blind screening and limited valuable computing resources, the traditional experimental methods and theoretical calculations are difficult to meet with the requirements. In the past decades, computer science has made great progress, especially in the field of machine learning (ML). As a new research paradigm, ML greatly accelerates the theoretical calculation methods represented by first principal calculation and molecular dynamics, and establish the physical picture of heterogeneous catalytic processes for energy and environment. This review firstly summarized the general research paradigms of ML in the discovery of catalysts. Then, the latest progresses of ML in light-, electricity- and enzyme-mediated heterogeneous catalysis were reviewed from the perspective of catalytic performance, operating conditions and reaction mechanism. The general guidelines of ML for heterogeneous catalysis were proposed. Finally, the existing problems and future development trend of ML in heterogeneous catalysis mediated by light, electricity and enzyme were summarized. We highly expect that this review will facilitate the interaction between ML and heterogeneous catalysis, and illuminate the development prospect of heterogeneous catalysis.