Statistically Rigorous Silver Nanowire Diameter Distribution Quantification by Automated Electron Microscopy and Image Analysis.

Silver nanowire (AgNW) diameters are typically characterized by manual measurement from high magnification electron microscope images. Measurement is monotonous and has potential ergonomic hazards. Because of this, statistics regarding wire diameter distribution can be poor, costly, and low-throughput. In addition, manual measurements are of unknown uncertainty and operator bias. In this paper we report an improved microscopy method for diameter and yield measurement of nanowires in terms of speed/automation and reduction of analyst variability. Each step in the process to generate these measurements was analyzed and optimized: microscope imaging conditions, sample preparation for imaging, image acquisition, image analysis, and data processing. With the resulting method, average diameter differences between samples of just a few nanometers can be confidently and statistically distinguished, allowing the identification of subtle incremental improvements in reactor processing conditions, and insight into nucleation and growth kinetics of AgNWs.

New Image Texture Analysis, and Application to Polymer Membrane Surface Morphologies and Roughness.

A new method of image texture analysis is presented, based on the mean and standard deviation of gray levels within domains in an image. The calculations are performed recursively on domains of various sizes within the images. These gray level calculations are used as the input matrix for principal component analysis. The technique analyzes the entire image as a whole and is not for image segmentation. The analysis routine operates across all distances, frequencies and directions in the image, and is not computationally burdensome. The method was applied to scanning electron microscope images of reverse osmosis membranes on domains from 23 nm to 3 µm. The texture analysis technique performed well in identifying the surface morphology and, once calibrated, in predicting the surface roughness as measured by atomic force microscopy.

Nondestructive Thickness Quantification for Nanoscale Coatings on Li-Ion Battery Cathode Material.

Nickel manganese cobalt oxide (NMC) is a high energy capacity cathode material that attracts the interest of many research groups. Coating a protection layer on the NMC surface is one approach to improve its cycling and safety performance. However, there is no standard and consistent way to characterize the coating performance (thickness) of this protection layer, especially due to the nanoscale of primary particle and spherical morphology of the secondary particle. In this paper, a novel empirical method based on energy dispersive X-ray spectroscopy (EDX) analysis at low accelerating voltage is proposed to evaluate the protection layer thickness on the scale of tens of nanometers. The layer thickness is characterized by measuring the intensity decrease of a substrate element due to absorption by overlying coating layers. An internal standard coating (metal layer) is applied to mimic the morphology influence and improve the accuracy of thickness quantitation. For the model sample evaluation, carbon layer coatings of 1 to 10 nm thickness were successfully quantified by this method.

Characterization of the thickness and distribution of latex coatings on polyvinylidene chloride beads by backscattered electron imaging.

Polyvinylidene chloride (PVDC) co-polymer resins are commonly formulated with a variety of solid additives for the purpose of processing or stabilization. A homogeneous distribution of these additives during handling and processing is important. The Dow Chemical Company developed a process to incorporate solid materials in latex form onto PVDC resin bead surfaces using a coagulation process. In this context, we present a method to characterize the distribution and thickness of these latex coatings. The difference in backscattered electron signal from the higher mean atomic number PVDC core and lower atomic number latex coating in conjunction with scanning electron microscopy (SEM) imaging using a range of accelerating voltages was used to characterize latex thickness and distribution across large numbers of beads quickly and easily. Monte Carlo simulations were used to quantitatively estimate latex thickness as a function of brightness in backscatter electron images. This thickness calibration was validated by cross-sectioning using a focused ion-beam SEM. Thicknesses from 100 nm up to about 1.3 µm can be determined using this method.

Closed-cell foam skin thickness measurement using a scanning electron microscope.

Closed cell polymer foam skin thickness can be assessed by taking backscatter electron (BSE) images in a scanning electron microscope (SEM) at a series of accelerating voltages. Under a given set of experimental conditions, the electron beam mostly passes through thin polymer skin cell walls. That cell appears dark compared to adjacent thicker-skinned cells. Higher accelerating voltages lead to a thicker skin being penetrated. Monte Carlo modeling of beam-sample interactions indicates that at 5 keV, skin less than ∼0.5 µm in thickness will appear dark, whereas imaging at 30 keV allows skin thicknesses up to ∼4 µm to be identified. The distribution of skin thickness can be assessed over square millimeters of foam surface in this manner. Qualitative comparisons of the skin thicknesses of samples can be made with a simple visual inspection of the images. A semiquantitative comparison is possible by applying image analysis. The proposed method is applied to two example foams. Characterizing foam skin thickness by this method is possible using any SEM that is capable of collecting useful BSE images over a range of accelerating voltages. Imaging in low vacuum, where an electrically conductive metal coating is not required, leads to more sensitivity in skin thickness characterization.

Chemometric Evaluation of Ultraviolet-Visible (UV-Vis) Spectra for Characterization of Silver Nanowire Diameter and Yield.

The main tool used for routine screening of silver nanowire diameter and wire-to-particle yield is ultraviolet-visible (UV-Vis) spectroscopy. The normalized absorbance near 500 nm is generally taken to correlate with wire yield (lower absorbance means fewer particles and higher wire yield). The location of the UV-Vis peak near 375 nm is generally believed to correlate with wire diameter. These qualitative assessments are of unknown uncertainty. Improved microscopy-based analysis of wire diameter distribution and wire yield had recently been developed and were used to characterize synthesis products in parallel with UV-Vis data collection. Here we present results of leveraging this quantitative wire yield and diameter distribution data to quantitatively calibrate the UV-Vis methods for characterizing wire diameter and yield. Chemometric analysis was also applied to this UV-Vis data set and resulted in statistically significant models that can predict average wire diameter and wire/particle yield slightly better than the univariate method.