125 citations · 461 across the 17 of their papers we have counts for
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Machine learning for impurity charge-state transition levels in semiconductors from elemental properties using multi-fidelity datasets
Maciej P. Polak, Ryan Jacobs, Arun Mannodi-Kanakkithodi +2
Quantifying charge-state transition energy levels of impurities in semiconductors is critical to understanding and engineering their optoelectronic properties for applications rang…
Data-Driven Design of Novel Halide Perovskite Alloys
Arun Mannodi-Kanakkithodi, Maria K. Y. Chan
The great tunability of the properties of halide perovskites presents new opportunities for optoelectronic applications as well as significant challenges associated with exploring…
Ultrafast formation of transient 2D diamond-like structure in twisted bilayer graphene
Duan Luo, Dandan Hui, Bin Wen +17
Due to the absence of matching carbon atoms at honeycomb centers with carbon atoms in adjacent graphene sheets, theorists predicted that a sliding process is needed to form AA, AB,…
Machine-learned impurity level prediction for semiconductors: the example of Cd-based chalcogenides
Arun Mannodi-Kanakkithodi, Michael Y. Toriyama, Fatih G. Sen +3
The ability to predict the likelihood of impurity incorporation and their electronic energy levels in semiconductors is crucial for controlling its conductivity, and thus the semic…
Atomistic manipulation of reversible oxidation and reduction in Ag by electron beam
Huaping Sheng, He Zheng, Lifen Wang +6
Employing electrons for direct control of nanoscale reaction is highly desirable since it provides fabrication of nanostructures with different properties at atomic resolution and…
Computational prediction of lattice thermal conductivity -- a comparison of molecular dynamics and Boltzmann transport approaches
Marcello Puligheddu, Yi Xia, Maria K. Y. Chan +1
The predictive modeling of lattice thermal conductivity is of fundamental importance for the understanding and design of materials for a wide range of applications. Two major appro…
Phonon-pump electronic-probe study of methylammonium lead iodide reveals electronically decoupled organic and inorganic sublattices
Peijun Guo, Arun Mannodi-Kanakkithodi, Jue Gong +10
Organic-inorganic hybrid perovskites such as methylammonium lead iodide (CH3NH3PbI3) are game-changing semiconductors for solar cells and light-emitting devices owing to their exce…
Anharmonic stabilization and lattice heat transport in rocksalt -GeTe
Yi Xia, Maria K. Y. Chan
Peierls-Boltzmann transport equation, coupled with third-order anharmonic lattice dynamics calculations, has been widely used to model lattice thermal conductivity () in bul…
Lattice thermal transport in group II-alloyed PbTe
Yi Xia, James M. Hodges, Mercouri G. Kanatzidis +1
PbTe, one of the most promising thermoelectric materials, has recently demonstrated thermoelectric figure of merit () of above 2.0 when alloyed with group II elements. The impr…
Renormalized Lattice Dynamics and Thermal Transport in VO
Yi Xia, Maria K. Y. Chan
Vanadium dioxide (VO) undergoes a first-order metal-insulator transition (MIT) upon cooling near room temperature, concomitant with structural change from rutile to monoclini…
Evolutionary optimization of a charge transfer ionic potential model for Ta/Ta-oxide hetero-interfaces
Kiran Sasikumar, Badri Narayanan, Mathew Cherukara +5
Tantalum, tantalum oxide and their hetero-interfaces are of tremendous technological interest in several applications spanning electronics, thermal management, catalysis and bioche…
Unraveling the Planar-Globular Transition in Gold Nanoclusters through Evolutionary Search
Alper Kinaci, Badri Narayanan, Fatih G. Sen +4
Au nanoclusters are of technological relevance for catalysis, photonics, sensors, and of fundamental scientific interest owing to planar to globular structural transformation at an…
Describing the diverse geometries of gold from nanoclusters to bulk-- a first-principles based hybrid bond order potential
Badri Narayanan, Alper Kinaci, Fatih G. Sen +4
Molecular dynamics simulations using empirical force fields (EFFs) are crucial for gaining fundamental insights into atomic structure and long timescale dynamics of Au nanoclusters…