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The purpose of this paper is to research the morphologies of the oxide films formed on the internal surfaces of water wall tubes in a 600 MW furnace at 300° while using CPT, CT, AVT(R) and AVT(O) water chemistry. In these water chemistry conditions, a layer of oxide film spontaneously forms in the furnace wall which could prevent corrosions in boiler water directly contact with the inner tube and reduce the probability of tube perforation.

The different morphologies, specific functions and distribution in the oxide film were identified by electrochemical workstation, XRD, SEM and EDAX.

It is concluded that metal surface was rugged and had deep corrosion in CPT. Ions penetrated into the oxides of large particles with gaps and intergranular corrosion occurred in CT conditions. In AVT(R), the oxide film uniformly covered on the metal surface played a protective role, but could be easily washed away by solution. The oxide film formed in AVT(O) was similar to AVT(R), but the difference is that large solid particles of Fe₂O₃ cover the outermost oxide film, which prevents the oxide film from being taken away by the flowing solution. In consequence, the degree of corrosion sustained by the tube walls is lowest in the case of AVT(O).

The results can provide reference for reducing the high temperature corrosion of metal in the actual operation.

The purpose of this paper is to investigate the influence of Cl‐ions on the pitting corrosion of water‐wall tube of a boiler and the principle behind it.

The specimens were immersed for seven hours at 300°C in deaerated water subjected to simulation‐modified equilibrium phosphate treatment, containing Cl‐ions at various concentrations. The effects of Cl‐ions on pitting corrosion were assessed by the rate mass loss, transmission reflection metallurgical microscopy, SEM, EDS, and XRD.

The results indicated that Cl‐ions cause the breakdown of passive films. The corrosion mechanism of Cl‐is proposed to involve an intermediate dissolution stage. The Cl‐ions act as a catalyst of corrosion, by inducing the hydrolysis of Fe2+. The critical susceptive Cl‐concentrations are 0.2 and 0.6 mg·L^‐1 for the passivated specimens and for the unpassivated specimens, respectively.

The paper provides information regarding the relationship between Cl‐concentrations and pitting corrosion, useful for understanding the mechanism of Cl‐induced pitting corrosion, and the research results can provide theoretical guidelines for preventing water‐wall of power plants from corroding.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

To combine the forecasting by single method using influence information fully, other than regular combined methods only focusing on historical forecasting errors.

To combine the single methods based on the analysis of improved gray correlation, with more related information being considered to enhance the price forecasting precision, such as the trend of the prices, the historical forecasting errors, and the temporal influence factors on prices.

A case of PJM market of USA shows that the proposed method has better performance than any other combined methods, and all single models as well.

The combined performance depends on the forecasting precision of single methods, and the correlation between the single methods, as well as the number of single method that to be combined.

It is a novel idea for combined method to forecasting the time series data, such as electricity prices, electric power loads.

The proposed method considers all the following factors: the similarity between the trends of the single forecasting, the errors of the single models and the temporal influence.

The paper aims to clarify the influence of different picture contents on consumer's willingness to click pictures when shopping for agricultural products online and examine the intermediary mechanism and boundary conditions of the impact.

The paper opted for an empirical study based on the cue utilization theory and information processing theory, including three experiments to test the existence, intermediary mechanism and boundary conditions of the impact of online picture contents of agricultural products on consumers' clicking intention.

The paper provides empirical insights about the influence of picture contents on consumer's willingness to click when shopping for agricultural products online. The picture of product's production environment or grower on the search result page can effectively improve consumer's willingness to click the product under dual systemic information processing modes. Compared with product pictures, pictures displaying products and production environment can stimulate more cognitive system processing, and pictures displaying products and its growers can stimulate more emotional system processing, both resulting in higher click intention. However, the above effects only exist in the context of non-branded agricultural products.

The research results not only provide practical guidance for merchants, but also fill the gap in the research on the impact of picture contents on consumers in the field of agricultural products in online marketing.