Correlative EDS and Raman Spectroscopy
Abstract
In this study correlative microscopy techniques are used to analyze materials at a micro and nanoscale level. Specifically, the study combines Raman and EDS analytics with SEM and LM imaging to obtain a comprehensive understanding of the chemical and structural properties of materials. The methodology used to integrate these techniques is using a software-based solution including an image-based alignment step. Instead of using holders decorated with fiducials, like in the ‘Shuttle and Find’ based workflow [1], here one can use any characteristic landmarks of the sample. As a result, for a battery sample, we can demonstrate the benefit of combining multiple analytical techniques, to gain a more complete understanding of material properties. The sample workspace (Fig. 1, left) is used to align images from different microscopes. It enables navigation on the SEM using the LM and Raman maps from the Raman microscope. The ‘ZEN Connect’ software module (Zeiss Microscopy) is used to organize and visualize different microscopy images and data from the same sample in context. For sample-centric analysis, ZEN Connect workflows enable you to get from a quick overview image to advanced imaging. The alignment step consists of 3 landmarks imaged with the Raman microscope are reimaged with the SEM. The workflow continues with re-finding the position for correlative SEM imaging and EDS analysis. The sample workspace is used to control the stage by image-based navigation. The advantage of…
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.