Comparative Study of the Gasification of Coal and Its Macerals and Prediction of the Synergistic Effects Under Typical Entrained-Bed Pulverized Coal Gasification Conditions

This research is focused on the gasification performance of coal and its corresponding macerals as well as on the interactions among macerals under typical gasification conditions by Aspen Plus modeling. The synergistic coefficient was employed to show the degree of interactions, while the performance indicators including specific oxygen consumption (SOC), specific coal consumption (SCC), cold gas efficiency (CGE), and effective syngas (CO + H2) content were used to evaluate the gasification process. Sensitivity analyses showed that the parent coal and its macerals exhibited different gasification behaviors at the same operating conditions, such as the SOC and SCC decreased in the order of inertinite > vitrinite > liptinite, whereas CGE changed in the order of liptinite > vitrinite > inertinite. The synergistic coefficients of SOC and SCC for the simulated coals were in the range of 0.94–0.97, whereas the synergistic coefficient of CGE was 1.05–1.13. Moreover, it was found that synergistic coefficients of gasification indicators correlated well with maceral contents. In addition, the increase in temperature was found to promote the synergistic coefficients slightly, whilst at an oxygen to coal mass ratio of 0.8 and a steam to coal mass ratio of 0.8, the highest synergistic coefficient was obtained.

Extraction of Palladium(II) from Hydrochloric Acid Solutions by Solvent Extraction with Cationic Mixtures

Cyanex 301 and LIX 63 can seletively extract Pd(II) over Pt(IV) from strong hydrochloric acid solutions. Therefore, solvent extraction experiments have been performed by extractant mixtures containing either Cyanex 301 or LIX 63 and the extraction behavior of Pd(II) was compared. Among the mixture of Cyanex 301, the highest synergistic enhancement coefficient was achieved by mixing Cyanex 301 and TOPO. However, it was very diffiuclt to strip the Pd(II) from the loaded mixture. Among the mixture of LIX 63, the mixture of LIX 63 and Alamine 336/TOPO enhanced the extraction of Pt(II). Although the synergistic coefficient by Cyanex 301 + TOPO was higher than that by LIX 63 + Alamine 336, the Pd(II) in the loaded mixture of LIX 63 and Alamine 336 was easily stripped by thiourea.

Nonadditive Interactions and Hamilton’s Rule

This chapter examines what happens in nonadditive interactions when such interactions take place between relatives, and how Hamilton's rule can be extended in two different ways to accommodate such nonadditivity. It first considers the selective pressures on nonadditive behaviors directed towards relatives by making use of the replicator dynamics to capture interactions within structured populations, so that on average, interactions within the population occur between relatives. It then describes two extensions to Hamilton's rule to deal with nonadditive interactions. One approach takes deviations from additivity and accounts for them all in a single synergistic coefficient. The other approach applies partial regression to keep a version of Hamilton's rule with only three parameters, in which costs and benefits vary according to the frequency of social individuals in a population. The chapter also explains the use of the Price equation to study nonadditive social interactions between relatives.

Variants of Hamilton’s Rule and Evolutionary Explanations

This chapter examines four variants of Hamilton's rule and how they give different evolutionary explanations for certain social behaviors such as greenbeard traits. These variants are: HR1, which extends Hamilton's rule with a synergistic coefficient capturing the deviation from additivity of fitness interactions; HR2, which deals with the conditional expression of phenotype; HR3, which is concerned with fitness as partial regression; and HR4, the geometric view of relatedness. These variants differ in how they treat the three key parameters of the original: “relatedness,” “cost,” and “benefit.” The chapter also considers how the nongenetic explanation of the evolution of altruism can actually be recast in a version with genetic relatedness, and how geometric relatedness underlies phenotypic assortment. Finally, it discusses different viewpoints on conditional behaviors.