arXiv subjects

Soumyadip Hazra

Publications and source records attributed to Soumyadip Hazra.

2 recordsLinked to original sources

arXiv2026

Investigating Sulfur Vacancy Passivation in Monolayer MoS2 FETs via Optically Coupled Low-Frequency Electrical Noise Spectroscopy

Transition metal dichalcogenide monolayers are promising materials for electronic and photonic applications, yet the performance of chemical vapour deposition grown films is severely limited by native sulphur vacancies that introduce mid-gap trap states, degrade carrier mobility, and elevate electrical noise. Here we investigate octane thiol passivation of sulphur vacancies in monolayer MoS2 field effect transistors, combining x-ray photoelectron spectroscopy, photoluminescence, and Raman scattering with electrical transport and optically coupled low-frequency noise spectroscopy. Thiol treatment reduces the sulphur vacancy concentration from 7.5% to 5%, which increases the channel resistance 35-fold while restoring gate switching with an on/off ratio of 10^4 and improving field-effect mobility from 1 to 5 cm^2/Vs. Low frequency noise spectroscopy directly quantifies the defect suppression: the Hooge parameter drops by more than two orders of magnitude after passivation. Gate-dependent noise confirms carrier mobility fluctuation as the dominant dark noise mechanism, while optical excitation drives a crossover to carrier number fluctuation dominated noise, reflecting preferential interaction of photogenerated carriers with residual vacancy states via generation-recombination trapping, a mechanistic distinction inaccessible to gate- bias measurements alone. Density functional theory calculations corroborate these findings, showing suppression of vacancy-induced mid-gap states by more than 50% and partial restoration of the intrinsic bandgap. These results establish optically coupled low-frequency noise spectroscopy as a sensitive, low-cost, and non-destructive tool for quantifying defect passivation in TMDC-based devices.

cond-mat.mtrl-sci↗

arXiv2026

Machine Learning Assisted Reconstruction of Local Electronic Structure of Non-Uniformly Strained MoS2

Wrinkles and nanobubbles are an integral and often unavoidable part of integrating 2D van der Waals semiconductors into actual device architectures. Despite their ubiquitous nature, quantitative correlation between such spatially non-uniform strain and modifications to the local electronic structure remains challenging. Here, density functional theory is combined with a recurrent neural network to reconstruct the local electronic structure of monolayer MoS2 from strain maps derived from atomic force microscopy (AFM) topography and Raman spectral maps. The analysis reveals that biaxial bending induced strain is significantly more effective than both uniaxial bending or in-plane strain in modifying electronic and dielectric properties. A ~ 0.35% strain induced by biaxial bending results in ~ 22% reduction in band gap and ~ 7% increase in dielectric constant, compared to a ~ 5% reduction in band gap and ~ 1% increase in dielectric constant under comparable uniaxial bending. The modified band structure reveals band edge states that concentrate charge in regions of high curvature or strain. While conductive AFM measurements indicate increased local conductance (carrier density) at wrinkles and nanobubbles, the spatial band gap maps predicted by the model are validated against experimental photoluminescence peak energy maps. The results indicate that strained features like wrinkles and nanobubbles commonly present in real devices influence the band gap, carrier distribution, and dielectric response, which favourably affects electrical transport in such systems. The framework developed here can be readily extended to other 2D materials and heterostructures, offering a computationally efficient route for studying and exploiting strain effects.

cond-mat.mtrl-sci↗