Nanoparticle Analysis – Rapidly Determining the Area of Nucleated Nanoparticles

Nov 16 2016

Introduction

NanoMet is measurement tool for converting images of nanoscale materials to quantitative size data. It includes modules for particle and fiber diameters, as well as a module for object areas.

These modules can be used individually or together to solve problems depending upon the information needed and the nature of the objects to be measured.

The particle module will measure the diameters of circular and globular particles, while the area module will calculate the area of complex shapes-- including shapes that can't be modeled. If desired, these areas can be converted to effective circular diameters.

In this example, Au clusters were evaporated on freshly cleaved HOPG. The mobility of Au at the substrate surface is controlled by the substrate temperature resulting in a distribution of nano-particle diameters.

These particles nucleate into complex lobed shapes for which it would be difficult to provide a simple "diameter". Instead, using the NanoMet area module, the areas of thousands of Au nano-clusters can be measured in a few seconds, including nucleated particles with the most complex shapes.

NanoMet also produces histograms of particle areas allowing size data to be quickly compared to theoretical surface nucleation models.

Describing the Analysis

3 images of sample batch Au clusters 1-3 were received for NanoMet dimensional analysis report generation.

This report was automatically generated with a corresponding raw data spreadsheet containing all measurement information. Annotated images were created to display the object assignments and measurement locations to correlate each assignment with corresponding data in the results spreadsheet.

The NanoMet algorithms identified and assigned individual objects, subsequently conducting measurements and outputting results. All data collected is represented in this report in its entirety. All data has been converted to physical dimensions using NanoMet's calibration function.

Description of the Software Used

The NanoMet version used to generate this report, 1.0.0 BETA, is a developmental software that has the functionality to automatically identify and measure objects in an electron microscope image then populate a correlated database entry and output a final report.

Annotated images are automatically produced by NanoMet to verify and visualize the analysis results. The preprocessing steps and algorithm measurements can be optimized by threshold parameters to govern the contrast ratio cutoff for conversion of the image to binary format, object identication according to how much of the object is identied and measurement tolerances.

Additional information containing the measurement location coordinates is recorded in our database and available for export.

Sample #1 - Au clusters 1

Description: Au clusters on HOPG

Original Image Metadata
Analysis Date:	11/13/2016 9:03:00 PM

Object Assignment Annotations

Notes: Image shows object assignment numbering.

Measurement Location Annotations 1

Notes: Image shows red circles indicating where measurements were taken.

Measurement Location Annotations 2 – Heatmap

Notes: Image shows colored circles coded by diameters.

Image Statistics

Tabular Statistics

Calibrated Statistics [nm]
Minimum	8.26
First Quartile	45.42
Median	664.72
Third Quartile	1,799.42
Maximum	22,583.89
Mean	1,218.95
Std. Deviation	1,672.17
Skewness	3.26
Kurtosis	22.30

Number of Measurements	3235

Histogram

Sample #2 - Au clusters 2

Description: Au clusters on HOPG

Original Image Metadata
Analysis Date:	11/13/2016 9:16:00 PM

Object Assignment Annotations

Notes: Image shows object assignment numbering.

Measurement Location Annotations 1

Notes: Image shows red circles indicating where measurements were taken.

Measurement Location Annotations 2 – Heatmap

Notes: Image shows colored circles coded by diameters.

Image Statistics

Tabular Statistics

Calibrated Statistics [nm]
Minimum	2.08
First Quartile	12.48
Median	53.05
Third Quartile	1,166.33
Maximum	13,860.72
Mean	882.63
Std. Deviation	1,671.65
Skewness	2.88
Kurtosis	10.06

Number of Measurements	1281

Histogram

Sample #3 - Au clusters 3

Description: Au clusters on HOPG

Original Image Metadata
Analysis Date:	11/13/2016 9:21:26 PM

Object Assignment Annotations

Notes: Image shows object assignment numbering.

Measurement Location Annotations 1

Notes: Image shows red circles indicating where measurements were taken.

Measurement Location Annotations 2 – Heatmap

Notes: Image shows colored circles coded by diameters.

Image Statistics

Tabular Statistics

Calibrated Statistics [nm]
Minimum	0.33
First Quartile	8.79
Median	31.71
Third Quartile	441.08
Maximum	9,234.05
Mean	738.18
Std. Deviation	1,689.34
Skewness	3.02
Kurtosis	9.19

Number of Measurements	244

Histogram

Batch Statistics

This section of the report will show the processed statistics aggregated for the entire batch.

Tabular Statistics

Batch Statistics [nm]
Minimum	0.33
First Quartile	24.96
Median	322.04
Third Quartile	1,630.83
Maximum	22,583.89
Mean	1,103.80
Std. Deviation	1,681.22
Skewness	3.10
Kurtosis	17.98

Number of Measurements	4760

Histogram

Conclusion

Statistical calculations for batch Au clusters 1-3 were obtained from 4760 measurements conducted on features identified in 3 image(s).

The results for the batch were a median feature size of 322.04 nm, average feature size of 1,103.80 nm with standard deviation of 1,681.22 nm, a maximum of 22,583.89 nm, a minimum of 0.33 nm.