Nanographene with a Nitrogen‐Doped Cavity Wang, Fei‐Fan; Wang, Yu‐Xiang; Wu, Qiong ...
Angewandte Chemie International Edition,
January 8, 2024, Volume:
63, Issue:
2
Journal Article
Peer reviewed
Nitrogen‐doped cavities are pervasive in graphenic materials, and represent key sites for catalytic and electrochemical activity. However, their structures are generally heterogeneous. In this study, ...we present the synthesis of a well‐defined molecular cutout of graphene featuring N‐doped cavity. The graphitization of a macrocyclic pyridinic precursor was achieved through photochemical cyclodehydrochlorination. In comparison to its counterpart with pyridinic nitrogen at the edges, the pyridinic nitrogen atoms in this nanographene cavity exhibit significantly reduced basicity and selective binding to Ag+ ion. Analysis of the protonation and coordination equilibria revealed that the tri‐N‐doped cavity binds three protons, but only one Ag+ ion. These distinct protonation and coordination behaviors clearly illustrate the space confinement effect imparted by the cavities.
A nanographene with a tri‐N‐doped cavity was synthesized by photo‐induced cyclization. In comparison with nitrogen‐doping at the edge, this tri‐N‐doped holey nanographene exhibited markedly reduced basicity and selective affinity toward Ag+. This nanographene with a N‐doped cavity provides a precise model for understanding the binding in the nano‐confined defects of graphenic materials.
1 Most patients with cryptorchidism have this condition corrected by surgery before puberty. ...adult bilateral cryptorchidism (BC) is not observed frequently in clinical practice. According to the ...location of testicles, preoperative examination results, and doctors' experience, open or laparoscopic surgery was selected. ...the sample size was small and follow-up time was short.
As an advanced near-net shape technology, squeeze casting is an excellent method for producing high integrity castings. Numerical simulation is a very effective method to optimize squeeze casting ...process, and the interfacial heat transfer coefficient（IHTC） is an important boundary condition in numerical simulation. Therefore, the study of the IHTC is of great significance. In the present study, experiments were conducted and a “plate shape” aluminum alloy casting was cast in H13 steel die. In order to obtain accurate temperature readings inside the die, a special temperature sensor units（TSU） was designed. Six 1 mm wide and 1 mm deep grooves were machined in the sensor unit for the placement of the thermocouples whose tips were welded to the end wall. Each groove was machined to terminate at a particular distance（1, 3, and 6 mm） from the front end of the sensor unit. Based on the temperature measurements inside the die, the interfacial heat transfer coefficient（IHTC） at the metal-die interface was determined by applying an inverse approach. The acquired data were processed by a low pass filtering method based on Fast Fourier Transform（FFT）. The feature of the IHTC at the metal-die interface was discussed.
Flatness plays a crucial role in determining the quality of products in strip cold rolling. Data driven methods have shown promise in flatness prediction by effectively capturing the nonlinearities ...and strong coupling present in cold rolling processing, surpassing the capability of conventional methods. However, existing data driven models remain restricted by a lack of rolling theory guidance, a black-box nature of predictive processes, and gradient conflict of multi-channel flatness. To overcome these limitations, this paper proposes an interpretable mechanism guided multi-channel distributed meta learning framework for flatness prediction. Initially, significant physic-based parameters, such as theoretical rolling force deviation and tension deviation, and controller parameters are calculated to guide data driven modeling. Subsequently, a distributed meta learning framework is modeled for multi-channel flatness to eliminate gradient conflict. Furthermore, eXplainable Artificial Intelligence (XAI) technique is implemented to ensure the transparent predictive processes of multi-channel flatness. The analysis results present that theoretical parameters and controller parameters effectively improve the performance of flatness prediction. In addition, the comparative results demonstrate that the proposed framework outperforms the existing flatness prediction methods and other state-of-the-art machine learning methods by 4.24%. Importantly, the XAI-based explanation of the proposed framework effectively enhances the credibility of data driven flatness prediction.
Display omitted
•An interpretable distributed meta learning framework is proposed for flatness prediction.•The interpretability and performance of data driven model is enhanced by integrating rolling mechanism.•Distributed learning framework is effective in eliminating gradient conflict of multi-channel flatness in training procedure.•The predictive process of data-driven model in cold rolling is first explained by eXplainable Artificial Intelligence (XAI).
Nitrogen‐doped cavities are pervasive in graphenic materials, and represent key sites for catalytic and electrochemical activity. However, their structures are generally heterogeneous. In this study, ...we present the synthesis of a well‐defined molecular cutout of graphene featuring N‐doped cavity. The graphitization of a macrocyclic pyridinic precursor was achieved through photochemical cyclodehydrochlorination. In comparison to its counterpart with pyridinic nitrogen at the edges, the pyridinic nitrogen atoms in this nanographene cavity exhibit significantly reduced basicity and selective binding to Ag+ ion. Analysis of the protonation and coordination equilibria revealed that the tri‐N‐doped cavity binds three protons, but only one Ag+ ion. These distinct protonation and coordination behaviors clearly illustrate the space confinement effect imparted by the cavities.
A nanographene with a tri‐N‐doped cavity was synthesized by photo‐induced cyclization. In comparison with nitrogen‐doping at the edge, this tri‐N‐doped holey nanographene exhibited markedly reduced basicity and selective affinity toward Ag+. This nanographene with a N‐doped cavity provides a precise model for understanding the binding in the nano‐confined defects of graphenic materials.
The solidification microstructure of Mg–Gd–Y–Zr alloy was investigated via an experimental study and cellular automaton (CA) simulation. In this study, step-shaped castings were produced, and the ...temperature variation inside the casting was recorded using thermocouples during the solidification process. The effects of the cooling rate and Zr content on the grain size of the Mg–Gd–Y–Zr alloy were studied. The results showed that the grain size decreased with an increase in the cooling rate and Zr content. Based on the experimental data, a quantitative model for calculating the heterogeneous nucleation rate was developed, and the model parameters were determined. The evolution of the solidification microstructure was simulated using the CA method, where the quantitative nucleation model was used and a solute partition coefficient was introduced to deal with the solute trapping in front of the solid–liquid (S/L) interface. The simulation results of the grain size were in good agreement with the experimental data. The simulation also showed that the fraction of the eutectics decreased with an increasing cooling rate in the range of 2.6–11.0 °C·s
−1
, which was verified indirectly by the experimental data.
Abstract Epidermal Growth Factor like domain 7 (EGFL7), also known as Vascular Endothelial-statin (VE-statin), is a secreted angiogenic factor. Recent data have demonstrated the potential oncogenic ...role and prognostic significance of EGFL7 in several human cancers. However, the clinical signature and further mechanisms of EGFL7's function in gliomagenesis are poorly understood. In the present study, we found that increased EGFL7 expression was associated with tumor grade. High expression of EGFL7 in EGFRvIII-positive glioblastoma multiforme (GBM) was determined to be a strong and independent risk factor for reduced life expectancy. EGFRvIII cells can secrete the EGFL7 protein to improve the activity of the β-catenin/TCF4 Transcription complex in EGFRwt cells, thus promoting their own EGFL7 expression. Our research demonstrates that oncogenic activation of EGFRwt in GBM is likely maintained by a continuous EGFL7 autocrine flow line, and may be an attractive target for therapeutic intervention.
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