Unlocking the electronic and adsorption origin of doping-engineered WS2 monolayers: a DFT investigation with machine learning validation
9 affiliations
- 1Laboratory for Computational Physics, Institute for Computational Science and Artificial Intelligence, Van Lang University Ho Chi Minh City Vietnam
- 2Faculty of Mechanical, Electrical, and Computer Engineering, Van Lang School of Technology, Van Lang University Ho Chi Minh City Vietnam
- 3School of Natural Sciences, Can Tho University Can Tho City Vietnam
- 4Faculty of Basic Sciences, Nam Can Tho University Can Tho City Vietnam
- 5Institute of Theoretical and Applied Research, Duy Tan University Ha Noi 100000 Vietnam
- 6School of Engineering and Technology, Duy Tan University Da Nang 550000 Vietnam
- 7Faculty of Science and Technology, Jan Długosz University Armii Krajowej 13/15 42-200 Częstochowa Poland
- 8Frantsevich Institute for Problems of Materials Science, National Academy of Sciences of Ukraine 3 Omeljan Pritsak Street Kyiv 03142 Ukraine
- 9Department of Chemical System Engineering, School of Engineering, The University of Tokyo Japan
Abstract
Defect-engineered tungsten disulfide (WS2) monolayers provide a tunable platform for clarifying how local dopant chemistry that converts weak gas adsorption into measurable electronic perturbation. Here, N-doped and N–O co-doped WS2 monolayers are investigated to decouple adsorption strength from electronic-response descriptors toward CO, CO2, and NH3 sensing. Machine learning force field (MLFF)-assisted DFT calculations show that MLFF reproduces the DFT energy–force relationships and phonon trends for pristine WS2 and N–WS2, whereas the larger deviations for N–O–WS2 indicate that co-doped configurations should be interpreted together with direct DFT descriptors. Complementary 10 ps ab initio Molecular Dynamics (AIMD) simulations further show bounded energy fluctuations without obvious thermal drift, supporting the finite-temperature stability of the optimized doped structures within the present simulation window. Pristine WS2 exhibits negligible gas-induced perturbation, including weak adsorption, long gas–surface distances, limited charge redistribution, and minor work-function changes. N and N–O substitutions distort the local W–S coordination environment and introduce dopant-derived states near the Fermi level, increasing surface polarizability. NH3 exhibits the strongest response in the doped WS2 due to lone-pair-induced polarization that significantly modulates the surface dipole. Although N–O–WS2 binds NH3 slightly more strongly, N–WS2–NH3 delivers the largest relative work-function response of 6.04%, indicating that adsorption strength and electronic sensitivity are distinct descriptors. Energy-resolved conductivity-sensitivity analysis identifies NH3 as the most effective electronic perturbant for the doped WS2 systems, although the dominant response maxima are offset from the Fermi level and therefore represent spectral modulation rather than directly accessible low-bias sensing performance. Picosecond recovery times indicate rapid reversible desorption but limited residence time. Overall, MLFF-assisted DFT identifies doped WS2 as a reversible weak-physisorption platform with preferential NH3 electronic response rather than a strongly adsorbing gas-sensor material.
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BibTeX
@article{nguyen2026unlocking,
title = {{Unlocking the electronic and adsorption origin of doping-engineered WS2 monolayers: a DFT investigation with machine learning validation}},
author = {Duy Khanh Nguyen and Minh Nguyen and Khiet An Vuong and Nguyen Hai Dang and D. M. Hoat and Vo Duy Dat and Oleg Khyzhun and Michal Piasecki and Minh-Thuan Pham},
journal = {RSC advances},
year = {2026},
month = oct,
doi = {10.1039/d6ra09476g},
url = {https://europepmc.org/article/PMC/PMC13721793},
note = {CC BY-NC},
}
RIS
TY - JOUR
TI - Unlocking the electronic and adsorption origin of doping-engineered WS2 monolayers: a DFT investigation with machine learning validation
AU - Duy Khanh Nguyen
AU - Minh Nguyen
AU - Khiet An Vuong
AU - Nguyen Hai Dang
AU - D. M. Hoat
AU - Vo Duy Dat
AU - Oleg Khyzhun
AU - Michal Piasecki
AU - Minh-Thuan Pham
PY - 2026
DA - 2026/10/30
JO - RSC advances
DO - 10.1039/d6ra09476g
UR - https://europepmc.org/article/PMC/PMC13721793
AB - Defect-engineered tungsten disulfide (WS2) monolayers provide a tunable platform for clarifying how local dopant chemistry that converts weak gas adsorption into measurable electronic perturbation. Here, N-doped and N–O co-doped WS2 monolayers are investigated to decouple adsorption strength from electronic-response descriptors toward CO, CO2, and NH3 sensing. Machine learning force field (MLFF)-assisted DFT calculations show that MLFF reproduces the DFT energy–force relationships and phonon trends for pristine WS2 and N–WS2, whereas the larger deviations for N–O–WS2 indicate that co-doped configurations should be interpreted together with direct DFT descriptors. Complementary 10 ps ab initio Molecular Dynamics (AIMD) simulations further show bounded energy fluctuations without obvious thermal drift, supporting the finite-temperature stability of the optimized doped structures within the present simulation window. Pristine WS2 exhibits negligible gas-induced perturbation, including weak adsorption, long gas–surface distances, limited charge redistribution, and minor work-function changes. N and N–O substitutions distort the local W–S coordination environment and introduce dopant-derived states near the Fermi level, increasing surface polarizability. NH3 exhibits the strongest response in the doped WS2 due to lone-pair-induced polarization that significantly modulates the surface dipole. Although N–O–WS2 binds NH3 slightly more strongly, N–WS2–NH3 delivers the largest relative work-function response of 6.04%, indicating that adsorption strength and electronic sensitivity are distinct descriptors. Energy-resolved conductivity-sensitivity analysis identifies NH3 as the most effective electronic perturbant for the doped WS2 systems, although the dominant response maxima are offset from the Fermi level and therefore represent spectral modulation rather than directly accessible low-bias sensing performance. Picosecond recovery times indicate rapid reversible desorption but limited residence time. Overall, MLFF-assisted DFT identifies doped WS2 as a reversible weak-physisorption platform with preferential NH3 electronic response rather than a strongly adsorbing gas-sensor material.
SN - 2046-2069
ER -