The
relative ease of Mössbauer spectroscopy and of density
functional theory (DFT) calculations encourages the use of Mössbauer
parameters as a validation method for calculations, and the use of
calculations as a double check on crystallographic structures. A number
of studies have proposed correlations between the computationally
determined electron density at the iron nucleus and the observed isomer
shift, but deviations from these correlations in low-valent iron β-diketiminate
complexes encouraged us to determine a new correlation for these compounds.
The use of B3LYP/def2-TZVP in the ORCA platform provides an excellent
balance of accuracy and speed. We provide here not only this new correlation
and a clear guide to its use but also a systematic analysis of the
limitations of this approach. We also highlight the impact of crystallographic
inaccuracies, DFT model truncation, and spin states, with intent to
assist experimentalists to use Mössbauer spectroscopy and calculations
together.
Background
Demographic characteristics are known to influence participation in cocurricular activities. Less studied are the effects of other background characteristics.
Purpose
We hypothesize that considering college knowledge and students' proactive behaviors in tandem with demographics provides better models for predicting such participation.
Method
We developed a questionnaire and administered it to 3,618 domestic third‐ and fourth‐year undergraduate engineering students at a large public R1 Midwestern university, yielding 860 responses. Logistic regression models predicting five types of cocurricular participation were constructed with demographic characteristics, college knowledge, and proactive behaviors in all combinations as predictors.
Results
Four of five types of cocurricular participation were better modeled using factors beyond demographics. Two were better modeled using only proactive behavior as predictors and two were better modeled using demographics in combination with either college knowledge or proactive behavior. Only one type of participation could be best predicted by demographics alone.
Conclusions
These findings contribute quantitative evidence establishing relationships between participation in engineering cocurricular activities and a wider range of factors than previously reported. Furthermore, they provide guidance for creating intervention programs because, unlike demographics, college knowledge and proactive behavior can be shaped by either the individual or the institution.
I n the publication, there were several errors in Table 12.In the column for S, the first six entries should have been 0, 1, 2, 0, 1, and 2 (since 0, 1, and 2 are the possible values of S for each of the high-spin iron(II) compounds L tBu FeCH 3 and Me L Me,Me Fe(η 5 -Ind)). The correct values of S were used for the computations, and therefore the paper's interpretations and conclusions are the same. We regret this error.
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