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For 4000 “low-Tc” superconductors (i.e., non-cuprate and non-iron-based), Tc is plotted vs. the a) average atomic weight, b) average covalent radius, and c) average number of d) valence electrons. Having low average atomic weight and low average number of d) valence electrons are necessary (but not sufficient) conditions for achieving high Tc in this group. d) Scatter plot of Tc for all known superconducting cuprates vs. the mean number of unfilled orbitals. c), d) suggest that the values of these predictors lead to hard limits on the maximum achievable Tc
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So far a really interesting paper. Published in 2018. Adding some informal notes and interesting findings here. Finding out how much literature is based on this study.
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We notice that near the true Tc, we are starting to predict non-superconductivity, but it's only two points below 50% and they aren't necessarily continuous because of how measured temperature is fluctuating.
Looking at the model predictions for the 200 K above Tc to get to room temperature, we see consistent and stable predictions for the non-superconducting state.
a) Histogram of materials categorized by Tc (bin size is 2 K, only those with finite Tc are counted). Blue, green, and red denote low-Tc, iron-based, and cuprate superconductors, respectively. In the inset: histogram of materials categorized by ln(Tc) restricted to those with Tc > 10 K. b) Performance of different classification models as a function of the threshold temperature (Tsep) that separates materials in two classes by Tc. Performance is measured by accuracy (gray), precision (red), recall (blue), and F1 score (purple). The scores are calculated from predictions on an independent test set, i.e., one separate from the dataset used to train the model. In the inset: the dashed red curve gives the proportion of materials in the above-Tsep set. c) Accuracy, precision, recall, and F1 score as a function of the size of the training set with a fixed test set. d) Accuracy, precision, recall, and F1 as a function of the number of predictors