Single-Atom Ru Alloyed with Ni Nanoparticles Boosts CO2 Methanation.

Designing catalysts to proceed with catalytic reactions along the desired reaction pathways, e.g., CO2 methanation, has received much attention but remains a huge challenge. This work reports one Ru1Ni single-atom alloy (SAA) catalyst (Ru1Ni/SiO2) prepared via a galvanic replacement reaction between RuCl3 and Ni nanoparticles (NPs) derived from the reduction of Ni phyllosilicate (Ni-ph). Ru1Ni/SiO2 achieved much improved selectivity toward hydrogenation of CO2 to CH4 and catalytic activity (Turnover frequency (TOF) value: 40.00 × 10-3 s-1), much higher than those of Ni/SiO2 (TOF value: 4.40 × 10-3 s-1) and most reported Ni-based catalysts (TOF value: 1.03 × 10-3-11.00 × 10-3 s-1). Experimental studies verify that Ru single atoms are anchored onto the Ni NPs surface via the Ru1-Ni coordination accompanied by electron transfer from Ru1 to Ni. Both in situ experiments and theoretical calculations confirm that the interface sites of Ru1Ni-SAA are the intrinsic active sites, which promote the direct dissociation of CO2 and lower the energy barrier for the hydrogenation of CO* intermediate, thereby directing and enhancing the CO2 hydrogenation to CH4.

Direct Pyrolysis of Reed Black Liquor Droplets in a Fluidized Bed.

Pyrolysis of reed black liquor was tested in the form of both dried powder in a thermogravimeter connected to a mass spectrometer (TG-MS) and fed droplets (RBLD) in an atmospheric fluidized bed at temperatures of 530-780 °C. The effects of temperature were examined to clarify the variations in composition of gaseous products and the microscopic appearance of char. Examination was also performed for the releases of species containing Na, K, and Cl during pyrolysis. The results obtained show that the concentration of combustible components (CH4, H2, and CO) in pyrolysis gas increased with increasing bed temperature to reach 66.1% at 780 °C. There are more Na, K, and Cl releasing into the gaseous product at higher temperatures. The variation in the micromorphology of char from RBLD pyrolysis has been obtained and analyzed.

SARS-CoV-2 nucleocapsid protein enhances the level of mitochondrial reactive oxygen species.

Coronavirus disease 2019 (COVID-19) pathogenesis is influenced by reactive oxygen species (ROS). Nevertheless, the precise mechanisms implicated remain poorly understood. The nucleocapsid (N) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the main driver for this condition, is a structural protein indispensable for viral replication and assembly, and its role in ROS production has not been reported. This study shows that SARS-CoV-2 N protein expression enhances mitochondrial ROS level. Bulk RNA-sequencing suggests of aberrant redox state of the electron transport chain. Accordingly, this protein hinders ATP production but simultaneously augments the activity of complexes I and III, and most mitochondrially encoded complex I and III proteins are upregulated by it. Mechanistically, N protein of SARS-CoV-2 shows significant mitochondrial localization. It interacts with mitochondrial transcription components and stabilizes them. Moreover, it also impairs the activity of antioxidant enzymes with or without detectable interaction.

Recycling the CoMo/Al2O3 catalyst for effectively hydro-upgrading shale oil with high sulfur content and viscosity.

Hydrotreatment is an effective upgrading technology for removing contaminants and saturating double bonds. Still, few studies have reported the hydro-upgrading of shale oil, with unusually high sulfur (13200 ppm) content, using the CoMo/Al2O3 catalyst. Here we report an extensive study on the upgrading of shale oil by hydrotreatment in a stirred batch autoclave reactor (500 ml) for sulfur removal and viscosity reduction. From a preliminary optimization of the reaction factors, the best-operating conditions were 400 °C, an initial H2-pressure of 5 MPa, and an agitation rate of 800 rpm, a catalyst-to-oil ratio of 0.1, and a reaction time of 1 h. We could achieve a sulfur removal efficiency of 87.1% and 88.2% viscosity reduction under the optimal conditions. After that, the spent CoMo/Al2O3 was repeatedly used for subsequent upgrading tests without any form of pre-treatment. The results showed an increase in the sulfur removal efficiency with an increase in the number of catalyst runs. Ultimately, 99.5-99.9% sulfur removal from the shale oil was achieved by recycling the spent material. Both the fresh and the spent CoMo/Al2O3 were characterized and analyzed to ascertain their transformation levels by XRD, TEM, TG, XPS, TPD and N2 adsorption analysis. The increasing HDS efficiency is attributed to the continuing rise in the sulfidation degree of the catalyst in the sulfur-rich shale oil. The light fraction component in the liquid products (IBP-180 °C) was 30-37 vol% higher than in the fresh shale oil. The product oil can meet the sulfur content requirement of the national standard marine fuel (GB17411-2015/XG1-2018) of China.

A Hybrid De-Noising Algorithm for the Gear Transmission System Based on CEEMDAN-PE-TFPF.

In order to remove noise and preserve the important features of a signal, a hybrid de-noising algorithm based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Permutation Entropy (PE), and Time-Frequency Peak Filtering (TFPF) is proposed. In view of the limitations of the conventional TFPF method regarding the fixed window length problem, CEEMDAN and PE are applied to compensate for this, so that the signal is balanced with respect to both noise suppression and signal fidelity. First, the Intrinsic Mode Functions (IMFs) of the original spectra are obtained using the CEEMDAN algorithm, and the PE value of each IMF is calculated to classify whether the IMF requires filtering, then, for different IMFs, we select different window lengths to filter them using TFPF; finally, the signal is reconstructed as the sum of the filtered and residual IMFs. The filtering results of a simulated and an actual gearbox vibration signal verify that the de-noising results of CEEMDAN-PE-TFPF outperforms other signal de-noising methods, and the proposed method can reveal fault characteristic information effectively.

Correlating micro/meso pore evolution and chemical structure variation in a mild thermal treatment of a subbituminite.

This work investigates the evolution of micro/meso pores during a mild thermal treatment of subbituminous coal based on the observation of coal structure changes with the gradual detachment of organic matter from the coal. Pores in coal can be described as super-micropores (d < 1 nm), micropores (1 nm < d < 2 nm) and mesopores (2 nm < d < 50 nm). The decomposition of the carboxyl group at 200 °C decreases the super-micropore volume. A mild and sustained reaction takes place at 300 °C to gradually change the aromaticity and CH2/CH3 ratio of the treated coal. The amount of micropore structure sharply decreases in the early stages of heating, while the amount of mesopore structure continuously decreases during the whole process. A dramatic reaction takes place at 400 °C to sharply change the aromaticity and CH2/CH3 ratio of the treated coal, while the detachment of volatile compounds from the coal matrix caused an evident variation in the mesopore structure of the coal. The aromaticity and CH2/CH3 ratio of coal organics are found to correlate with the volumes of super-micropores and mesopores, respectively. The super-micropores are identified as comprising the inter-layer distance between stacks of aromatic rings, and mesopores are the spaces between macromolecular aromatic rings which are inter-connected via aliphatic chains.

A novel procedure for diagnosing multiple faults in rotating machinery.

In analyzing signals from a wind turbine gearbox this paper suggests a new signal processing procedure named as CMF-EEMD method which is formed by applying conventional EEMD to a new type of combined mode function (CMF). This CMF consists of a low frequency CMF, denoted as CL, and a high frequency CMF, denoted as Ch. Then it optimizes the amplitude of the added noise in decomposing Ch and CL using EEMD. Finally, it calculates cyclic autocorrelation function (CAF) for every characteristic IMF from EEMD. The proposed procedure is applied to analyze the multi-faults of a wind turbine gearbox and the results confirm better performances in resolving different signal components by the proposed method than that from the cyclic autocorrelation function (CAF) of a direct EEMD analysis.