The use of lithium-intercalated transition metal dichalcogenides, Li x ES 2 , as redox-recyclable ion-exchange materials for the extraction of the aqueous heavy metal ions Hg 2+ , Pb 2+ , Cd 2+ , and Zn 2+ was investigated (0.25 e x e 1.9; E ) Mo, W, Ti, Ta). For Li x TiS 2 and Li x TaS 2 , hydrolysis produced S 2-(aq) ions, which precipitated Hg(II) as HgS(s). In contrast, the materials Li x MoS 2 and Li x WS 2 did not undergo hydrolysis to form S 2ions. Instead, ionexchanged materials such as Hg 0.50 MoS 2 and Pb 0.15 MoS 2 were isolated. The selectivity of Li x MoS 2 for the heavy metal ions was Hg 2+ > Pb 2+ > Cd 2+ > Zn 2+ . The affinities for the latter three ions but not for Hg 2+ increased when the extractions were performed under anaerobic conditions. When Hg y MoS 2 was heated under vacuum at 425 °C, an entropy-driven internal redox reaction resulted in deactivation of the extractant, producing essentially mercury-free MoS 2 and a near-quantitative amount of mercury vapor (collected in a cold trap). The ratio of the volume of metallic mercury (secondary waste) to the volume of 10.0 mM Hg 2+ (aq) (primary waste) was 1.5 × 10 -4 . Samples of MoS 2 produced by heating Hg y MoS 2 were reactivated to Li x MoS 2 by treatment with n-butyllithium. Some samples were used for three cycles of extraction, deactivation/recovery, and reactivation with a primary waste simulant consisting of 10 mM Hg 2+ (aq) in 0.1 M HNO 3 with no loss in ion-exchange capacity. When the Mo/Hg molar ratio was 5.0 and the initial [Hg 2+ (aq)] ) 1 mM, only 0.033(2) µM mercury (6.5 ppb) was detected in the filtrate after the extraction step. The highest observed capacity of Li x MoS 2 for Hg 2+ (aq) was 580 mg of mercury/g of Li 1.9 MoS 2 .

Metacognitive monitoring of one's own understanding plays a key role in learning. An aspect of metacognitive monitoring can be measured by comparing a student's prediction or postdiction of performance (a judgment made before or after completing the relevant task) with the student's actual performance. In this study, we investigated students' postdiction accuracies for a series of exams within a twosemester general chemistry course. The research questions addressed include (1) How accurate are general chemistry students at postdicting their exam scores? Are there gender differences in postdiction accuracy?(2) How do general chemistry students' postdiction accuracies relate to their exam performance? (3) How do general chemistry students' postdiction accuracies and metacognitive monitoring of their exam performance change over time? Results indicate that most general chemistry students are not accurate in their exam score postdictions and that, consistent with research conducted in other domains, higher-performing students make more accurate postdictions than lower-performing students. In addition, although students who were new to a general chemistry course appeared to improve in their metacognitive monitoring on the second course exam compared with the first, monitoring did not significantly improve after that initial adjustment. Given the importance of metacognitive monitoring for student learning of chemistry, these findings suggest that further research and development of interventions to improve the metacognitive monitoring of introductory chemistry students is warranted.

This study investigated relationships between the thinking processes that 28 undergraduate chemistry students engaged in during guided discovery and their subsequent success at reasoning through a transfer problem during an end-of-semester interview. During a guided-discovery laboratory module, students were prompted to use words, pictures, and symbols to make their mental models of chemical compounds added to water explicit, both prior to the start (initial model) and at the end (refined model) of the module. Based on their responses to these model assignments, we characterized students’ knowledge and thinking processes, including the extent to which individual students engaged in (a) constructing molecular-level models that were consistent with experimental evidence; (b) constructing molecular-level models that progressed toward scientific accuracy; (c) constructing molecular-level models that were scientifically correct; (d) making connections between laboratory observations and the molecular-level behavior of particles; (e) accurate metacognitive monitoring of how their molecular-level models changed; and (f) using evidence to justify model refinements. Analyses revealed three thinking processes that were strongly associated with correct reasoning in the transfer context during an end-of-semester interview: constructing molecular-level models that were consistent with experimental evidence, engaging in accurate metacognitive monitoring, and using evidence to justify model refinements. The extent of student engagement in these three key thinking processes predicted correct reasoning in a new context better than the scientific correctness of a student’s content knowledge prior to instruction. Although we did not explore causal relationships, these results suggest that integrating activities that promote the key thinking processes identified into instruction may improve students’ understanding and success at transfer.

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