An Overview of Nanomaterial Characterization Methods

By Samudrapom DamReviewed by Lexie CornerOct 24 2024

Nanomaterial characterization involves analyzing the behavior, structure, and properties of materials at the nanoscale. To achieve this, various techniques are employed to gather data on aspects such as crystal structure, surface characteristics, shape, size, and composition of the nanomaterials.¹

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Nanomaterials are used in various fields due to their distinct size-dependent properties, and accurate characterization is essential to optimize and design them for specific applications.¹

For instance, nanomaterials play a critical role in improving energy storage and conversion, and characterization methods enable the optimization of these materials for enhanced capacity, stability, and effectiveness; similarly, effective characterization is vital in nanomedicine for developing safe and efficient therapeutic and diagnostic agents.²

Methods frequently utilized for nanomaterial characterization include scanning electron microscopy (SEM), transmission electron microscopy (TEM), atomic force microscopy (AFM), and X-ray diffraction (XRD).¹  

Scanning Electron Microscopy

SEM analyzes the morphology of nanomaterials and provides detailed surface imaging.¹ It utilizes a beam of accelerated electrons and electromagnetic lenses, achieving magnification up to 100,000× and enhanced depth of field. The high-energy electrons are focused on the solid sample's surface, generating various signals that convey information about the topographical details and atomic composition.³

However, SEM analysis requires sample preparation, including contrasting and drying, to accurately determine the shape and size of nanomaterials. This preparation can alter the characteristics of the nanomaterials and lead to specimen shrinkage. In contrast, new microscopy techniques such as cryo-SEM and environmental SEM allow for the determination of nanomaterial topography without extensive sample preparation.³

For instance, environmental SEM enables imaging of samples in their natural state without modification, as the sample chamber operates in a low-pressure gaseous environment of 10–50 Torr and high humidity. Similarly, cryo-SEM involves freezing and has been used to characterize nano-emulsions and microspheres.³

Recent technical advances in backscattered electron detection during SEM have significantly improved resolution. These advances include low-vacuum SEM (LVSEM), scanning transmission electron microscopy (STEM), and three-dimensional electron microscopy (3D-EM).⁴

Although performing 3D-EM analysis was previously difficult, recent technologies like focused ion beam SEM and serial block-face SEM have simplified the process by automating sectioning and image acquisition. Additionally, LVSEM and STEM enable high-resolution observation of samples.⁴

A study published in RSC Advances utilized convolutional neural networks to develop a deep learning method for automating the examination of nanoparticles imaged by SEM. This approach allowed for the separation of overlapping or contacting particles by segmenting nanoparticle SEM images into background and coherent foreground areas (particles).⁵

Both pseudo-three-dimensional secondary electron micrographs and two-dimensional scanning transmission electron micrographs provided quantitative data on particle shape and size distributions.⁵

Transmission Electron Microscopy

TEM is the most effective method for nanomaterial characterization, offering spatial resolution from the atomic level (1–100 nm) to the micrometer level. It provides direct images and chemical information about nanomaterials. TEM offers higher resolution than SEM as it utilizes powerful electron beams.³

This technique also provides information on the granularity and crystallinity of nanomaterials. TEM can be combined with various analytical methods for a range of applications. For instance, the chemical composition of nanomaterials could be investigated using TEM coupled to energy-dispersive X-ray diffraction.³

Additionally, TEM can assess the dynamic displacement of nanomaterials in an aqueous environment. However, key limitations of this technique include potential sample destruction from exposure to high-voltage electron beams and the time-consuming nature of sample preparation.³

TEM is essential in various nanotechnology research areas, including the analysis of drug nanocarriers and their morphology before and after drug incorporation at different concentrations.³ Recent advancements in TEM have enhanced its effectiveness. For example, in-situ TEM enables real-time observation of structural changes in materials under reaction conditions.⁶

A paper published in eTransportation utilized these advances in in-situ TEM to understand interface difficulties and materials in all-solid-state lithium batteries (ASSLBs), challenges in all-solid-state lithium batteries (ASSLBs), focusing on real-time observations of degradation and reactions occurring in electrodes, solid electrolytes, and their interfaces.⁶

Atomic Force Microscopy

AFM measures forces at the nanoscale and produces surface topographical images. This surface probe microscopy technique uses a micro-machined cantilever made of silicon or silicon nitride, with a sharp tip that detects deflection caused by van der Waals (vdW) forces, electrostatic repulsion, and attraction between the tip and the atoms on the measured surface.³ The oscillating cantilever scans the specimen surface with a resolution of fractions of a nanometer.

This technique is used to analyze the structure, dispersion, and aggregation of nanomaterials. AFM enables the study of nanomaterials’ shape and size under physiological conditions, as well as the characterization of their dynamics in biological environments.³

In a study published in Nature Communications, researchers have developed a novel technique to enhance the detection ability of nanoscale chemical imaging using AFM. The improvements could decrease the noise associated with the microscope, increasing the precision and versatility of the instrument.⁷

X-Ray Diffraction

XRD determines the crystal structure and phase composition of nanomaterials. This technique is used to analyze the tertiary structures of polycrystalline/crystalline materials at the atomic scale. In XRD, a collimated X-ray beam is directed at the sample, and then the scattering type and intensity are detected at specific angles.³

XRD is a widely used analytical technique for determining the size, phase, and orientation of crystals. In the pharmaceutical industry, it is employed to evaluate drug carriers, crystallinity phases of contaminants, and the crystallinity of excipients, drugs, and metabolites.³

A paper published in Applied Surface Science Advances utilized XRD to investigate synthesized zinc oxide nanoparticles. The crystallinity and phase of the zinc oxide nanoparticles were confirmed by recording their X-ray diffraction pattern. For instance, narrow and distinct diffraction peaks implied that the product's particles possessed a clearly defined crystalline structure.⁸

Artificial intelligence (AI) significantly enhances XRD analysis, enabling ultrafast processing and interpretation of XRD patterns, which reduces computational cost and time compared to traditional tools.⁹

Conclusion 

Nanomaterial characterization techniques are essential for understanding the behaviors, properties, and potential applications of nanoscale materials. These techniques are crucial for fundamental research, allowing for precise optimization and control of nanomaterial synthesis, facilitating the design of novel nanomaterials and devices, and ensuring the safety and quality of nanotechnology-enabled products.

Leading manufacturers of nanomaterial characterization equipment include Thermo Fisher Scientific, Hitachi, JEOL Ltd., and Tescan, while NanoComposix is major provider of characterization services.

However, further research is needed to refine and integrate these characterization techniques. Future advancements will likely involve the synergistic use of multiple techniques, along with data analysis and computational modeling, enabling researchers to gain deeper insights into nanomaterial properties and behavior.¹

More from AZoNano: A New Method for Non-invasive or Inline Detection of Aggregates and Oversized Particles in Nanosuspensions

References and Further Reading

1. Singh, A., et al. (2024). Nanomaterial Characterization Techniques. Futuristic Trends in Chemical Material Sciences & Nano Technology. DOI: 10.58532/V3BECS13P1CH2, https://www.researchgate.net/publication/380324645_NANOMATERIAL_CHARACTERIZATION_TECHNIQUES
2. Mahmoudi, M. (2021). The need for robust characterization of nanomaterials for nanomedicine applications. Nature Communications. DOI: 10.1038/s41467-021-25584-6, https://www.nature.com/articles/s41467-021-25584-6
3. Thaher, Y., Chandrasekaran, B., Panchu, SJ. (2020). The Importance of Nano-materials Characterization Techniques. Integrative Nanomedicine for New Therapies. DOI: 10.1007/978-3-030-36260-7_2, https://link.springer.com/chapter/10.1007/978-3-030-36260-7_2
4. Honda, K., Takaki, T., Kang, D. (2023). Recent advances in electron microscopy for the diagnosis and research of glomerular diseases. Kidney Research and Clinical Practice. DOI: 10.23876/j.krcp.21.270, https://pubmed.ncbi.nlm.nih.gov/35545227/
5. Bals, J., Epple, M. (2023). Deep learning for automated size and shape analysis of nanoparticles in scanning electron microscopy. RSC Advances. DOI: 10.1039/D2RA07812K, https://pubs.rsc.org/en/content/articlehtml/2023/ra/d2ra07812k
6. Sun, Z. et al. (2022). In situ transmission electron microscopy for understanding materials and interface challenges in all-solid-state lithium batteries. ETransportation. DOI: 10.1016/j.etran.2022.100203, https://www.sciencedirect.com/science/article/abs/pii/S2590116822000480
7. Kenkel, S., Mittal, S., Bhargava, R. (2020). Closed-loop atomic force microscopy-infrared spectroscopic imaging for nanoscale molecular characterization. Nature Communications. DOI: 10.1038/s41467-020-17043-5, https://www.nature.com/articles/s41467-020-17043-5
8. MuthuKathija, M., Sheik Muhideen Badhusha, M., Rama, V. (2023). Green synthesis of zinc oxide nanoparticles using Pisonia Alba leaf extract and its antibacterial activity. Applied Surface Science Advances. DOI: 10.1016/j.apsadv.2023.100400, https://www.sciencedirect.com/science/article/pii/S2666523923000351
9. Prasianakis, NI. (2024). AI-enhanced X-ray diffraction analysis: towards real-time mineral phase identification and quantification. IUCrJ. DOI: 10.1107/S2052252524008157, https://journals.iucr.org/m/issues/2024/05/00/me6289/index.html

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