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A. S. Thind

Publications and source records attributed to A. S. Thind.

2 recordsLinked to original sources

Polymorphism in Ruddlesden-Popper $La_{3}Ni_{2}O_{7}$: Discovery of a Hidden Phase with Distinctive Layer Stacking

We report the discovery of a novel form of Ruddlesden-Popper (RP) oxide, which stands as the first example of long-range, coherent polymorphism in this class of inorganic solids. Rather than the well-known, uniform stacking of perovskite blocks ubiquitously found in RP phases, this newly discovered polymorph of the bilayer RP phase $La_{3}Ni_{2}O_{7}$adopts a novel stacking sequence in which single and trilayer blocks of $NiO_{6}$ octahedra alternate in a 1313 sequence. Crystals of this new polymorph are described in space group Cmmm, although we note evidence for a competing Imcm variant. Transport measurements at ambient pressure reveal metallic character with evidence of a charge density wave transition with onset at T = 134 K, which lies intermediate between that of the standard 2222 polymorph of $La_{3}Ni_{2}O_{7}$ (space group Amam) and the trilayer RP phase, $La_{4}Ni_{3}O_{10}$. The discovery of such polymorphism could reverberate to the expansive range of science and applications that rely on RP materials, particularly the recently reported signatures of superconductivity with $T_{c}$ as high as 80 K above 14 GPa in bilayer $La_{3}Ni_{2}O_{7}$.

cond-mat.supr-con

Stochastic Replica Voting Machine Prediction of Stable Cubic and Double Perovskite Materials and Binary Alloys

A machine learning approach that we term the `Stochastic Replica Voting Machine' (SRVM) algorithm is presented and applied to a binary and a 3-class classification problems in materials science. Here, we employ SRVM to predict candidate compounds capable of forming stable perovskites and double perovskites and further classify binary ($AB$) solids. The results of our binary and ternary classifications compared well to those obtained by SVM and neural network algorithms.

cond-mat.mtrl-sci