Ensemble Monte Carlo and DFPT simulation data for charge transport and gas sensing in monolayer MoS2

This dataset holds the simulation data behind the paper "Multiscale ensemble Monte Carlo of transport and gas sensing in monolayer MoS2". It contains the ensemble Monte Carlo (EMC) transport outputs, the drivers and parameter files that produced them, and the first-principles (DFPT) calculations that parameterise the model.

Context and methodology

• Computational device physics: charge transport and gas sensing in two-dimensional semiconductors.
• It provides the simulation data and inputs underpinning the associated paper.
• Transport data come from ensemble Monte Carlo simulations (ViennaEMC framework) with a model of the K valleys and the two spin-orbit-split sets of Q valleys.
• Every intrinsic parameter of that model is computed for this work with density-functional perturbation theory (Quantum ESPRESSO 7.3.1, PBE), by two independent routes, direct electron-phonon matrix elements at 34 explicit phonon wavevectors, and Wannier interpolation with EPW, which also provides the linearised Boltzmann solution against which the model is checked.

Technical details

• Everything is uploaded as a single archive. It extracts to one folder with three parts: emc/ (transport outputs, the 17-point self-consistent device sweep, and the C++ drivers and parameter headers that produced them), dfpt/ (the first-principles calculations, namely electron-phonon couplings at 34 wavevectors, the Wannier interpolation and Boltzmann-solution files, the K-Q valley separation study, and the adsorbate relaxations for NO2, NH3 and O2), and scripts/ (the Python scripts that turn the outputs into the figures of the paper).
• Data files are plain text, whitespace-delimited, each with a # header naming its columns and units. The binary files are Quantum ESPRESSO dynamical matrices and matrix-element files, and some large outputs are gzipped. Both are documented in the READMEs.
• Reading the data needs only a text viewer or Python with NumPy. Rerunning the decks needs the ViennaEMC framework, and repeating the first-principles work needs Quantum ESPRESSO 7.3.1 with the PseudoDojo norm-conserving PBE pseudopotentials, EPW 5.8 and Wannier90 3.1. The charge-transfer analysis also uses the Bader program of Henkelman et al.
• A README at the top level documents every file, with further READMEs in dfpt/couplings/ and dfpt/inputs/. The framework and example decks are at https://github.com/ViennaTools/ViennaEMC.

Further details

• The record contains the authors' own simulation data, with one exception. Two small files hold points extracted from the published figures of Liu et al. (2014) [https://doi.org/10.1021/nn5015215] and Late et al. (2013) [https://doi.org/10.1021/nn400026u], so that the comparison figures can be reproduced, and those measurements belong to the cited publications. Other comparison data used in the paper (Ahn 2017 [https://doi.org/10.1038/s41598-017-04350-z], Kumar 2025 [https://doi.org/10.1016/j.chphi.2025.100847] and others) are not redistributed.
• Quantum ESPRESSO wavefunction scratch, charge-density cubes and the frozen-strain deformation-potential runs are excluded, being regenerable from the decks and not needed to reproduce the provided data.