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 conversion of ethane and the mechanism understanding over single iron atoms confined in graphene

Abstract(#br)The catalytic conversion of ethane to high value-added chemicals is significantly important for utilization of hydrocarbon resources. However, it is a great challenge due to the typically required high temperature (> 400 °C) conditions. Herein, a highly active catalytic conversion process of ethane at room temperature (25 °C) is reported on single iron atoms confined in graphene via the porphyrin-like N 4 -coordination structures. Combining with the operando time of flight mass spectrometer and density functional theory calculations, the reaction is identified as a radical mechanism, in which the C–H bonds of the same C atom are preferentially and sequentially activated, generating the value-added C 2 chemicals, simultaneously avoiding the over-oxidation of the products to CO 2 . The in-situ formed O–FeN 4 –O structure at the single iron atom serves as the active center for the reaction and facilitates the formation of ethyl radicals. This work deepens the understanding of alkane C–H activation on the FeN 4 center and provides the reference in development of efficient catalyst for selective oxidation of light alkane

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

Abstract 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 CRD4202238401

Additional file 1 of Predicting sepsis onset in ICU using machine learning models: a systematic review and meta-analysis

Additional file 1. PRISMA 2020 Checklist

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Additional file 2 of Predicting sepsis onset in ICU using machine learning models: a systematic review and meta-analysis

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Single layer graphene encapsulating non-precious metals as high-performance electrocatalysts for water oxidation

The oxygen evolution reaction (OER) is recognized as a key half-reaction in water electrolysis for clean hydrogen energy, which is kinetically not favored and usually requires precious metal catalysts such as IrO2 and RuO2 to reduce the overpotential. The major challenge in using non-precious metals in place of these precious metal catalysts for OER is their low efficiency and poor stability, which urgently demand new concepts and strategies to tackle this issue. Herein, we report a universal strategy to directly synthesize single layer graphene encapsulating uniform earth-abundant 3d transition-metal nanoparticles such as Fe, Co, Ni and their alloys in a confined channel of mesoporous silica. The single atomic thickness of the graphene shell immensely promotes the electron transfer from the encapsulated metals to the graphene surface, which efficiently optimizes the electronic structure of the graphene surface and thereby triggers the OER activity of the inert graphene surface. We investigated a series of non-precious 3d metals encapsulated within single layer graphene, and found that the encapsulated FeNi alloy showed the best OER activity in alkaline solutions with only 280 mV overpotential at 10 mA cm(-2), and also possessed a high durability after 10000 cycles. Both the activity and durability of the non-precious catalyst even exceed that of the commercial IrO2 catalyst, showing great potential to replace precious metal catalysts in the OER

Vanadium Dioxide-Based Terahertz Metamaterial Devices Switchable between Transmission and Absorption

Terahertz metamaterial plays a significant role in the development of imaging, sensing, and communications. The function of conventional terahertz metamaterials was fixed after fabrication. They can only achieve a single function and do not have adjustable characteristics, which greatly limits the scalability and practical application of metamaterial. Here, we propose a vanadium dioxide-based terahertz metamaterial device, which is switchable between being a transmitter and an absorber. The transmission and absorption characteristics and temperature tunable properties of phase change metamaterials in the terahertz band were investigated. As the temperature of vanadium dioxide is varied between 20 °C and 80 °C, the device can switch between transmission and quad-band resonance absorption at the terahertz frequency range, with a high transmission rate of over 80% and a peak absorbance of 98.3%, respectively. In addition, when the device acts as an absorber, the proposed metamaterial device is tunable, and the modulation amplitude can reach 94.3%; while the device is used as a transmissive device, the modulation amplitude of the transmission peak at 81%. The results indicate that the proposed metamaterial device can promote the applications of terahertz devices, such as switching, modulation, and sensing

Electrophysiological correlates for response inhibition in intellectually gifted children: A Go/NoGo study

Superior response inhibition is an essential component of the advanced cognitive abilities of gifted children. This study investigated response inhibition in intellectually gifted children by recording event-related brain potentials (ERPs) during a Go/NoGo task. Fifteen intellectually gifted children and 15 intellectually average children participated. Our present findings showed that intellectually gifted children had shorter Go-P3 latency, indicating faster processing of Go stimuli, a finding consistent with previous studies. We focused on the two inhibition-related components, NoGo-N2 and NoGo-P3. The results showed that NoGo-P3 latency was shorter for intellectually gifted children compared to their average peers. N2 latency did not indicate the intelligence difference. These results suggested that intellectually gifted children showed faster inhibition when dealing with NoGo stimuli, and this superiority came from the later stages of inhibition, i.e., response evaluation or the success of inhibiting a response, as indexed by the shorter P3 latency.Superior response inhibition is an essential component of the advanced cognitive abilities of gifted children. This study investigated response inhibition in intellectually gifted children by recording event-related brain potentials (ERPs) during a Go/NoGo task. Fifteen intellectually gifted children and 15 intellectually average children participated. Our present findings showed that intellectually gifted children had shorter Go-P3 latency, indicating faster processing of Go stimuli, a finding consistent with previous studies. We focused on the two inhibition-related components, NoGo-N2 and NoGo-P3. The results showed that NoGo-P3 latency was shorter for intellectually gifted children compared to their average peers. N2 latency did not indicate the intelligence difference. These results suggested that intellectually gifted children showed faster inhibition when dealing with NoGo stimuli, and this superiority came from the later stages of inhibition, i.e., response evaluation or the success of inhibiting a response, as indexed by the shorter P3 latency. (C) 2009 Elsevier Ireland Ltd. All rights reserved

Direct Methane Conversion under Mild Condition by Thermo-, Electro-, or Photocatalysis

Direct conversion of earth-abundant methane into value-added chemicals under mild conditions is an attractive technology in response to the increasing industrial demand of feedstocks and worldwide appeal of energy conservation. Exploring advanced low-temperature C-H activation catalysts and reaction systems is the key to converting methane in a direct and mild manner. The recently developed reaction processes operated at low-temperature thermocatalysis systems or driven in electro- and photocatalysis systems shine light on the way to achieve efficient methane conversion with much economical energy input. In this review, we summarize the typical catalytic processes employed in these reaction systems and in particular highlight the potential heterogeneous catalysts with noteworthy C-H activation performance. We also present the progress along with our perspectives on catalyst design, theoretical simulations, the choice of reaction condition, and the method of reaction product analysis to encourage more viable technology for low-temperature methane conversion in the future