Search

This work investigated the effect of nanodiamond (ND) additives on the tribological properties of CrN-coated piston ring mating with the chromium-plated and BP alloy iron cylinder liners, which is one of the key friction pairs in the internal combustion engines. To enhance the dispersion of the NDs in the base oil, the surface of ND particles was modified with polyaniline via in situ polymerization. The friction and wear as well as the scuffing characteristics of the friction pair lubricated with different contents of ND composite-added base oil were evaluated by using the reciprocating tribotests, which are close to the actual conditions. The wear surface morphologies and elements distribution were analyzed to explore the wear behaviors and the associated mechanisms of friction pairs under the lubrication incorporated with the ND composites. The results show that the ND additive is beneficial for the pair of Cr liner and CrN-coated piston ring in the friction and wear as well as scuffing properties, and the best concentration of ND additive is expected to be around 1 wt%. But for the BP liner, the developed nanocomposite has a negative impact. The friction force and the wear loss of the pair lubricated by the ND composite-added oil are even worse than that tested with the base lubricating oil.

Report to the 20th National Congress of the CPC emphasized the importance of "working actively and prudently towards the goals of reaching peak carbon emissions and carbon neutrality", as well as "speeding up the planning and development of a system for new energy sources". As a green and low-carbon secondary energy source, hydrogen energy has multiple applications in promoting the large-scale and efficient use of renewable energy as well as energy substitution in the field of transportation. It can also accelerate decarbonization in industry, and as such, is an indispensable part of building a new energy system, reaching peak carbon emissions and achieving carbon neutrality. This study takes 621 hydrogen energy policy documents issued by national and local government as research objects, designating to comprehensively study the hydrogen energy policy system. Based on policy informatics, this study uses natural language processing technology to mine data deeply and draws on hydrogen energy policy element information and key data indicators. It also combines content analysis, quantitative analysis and makes use of data visualization technology to study the evolution of hydrogen energy policy. It examines evolution trajectory of hydrogen energy policy, regional patterns of industry, the industrial chain layout, and other characteristics. The research framework and analysis methods used herein can help improve the systematization and timeliness of hydrogen energy policy research and proposes hydrogen energy policy suggestions to accelerate the development of hydrogen energy. [ABSTRACT FROM AUTHOR]

A thermodynamically consistent model for the carbon dioxide (CO2) absorption in aqueous alkanolamine system is of great importance in the research and development of a CO2 capture process. To facilitate the development of thermodynamic models, linear Gibbs free energy, enthalpy, and heat capacity relationships using well‐known amines as reference are used to correlate the standard reference state properties of ionic species with those of molecular species in the electrolyte system, which has been approved to provide a reliable and consistent way to estimate required parameters when there is minimal or no appropriate experimental data available. The proposed relationships have been applied to the development of an electrolyte nonrandom two liquid (NRTL) activity coefficient model for CO2 absorption in aqueous 1‐amino‐2‐propanol (A2P) solution, as an example to demonstration the methodology. With limited vapor–liquid equilibrium data and other thermodynamic properties, the parameters in the electrolyte NRTL model are identified with good accuracy. [ABSTRACT FROM AUTHOR]

The methanol to olefins (MTO) process has received considerable interest due to its importance in transforming abundant resources such as coal, natural gas, and biomass to widely‐demanded light olefins. In the MTO process, the coke deposited on the catalyst governs the catalyst activity and product selectivity, and thus is critical to the reaction behaviour. In the industrial processes, the residence time and coke content of catalyst particles in the reactor show a certain distribution due to the continuous outflow of spent catalyst and inflow of regenerated catalyst, which need further attention. The multi‐phase particle‐in‐cell (MP‐PIC) approach was used in the current work to simulate the catalyst residence time and coke content distribution. The effect of gas‐solid flow patterns, reactor structure, and average catalyst residence time on the residence time and coke content distribution was investigated. It was found that at high superficial velocities, the coke content distributions obtained with the MP‐PIC method are consistent with the distribution deduced from the ideally mixed flow assumption of catalyst particles. The results suggested that it is possible to simulate large‐scale MTO reactors by use of the coke distribution. In particular, by incorporating an initial coke distribution, the time needed to reach steady state in the MTO reactor simulations could be greatly reduced. [ABSTRACT FROM AUTHOR]

A kinetic model for methanol to olefins (MTO) process over SAPO‐34 catalyst was established based on the dual‐cycle reaction mechanism. Simplifications were made by assuming olefins‐based cycle as virtual species S, and aromatics‐based cycle as R, where the former mainly accounts for the production of higher olefins, while the latter for lower olefins. Transformation of S to R was considered with the participation of methanol and olefins. Meanwhile, a phenomenological deactivation model was developed to account for the deactivation process. With the proposed model, the evolution of methanol conversion and product selectivity with time on stream could be predicted, and key reaction characteristics, such as the autocatalytic nature of the reaction, could also be captured due to its mechanism‐based nature. Further simulations of MTO reactors at different scales validated the robustness and applicability of the current model in MTO process development and optimization. © 2018 American Institute of Chemical Engineers AIChE J, 65: 662–674, 2019 [ABSTRACT FROM AUTHOR]

Background: Accurate clinical staging of non-small cell lung cancer (NSCLC) is essential for developing an optimal treatment strategy. This study aimed to determine the predictive risk factors for lymph node metastasis, including both N1 and N2 metastases, in clinical T1aN0 NSCLC patients., Methods: We retrospectively evaluated clinical T1aN0M0 NSCLC patients who showed no radiologic evidence of lymph node metastasis, and who had undergone surgical pulmonary resection with systematic mediastinal node dissection or sampling at the First Affiliated Hospital of Zhejiang University between January 2011 and June 2013. Univariate and multivariate logistic regression analyses were performed to identify predictive factors for node metastasis., Results: Pathologically positive lymph nodes were found in 16.2% (51/315) of the patients. Positive N1 nodes were found in 12.4% (39/315) of the patients, and positive N2 nodes were identified in 13.0% (41/315) of the patients. Some 9.2% (29/315) of the patients had both positive N1 and N2 nodes, and 3.8% (12/315) of the patients had nodal skip metastasis. Variables of preoperative radiographic tumor size, non-upper lobe located tumors, high carcinoembryonic antigen (CEA) levels and micropapillary predominant adenocarcinoma (AC) were identified as predictors for positive N1 or N2 node multivariate analysis., Conclusions: Pathologically positive lymph nodes were common in small size NSCLC patients with clinical negative lymph nodes. Therefore, preoperative staging should be performed more thoroughly to increase accuracy, especially for patients who have the larger size, non-upper lobe located, high CEA level or micropapillary predominant ACs.

Telomerase Cajal body protein 1 (TCAB1) is a telomerase holoenzyme, which is markedly enriched in Cajal bodies (CBs) and facilitates the recruitment of telomerase to CBs in the S phase of the cell cycle. This recruitment is dependent on TCAB1 binding to a telomerase RNA component. The majority of cancer cells are able to grow indefinitely due to telomerase and its mechanism of trafficking to telomeres. In the present study, a certain level of TCAB1 expression in A549 human lung cells was identified and TCAB1 knockdown exhibited a potent antiproliferative effect on these cells, which was coupled with a decrease in the cell density and activity of the cellular enzymes. In addition, TCAB1-depletion was demonstrated to inhibit telomerase trafficking to telomeres in the A549 cells, leading to subsequent G 1 cell cycle arrest without inducing apoptotic cell death. Overall, these observations indicated that TCAB1 may be essential for A549 cell proliferation and cell cycle regulation, and may be a potential candidate for the development of a therapeutic target for lung adenocarcinomas.