Learning from Correlations Based on Local Structure: Rare-Earth Nickelates Revisited

Statistical analysis of local atomic distortions in crystalline materials is a powerful tool for understanding coupled electronic and structural phase transitions in transition metal compounds. The analyses of such complex materials, however, often require significant domain knowledge to recognize limitations in the available data, whether it be experimentally reported crystal structures, property measurements, or computed quantities, and to understand when additional experiments or simulations may be necessary. Here we show how additional descriptive statistics and computational experiments can help researchers explicitly recognize these limitations and fill in missing gaps by constructing amplitude (a) and normalized-amplitude (n) distortion-mode property correlation-coefficient heat maps, aCCHMs and nCCHMs, respectively. We demonstrate this utility within the rare-earth nickelate perovskites RNiO3 (R = rare earth ≠ La), which exhibit antiferromagnetic and metal–insulator transitions with crystallograph...