Promoting the Synthesis of Ethanol and Butanol by Salicylic Acid

Multiwalled carbon nanotubes (MWCNTs) were functionalized with salicylic acid (SA). The copper-cobalt catalyst was impregnated on the SA functionalized MWCNTs (SA-MWCNTs). The catalyst copper-cobalt/SA-MWCNTs was used to catalyze the synthesis of alcohols from synthesis gas. Salicylic acid can promote the synthesis of ethanol and butanol from synthesis gas, thus reducing the synthesis of methanol. This work demonstrated that salicylic acid not only can be used to functionalize carbon nanotubes, but also can enhance the production of ethanol and butanol from synthesis gas. On the other hand, the copper-cobalt catalyst supported on MWCNTs of 30 nm in diameter can synthesize more ethanol and butanol than supported on MWCNTs of 15 and 50 nm in diameter, indicating that the diameter of MWCNTs also has an effect on the synthesis of alcohols

Mechanism of Radical Initiation and Transfer in Class Id Ribonucleotide Reductase Based on Density Functional Theory

Class Id ribonucleotide reductase (RNR) is a newly discovered enzyme, which employs the dimanganese cofactor in the superoxidized state (MnIII/MnIV) as the radical initiator. The dimanganese cofactor of class Id RNR in the reduced state (inactive) is clearly based on the crystal structure of the Fj-β subunit. However, the state of the dimanganese cofactor of class Id RNR in the oxidized state (active) is not known. The X-band EPR spectra have shown that the activated Fj-β subunit exists in two distinct complexes, 1 and 2. In this work, quantum mechanical/molecular mechanical calculations were carried out to study class Id RNR. First, we have determined that complex 2 contains a MnIII-(μ-oxo)2-MnIV cluster, and complex 1 contains a MnIII-(μ-hydroxo/μ-oxo)-MnIV cluster. Then, based on the determined dimanganese cofactors, the mechanism of radical initiation and transfer in class Id RNR is revealed. The MnIII-(μ-oxo)2-MnIV cluster in complex 2 has not enough reduction potential to initiate radical transfer directly. Instead, it needs to be monoprotonated into MnIII-(μ-hydroxo/μ-oxo)-MnIV (complex 1) before the radical transfer. The protonation state of μ-oxo can be regulated by changing the protein microenvironment, which is induced by the protein aggregation and separation of β subunits with α subunits. The radical transfer between the cluster of MnIII-(μ-hydroxo/μ-oxo)-MnIV and Trp30 in the radical-transfer chain of the Fj-β subunit (MnIII/MnIV ↔ His100 ↔ Asp194 ↔ Trp30 ↔ Arg99) is a water-mediated tri-proton-coupled electron transfer, which transfers proton from the ε-amino group of Lys71 to the carboxyl group of Glu97 via the water molecule Wat551 and the bridging μ-hydroxo ligand through a three-step reaction. This newly discovered proton-coupled electron-transfer mechanism in class Id RNR is different from those reported in the known Ia–Ic RNRs. The ε-amino group of Lys71, which serves as a proton donor, plays an important role in the radical transfer

Analysis of Winding Vibration Characteristics of Power Transformers Based on the Finite-Element Method

The winding is the core component of a transformer, and the technology used to diagnose its current state directly affects the operation and maintenance of the transformer. The mechanical vibration characteristics of a dry-type transformer winding are studied in this paper. A short-circuit test was performed on an SCB10-1000/10 dry-type transformer, and the vibration signal at the surface was measured. Based on actual experimental conditions, a vibration-simulation model of the transformer was established using COMSOL Multiphysics software. A multiphysics coupling simulation of the circuit, magnetic field, and solid mechanics of the transformer was performed on this model. The simulation results were compared with measured data to verify the validity of the simulation model. The simulation model for a transformer operating under normal conditions was then used to develop simulation models of transformer-winding looseness, winding deformation, and winding-insulation failure, and the winding fault vibration characteristics were analyzed. The results provide a basis for detecting and analyzing the mechanical state of transformer windings

A New Prediction Model for Transformer Winding Hotspot Temperature Fluctuation Based on Fuzzy Information Granulation and an Optimized Wavelet Neural Network

Winding hotspot temperature is the key factor affecting the load capacity and service life of transformers. For the early detection of transformer winding hotspot temperature anomalies, a new prediction model for the hotspot temperature fluctuation range based on fuzzy information granulation (FIG) and the chaotic particle swarm optimized wavelet neural network (CPSO-WNN) is proposed in this paper. The raw data are firstly processed by FIG to extract useful information from each time window. The extracted information is then used to construct a wavelet neural network (WNN) prediction model. Furthermore, the structural parameters of WNN are optimized by chaotic particle swarm optimization (CPSO) before it is used to predict the fluctuation range of the hotspot temperature. By analyzing the experimental data with four different prediction models, we find that the proposed method is more effective and is of guiding significance for the operation and maintenance of transformers

Multi-time-scale robust economic dispatching method for the power system with clean energy

Clean energies such as wind energy and solar energy have increased very fast in order to meet the environmental requirements. However, due to the uncertainties of wind and solar energy, the large-scale integration of new energy presents a great challenge to the power system economic dispatch. Thus, a multi-time-scale robust economic dispatch strategy of a multi-source hybrid power system based on the variable confidence level is proposed. The deterministic constraints of each time scale are transformed into robust constraints that take the uncertainty into account. Meanwhile, the robust level whose confidence level increases with the shortening of time scale is set to improve the scheduling conservative degree step by step. The selection principle of the robust level of each time scale is also presented. The proposed approach is applied to an IEEE 9-bus system. The calculation results are compared with those from the traditional multi-time scheduling method and show the effectiveness of the paper, which can reduce the uncertainty impact of wind, solar, and load forecast, as well as achieve a great balance of security, economic, and environmental benefits

Study on Microstructure, Mechanical Performance and Thermal Shock Resistance of Diffusion Welded Joint of ODS-W and TZC Alloy

The diffusion welded joint of oxide dispersion strengthened tungsten (ODS-W) and Mo-Ti-Zr-C alloy (TZC) was successfully fabricated with the use of spark plasma sintering (SPS) at a vacuum level of 10 Pa. This study systematically investigates the microstructure, mechanical performance, and thermal shock resistance of the ODS-W/TZC connector at four different temperatures, ranging from 1300 to 1600 °C. The diffusion distance between the W and Mo atoms at the interface of ODS-W/TZC joint raises as the sintering temperature increases, with a maximum diffusion distance of up to 2 μm at 1500 °C, but then slightly decreases at 1600 °C. The ODS-W/TZC connector bonded at 1500 °C exhibits the best tensile performance, with tensile strengths of 459 MPa and 786 MPa at room temperature and 500 °C, respectively. A maximum hardness of 446 HV is obtained at the interface when the sample is sintered at 1600 °C. Thermal shock tests are conducted on the surface and interface of the ODS-W/TZC connector sintered at various temperatures. ODS-W/TZC samples prepared below 1500 °C were severely damaged, leading to exfoliation after laser thermal shock, while samples prepared above 1500 °C produced fewer damage cracks. Confocal laser scanning microscope (CLSM) analysis demonstrated that the ODS-W/TZC joint fabricated at 1500 °C exhibited substantially reduced height perturbation of both its surface and interface compared to that of ODS-W, providing evidence for its superior thermal shock resistance

Multi-Omics Analysis of Low-Temperature Fruiting Highlights the Promising Cultivation Application of the Nutrients Accumulation in Hypsizygus marmoreus

Hypsizygus marmoreus is a representative edible mushroom with low-temperature fruiting after a long postripening (LFLP). Clarifying the mechanism of LFLP and applying a rigorous low-temperature-limited process will optimize the mushroom cultivation process. This study performed an integrative multi-omics analysis of the molecular mechanism of LFLP in combination with genetic, physiological, and cultivation confirmation. The results showed that the amino acid content was increased during LFLP, mainly arginine. pH analysis showed acidification in the postripening stage and alkalization in the substrates of the reproductive growth stage. An enzyme activity test confirmed the increased enzyme activity of arginase and citrate synthase in the postripening stage. Weighted gene coexpression network analysis of the transcriptome and metabolomics indicated that pH variation is correlated mainly with changes in citrate and arginine. Multi-omics reveals a straightforward way of providing enriched materials for amino acid biosynthesis, namely, synergistically elevating citric acid and arginine through enhanced activity of the arginine synthesis branch pathway in the citrate cycle. Our study confirmed that GCN2 mediated metabolic adaptation by enhancing protein translation, highlighting its regulatory role during LFLP. Exogenously added citric acid and arginine shortened the postripening period by 10 days and increased the fruiting body yield by 10.2~15.5%. This research sheds light on the molecular mechanism of LFLP in H. marmoreus and highlights the promising application of nutrient accumulation in high-efficiency cultivation

Fully Mechanically Controlled Automated Electron Microscopic Tomography.

Knowledge of three-dimensional (3D) structures of each individual particles of asymmetric and flexible proteins is essential in understanding those proteins' functions; but their structures are difficult to determine. Electron tomography (ET) provides a tool for imaging a single and unique biological object from a series of tilted angles, but it is challenging to image a single protein for three-dimensional (3D) reconstruction due to the imperfect mechanical control capability of the specimen goniometer under both a medium to high magnification (approximately 50,000-160,000×) and an optimized beam coherence condition. Here, we report a fully mechanical control method for automating ET data acquisition without using beam tilt/shift processes. This method could reduce the accumulation of beam tilt/shift that used to compensate the error from the mechanical control, but downgraded the beam coherence. Our method was developed by minimizing the error of the target object center during the tilting process through a closed-loop proportional-integral (PI) control algorithm. The validations by both negative staining (NS) and cryo-electron microscopy (cryo-EM) suggest that this method has a comparable capability to other ET methods in tracking target proteins while maintaining optimized beam coherence conditions for imaging

Fully Mechanically Controlled Automated Electron Microscopic Tomography.

Knowledge of three-dimensional (3D) structures of each individual particles of asymmetric and flexible proteins is essential in understanding those proteins' functions; but their structures are difficult to determine. Electron tomography (ET) provides a tool for imaging a single and unique biological object from a series of tilted angles, but it is challenging to image a single protein for three-dimensional (3D) reconstruction due to the imperfect mechanical control capability of the specimen goniometer under both a medium to high magnification (approximately 50,000-160,000×) and an optimized beam coherence condition. Here, we report a fully mechanical control method for automating ET data acquisition without using beam tilt/shift processes. This method could reduce the accumulation of beam tilt/shift that used to compensate the error from the mechanical control, but downgraded the beam coherence. Our method was developed by minimizing the error of the target object center during the tilting process through a closed-loop proportional-integral (PI) control algorithm. The validations by both negative staining (NS) and cryo-electron microscopy (cryo-EM) suggest that this method has a comparable capability to other ET methods in tracking target proteins while maintaining optimized beam coherence conditions for imaging