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.
