arXiv subjects

Sharmila Shirodkar

Publications and source records attributed to Sharmila Shirodkar.

3 recordsLinked to original sources

arXiv2022

Magnetotransport in graphene/Pb0.24Sn0.76Te heterostructures: finding a way to avoid catastrophe

While heterostructures are ubiquitous tools enabling new physics and device functionalities, the palette of available materials has never been richer. Combinations of two emerging material classes, two-dimensional materials and topological materials, are particularly promising because of the wide range of possible permutations that are easily accessible. Individually, both graphene and Pb0.24Sn0.76Te (PST) are widely investigated for spintronic applications because graphene's high carrier mobility and PST's topologically protected surface states are attractive platforms for spin transport. Here, we combine monolayer graphene with PST and demonstrate a hybrid system with properties enhanced relative to the constituent parts. Using magnetotransport measurements, we find carrier mobilities up to 20,000 cm2/Vs and a magnetoresistance approaching 100 percent, greater than either material prior to stacking. We also establish that there are two distinct transport channels and determine a lower bound on the spin relaxation time of 4.5 ps. The results can be explained using the polar catastrophe model, whereby a high mobility interface state results from a reconfiguration of charge due to a polar/non-polar interface interaction. Our results suggest that proximity induced interface states with hybrid properties can be added to the still growing list of remarkable behaviors in these novel materials.

cond-mat.mtrl-sci↗

arXiv2022

Predicting phase preferences of two-dimensional transition metal dichalcogenides using machine learning

Two-dimensional transition metal dichalcogenides (TMDs) can adopt one of several possible structures, with the most common being the trigonal prismatic and octahedral symmetry phases. Since the structure determines the electronic properties, being able to predict phase-preferences of TMDs from just the knowledge of the constituent atoms is highly desired, but has remained a long-standing problem. In this study, we applied high-throughput quantum mechanical computations with machine learning algorithms to solve this old problem. Our analysis provides insights into determining physiochemical factors that dictate the phase-preference of a TMD, identifying and going beyond the attributes considered by earlier researchers in predicting crystal structures. A knowledge of these underlying physiochemical factors not only helps us to rationalize, but also to accurately predict structural preferences. We show that machine learning algorithms are powerful tools that can be used not only to find new materials with targeted properties, but also to find connections between elemental attributes and the target property/properties that were not previously obvious.

cond-mat.mtrl-sci↗

arXiv2014

Discovery of an isostructural phase transition within orthorhombic phase field of CaTiO3

Earths lower mantle extending from 670 to 2,990 km deep is predominantly composed of a perovskite-type (Mg,Fe)SiO3 phase1,2. The perovskite phase undergoes a structural phase transition to a post-perovskite phase responsible for D" layer seismic discontinuity2,3 at about 2690 km depth in the lowermost region of the lower mantle. However, structural basis of other seismic discontinuities occurring in the upper region of the lower mantle (700 km to 1,200 km deep) remains unexplained4-7, as no apparent change in the crystal symmetry of the orthorhombic perovskite phase has been reported5. We present here unambiguous evidence for a non-apparent isostructural phase transition8 in the stable orthorhombic perovskite phase of CaTiO3 which may have relevance to phase transitions in the perovskite phase of (Mg,Fe)SiO3 also, as both the compounds have similar structure, tolerance factor and thermochemical properties9-11. Our results are based on the analysis of neutron powder diffraction patterns using Rietveld and mode crystallography techniques and are supported by density functional and Landau theory calculations. The present results on CaTiO3 would encourage search for isostructural phase transition in the perovskite phase of (Mg,Fe)SiO3 that may provide clue to the unexplained geophysical phenomena in the upper part of the earths lower mantle.

cond-mat.mtrl-sci↗