High-Pressure Electro-Fenton Driving CH4 Conversion by O2 at Room Temperature.

Electrochemical conversion of CH4 to easily transportable and value-added liquid fuels is highly attractive for energy-efficient CH4 utilization, but it is challenging due to the low reactivity and solubility of CH4 in the electrolyte. Herein, we report a high-pressure electro-Fenton (HPEF) strategy to establish a hetero-homogeneous process for the electrocatalytic conversion of CH4 by O2 at room temperature. In combination with elevation of reactant pressure to accelerate reaction kinetics, it delivers an unprecedented HCOOH productivity of 11.5 mmol h-1 gFe-1 with 220 times enhancement compared to that under ambient pressure. Remarkably, an HCOOH Faradic efficiency of 81.4% can be achieved with an ultralow cathodic overpotential of 0.38 V. The elevated pressure not only promotes the electrocatalytic reduction of O2 to H2O2 but also increases the reaction collision probability between CH4 and •OH, which is in situ generated from the Fe2+-facilitated decomposition of H2O2.

Predicting sepsis onset in ICU using machine learning models: a systematic review and meta-analysis.

BACKGROUND: Sepsis is a life-threatening condition caused by an abnormal response of the body to infection and imposes a significant health and economic burden worldwide due to its high mortality rate. Early recognition of sepsis is crucial for effective treatment. This study aimed to systematically evaluate the performance of various machine learning models in predicting the onset of sepsis. METHODS: We conducted a comprehensive search of the Cochrane Library, PubMed, Embase, and Web of Science databases, covering studies from database inception to November 14, 2022. We used the PROBAST tool to assess the risk of bias. We calculated the predictive performance for sepsis onset using the C-index and accuracy. We followed the PRISMA guidelines for this study. RESULTS: We included 23 eligible studies with a total of 4,314,145 patients and 26 different machine learning models. The most frequently used models in the studies were random forest (n = 9), extreme gradient boost (n = 7), and logistic regression (n = 6) models. The random forest (test set n = 9, acc = 0.911) and extreme gradient boost (test set n = 7, acc = 0.957) models were the most accurate based on our analysis of the predictive performance. In terms of the C-index outcome, the random forest (n = 6, acc = 0.79) and extreme gradient boost (n = 7, acc = 0.83) models showed the highest performance. CONCLUSION: Machine learning has proven to be an effective tool for predicting sepsis at an early stage. However, to obtain more accurate results, additional machine learning methods are needed. In our research, we discovered that the XGBoost and random forest models exhibited the best predictive performance and were most frequently utilized for predicting the onset of sepsis. TRIAL REGISTRATION: CRD42022384015.

Inactivating SARS-CoV-2 by electrochemical oxidation.

Fully inactivating SARS-CoV-2, the virus causing coronavirus disease 2019, is of key importance for interrupting virus transmission but is currently performed by using biologically or environmentally hazardous disinfectants. Herein, we report an eco-friendly and efficient electrochemical strategy for inactivating the SARS-CoV-2 using in-situ formed nickel oxide hydroxide as anode catalyst and sodium carbonate as electrolyte. At a voltage of 5 V, the SARS-CoV-2 viruses can be rapidly inactivated with disinfection efficiency reaching 95% in only 30 s and 99.99% in 5 min. Mass spectrometry analysis and theoretical calculations indicate that the reactive oxygen species generated on the anode can oxidize the peptide chains and induce cleavage of the peptide backbone of the receptor binding domain of the SARS-CoV-2 spike glycoprotein, and thereby disables the virus. This strategy provides a sustainable and highly efficient approach for the disinfection of the SARS-CoV-2 viruliferous aerosols and wastewater.

Robust Interface Ru Centers for High-Performance Acidic Oxygen Evolution.

RuO2 is considered as the state-of-the-art electrocatalyst for the oxygen evolution reaction (OER) in acidic media. However, its practical application is largely hindered by both the high reaction overpotential and severe electrochemical corrosion of the active centers. To overcome these limitations, innovative design strategies are necessary, which remains a great challenge. Herein, robust interface Ru centers between RuO2 and graphene, via a controllable oxidation of graphene encapsulating Ru nanoparticles, are presented to efficiently enhance both the activity and stability of the acidic OER. Through precisely controlling the reaction interface, a much lower OER overpotential of only 227 mV at 10 mA cm-2 in acidic electrolyte, compared with that of 290 mV for commercial RuO2 , but a significantly higher durability than the commercial RuO2 , are achieved. Density functional theory (DFT) calculations reveal that the interface Ru centers between the RuO2 and the graphene can break the classic scaling relationships between the free energies of HOO* and HO* to reduce the limiting potential, rendering an enhancement in the intrinsic OER activity and the resistance to over-oxidation and corrosion for RuO2 .

Highly Selective Production of Ethylene by the Electroreduction of Carbon Monoxide.

Conversion of carbon monoxide to high value-added ethylene with high selectivity by traditional syngas conversion process is challenging because of the limitation of Anderson-Schulz-Flory distribution. Herein we report a direct electrocatalytic process for highly selective ethylene production from CO reduction with water over Cu catalysts at room temperature and ambient pressure. An unprecedented 52.7 % Faradaic efficiency of ethylene formation is achieved through optimization of cathode structure to facilitate CO diffusion at the surface of the electrode and Cu catalysts to enhance the C-C bond coupling. The highly selective ethylene production is almost without other carbon-based byproducts (e.g. C1 -C4 hydrocarbons and CO2 ) and avoids the drawbacks of the traditional Fischer-Tropsch process that always delivers undesired products. This study provides a new and promising strategy for highly selective production of ethylene from the abundant industrial CO.

Room-temperature electrochemical water-gas shift reaction for high purity hydrogen production.

Traditional water-gas shift reaction provides one primary route for industrial production of clean-energy hydrogen. However, this process operates at high temperatures and pressures, and requires additional separation of H2 from products containing CO2, CH4 and residual CO. Herein, we report a room-temperature electrochemical water-gas shift process for direct production of high purity hydrogen (over 99.99%) with a faradaic efficiency of approximately 100%. Through rational design of anode structure to facilitate CO diffusion and PtCu catalyst to optimize CO adsorption, the anodic onset potential is lowered to almost 0 volts versus the reversible hydrogen electrode at room temperature and atmospheric pressure. The optimized PtCu catalyst achieves a current density of 70.0 mA cm-2 at 0.6 volts which is over 12 times that of commercial Pt/C (40 wt.%) catalyst, and remains stable for even more than 475 h. This study opens a new and promising route of producing high purity hydrogen.

A Graphene Composite Material with Single Cobalt Active Sites: A Highly Efficient Counter Electrode for Dye-Sensitized Solar Cells.

The design of catalysts that are both highly active and stable is always challenging. Herein, we report that the incorporation of single metal active sites attached to the nitrogen atoms in the basal plane of graphene leads to composite materials with superior activity and stability when used as counter electrodes in dye-sensitized solar cells (DSSCs). A series of composite materials based on different metals (Mn, Fe, Co, Ni, and Cu) were synthesized and characterized. Electrochemical measurements revealed that CoN4 /GN is a highly active and stable counter electrode for the interconversion of the redox couple I(-) /I3 (-) . DFT calculations revealed that the superior properties of CoN4 /GN are due to the appropriate adsorption energy of iodine on the confined Co sites, leading to a good balance between adsorption and desorption processes. Its superior electrochemical performance was further confirmed by fabricating DSSCs with CoN4 /GN electrodes, which displayed a better power conversion efficiency than the Pt counterpart.

A single iron site confined in a graphene matrix for the catalytic oxidation of benzene at room temperature.

Coordinatively unsaturated (CUS) iron sites are highly active in catalytic oxidation reactions; however, maintaining the CUS structure of iron during heterogeneous catalytic reactions is a great challenge. Here, we report a strategy to stabilize single-atom CUS iron sites by embedding highly dispersed FeN4 centers in the graphene matrix. The atomic structure of FeN4 centers in graphene was revealed for the first time by combining high-resolution transmission electron microscopy/high-angle annular dark-field scanning transmission electron microscopy with low-temperature scanning tunneling microscopy. These confined single-atom iron sites exhibit high performance in the direct catalytic oxidation of benzene to phenol at room temperature, with a conversion of 23.4% and a yield of 18.7%, and can even proceed efficiently at 0°C with a phenol yield of 8.3% after 24 hours. Both experimental measurements and density functional theory calculations indicate that the formation of the Fe═O intermediate structure is a key step to promoting the conversion of benzene to phenol. These findings could pave the way toward highly efficient nonprecious catalysts for low-temperature oxidation reactions in heterogeneous catalysis and electrocatalysis.