Raman Mapping of Single-walled Carbon Nanotube Distribution on Phase Separated Polystyrene and Polymethylmethacrylate
Applications | 2009 | Thermo Fisher ScientificInstrumentation
Mapping the distribution of polymers and nanomaterials at the micron scale is critical in optimizing advanced coatings, composite interfaces and electronic devices. Raman imaging provides a non‐destructive approach to visualize phase separation in polymer blends and to locate carbon nanotubes with high spatial resolution, enabling precise material characterization in research and quality control contexts.
This study aimed to demonstrate the use of dispersive Raman mapping to:
The analysis employed the Thermo Scientific Nicolet Almega XR dispersive Raman spectrometer configured with a 532 nm laser and research-grade microscope. Spectral maps were collected using the OMNIC™ Atlµs™ software, with point exposures of 8 s and step sizes down to 1 µm. Key spectral bands monitored included the 1605 cm−1 PS C–C stretch and characteristic SWCNT features (G band at ~1598 cm−1, D band at ~1327 cm−1 and radial breathing modes at 185–267 cm−1).
Chemical imaging of the 1605 cm−1 band revealed PS domains (red/yellow/green) interspersed with PMMA regions (blue). Overlay of chemical and visual images confirmed spatial distribution across 10–50 µm features. Spectral correlation mapping against an SWCNT reference spectrum identified nanotube aggregates primarily on PS, with correlation coefficients approaching unity in red-coded zones. Quantitative image analysis indicated ~38 % surface coverage by PS and ~5 % by SWCNTs within the mapped area.
Dispersive Raman mapping offers:
This method supports material development in coatings, electronics, composites and quality assurance of surface treatments.
Emerging directions include:
Dispersive Raman spectroscopy combined with chemical mapping and image analysis provides a powerful toolkit for characterizing polymer phase separation and carbon nanotube deposition on substrates. The approach yields spatially resolved, quantitative data critical for materials research and industrial applications.
RAMAN Spectroscopy, Microscopy
IndustriesMaterials Testing
ManufacturerThermo Fisher Scientific
Summary
Significance of the Topic
Mapping the distribution of polymers and nanomaterials at the micron scale is critical in optimizing advanced coatings, composite interfaces and electronic devices. Raman imaging provides a non‐destructive approach to visualize phase separation in polymer blends and to locate carbon nanotubes with high spatial resolution, enabling precise material characterization in research and quality control contexts.
Objectives and Study Overview
This study aimed to demonstrate the use of dispersive Raman mapping to:
- Confirm phase separation of vapor-deposited polystyrene (PS) and polymethylmethacrylate (PMMA) on silicon substrates.
- Determine the preferential deposition and coverage of single-walled carbon nanotubes (SWCNTs) on the PS/PMMA patterned surface.
Methodology and Instrumentation
The analysis employed the Thermo Scientific Nicolet Almega XR dispersive Raman spectrometer configured with a 532 nm laser and research-grade microscope. Spectral maps were collected using the OMNIC™ Atlµs™ software, with point exposures of 8 s and step sizes down to 1 µm. Key spectral bands monitored included the 1605 cm−1 PS C–C stretch and characteristic SWCNT features (G band at ~1598 cm−1, D band at ~1327 cm−1 and radial breathing modes at 185–267 cm−1).
Instrumentation Used
- Nicolet Almega XR dispersive Raman spectrometer
- 532 nm visible laser excitation
- OMNIC Atlµs mapping software
- DXR Raman microscope for precise laser power control
Results and Discussion
Chemical imaging of the 1605 cm−1 band revealed PS domains (red/yellow/green) interspersed with PMMA regions (blue). Overlay of chemical and visual images confirmed spatial distribution across 10–50 µm features. Spectral correlation mapping against an SWCNT reference spectrum identified nanotube aggregates primarily on PS, with correlation coefficients approaching unity in red-coded zones. Quantitative image analysis indicated ~38 % surface coverage by PS and ~5 % by SWCNTs within the mapped area.
Benefits and Practical Applications
Dispersive Raman mapping offers:
- Sub-micron spatial resolution for detailed phase morphology studies.
- Non-destructive analysis without reflective substrates.
- Simultaneous chemical and distribution data for polymer blends and nanomaterials.
This method supports material development in coatings, electronics, composites and quality assurance of surface treatments.
Future Trends and Opportunities
Emerging directions include:
- Integration of multivariate analysis (PCA, MCR) for enhanced component separation.
- 3D Raman tomography to probe subsurface distributions.
- Real-time, in situ mapping during film growth or processing.
- Automated image analysis workflows for high-throughput screening.
Conclusion
Dispersive Raman spectroscopy combined with chemical mapping and image analysis provides a powerful toolkit for characterizing polymer phase separation and carbon nanotube deposition on substrates. The approach yields spatially resolved, quantitative data critical for materials research and industrial applications.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
Similar PDF
Building Better Batteries: Raman Spectroscopy – An Essential Tool for Evaluating New Lithium Ion Battery Components
|Thermo Fisher Scientific|Presentations
Building Better Batteries: Raman Spectroscopy – An Essential Tool for Evaluating New Lithium Ion Battery Components Robert Heintz, Ph.D. Senior Applications Specialist Thermo Fisher Scientific [email protected] Presentation Overview • Lithium-Ion Batteries • Why the interest in lithium ion batteries •…
Key words
raman, ramanlithium, lithiumgraphene, graphenespectroscopy, spectroscopybatteries, batteriesbattery, batterymaterials, materialsanode, anodecycling, cyclingint, intcarbon, carbonband, bandion, iondxr, dxrhybrid
Microscope Mapping on Formulated Pharmaceutical Samples Using the Dispersive Raman Technique
2008|Thermo Fisher Scientific|Applications
Technical Note: 50835 Key Words • Dispersive Raman • Identification • Microscopy • Pharmaceutical • Spectral Mapping Imaging Microscope Mapping on Formulated Pharmaceutical Samples Using the Dispersive Raman Technique Introduction Composition of a Tablet Product characterization, such as component identification,…
Key words
spectrum, spectrumraman, ramansubtraction, subtractiondispersive, dispersivespectral, spectralmapping, mappingpharmaceutical, pharmaceuticaltablet, tabletaspirin, aspirinmap, mapdistribution, distributionacetaminophen, acetaminophennicolet, nicoletmicroscope, microscopespatial
Characterization of single-walled carbon nanotubes by Raman spectroelectrochemistry
2019|Metrohm|Applications
AN-RA-005 Characterization of single-walled carbon nanotubes by Raman spectroelectrochemistry Summary Spectroelectrochemistry is a multi-response technique that provides electrochemical and spectroscopic information about a chemical system in a single experiment, i.e., it offers information from two different points of view. Raman…
Key words
raman, ramannanotubes, nanotubesmetrohm, metrohmwalled, walledspectroelectrochemistry, spectroelectrochemistryspelecraman, spelecramancarbon, carbonspelec, spelecspectroelectrochemical, spectroelectrochemicalintensity, intensityhove, hovesingularities, singularitieselectrochemical, electrochemicalcharacterization, characterizationsingle
Calibrationless Semi-Quantitative Analysis of a Heterogeneous Sample Using Raman Microscope Mapping
2009|Thermo Fisher Scientific|Applications
Application Note: 51184 Calibrationless Semi-Quantitative Analysis of a Heterogeneous Sample Using Raman Microscope Mapping Koichi Nishikida, Steve Lowry, Thermo Fisher Scientific, Madison, WI, USA Introduction Key Words • Calibrationless Semi-quantitative Analysis • Heterogeneous Sample • Imaging Analysis • Multivariate Curve…
Key words
calibrationless, calibrationlessraman, ramanatlµs, atlµsimage, imagetablet, tabletmcr, mcrheterogeneous, heterogeneousmapping, mappingmaps, mapsomnic, omnicsemi, semicomponents, componentsalmega, almegausing, usingquantitative