ZIF Biocomposite Explorer App for Interactive Visualisation and Prediction of Synthesis-Structure-Property Data

This software record archives the ZIF Biocomposite Explorer App, an interactive web-based visualisation and prediction interface for exploring ZIF biocomposite synthesis-structure-property data. The app forms the visual analytics layer of a broader digital workflow for ZIF biocomposite synthesis. It connects structured synthesis coordinates, PXRD-derived phase and crystallinity descriptors, ATR-IR-derived descriptors, encapsulation efficiency, loading capacity, repeated characterisation measurements, and model-derived prediction overlays in a single browser-based interface. The app enables users to inspect measured synthesis points across ternary precursor composition space, compare concentration layers, switch between 2D and 3D composition-space views, examine selected samples through inspector panels, access experiment-level ATR-IR and XRD spectra, and explore phase and crystallinity trends across the experimentally supported domain. The overall digital workflow, from software-supported experimental execution and structured data capture to processed characterisation descriptors, visual analytics, spectrum inspection, and machine-learning-ready exploration, was originally conceptualised, developed, and maintained by Aleksandar Kondinski at Graz University of Technology. Role in the digital workflow Stage Role of the app Synthesis-space representation Displays synthesis coordinates across ternary metal, ligand, and BSA precursor composition space and across precursor concentration layers. Characterisation linkage Connects each synthesis point to PXRD, ATR-IR, encapsulation efficiency, loading capacity, and replicate-level measurement information. Processed data integration Uses structured JSON outputs generated from the ZIF Biocomposite Analytics pipeline, including phase, crystallinity, ATR-IR, and sample-level descriptors. Interactive visual analytics Provides 2D and 3D composition-space views, filtering controls, hover summaries, inspector panels, and downloadable data access where available. Prediction support Displays model-derived prediction overlays within the experimentally supported composition domain, enabling exploratory comparison between measured and predicted regions. The app is associated with the ZIF Biocomposite Dataset and supports interactive exploration of software-controlled syringe-pump synthesis data for ZIF biocomposites. A live version of the app is available at the time of deposition at https://digital-chemistry.io/zif/. Source repository: https://github.com/digital-chemistry/zif-vis.