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Defect engineered 2D MoS2 materials for ML-enabled SERS detection of neurotransmitters
Md Arifur R Khan1, Besan Khader1, Nicholas Trainor2
1Department of Nanoscience, Joint School of Nanoscience and Nanoengineering, the University of North Carolina at Greensboro, Greensboro, NC, USA. t_ignato@uncg.edu.
Nanoscale
|July 20, 2026
Summary
Researchers developed a defect-engineered molybdenum disulfide (MoS₂) platform for sensitive neurotransmitter detection. This advanced material selectively identifies dopamine and epinephrine using surface-enhanced Raman spectroscopy (SERS) and machine learning.
Area of Science:
- Materials Science
- Nanotechnology
- Analytical Chemistry
- Biomedical Engineering
Background:
- Accurate neurotransmitter detection is crucial for understanding neurological processes and diagnosing diseases.
- Existing sensing platforms often lack the required sensitivity, selectivity, or cost-effectiveness for widespread application.
- Two-dimensional materials like molybdenum disulfide (MoS₂) offer unique electronic and optical properties for sensing applications.
Purpose of the Study:
- To investigate the mechanisms of neurotransmitter detection using a defect-engineered MoS₂ platform.
- To enhance the sensitivity and selectivity of surface-enhanced Raman spectroscopy (SERS) for neurotransmitter analysis.
- To develop a tunable, low-cost SERS platform for distinguishing structurally similar biomolecules.
Main Methods:
- Fabrication of defect-engineered MoS₂ monolayer films via soft plasma etching to introduce sulfur vacancies.
- Characterization of material quality using Raman spectroscopy, photoluminescence, atomic force microscopy (AFM), and X-ray photoelectron spectroscopy (XPS).
- Application of machine learning algorithms (PCA-LDA) for spectral analysis and analyte discrimination.
- Demonstration of SERS detection of catechol-containing neurotransmitters, specifically dopamine and epinephrine.
Main Results:
- Defect engineering, specifically sulfur vacancies in MoS₂, significantly enhanced the SERS effect and selective biomolecule docking.
- The MoS₂ sensor achieved sub-nanomolar detection limits (5 × 10⁻¹⁰ M) for dopamine and epinephrine with high calibration reliability (R² = 0.95-0.99).
- The sensor exhibited high specificity, showing no response to serotonin, confirming catechol-specific molecular adsorption.
- Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA) achieved 100% accuracy in distinguishing dopamine and epinephrine.
Conclusions:
- Defect-engineered MoS₂ serves as a highly sensitive and selective SERS platform for neurotransmitter detection.
- The introduction of sulfur vacancies is key to activating SERS through molecular charge transfer and enabling catechol-specific adsorption.
- This tunable, low-cost MoS₂ platform holds significant promise for future advanced sensing applications in neuroscience and diagnostics.
