DELFI is a comprehensive application that revolutionizes molecular science and chemistry research. It offers a wide array of functionalities tailored to meet the diverse needs of researchers, chemists, and scientists. Through DELFI, users can engage in predictive modeling, leveraging advanced algorithms to forecast molecular properties and behaviors with remarkable precision. The platform also facilitates in-depth analysis of scoring systems applied to molecular datasets, enabling researchers to refine methodologies and optimize experimental approaches. With the ability to upload custom datasets in various formats, such as SMILES or CSV, DELFI empowers users to conduct tailored analyses, extract meaningful insights, and accelerate research outcomes. Furthermore, DELFI serves as an invaluable educational tool, providing accessible explanations of complex concepts and techniques in molecular science. By streamlining workflows, facilitating data-driven decision-making, and fostering collaboration, DELFI is poised to drive innovation and discovery in the field of molecular science.

See owner's GitHub repository for more information: https://github.com/SebA-R/streamlit.

This app is based on the paper:

Avagliano, D., Skreta, M., Arellano-Rubach, S., & Aspuru-Guzik, A. (2023). DELFI: A computer oracle for recommending the best density functional for excited states calculations. ChemRxiv. doi:10.26434/chemrxiv-2023-v9841

This application was not uploaded by the author, but through their publicly available Github repository, https://github.com/SebA-R/streamlit.