DIFFRAC.EVA

Effortless PDF generation: We are proud to present the results of a collaboration with Prof. Olivier Masson from the University of Limoges, an expert in the field of PDF analysis. Utilizing his expertise, DIFFRAC.EVA now includes the powerful PyTSRedX algorithms for generating experimental PDFs from raw diffraction data. Entry into PDF analysis has never been this simple: with just a few clicks, users can quickly and painlessly create high-quality PDFs. DIFFRAC.EVA automatically corrects for background and Compton scattering, absorption, polarization, and X-ray fluorescence, then normalizes and Fourier transforms the data, all within seconds!

Export the experimental PDF for further quantitative evaluation in DIFFRAC.TOPAS and explore new horizons in X-ray data evaluation of amorphous materials, nanoscopic structures, or local effects in disordered structures.

Effortlessly repeat previously recorded commands with the power of workflows. Record a sequence of EVA commands and replay them at any time. During the recording process, only applicable commands are enabled. The workflow runner control displays context-sensitive workflows, showing only those actions that start with a command relevant to the current selection. Instantly start a workflow using the convenient drop-down list in the toolbar. Modify command parameters within pre-recorded workflows using the edit button.

The benefits of workflows in DIFFRAC.EVA are:

• Increased Efficiency: Workflows allow users to record and replay a sequence of commands, saving time and effort in executing repetitive tasks. By automating complex or frequently performed operations, workflows streamline the analysis process and enhance overall efficiency.
• Consistency and Reproducibility: Workflows ensure consistency and reproducibility in data analysis by capturing the exact sequence of commands used during a specific analysis. This feature is particularly valuable when working on collaborative projects or when revisiting previous analyses.
• Error Reduction: With workflows, there is a reduced risk of human error during data analysis. Since recorded workflows execute predefined commands accurately, the likelihood of mistakes or omissions is minimized, leading to more reliable and trustworthy results.
• Simplified Operation: Workflows simplify the execution of complex analysis procedures by breaking them down into a series of manageable steps. Users can execute the entire workflow with a single click, eliminating the need to remember and execute multiple commands manually.
• Flexibility and Customization: Workflows offer flexibility and customization options to suit individual analysis requirements. Users can modify and fine-tune recorded workflows by adjusting parameters, allowing for adaptability and tailoring to specific analysis needs.
• Streamlined Collaboration: Workflows facilitate collaboration among researchers by providing a standardized approach to data analysis. Recorded workflows can be easily shared with team members, ensuring consistency across multiple users and enabling seamless collaboration on projects.

Overall, the use of workflows in DIFFRAC.EVA provides users with improved efficiency, enhanced accuracy, reproducibility, and collaboration capabilities, resulting in a more streamlined and productive data analysis experience.

DIFFRAC.EVA brings significant advancements to pattern fitting capabilities, enhancing the accuracy and reliability of your analyses. Benefit from improved algorithms, faster performance, and more stable results.

• Refinement of Lattice Parameters: Achieve higher precision and accuracy in our new lattice parameter refinement with the addition of offset and sample height corrections.
• Preferred Orientation and Intensity Fitting: Explore advanced features such as the March-Dollase model and spherical harmonics up to the 6th degree for preferred orientation corrections. Conduct peak height fits without constraints using a Pawley-like approach. The replacement of pseudo-Voigt peaks with Voigt peak-shape function and Pearson VII further enhances profile fitting, resulting in better micro-structure evaluations.
• Improved Emission Profile: Enhance the clarity and assign minor signals accurately within the total fit by including spectral impurities such as K-beta and tungsten lines in the K-alpha spectrum. This feature improves the unambiguous identification of signals and provides a more comprehensive analysis of your X-ray data.
• Quantitative Analysis and Amorphous Phases: Perform semi-quantitative analysis using options like the Reference Intensity Ratio (RIR) for the highest peak or all fitted peaks. Add one or more amorphous "phases" easily using the dedicated buttons in the "Amorphous Phases" tab.

With these enhancements, DIFFRAC.EVA empowers you to achieve more accurate and meaningful results, enabling advanced pattern fitting and comprehensive analysis of your X-ray data.

Expanded Data Accessibility and Management: Access raw data from PDF-4 databases using the well-known Search/Match functionality in EVA, effortlessly extracting original scan data for further evaluation.

Furthermore, leverage the capabilities of user databases by including your own measured patterns, enabling you to store reference measurements and other valuable data alongside your analysis results. Utilize these user databases as reference inputs for Cluster Analysis, Positive Materials Identification (PMI), or the powerful semi-quantitative pattern matching (SQUALL) feature. By combining User Databases and Pattern Matching, you can perform advanced analysis and comparison of your patterns, enhancing the accuracy and depth of your X-ray data evaluation. With improved data accessibility, comprehensive management options, and advanced pattern matching capabilities, DIFFRAC.EVA empowers you to streamline and elevate your X-ray data analysis process.