Tritsaris GA, Şensoy MG, Shirodkar SN, Kaxiras E.

First-principles study of coupled effect of ripplocations and S-vacancies in MoS2. Journal of Applied Physics. 2019;126 (8) :084303.

Klein DR, MacNeill D, Song Q, Larson DT, Fang S, Xu M, Ribeiro RA, Canfield PC, Kaxiras E, Comin R, et al. Enhancement of interlayer exchange in an ultrathin two-dimensional magnet. Nature Physics. 2019;15 (12) :1255–1260.

Neofotistos GN, M.Mattheakis, Barbaris G, Hitzanidi J, Tsironis GP, Kaxiras E.

Machine learning with observers predicts complex spatiotemporal behavior. Front. Phys. - Quantum Computing. 2019;7 (24) :1-9.

Publisher's VersionAbstractChimeras and branching are two archetypical complex phenomena that appear in many physical systems; because of their different intrinsic dynamics, they delineate opposite non-trivial limits in the complexity of wave motion and present severe challenges in predicting chaotic and singular behavior in extended physical systems. We report on the long-term forecasting capability of Long Short-Term Memory (LSTM) and reservoir computing (RC) recurrent neural networks, when they are applied to the spatiotemporal evolution of turbulent chimeras in simulated arrays of coupled superconducting quantum interference devices (SQUIDs) or lasers, and branching in the electronic flow of two-dimensional graphene with random potential. We propose a new method in which we assign one LSTM network to each system node except for {\textquotedblleft}observer{\textquotedblright} nodes which provide continual {\textquotedblleft}ground truth{\textquotedblright} measurements as input; we refer to this method as {\textquotedblleft}Observer LSTM{\textquotedblright} (OLSTM). Wedemonstrate that even a small number of observers greatly improves the data-driven (model-free) long-term forecasting capability of the LSTM networks and provide the framework for a consistent comparison between the RC and LSTM methods. We find that RC requires smaller training datasets than OLSTMs, but the latter require fewer observers. Both methods are benchmarked against Feed-Forward neural networks (FNNs), also trained to make predictions with observers (OFNNs).

Maier M, M.Mattheakis, Kaxiras E, Luskin M, Margetis D.

Homogenization of plasmonic crystals: Seeking the epsilon-near-zero behavior. Proceedings of the Royal Society A. 2019;475 (2230).

Publisher's VersionAbstractBy using an asymptotic analysis and numerical simulations, we derive and investigate a system of homogenized Maxwell{\textquoteright}s equations for conducting material sheets that are periodically arranged and embedded in a heterogeneous and anisotropic dielectric host.\ This structure is motivated by the need to design plasmonic crystals that enable the propagation of electromagnetic waves with no phase delay (epsilon-near-zero effect). Our microscopic model incorporates the surface conductivity of the two-dimensional (2D) material of each sheet and a corresponding line charge density through a line conductivity along possible edges of the sheets. Our analysis generalizes averaging principles inherent in previous Bloch-wave approaches. We investigate physical implications of our findings. In particular, we emphasize the role of the vector-valued corrector field, which expresses microscopic modes of surface waves on the 2D material. By using a Drude model for the surface conductivity of the sheet, we construct a Lorentzian function that describes the effective dielectric permittivity tensor of the plasmonic crystal as a function of frequency.

2018_homogenization_1809.08276.pdf Choukroun J, Pala M, Fang S, Kaxiras E, Dollfus P.

High performance tunnel field effect transistors based on in-plane transition metal dichalcogenide heterojunctions. NANOTECHNOLOGY. 2019;30 (2).

AbstractIn-plane heterojunction tunnel field effect transistors based on monolayer transition metal dichalcogenides are studied by means of self-consistent non-equilibrium Green's functions simulations and an atomistic tight-binding Hamiltonian. We start by comparing several heterojunctions before focusing on the most promising ones, i.e. WTe2-MoS2 and MoTe2-MoS2. The scalability of those devices as a function of channel length is studied, and the influence of backgate voltages on device performance is analyzed. Our results indicate that, by fine-tuning the design parameters, those devices can yield extremely low subthreshold swings (<5 mV/decade) and I-ON/I-OFF ratios higher than 10(8) at a supply voltage of 0.3 V, making them ideal for ultra-low power consumption.

Ma Q, Xu S-Y, Shen H, MacNeill D, Fatemi V, Chang T-rong, Valdivia AMM, Wu S, Du Z, Hsu C-H, et al. Observation of the nonlinear Hall effect under time-reversal-symmetric conditions. NATURE. 2019;565 (7739) :337+.

AbstractThe electrical Hall effect is the production, upon the application of an electric field, of a transverse voltage under an out-of-plane magnetic field. Studies of the Hall effect have led to important breakthroughs, including the discoveries of Berry curvature and topological Chern invariants(1,2). The internal magnetization of magnets means that the electrical Hall effect can occur in the absence of an external magnetic field(2); this `anomalous' Hall effect is important for the study of quantum magnets(2-7). The electrical Hall effect has rarely been studied in non-magnetic materials without external magnetic fields, owing to the constraint of timer-eversal symmetry. However, only in the linear response regime-when the Hall voltage is linearly proportional to the external electric field-does the Hall effect identically vanish as a result of time-reversal symmetry; the Hall effect in the nonlinear response regime is not subject to such symmetry constraints(8-10). Here we report observations of the nonlinear Hall effect(10) in electrical transport in bilayers of the non-magnetic quantum material WTe2 under time-reversal-symmetric conditions. We show that an electric current in bilayer WTe2 leads to a nonlinear Hall voltage in the absence of a magnetic field. The properties of this nonlinear Hall effect are distinct from those of the anomalous Hall effect in metals: the nonlinear Hall effect results in a quadratic, rather than linear, current-voltage characteristic and, in contrast to the anomalous Hall effect, the nonlinear Hall effect results in a much larger transverse than longitudinal voltage response, leading to a nonlinear Hall angle (the angle between the total voltage response and the applied electric field) of nearly 90 degrees. We further show that the nonlinear Hall effect provides a direct measure of the dipole moment(10) of the Berry curvature, which arises from layer-polarized Dirac fermions in bilayer WTe2. Our results demonstrate a new type of Hall effect and provide a way of detecting Berry curvature in nonmagnetic quantum materials.