arXiv subjects

Sara Shabani

Publications and source records attributed to Sara Shabani.

14 recordsLinked to original sources

arXiv2025

Invading activity fronts stabilize excitable systems against stochastic extinction

Stochastic chemical reaction or population dynamics in finite systems often terminates in an absorbing state. Yet in large spatially extended systems, the time to reach species extinction (or fixation) becomes exceedingly long. Tuning control parameters may diminish the survival probability, rendering species coexistence susceptible to stochastic extinction events. In inhomogeneous settings, where a vulnerable subsystem is diffusively coupled to an adjacent stable patch, the former is reanimated through continuous influx from the interfaces, provided the absorbing region sustains spreading activity fronts. We demonstrate this generic elimination of finite-size extinction instabilities via immigration flux in predator-prey, epidemic spreading, and cyclic competition models.

q-bio.PE↗

arXiv2025

Tweets vs Pathogen Spread: A Case Study of COVID-19 in American States

The concept of the mutual influence that awareness and disease may exert on each other has recently presented significant challenges. The actions individuals take to prevent contracting a disease and their level of awareness can profoundly affect the dynamics of its spread. Simultaneously, disease outbreaks impact how people become aware. In response, we initially propose a null model that couples two Susceptible-Infectious-Recovered (SIR) dynamics and analyze it using a mean-field approach. Subsequently, we explore the parameter space to quantify the effects of this mutual influence on various observables. Finally, based on this null model, we conduct an empirical analysis of Twitter data related to COVID-19 and confirmed cases within American states. Our findings indicate that in specific regions of the parameter space, it is possible to suppress the epidemic by increasing awareness, and we investigate phase transitions. Furthermore, our model demonstrates the ability to alter the dominant population group by adjusting parameters throughout the course of the outbreak. Additionally, using the model, we assign a set of parameters to each state, revealing that these parameters change at different pandemic peaks. Notably, a robust correlation emerges between the ranking of states' Twitter activity, as gathered from empirical data, and the immunity parameters assigned to each state using our model. This observation underscores the pivotal role of sustained awareness transitioning from the initial to the subsequent peaks in the disease progression.

cs.SI↗

arXiv2024

Deep learning analysis of polaritonic waves images

Deep learning (DL) is an emerging analysis tool across sciences and engineering. Encouraged by the successes of DL in revealing quantitative trends in massive imaging data, we applied this approach to nano-scale deeply sub-diffractional images of propagating polaritonic waves in complex materials. We developed a practical protocol for the rapid regression of images that quantifies the wavelength and the quality factor of polaritonic waves utilizing the convolutional neural network (CNN). Using simulated near-field images as training data, the CNN can be made to simultaneously extract polaritonic characteristics and materials parameters in a timescale that is at least three orders of magnitude faster than common fitting/processing procedures. The CNN-based analysis was validated by examining the experimental near-field images of charge-transfer plasmon polaritons at Graphene/α-RuCl3 interfaces. Our work provides a general framework for extracting quantitative information from images generated with a variety of scanning probe methods.

cond-mat.mtrl-sci↗

arXiv2024

Uniaxial plasmon polaritons $\textit{via}$ charge transfer at the graphene/CrSBr interface

Graphene is a privileged 2D platform for hosting confined light-matter excitations known as surface plasmon-polaritons (SPPs), as it possesses low intrinsic losses with a high degree of optical confinement. However, the inherently isotropic optical properties of graphene limit its ability to guide and focus SPPs, making it less suitable than anisotropic elliptical and hyperbolic materials as a platform for polaritonic lensing and canalization. Here, we present the graphene/CrSBr heterostructure as an engineered 2D interface that hosts highly anisotropic SPP propagation over a wide range of frequencies in the mid-infrared and terahertz. Using a combination of scanning tunneling microscopy (STM), scattering-type scanning near-field optical microscopy (s-SNOM), and first-principles calculations, we demonstrate mutual doping in excess of 10$^{13}$ cm$^{-2}$ holes/electrons between the interfacial layers of graphene/CrSBr heterostructures. SPPs in graphene activated by charge transfer interact with charge-induced anisotropic intra- and interband transitions in the interfacial doped CrSBr, leading to preferential SPP propagation along the quasi-1D chains that compose each CrSBr layer. This multifaceted proximity effect both creates SPPs and endows them with anisotropic transport and propagation lengths that differ by an order-of-magnitude between the two in-plane crystallographic axes of CrSBr.

cond-mat.mes-hall↗

arXiv2024

Low-Energy Electronic Structure in the Unconventional Charge-Ordered State of ScV$_6$Sn$_6$

Kagome vanadates {\it A}V$_3$Sb$_5$ display unusual low-temperature electronic properties including charge density waves (CDW), whose microscopic origin remains unsettled. Recently, CDW order has been discovered in a new material ScV$_6$Sn$_6$, providing an opportunity to explore whether the onset of CDW leads to unusual electronic properties. Here, we study this question using angle-resolved photoemission spectroscopy (ARPES) and scanning tunneling microscopy (STM). The ARPES measurements show minimal changes to the electronic structure after the onset of CDW. However, STM quasiparticle interference (QPI) measurements show strong dispersing features related to the CDW ordering vectors. A plausible explanation is the presence of a strong momentum-dependent scattering potential peaked at the CDW wavevector, associated with the existence of competing CDW instabilities. Our STM results further indicate that the bands most affected by the CDW are near vHS, analogous to the case of {\it A}V$_3$Sb$_5$ despite very different CDW wavevectors.

cond-mat.str-el↗

arXiv2023

Fair coins tend to land on the same side they started: Evidence from 350,757 flips

Many people have flipped coins but few have stopped to ponder the statistical and physical intricacies of the process. We collected $350{,}757$ coin flips to test the counterintuitive prediction from a physics model of human coin tossing developed by Diaconis, Holmes, and Montgomery (DHM; 2007). The model asserts that when people flip an ordinary coin, it tends to land on the same side it started -- DHM estimated the probability of a same-side outcome to be about 51\%. Our data lend strong support to this precise prediction: the coins landed on the same side more often than not, $\text{Pr}(\text{same side}) = 0.508$, 95\% credible interval (CI) [$0.506$, $0.509$], $\text{BF}_{\text{same-side bias}} = 2359$. Furthermore, the data revealed considerable between-people variation in the degree of this same-side bias. Our data also confirmed the generic prediction that when people flip an ordinary coin -- with the initial side-up randomly determined -- it is equally likely to land heads or tails: $\text{Pr}(\text{heads}) = 0.500$, 95\% CI [$0.498$, $0.502$], $\text{BF}_{\text{heads-tails bias}} = 0.182$. Furthermore, this lack of heads-tails bias does not appear to vary across coins. Additional analyses revealed that the within-people same-side bias decreased as more coins were flipped, an effect that is consistent with the possibility that practice makes people flip coins in a less wobbly fashion. Our data therefore provide strong evidence that when some (but not all) people flip a fair coin, it tends to land on the same side it started.

math.HO↗

arXiv2022

High-Throughput $\textit{Ab Initio}$ Design of Atomic Interfaces using InterMatch

Forming a hetero-interface is a materials-design strategy that can access an astronomically large phase space. However, the immense phase space necessitates a high-throughput approach for optimal interface design. Here we introduce a high-throughput computational framework, InterMatch, for efficiently predicting charge transfer, strain, and superlattice structure of an interface by leveraging the databases of individual bulk materials. Specifically, the algorithm reads in the lattice vectors, density of states, and the stiffness tensors for each material in their isolated form from the Materials Project. From these bulk properties, InterMatch estimates the interfacial properties. We benchmark InterMatch predictions for the charge transfer against experimental measurements and supercell density-functional theory calculations. We then use InterMatch to predict promising interface candidates for doping transition metal dichalcogenide MoSe$_2$. Finally, we explain experimental observation of factor of 10 variation in the supercell periodicity within a few microns in graphene/$α$-RuCl$_3$ by exploring low energy superlattice structures as a function of twist angle using InterMatch. We anticipate our open-source InterMatch algorithm accelerating and guiding ever-growing interfacial design efforts. Moreover, the interface database resulting from the InterMatch searches presented in this paper can be readily accessed through https://contribs.materialsproject.org/projects/intermatch/ .

cond-mat.mtrl-sci↗

arXiv2022

Ultra Localized Optoelectronic Properties of Nanobubbles in 2D Semiconductors

The optical properties of transition metal dichalcogenides have previously been modified at the nanoscale by using mechanical and electrical nanostructuring. However, a clear experimental picture relating the local electronic structure with emission properties in such structures has so far been lacking. Here, we use a combination of scanning tunneling microscopy (STM) and near-field photoluminescence (nano-PL) to probe the electronic and optical properties of single nano-bubbles in bilayer heterostructures of WSe2 on MoSe2. We show from tunneling spectroscopy that there are electronic states deeply localized in the gap at the edge of such bubbles, which are independent of the presence of chemical defects in the layers. We also show a significant change in the local bandgap on the bubble, with a continuous evolution to the edge of the bubble over a length scale of ~20 nm. Nano-PL measurements observe a continuous redshift of the interlayer exciton on entering the bubble, in agreement with the band to band transitions measured by STM. We use self-consistent Schrödinger-Poisson (SP) simulations to capture the essence of the experimental results and find that strong doping in the bubble region is a key ingredient to achieving the observed localized states, together with mechanical strain.

cond-mat.mes-hall↗

arXiv2022

Unconventional Charge-density-wave Order in a Dilute d-band Semiconductor

Electron-lattice coupling effects in low dimensional materials give rise to charge density wave (CDW) order and phase transitions. These phenomena are critical ingredients for superconductivity and predominantly occur in metallic model systems such as doped cuprates, transition metal dichalcogenides, and more recently, in Kagome lattice materials. However, CDW in semiconducting systems, specifically at the limit of low carrier concentration region, is uncommon. Here, we combine electrical transport, synchrotron X-ray diffraction and optical spectroscopy to discover CDW order in a quasi-one-dimensional (1D), dilute d-band semiconductor, BaTiS3, which suggests the existence of strong electron-phonon coupling. The CDW state further undergoes an unusual transition featuring a sharp increase in carrier mobility. Our work establishes BaTiS3 as a unique platform to study the CDW physics in the dilute filling limit to explore novel electronic phases.

cond-mat.mtrl-sci↗

arXiv2022

Machine Learning for Optical Scanning Probe Nanoscopy

The ability to perform nanometer-scale optical imaging and spectroscopy is key to deciphering the low-energy effects in quantum materials, as well as vibrational fingerprints in planetary and extraterrestrial particles, catalytic substances, and aqueous biological samples. The scattering-type scanning near-field optical microscopy (s-SNOM) technique has recently spread to many research fields and enabled notable discoveries. In this brief perspective, we show that the s-SNOM, together with scanning probe research in general, can benefit in many ways from artificial intelligence (AI) and machine learning (ML) algorithms. We show that, with the help of AI- and ML-enhanced data acquisition and analysis, scanning probe optical nanoscopy is poised to become more efficient, accurate, and intelligent.

physics.optics↗

arXiv2021

Nanometer-scale lateral p-n junctions in graphene/$α$-RuCl$_3$ heterostructures

The ability to create high-quality lateral p-n junctions at nanometer length scales is essential for the next generation of two-dimensional (2D) electronic and plasmonic devices. Using a charge-transfer heterostructure consisting of graphene on $α$-RuCl$_3$, we conduct a proof-of-concept study demonstrating the existence of intrinsic nanoscale lateral p-n junctions in the vicinity of graphene nanobubbles. Our multi-pronged experimental approach incorporates scanning tunneling microscopy (STM) and spectroscopy (STS) and scattering-type scanning near-field optical microscopy ($\textit{s}$-SNOM) in order to simultaneously probe both the electronic and optical responses of nanobubble p-n junctions. Our STM and STS results reveal that p-n junctions with a band offset of more than 0.6 eV can be achieved over lateral length scale of less than 3 nm, giving rise to a staggering effective in-plane field in excess of 10$^8$ V/m. Concurrent $\textit{s}$-SNOM measurements confirm the utility of these nano-junctions in plasmonically-active media, and validate the use of a point-scatterer formalism for modeling surface plasmon polaritons (SPPs). Model $\textit{ab initio}$ density functional theory (DFT) calculations corroborate our experimental data and reveal a combination of sub-angstrom and few-angstrom decay processes dictating the dependence of charge transfer on layer separation. Our study provides experimental and conceptual foundations for the use of charge-transfer interfaces such as graphene/$α$-RuCl$_3$ to generate p-n nano-junctions.

cond-mat.mes-hall↗

arXiv2021

Hidden low-temperature magnetic order revealed through magnetotransport in monolayer CrSBr

Magnetic semiconductors are a powerful platform for understanding, utilizing and tuning the interplay between magnetic order and electronic transport. Compared to bulk crystals, two-dimensional magnetic semiconductors have greater tunability, as illustrated by the gate modulation of magnetism in exfoliated CrI$_3$ and Cr$_2$Ge$_2$Te$_6$, but their electrically insulating properties limit their utility in devices. Here we report the simultaneous electrostatic and magnetic control of electronic transport in atomically-thin CrSBr, an A-type antiferromagnetic semiconductor. Through magnetotransport measurements, we find that spin-flip scattering from the interlayer antiferromagnetic configuration of multilayer flakes results in giant negative magnetoresistance. Conversely, magnetoresistance of the ferromagnetic monolayer CrSBr vanishes below the Curie temperature. A second transition ascribed to the ferromagnetic ordering of magnetic defects manifests in a large positive magnetoresistance in the monolayer and a sudden increase of the bulk magnetic susceptibility. We demonstrate this magnetoresistance is tunable with an electrostatic gate, revealing that the ferromagnetic coupling of defects is carrier mediated.

cond-mat.mes-hall↗

arXiv2020

Moiré metrology of energy landscapes in van der Waals heterostructures

The emerging field of twistronics, which harnesses the twist angle between two-dimensional materials, represents a promising route for the design of quantum materials, as the twist-angle-induced superlattices offer means to control topology and strong correlations. At the small twist limit, and particularly under strain, as atomic relaxation prevails, the emergent moiré superlattice encodes elusive insights into the local interlayer interaction. Here we introduce moiré metrology as a combined experiment-theory framework to probe the stacking energy landscape of bilayer structures at the 0.1 meV/atom scale, outperforming the gold-standard of quantum chemistry. Through studying the shapes of moiré domains with numerous nano-imaging techniques, and correlating with multi-scale modelling, we assess and refine first-principle models for the interlayer interaction. We document the prowess of moiré metrology for three representative twisted systems: bilayer graphene, double bilayer graphene and H-stacked $MoSe_2/WSe_2$. Moiré metrology establishes sought after experimental benchmarks for interlayer interaction, thus enabling accurate modelling of twisted multilayers.

cond-mat.mes-hall↗

arXiv2020

Deep moiré potentials in twisted transition metal dichalcogenide bilayers

In twisted bilayers of semiconducting transition metal dichalcogenides (TMDs), a combination of structural rippling and electronic coupling gives rise to periodic moiré potentials that can confine charged and neutral excitations. Here, we report experimental measurements of the structure and spectroscopic properties of twisted bilayers of WSe2 and MoSe2 in the H-stacking configuration using scanning tunneling microscopy (STM). Our experiments reveal that the moiré potential in these bilayers at small angles is unexpectedly large, reaching values of above 300 meV for the valence band and 150 meV for the conduction band - an order of magnitude larger than theoretical estimates based on interlayer coupling alone. We further demonstrate that the moiré potential is a non-monotonic function of moiré wavelength, reaching a maximum at around a 13nm moiré period. This non-monotonicity coincides with a drastic change in the structure of the moiré pattern from a continuous variation of stacking order at small moiré wavelengths to a one-dimensional soliton dominated structure at large moiré wavelengths. We show that the in-plane structure of the moiré pattern is captured well by a continuous mechanical relaxation model, and find that the moiré structure and internal strain rather than the interlayer coupling is the dominant factor in determining the moiré potential. Our results demonstrate the potential of using precision moiré structures to create deeply trapped carriers or excitations for quantum electronics and optoelectronics.

cond-mat.mes-hall↗