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Taking the block polyether which made from ethylene oxide/propylene oxide, and acrylic acid as the main polymerization monomer, and then acrylamide containing amide groups, and 2-acrylamide-2-methylpropane sulfonic acid were selected as functional monomers to produce early-strength polycarboxylate superplasticizer under normal temperature and pressure. The effects of different amounts of acrylic acid, redox system, chain transfer agent, reaction temperature and other factors on the products performance were investigated. The results showed that the early-strength performance of the superplasticizer was outstanding under the reaction conditions of n (polyether monomer) :n (acrylic acid) :n (acrylamide) =1:8:0.24, H2O2/ascorbic acid redox system at 40 °C. When the cement content of superplasticizer is 0.28% of the cement content, compared with conventional polycarboxylic acid superplasticizer, the 1 d and 3d compressive strength of the superplasticizer which containing acylamide group could be increased by 18.5% and 17.8% respectively. The initial and final setting time were reduced by 53% and 35% respectively. [ABSTRACT FROM AUTHOR]

The geometric structure, energy properties, and electronic properties of the aerogen-bonding interaction formed by C2H4 and NgOX2 (Ng = Kr, Xe; X = F, Cl, Br) have been studied at the B2PLYP-D3(BJ)/ aug-cc-pVTZ (PP) level. Two kinds of aerogen-bonding interactions were observed among the title systems: the σ-hole and the π-hole complexes. The σ-hole aerogen-bonding complex has a binding energy in the range of − 6.29 ~ − 8.17 kcal/mol, which is the most stable. The binding energies of C2H4···NgOX2 increased as X = F < Cl < Br and Ng = KrOX2 < XeOX2 for the σ/π-hole aerogen-bonding complexes. The atoms in molecules (AIM), the non-covalent interaction (NCI) index, and the LMO-EDA energy decomposition analysis were adopted to study the nature of the σ/π-hole aerogen-bonding interaction. The results show that the electrostatic term contributes the most to the total interaction energy for the σ/π-hole aerogen-bonding complexes. [ABSTRACT FROM AUTHOR]

The oxidation mechanisms of thiophene (Tp) with H2O2 over defect and perfect titanium silicalite-1 (TS-1) were investigated by means of DFT/ONIOM2 calculations for different models 7T:45T, 9T:45T and 13T:45T. The B3LYP, ωB97X-D, and M06-2X functionals were used in the high-level part of ONIOM2, with PM6 in the lower-level part. The related potential energy surface profiles are constructed based on the ωB97X-D/ONIOM2 method for 13T:45T cluster. Four possible paths are proposed for the oxidation of Tp into sulfoxide and sulfoxide into sulfone using H2O2 as an oxidant over defect and perfect TS-1. The dimerization of sulfoxide and sulfone through Diels-Alder cycloaddition is also studied. It is found that perfect TS-1 is highly unfavorable compared to defect TS-1 (TS-d). The calculated activation energy of Tp oxidation with TS-d is found to be remarkably lower than that without any zeolite catalyst. The calculated results may contribute to the understanding of the reaction mechanism of the catalytic oxidative desulfurization of sulfides in liquid fuels. [ABSTRACT FROM AUTHOR]

Tin-based perovskite solar cells have garnered attention for their biocompatibility, narrow bandgap, and long thermal carrier lifetime. However, nip-type tin-based perovskite solar cells have underperformed largely due to the indiscriminate use of metal oxide electron transport layers originally designed for nip-type lead-based perovskite solar cells. Here, we reveal that this underperformance is caused by oxygen vacancies and deeper energy levels in metal oxide. To address these issues, we propose a metal chalcogenide electron transport layer, specifically Sn(S0.92Se0.08)2, which circumvents the oxygen molecules desorption and impedes the Sn2+ oxidation. As a result, tin-based perovskite solar cells with Sn(S0.92Se0.08)2 demonstrate a VOC increase from 0.48 – 0.73 V and a power conversion efficiency boost from 6.98 – 11.78%. Additionally, these cells exhibit improved stability, retaining over 95% of their initial efficiency after 1632 h. Our findings showcase metal chalcogenides as promising candidates for future nip-type tin-based perovskite solar cell applications. nip-Type tin-based perovskite solar cells have underperformed largely due to the metal oxide electron transport layers originally designed for lead-based devices. Here, authors employ metal chalcogenide as the electron transport layer, achieving enhanced efficiency up to 11.78% for stable devices. [ABSTRACT FROM AUTHOR]

The oxidative desulfurization mechanisms of aromatic sulfur compounds, including thiophene, benzothiophene, and dibenzothiophene, with H2O2 on fully coordinated and defective Ti sites on Ti-beta zeolites are investigated by means of density functional theory calculations. In this work, three current concerns are explored: First is the oxidation of sulfides into the sulfoxides and sulfones in the presence of H2O2; the second is the comparison between the sulfide oxidation mechanism on T5 and T2 defective sites in Ti-beta zeolites; and finally the comparison with the oxidation mechanism on fully coordinated Ti site on the Ti-beta zeolite. The model shows that T5 defect site in Ti-beta is the most catalytically active site for the oxidation of aromatic sulfides. [ABSTRACT FROM AUTHOR]

Vehicular safety is of considerable significance to the intelligent development of hybrid vehicles. However, the real-time stability control or reasonable torque distribution under the extreme road conditions remain a huge challenge due to the multiple uncertain parameters and difficulties to reconcile the handling and stability performance. To address the above problems for a through-the-road (TTR) 4-wheel-drive (4WD) hybrid vehicle, this study provides a handling and stability management (HSM) approach by incorporating the offline optimization rules and on-line model predictive control (MPC). Firstly, the vehicle dynamic model with seven degrees of freedom (7-DOF) is used to offline extract torque distribution rules (Offline-ETDR), and the online MPC feedback (Online-MPCF) is utilized to compensate the extra torque requirements for the poor effect under the extreme conditions. Accordingly, the offline optimization results and online correction are fused to provide the total torque demand given the real-time road condition detection. Finally, the real vehicle test are implemented to validate the effectiveness of the proposed torque coordination strategy. In comparison to the vehicle with no torque control strategy, the proposed method significantly improves the vehicle's cornering ability while also ensuring the high stability performance. [ABSTRACT FROM AUTHOR]

Fractures are developed in carbonate rock areas, and the fracture water flow significantly influences the heat exchange between buried pipes and the rock mass by induing heat convection, providing the carbonate rock area a strong heat exchange capacity and preferable conditions for shallow geothermal development and utilization. In this paper, the calculation method of heat exchange capacity of buried pipes based on fracture distribution characteristics is proposed and deduced, featuring such advantages as quick speed and low cost. Taking an actual project in carbonate rock area as an example, the heat exchange capacity of buried pipes was obtained by the following two methods: in-situ thermal response test and calculation based on fracture distribution characteristics. In the thermal response test, the initial ground temperatures of the two test holes were 15.18 °C and 12.72 °C. By fitting the linear equation of time and average temperature with a linear thermal source model, the heat exchange capacities were 57.21 W/m and 58.22 W/m, the thermal conductivities were 3.56 W/(m·K) and 2.32 W/(m·K), the thermal diffusivities were 1.71 × 10−6 m2/s and 1.12 × 10−6 m2/s, and the volume specific heat capacity was 2.08 × 106 J (m3·K). The test results indicated that the thermal property parameters of rock and soil mass were higher than those of other areas, with obvious wide-range distribution characteristics. Through the statistical analysis of outcrop fracture characteristics, combined with the cube law to calculate the fracture water flow and convective heat transfer, an alternative method for the calculation and optimization of buried pipe heat transfer in fractured rock mass area is also proposed in this paper. According to the measured fracture distribution characteristics of the field outcrop, the heat exchange capacities of the two holes were 57.26 W/m and 58.56 W/m, which were basically consistent with the thermal response test values and verified the reliability of the calculation method of heat exchange capacity of buried pipes based on fracture distribution characteristics. [ABSTRACT FROM AUTHOR]

Deep learning methods have been widely used in today's network security systems for their outperforming in detecting rates of the patterns of anomalous network actions. Particularly, in the field of malware traffic classification, time reduction for a detecting process is of great importance and can stop network damage at an early stage. To achieve a balance between the detection rate and time consumption, practical structures of relative systems are usually simple, complicating the application of appropriate accelerating methods. In this study, we propose a novel ant-colony -based clustering algorithm, which can efficiently select the most valuable data points for the next step of learning. In addition, to take advantage of the widely-used convolutional neural network architecture, we defined the mapping-image of each raw traffic data, and then transformed the intrusion detection problem into an image recognition problem. Before each training iteration, we applied the clustering algorithm to locate the most-featured part of each specific type of network traffic. Next, we utilized this featured part in the training, by considering its depth and shallow information, so that its precision and robustness can be improved. Preliminary experiments demonstrate that our method not only achieves high-detection-rate results but also manages to utilize much less processing time with proper parameter tuning of the neural networks. [ABSTRACT FROM AUTHOR]