The increasing use of in situ liquid cell systems for the TEM necessitates better knowledge of using analytical tools on the microscope with a liquid cell. Sample analysis extends beyond the scope of traditional TEM, and key information about the characteristics of samples in their native liquid environment can be extracted from STEM imaging.
One such analysis tool widely used by microscopists is electron energy loss spectroscopy (EELS), including energy filtered TEM (EFTEM), which yields sample information such as element determination and electronic structure. Quantifiable liquid thickness measurements can also be obtained for liquid cell systems.
In Situ EELS Analysis
The integration of EELS systems into a TEM is by means of a post- column filter (GIF by Gatan) or an Omega filter. This filter is placed in the column just underneath the objective lens. After the generation of an EEL spectrum, there are interactions of the electrons from the primary beam with the electrons near the atomic nucleus (core-loss spectrum) and the electrons in or close to the valence shell (low-loss spectrum) of the sample.
As a consequence, inelastic scattering of electrons takes place, and a spectrometer is used to detect and quantify the amount of scattering. Sample thickness affects the EEL signal and therefore signal deteriorates due to increased scattering caused by increasing sample thickness. Rigorous quantification describing the limitations of EELS analysis within an in situ liquid cell had not been performed until recently.
NIST researchers in Bethesda, Maryland, along with scientists in David Muller’s team at Cornell University explored the advantage of using in situ EELS for materials analysis in spectroscopy as well as imaging (EFTEM) modes with the help of the Protochips Poseidon liquid cell system.
This article examines the capabilities of EELS in liquid and presents the evaluation of core and low-loss areas of the EELS spectrum as a function of liquid thickness. Furthermore, it also discusses EFTEM imaging in the low and zero-loss region.
Two Poseidon E-chips consisting of a 50nm silicon nitride window were employed to hold liquid in the TEM column for all experiments. David Muller’s lab took EEL spectra and low-loss EFTEM images using an FEI Tecnai F20.
The TEM was run in both traditional TEM and STEM modes at 200kV and EELS analysis was performed using a Gatan 865 HR-GIF. Pure water was utilized to explore the impact of liquid thickness on the EEL spectrum.
NIST’s Kate Kline and Ian Anderson performed zero-loss EFTEM experiments with the help of a Philips / FEI CM300FEG running with a post column Gatan GIF at 300kV. Images of agglomerates of 30nm gold nanoparticles in pure water were taken in these experiments.
According to researchers in Muller’s team, it is possible to obtain meaningful low and core-loss signals when the ratio of liquid/sample thickness and inelastic mean free path (t/λ) of the electron in the sample is less than a threshold value. Sample thickness greatly affects the core- loss spectrum due to the possibility of multiple scattering of low-loss electrons.
As a result, the core-loss signal is dominated by the low-loss electrons. This means that it is possible to extract meaningful data in the low-loss signal for thicker layers. Moreover, obtaining meaningful core-loss data is possible only from thin liquid layers (Figure 1).
Figure 1. A series of EEL spectra as a function of increasing liquid thickness.
As shown in Figure 1, the low and core-loss spectrum of pure water was measured as a function of increasing thickness. The oxygen K-edge was observed only in the thinnest liquid layers (< 300nm, t/λ = ~2.7) and disappeared with increasing thickness. Nevertheless, the low-loss spectrum showed the optical gap of water (6.9eV) up to liquid thicknesses of ~650nm (t/λ = ~6.5) (inset).
Beer’s law (I=I0exp(t/λ)) was used to determine the liquid thicknesses observed in Figure 1. Here, I represents the count of unscattered electrons calculated through the zero-loss peak in the EEL spectrum, whereas I0 represents the count of incident electrons. Figure 2 illustrates another EELS analysis, showing the iron L-edge from a nanoparticle of LiFePO4 as well as the oxygen K-edge from the sample and liquid. The spectra of LiFePO4 in water indicate the easy identification of core-loss signatures with thin enough liquid layers (180nm).
Figure 2. The core-loss spectra of water and LiFePO4 in water. The liquid layer is ~180nm in this case, and the oxygen K-edge and iron L-edge is evident.
Figure 3 presents a low- loss EFTEM image of the same sample. This experiment involved centering of a 5eV slit in the EELS signal at 5eV, showing a strong FePO4 signal at this point (highlighted in green). Then centering of the slit was done at 10eV, showing a strong LiFePO4 signal at this point (highlighted in red).
Figure 3. A low-loss EFTEM image of LiFePO4 in water. The red areas indicate Li rich material, and the green area indicates Li poor material. The scale bar is 500nm.
Figure 3 shows an overlay of the images, thus allowing visualization of the location of the Li- rich regions at the nanometer scale. Additional benefits can be obtained from energy filtering on imaging through thick samples.
The use of a small energy selecting slit centered on the zero-loss peak increases the depth of field, thus yielding a much clearer image. Using a 10eV slit centered at the zero-loss peak, imaging of an agglomeration of gold nanoparticles in water was done in EFTEM mode (Figure 4). Imaging of the same area without a slit revealed the effect of energy filtering on the depth of field (wE).
Figure 4. An EFTEM image of 30nm Au nanoparticles using a 10eV slit on the zero-loss peak.
Figure 5 shows a traditional TEM image of the same are shown in Figure 4. Considerably more of the image is focused in the EFTEM image albeit decreasing signal intensity owing to the use of small slit. Compared to the unfiltered image, a crisper image revealing the structural information and configuration of the gold nanoparticle agglomerates can be obtained with EFTEM imaging.
Figure 5. A conventional TEM image of the same area shown in Figure 4.
In materials science, EELS analysis provides an effective tool for determining the characteristics of samples in dynamic liquid environments.
This method is a powerful tool in the TEM to study in situ liquid samples, yielding electronic structure information, determining elements, and mapping them spatially.
In addition, EELS analysis enables better identification of material changes and better quantification of the product of reactions.
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