Investigation of La0.6Sr0.4Co1-xNixO3-δ (x=0, 0.2, 0.4, 0.6, 0.8) catalysts on solid oxide fuel cells anode for biogas dry reforming

The introduction of catalyst on anode of solid oxide fuel cell (SOFC) has been an effective way to alleviate the carbon deposition when utilizing biogas as the fuel. A series of La_0.6Sr_0.4Co_1-xNi_xO_3-δ (x = 0, 0.2, 0.4, 0.6, 0.8) oxides are synthesized by sol-gel method and used as catalysts precursors for biogas dry reforming. The phase structure of La_0.6Sr_0.4Co_1-xNi_xO_3-δ oxides before and after reduction are characterized by X-ray diffraction (XRD). The texture properties, carbon deposition, CH₄ and CO₂ conversion rate of La_0.6Sr_0.4Co_1-xNi_xO_3-δ catalysts are evaluated and compared. The peak power density of 739 mW cm^?2 is obtained by a commercial SOFC with La_0.6Sr_0.4Co_0.4Ni_0.6O_3-δ catalyst at 850 °C when using a mixture of CH₄: CO₂ = 2:1 as fuel. This shows a great improvement from the cell without catalyst for internal dry reforming, which is attributed to the formation of NiCo alloy active species after reduction in H₂ atmosphere. The results indicate the benefits of inhibiting the carbon deposition on Ni-based anode through introducing the La_0.6Sr_0.4Co_0.4Ni_0.6O_3-δ catalyst precursor. Additionally, the dry reforming technology will also help to convert part of the exhaust heat into chemical energy and improve the efficiency of SOFC system with biogas fuel.     

Recent advances during CH4 dry reforming for syngas production: A mini review

Given the continuing issues of environment and energy, methane dry reforming for syngas production have sparked interest among researchers, but struggled with the process immaturity owing to catalyst deactivation. This review summarizes the recent advances in the development of efficient and stable catalysts with strong resistance to coking and metal sintering, including the application of novel materials, the assessment of advanced characterizations and the compatibility to improved reaction system. One feasible option is the crystalline oxide catalysts (perovskite, pyrochlore, spinel and LDHs), which feature a fine metal dispersion and surface confinement effect via a metal exsolution strategy and exhibit superior reactivity and stability. Some new materials (h-BN, clays and MOFs) also extend the option because of their unique morphology and microstructure. It also is elaborated that progresses were achieved in advanced characterizations application, leading to success in the establishment of reaction mechanisms and attributions to the formed robust catalysts. In addition, the perspective described the upgrade of reaction system to a higher reaction efficiency and milder reaction conditions. The combination of efficient reaction systems and robust catalysts paves a way for a scaling-up application of the process.     

LBM investigation of a Cu-water nanofluid over various configurations of pipes in the mixed convection flow

Increasing the heat capacity of heat exchangers is a crucial need for modern devices. The thermal conductivity of the usual fluids and the Nusselt (Nu) number of flows containing such fluids are two bottlenecks in the way of increasing heat delivery in the heat exchangers. For this reason, nanofluids have been introduced. The effect of utilizing a Cu-water nanofluid as a coolant of two hot pipes in a square cavity is investigated numerically with a two-component lattice Boltzmann method. The volume fraction of nanoparticles is assumed to be constant (0.03) while the Richardson (Ri) number varies from 0.02 to 20. Results show that the effectiveness of nanoparticles is better observed in the natural convection mode. However, sedimentation is also very probable at high Ri numbers, which significantly reduces the effectiveness of the nanoparticles. Configurations which produce a natural convection stream similar to the forced convection one as well as the configurations with high spacing and hence, low heat stream interactions, are the best choices for a uniform heat rate from the pipes.     

Modeling unaccounted-for gas among residential natural gas consumers using a comprehensive fuzzy cognitive map

Residential natural gas consumption depends on several factors. Available tools and methods to identify, categorize, and validate effective factors have some limitations, making consumption modeling more complex. Once a comprehensive model of effective consumption factors is developed for residential gas consumers, it can predict consumption. In addition, such a model could be used to verify the accuracy of measuring devices in order to reduce unaccounted for gas (UFG). The key factors affecting residential gas consumption were identified based on previous studies and their mutual effects were analyzed using a fuzzy cognitive mapping (FCM) method. The most significant factors and their effects on natural gas consumption in the residential sector were determined. In this study, for the first time, the expected consumption for each consumer was estimated using a consumption index. Generally, if the estimated consumption is significantly different from the amount recorded by the meter, it could suggest a potential source of UFG. The proposed method was applied to the data collected from the residential gas consumers of a small region in Iran (Dasht-e Arjan region, Fars province), and the results demonstrate the effectiveness of the proposed method.     

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.     

An integrated dimensionality reduction and surrogate optimization approach for plant-wide chemical process operation

With liquefied natural gas becoming increasingly prevalent as a flexible source of energy, the design and optimization of industrial refrigeration cycles becomes even more important. In this article, we propose an integrated surrogate modeling and optimization framework to model and optimize the complex CryoMan Cascade refrigeration cycle. Dimensionality reduction techniques are used to reduce the large number of process decision variables which are subsequently supplied to an array of Gaussian processes, modeling both the process objective as well as feasibility constraints. Through iterative resampling of the rigorous model, this data-driven surrogate is continually refined and subsequently optimized. This approach was not only able to improve on the results of directly optimizing the process flow sheet but also located the set of optimal operating conditions in only 2 h as opposed to the original 3 weeks, facilitating its use in the operational optimization and enhanced process design of large-scale industrial chemical systems.     

Influence of CO2 inleakage on the slight-alkalization of generator internal cooling water

The slight-alkalization of generator internal cooling water (GICW) is widely used to inhibit the corrosion of hollow copper conductor and thereby ensure the safe operation of the generator. CO₂ inleakage is increasingly identified as a potential security risk for GICW system. In this paper, the influence of CO₂ inleakage on the slight-alkalization of GICW was theoretically discussed. Based on the equilibriums of the CO₂-NaOH-H₂O system, CO₂ inleakage saturation was derived to quantify the amount of the dissolved CO₂ in GICW. This parameter can be directly calculated with the measured conductivity and the [Na⁺] of GICW. The influence of CO₂ inleakage on the slight-alkalization conditioning of GICW and the measurement of its water quality parameters were then analyzed. The more severe the inleakage, the narrower the water quality operation ranges of GICW, resulting in the more difficult the slight-alkalization conditioning of GICW. The temperature calibrations of the conductivity and the pH value of GICW show non-linear correlations with the amount of CO₂ inleakage and the NaOH dosage. This study provides insights into the influence of CO₂ inleakage on the slight-alkalization of GICW, which can serve as the theoretical basis for the actual slight-alkalization when CO₂ inleakage occurs.     

Defining Dry Eye from a Clinical Perspective

Over the past decades, the number of patients with dry eye disease (DED) has increased dramatically. The incidence of DED is higher in Asia than in Europe and North America, suggesting the involvement of cultural or racial factors in DED etiology. Although many definitions of DED have been used, discrepancies exist between the various definitions of dry eye disease (DED) used across the globe. This article presents a clinical consensus on the definition of DED, as formulated in four meetings with global DED experts. The proposed new definition is as follows: “Dry eye is a multifactorial disease characterized by a persistently unstable and/or deficient tear film (TF) causing discomfort and/or visual impairment, accompanied by variable degrees of ocular surface epitheliopathy, inflammation and neurosensory abnormalities.” The key criteria for the diagnosis of DED are unstable TF, inflammation, ocular discomfort and visual impairment. This definition also recommends the assessment of ocular surface epitheliopathy and neurosensory abnormalities in each patient with suspected DED. It is easily applicable in clinical practice and should help practitioners diagnose DED consistently. This consensus definition of DED should also help to guide research and clinical trials that, to date, have been hampered by the lack of an established surrogate endpoint.