Theoretical Studies for the Structural Properties and Electron Transfer Reactivity of C₄H₅N/C₄H₅N⁺ Coupling System

The geometries and vibrational frequencies of pyrrole, pyrrole cation, and their corresponding encounter complexes have been determined using density functional theory (DFT) and/or ab initio methods with 6-31G* and/or 6-311+G* basis sets. Optimizations indicate that there are three stable complex modes. One mode has the ring−ring parallel contact (face−face) and each N atom in two rings is vertically over the center of another ring (complex 1). In the second mode (complex 2), two rings are also parallel, but they are directly contacted by only one N−C bond in each ring (side-side). The third mode (complex 3) is H−bond mode, in which the N−H of one pyrrole ring is nearly collinearly directed to the N center of another pyrrole ring and two rings are perpendicular to each other. For three-encounter complexes, their main bond lengths are between those of the pyrrole and those of the pyrrole cation. The character contact distances are 2.754 Å (C3···C13), 2.727 Å (C3···C12), and 2.632 Å (N1···H16) at the B3P86/6-31G* level, respectively. The stabilization energies of the three encounter complexes are calculated to be 21.4 (complex 1), 20.2 (complex 2), and 15.9 (complex 3) kcal/mol at the B3LYP-DFT/6-311+G* level with the correction for BSSE. The inapplicability of DFT methods has been discussed in predicting the energy curves, especially with long contact distance in which the DFT methods give the abnormal behavior for the dissociation of the complexes due to the “inverse symmetry breaking” problem. On the basis of three stable encounter complexes, three coupling modes have been designed by keeping the relative orientation and changing the contact distance for further investigating electron-transfer reactivity. The contact distance dependences of the activation energy, the coupling matrix element, and the electron-transfer rate have also been determined at the MP2/6-31G* level. Electron transfer can occur over a range of encounter distance. For the C4H5N/C4H5N+ coupling system, electron transfer occurs chiefly over a range of contact distances where 2.0Ra-b <6.0 Å. The most favorable coupling mode to electron transfer is the coupling mode 3, which is related to complex 3. It should be noted that it is not always true that the electron transfer must take place via the most stable encounter complex mechanism. For the C4H5N/C4H5N+ systems, the most stable encounter complex is complex 1, but the most favorable coupling mode for the electron transfer is coupling mode 3, depending on the different contact distance ranges

Supplemental material 2 for Automatic band selection algorithm for envelope analysis

<p>Supplemental material 2 for Automatic band selection algorithm for envelope analysis by Peng Xu, Ahmad Ghasemloonia and Qiao Sun in Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science</p

Supplemental material 1 for Automatic band selection algorithm for envelope analysis

Supplemental material 1 for Automatic band selection algorithm for envelope analysis by Peng Xu, Ahmad Ghasemloonia and Qiao Sun in Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science</p

Charged-Controlled Separation of Nitrogen from Natural Gas Using Boron Nitride Fullerene

Natural gas (the main component is methane) has been widely used as a fuel and raw material in industry. Removal of nitrogen (N₂) from methane (CH₄) can reduce the cost of natural gas transport and improve its efficiency. However, their extremely similar size increases the difficulty of separating N₂ from CH_4. In this study, we have performed a comprehensive investigation of N₂ and CH₄ adsorption on different charge states of boron nitride (BN) nanocage fullerene, B₃₆N₃₆, by using a density functional theory approach. The calculational results indicate that B₃₆N₃₆ in the negatively charged state has high selectivity in separating N₂ from CH₄. Moreover, once the extra electron is removed from the BN nanocage, the N₂ will be released from the material. This study demonstrates that the B₃₆N₃₆ fullerene can be used as a highly selective and reusable material for the separation of N₂ from CH₄. The study also provides a clue to experimental design and application of BN nanomaterials for natural gas purification

The ROC curve of the test set is predicted by SVM.

The ROC curve of the test set is predicted by SVM.</p

Results of regression analysis of the effect of loan description on loan acquisition.

Results of regression analysis of the effect of loan description on loan acquisition.</p

Description statistics of control variables and linguistic feature variables.

Description statistics of control variables and linguistic feature variables.</p

Results of Pearson correlation analysis.

Information asymmetry is widespread in the P2P online lending market, creating an imbalance in the position of lenders and borrowers. This paper aims to expand the process of information exchange between lenders and borrowers by analyzing the link between soft information such as borrowers’ loan descriptions and lending outcomes. Based on the transaction data of the ‘Renrendai’ platform, this paper analyzed the linguistic features and extracted the content of loan descriptions using a latent Dirichlet allocation (LDA) theme model. To further explore the value of loan descriptions in predicting lending success, this paper conducts a prediction study based on a support vector machine model. It is found that: lenders focus on effective information in the loan descriptions, the linguistic complexity affects the transaction, with simple and direct statements being more favorable; the content for building a good personal image of the borrower will significantly contribute to the lending success. In the prediction study section, it is demonstrated that loan descriptions’ language feature indicators can improve prediction accuracy. This paper uncovers the importance of loan descriptions in online lending transactions, which has implications in assisting lenders’ investment judgments, as well as in platform information system improvements.</div

Evaluation index of the SVM.

Information asymmetry is widespread in the P2P online lending market, creating an imbalance in the position of lenders and borrowers. This paper aims to expand the process of information exchange between lenders and borrowers by analyzing the link between soft information such as borrowers’ loan descriptions and lending outcomes. Based on the transaction data of the ‘Renrendai’ platform, this paper analyzed the linguistic features and extracted the content of loan descriptions using a latent Dirichlet allocation (LDA) theme model. To further explore the value of loan descriptions in predicting lending success, this paper conducts a prediction study based on a support vector machine model. It is found that: lenders focus on effective information in the loan descriptions, the linguistic complexity affects the transaction, with simple and direct statements being more favorable; the content for building a good personal image of the borrower will significantly contribute to the lending success. In the prediction study section, it is demonstrated that loan descriptions’ language feature indicators can improve prediction accuracy. This paper uncovers the importance of loan descriptions in online lending transactions, which has implications in assisting lenders’ investment judgments, as well as in platform information system improvements.</div