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Preprint

Wave-Packet Transport in Graphene Under Asymmetric Electrostatic Arrays: Geometry-Tunable Confinement

Khakimjan ButanovInstitute of Materials Science , Uzbekistan Academy of Sciences , Tashkent 100084 , UzbekistanMaksudbek BaydjanovTashkent International University of Education , 31 Imam Bukhariy St. , Tashkent 100207 , UzbekistanHammid YusupovKimyo International University in Tashkent , 156 Shota Rustaveli St. , Tashkent 100121 , UzbekistanKomiljon BobojonovUrgench State University named after Abu Rayhan Biruni , 14 Kh. Alimdjan St , Urgench 220100 , UzbekistanMaksudbek YusupovTashkent State Technical University , Tashkent 100095 , UzbekistanAndrey ChavesUniversidade Federal do Ceará , Caixa Postal 6030 , Campus do Pici , 60455-900 Fortaleza , Ceará , BrazilKh. Yu. RakhimovInstitute of Materials Science , Uzbekistan Academy of Sciences , Tashkent 100084 , Uzbekistan
2025
ABI

Annotatsiya

We investigate time-resolved wave-packet transport in monolayer graphene patterned with asymmetric arrays of circular electrostatic scatterers. Using the Dirac continuum model with a split-operator scheme, we track how transmission evolves with scatterer radius and polarity sequence. To this end, we consider three potential configurations (Samples 1–3). The results reveal a geometry-controlled crossover from near-ballistic propagation at small radii to interference-dominated backscattering at large radii. Sample 1, where the potential exhibit two parallel lines of circles, each line sharing the same potential sign, preserves the highest transmission. Conversely, in Sample 3, where potential signs are intercalated between circles of the same line, the dwell time increases, which produces stronger confinement. As the radius increases, pronounced temporal oscillations emerge due to repeated internal reflections (similar to Fabry–Pérot), and the radius dependence of the saturated transmission probability exhibits anti-resonant dips that are tunable by geometry and potential magnitude. These behaviors establish simple design rules for graphene nanodevices: small-radius Sample 1 for high-throughput transport, Sample 2 (with inverted potential signs as compared to Sample 1) for broadband suppression, and Sample 3 for finely tunable, interference-based confinement.

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