Nabodita Anam Nova

• Prepared and harmonised energy, process, and raw-material datasets from multiple sources • Conducted literature-based data collection to fill gaps and document assumptions • Performed input-output calculations, carbon-footprint assessments, and consistency checks • Compared datasets and identified deviations and data-quality issues • Applied Python-based data cleaning, validation, quality control, and reporting workflows

• Prepared metal samples for metallographic analysis • Performed embedding, cutting, grinding, and polishing • Ensured consistent surface quality for microscopy and materials examination • Supported reliable research results through precise sample preparation

• Developed a SQL/Python data framework for plastic packaging end-of-life datasets • Built Excel-to-MariaDB ETL workflows with validation rules and controlled vocabularies • Created reproducible, analysis-ready exports with documented data provenance • Designed KPI tables for material quality assessment and dataset comparison • Produced Sankey visualisations for clear communication of material-flow results

• Developed data science-based RDM workflows for experimental materials science data • Built parsers for FullProf XRD refinement files and supported their integration into NOMAD • Supported sample tracking and metadata management using eLabFTW • Connected XRD and XPS datasets with FAIR data repositories • Improved data accessibility, traceability, and interoperability

- Developed an automated framework to process CSV data from CLAKS, transform it for eLabFTW format using Python, auto-fill metadata, and upload thousands of records into eLabFTW with one-click integration. - Developed a Python-based framework to extract, process, and combine neutron diffraction data (.sum files) from D20 beamline at Institut Laue-Langevin, Grenoble, enabling efficient structural analysis of oxygen transport membranes. - Digitalized chemical inventory for Materials & Resources Group

• Processed electron crystallography datasets using Python and HyperSpy • Converted raw image data into HDF5, TIFF, and other analysis-ready formats • Applied spatial drift correction to improve data quality • Extracted diffraction patterns using region-of-interest methods • Prepared datasets for further crystallographic analysis

• Developed an MFA-based data framework for plastic packaging waste • Automated data extraction, preprocessing, and Sankey visualisation using Python, Pandas, Plotly, and Excel • Aligned workflows with DIN SPEC 91446 and FAIR principles • Analysed LCA and sustainability tools used by companies and research institutions • Researched digital sorting technologies, current models, and improvement opportunities for circular resource management

• Analysed and managed large datasets generated from fluid dynamics simulations • Processed and interpreted post-simulation data to identify relevant patterns and insights • Improved the structure and usability of simulation datasets • Supported data preparation, evaluation, and documentation within the Mathematical Modelling and Analysis Research Group • Contributed to efficient research data handling and analysis workflows

Preparation of the Exercises of the Concepts in Materials Physics Course and Later on Explaining them to the Students via Zoom Class.

• Created technical and onboarding documentation, including Python code explanations • Documented research data and simulation workflows using Kadi4Mat • Conducted phase-field simulations with MOOSE and analysed results in ParaView • Researched experimental data for DED and LPBF processes • Supported scientific documentation, job advertisements, and research group news

• Supervised students in Fuel Cell and Recrystallization laboratory courses • Supported catalyst preparation, voltage testing, and data analysis using NOVA • Guided students in Vickers hardness testing, grain size analysis with Lince, and sample preparation • Ensured safe and correct experimental procedures • Supervised the Recrystallization lab for two terms and the Fuel Cell lab for one term

• Developed a research data management framework for simulation-based materials science • Designed and documented research workflows using Kadi4Mat • Automated data creation, modification, and extraction through the Kadi-APY interface • Visualised simulation workflows and data relationships using the Kadi4Mat Knowledge Graph • Improved the structure, traceability, and efficiency of research data management