Locating the cocktail and scaling-relation breaking effects of high-entropy alloy catalysts on the electrocatalytic volcano plot

High entropy alloys(HEAs)have been the star materials in electrocatalysis research in recent years.One of their key features is the greatly increased multiplicity of active sites compared to conventional catalytic materials.This increased multiplicity stimulates a cocktail effect and a scaling-relation breaking effect,and results in improved activity.However,the multiplicity of active sites in HEAs also poses new problems for mechanistic studies.One apparent problem is the inapplicability to HEA catalysts of the currently most popular mechanistic study method,which uses the electrocatalytic theoretical framework(ETF)based on the computational hydrogen electrode(CHE).The ETF uses a single adsorption energy to represent the catalyst,i.e.,a catalyst is represented by a'point'in the volcanic relationship.It naturally does not involve the multiplicity of active sites of a catalyst,and hence loses brevity in expressing the cocktail effect and scaling-relation breaking effect in HEA catalysis.This paper attempts to solve this inapplicability.Based on the fact that the adsorption energy distribution of HEAs is close to a normal distribution,the mean and variance of the adsorption energy distribution are introduced as descriptors of the ETF,replacing the original single adsorption energy.A quantitative relationship between the variance and the cocktail and scaling-relation braking effects is established.We believe the method described in this work will make the ETF more effective in mechanistic studies of HEA electrocatalysis.

EXPERIMENTAL STUDY OF ROCK BREAKING EFFECT OF STEEL PARTICLES

Particle impact drilling is an efficient drilling technology for deep-well hard formation, With this technology, the rock is cut mainly by high-speed spherical particle impact under hydraulic action. In this article, the influence of jet flow factors, hydraulic factors and abrasive factors on rock breaking is studied through indoor experiments of impact by steel particles. The results indicate that the particle water jet has an optimal standoff distance and particle concentration; the rock breaking effect declines with the increase of the confining pressure and the decrease of the pump pressure and particle diameter. This study will provide some food of thought for the development of particle impact drilling technology.

Effects of Breaking Waves on Composite Backscattering from Ship-Ocean Scene

The existence of the sea surface is bound to affect the electromagnetic （EM） scattering from marine targets. When dealing with the composite scattering from targets over a sea surface by applying high-frequency EM theories, the total scattering field can be decomposed into three parts in low sea states, namely, the direct scattering from the sea surface, the direct scattering from targets and the coupling scattering between the sea surface and targets. With regard to high sea states, breaking waves make the direct scattering from the sea surface and the coupling scattering more complicated. To solve this issue, a scattering model is proposed to analyze the composite scattering from a ship over a rough sea surface under high sea states. To consider the effect of breaking waves, a three dimensional geometric model is adopted together with Ufimtsev＇s theory of edge waves for the scattering from a breaker. In addition, the coupling scattering between targets and breaking waves is taken into account by considering all possible scattering paths. The simulated results indicate that the influence of breaking waves on the scattering field from the sea surface and on the coupling field is non-negligible, and the numerical results also show the effectiveness of the proposed scattering model.

A Comparative Study of Performance Between Operators With Work Discontinuity and Without Work Discontinuity

In situations where discontinuity in operation occurs, specifically in a country where coontractualization has an increasing trend, the performance level of operators after the work break is of great interest. Existing studies have found that the performance of an operator declines after her operation is completely stopped. However, when the operator performed other tasks （may it be similar or not from her previous task） during the work break, the performance after the work break seems to be affected at different level. Contractual and regular operators from a semiconductor and textile company were considered to replicate a discontinuous and continuous operation. The processing times of contractual workers before and after several months of work break were compared. Two types of work break were seen to have significant effect on an operator＇s performance after the work break, Type 1： 0% to 40% similarity from previous task and Type 2： 40% to 97% similarity from previous task. One can find that when 21% of tasks performed during the work break are similar to the operator＇s previous task, there would be no change in her performance upon returning. On the other hand, a 5% decline in performance was observed after work break type 1 and an 8.54% improvement after work break type 2. Also, a remission rate of 18% from end of stint 1 to start of stint 2 under work break type 1 was seen, while 8% for work break type 2. This may also be true to other industries. Thus, further study is suggested.

Determination of Variables That Affect the Remission Rate of Sewing Operations in a Textile Company

In operations management, the learning curve has been an effective tool in estimating operator performance. However, discontinuities in work disrupt the learning process and a phenomenon called remission or forgetting occurs, resulting in increased time of performing the task upon resumption of work. The study aims to identify variables that significantly affect the remission rate of sewing operations in a manufacturing setting. Four variables--length of stint 1, percent Differenceat stint t, gender, and product family, were identified. Statistical analyses, such as paired t-test, correlation, regression, and analysis of variance （ANOVA） were conducted in order to observe the relationships between the dependent variable and independent variables. For the results of the first general regression, gender was found to be an insignificant variable in predicting remission rate, while product family, length of stint 1, and percent Differenceat stint I were statistically significant. Moreover, the final general regression, which excluded the insignificant gender variable and considered the （regrouped） product families, revealed that product family, length of stint 1, and percent Differenceat stint 1 were still statistically significant. Length of stint 1 had a moderately positive correlation with remission rate, while percent Differenceat stint i had a moderately negative correlation with remission rate. Also, percent Differenceat stint 1 was the largest contributor to the remission rate model. In terms of R2, the goodness-of-fit of the model is moderate. Finally, the model yielded an absolute error of 5.08%, indicating a high accuracy in predicting remission rate.