Name: In Situ Heating Study of Gold on Iron Oxide Nanoparticles
Uploaded: 2023-06-23T14:25:00
Duration: 2 min 23 s
Description: Watch this Scientific Journal Video about In Situ Heating Study of Gold on Iron Oxide Nanoparticles at JoVE.com

in situ heating study of gold on iron oxide nanoparticles

TEM Workflows, Results Analysis, and Data Management Using a Machine-Vision Approach

Transmission electron microscopes (TEMs) and their capabilities have benefited enormously from advances in cameras, detectors, sample holders, and computing technologies. However, these advances are hampered by disconnected data streams, limitations of human operation, and cumbersome data analysis1,2. Moreover, in situ and operando experiments adapt TEMs into real-time nanoscale laboratories, enabling samples to be studied in gas or liquid environments while simultaneously applying a range of external stimuli3,4,5. The adoption of such complex workflows have only magnified these limitations, and the resulting increase of the size and complexity of these data streams is an area of growing concern. Thus, there is a growing emphasis on utilizing machine-actionability to find, access, interoperate, and reuse data, a practice known as the FAIR principles6. Publishing research data in accordance with the FAIR principles concept has received favorable attention from governmental agencies around the world7,8, and application of the FAIR principles using machine-vision software is a key step in their adoption.
A machine-vision synchronization (MVS) software platform has been developed in response to the specific pain points inherent to performing and analyzing complex, metadata-heavy TEM experiments (particularly in situ and operando experiments)9. Once installed on the TEM, the MVS software connects, integrates, and communicates with the microscope column, detectors, and integrated in situ systems. This enables it to continuously collect images and align those images with their experimental metadata, forming a comprehensive searchable database, a timeline of the experiment from start to finish (Figure 1). This connectivity allows the MVS software to apply algorithms that intelligently track and stabilize a region of interest (ROI), even when samples are undergoing morphological changes. The software applies adjustments to stage, beam, and digital corrections as necessary to stabilize the ROI through its Drift Control and Focus Assist functions. In addition to enriching the images with the raw metadata produced from the different experimental systems, the software can produce new, computational metadata using image analysis algorithms to calculate variables between images, which allow it to automatically correct for sample drift or changes in focus.
TEM images, and their associated metadata collected through the MVS software, are organized as an experimental timeline which can be opened and viewed by anyone via the free, offline version of the analysis software, Studio (hereafter referred to as the analysis software)10. During an experiment, the MVS software syncs and records three types of images from the microscope&#39;s camera or detector, which are displayed at the top of the timeline below the image viewer: single acquisition (individual single aquisition images acquired directly from the TEM software), raw&#160;(images from the detector/camera live stream that have not had any digital drift corrections applied; these images may have been physically corrected via stage movement or beam shift), and drift corrected (images from the detector/camera live stream that have been digitally drift). Data collected during an experiment or session can be further refined into smaller sections or snippets of data, known as collections, with no loss of embedded metadata. From the analysis software, images, image stacks, and metadata can be directly exported into a variety of open format images and spreadsheet types for analysis using other tools and programs.
The framework of microscope control, stabilization, and metadata integration enabled by the MVS software also allows the implementation of additional machine-vision programs or modules, designed to alleviate limitations in current TEM workflows. One of the first modules developed to take advantage of this synchronization platform is electron dose calibration and spatial tracking of beam exposed areas within the sample. All TEM images are formed from the interaction between the sample and the electron beam. However, these interactions can also result in negative, inescapable impacts on the sample, such as radiolysis and knock-on damage11,12, and require a careful balance between applying a high enough electron dose to generate the image and minimizing the resulting beam damage13,14.
Although many users rely on screen current measurements to estimate the electron dose, this method has been shown to widely underestimate the actual beam current15. Qualitative dose values can be obtained via the screen current on the same microscope with the same settings, but reproducing these dose conditions using different microscopes or settings is highly subjective. Additionally, any imaging parameter adjustments made by the user during the experiment, such as spot size, aperture, magnification, or intensity, require a separate measurement of the screen current to calculate the resulting dose. Users must either rigorously limit the imaging conditions used during a given experiment or meticulously measure and record each lens condition used, significantly complicating and extending the experiment beyond what is feasible for normal operation of the microscope16,17.
Dose, referred to as dose software for this protocol, is a dose calibration software module that utilizes a dedicated calibration holder designed to enable automated current measurements. A Faraday cup, the gold standard for accurate beam current calibration15, is integrated into the tip of the calibration holder. The MVS software performs a series of beam current and beam area calibrations for each lens condition and embeds those values on the images at the pixel level.
In this video article, MVS software protocols designed to enhance all areas of the TEM workflow are presented using representative nanomaterial samples. A beam sensitive zeolite nanoparticle sample14 is used to demonstrate the calibration and dose management workflows. We perform a representative in situ heating experiment using an Au/FeOx nanocatalyst18,19 sample that undergoes significant morphological changes when heated. This in situ experiment highlights the software&#39;s stabilization algorithms and its ability to collate multiple streams of metadata, which is an inherent challenge for in situ and operando studies. Although not described in the protocol, because of its unique electron dose sensitivity, we discuss representative examples of the software&#39;s utility for liquid-EM studies (protocols for which have been previously reported in the literature20,21,22), and how these techniques can be applied to improve the understanding of the effect of dose on liquid-EM experiments. Finally, we show how data analysis is streamlined using the offline analysis software to visualize, filter, and export a variety of image, video, and data files into other accessible formats.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/65446/65446fig01.jpg" /> 
Figure 1: User interface examples for MVS and analysis software. (A) The synchronization software image viewing pane and control panel. A connection between the TEM and the synchronization software is established by activating the Connect button, which streams the images and metadata from the microscope into the synchronization software. From the image viewer, the operator can perform a variety of machine-vision assisted operations, such as Drift Correct and Focus Assist. It also provides the ability to apply Tag Images and Review Session without disrupting data collection. (B) Screenshot of the image analysis software highlighting the location of the Image View Port, Timeline, and the Metadata and Analysis panel. The analysis software can be accessed at any point during an experiment to review the images acquired up to that time point using the Review Session button. <a href="https://www.jove.com/files/ftp_upload/65446/65446fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management  

A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management

This technology was developed to make high-performance TEM studies accessible to users of all skill levels. Furthermore, scientific advancements require the collaborative efforts of multiple investigators, so an efficient platform to share and analyze large, complex data sets is essential for successful research Operando and in situ studies transform a TEM into a real-time nanolaboratory, allowing researchers to explore the dynamic nano-scale processes that control materials'growth properties. One of the greatest challenges for in-situ TEM studies is isolating the beam irradiation effects from the intrinsic behavior of the sample.Accurate electron dose measurement and tracking is essential, but without dose management software, one can only measure electron dose rate rather than the total or critical dose Complex TEM workflows generate large data sets which must be manually aligned and indexed to their respective images. In this time-consuming process, the key information, such as adjustments to imaging conditions or samples environment, may be lost, complicating analysis and reproducibility. We have developed a machine-vision workflow to collect and index the images and metadata produced during an experiment into a data-enriched, searchable timeline.Computational and image analysis algorithms can calculate variables between images, apply corrections, and identify hidden trends. By calculating, synchronizing, and indexing new metadata into each image, multimodal analysis is suddenly a new possibility. For example, accurate accumulated dose and dose rate information in the zeolite images allows quantitative assessment of sample damage across thousands of images.We will continue to push the capabilities of in-situ TEM by making results accessible and interpretable and improving experimental reproducibility. This software is a platform to develop workflow-driven modules that target specific, historically difficult applications to make in-situ TEM experiments easier and more information rich.

Watch this Scientific Journal Video about In Situ Heating Study of Gold on Iron Oxide Nanoparticles at JoVE.com

In Situ Heating Study of Gold on Iron Oxide Nanoparticles  

To begin, select the appropriate workflow option from the MVS software. Follow the workflow prompts to confirm the electrical connection between the holder and the heating e-chip by loading the calibration file and performing a device check. After connecting the microscope to the MVS software, center the sample ROI in the field of view.Access the Temperature Control Settings by clicking the Experiment button and Manual Control mode. Then, set the ramp rate to 25 degrees Celsius per second and the target to 200 degrees Celsius. Click on Apply to start the experiment.After reaching 200 degrees Celsius, set the ramp rate to 10 degrees Celsius per second. Adjust the target to 600 degrees Celsius and click Apply. After the set temperature of 600 degrees Celsius is reached, change the ramp rate to 2 degrees Celsius and the target to 800 degrees Celsius.Click on Apply to start the experiment. Once done, open the Analysis Software to review the session. In the timeline, plot the temperature, template morphing factor, dose rate, and cumulative dose.Export images and movies using the Publish option with or without the dose map overlays. The heating experiment performed using a representative nanocatalyst sample gold on iron oxide showed that at elevated temperatures, the gold nanoparticles within the gold on iron oxide migrated along the surface of the iron oxide support and centered to form larger particles. An in-situ heating experiment recorded a series of TEM snapshots of a porous region within a gold on iron oxide nanocatalyst at various time points.The coordinated drift of the sample increased with the increased temperature from a rate of 9 to 62 nanometers per minute, and began to decrease towards leveling off with the constant temperature. The MVS software stabilized the particle in the field of view throughout the entire temperature ramp profile, enabling high resolution imaging.