AI-SCOPE Poster: AI-Driven Enhancement of Surface Scattering Data for Open Science Platforms Across Europe

Stefan Kowarik; Nada Mrkyvkova; Frank Schreiber; Alexander Hinderhofer; Dmitry Lapkin; Erwin Pfeiler; Ainur F. Abukaev; Mikhail Romodin; Michael Häberl

doi:10.5281/zenodo.18827597

March 1, 2026Open Access

AI-SCOPE Poster: AI-Driven Enhancement of Surface Scattering Data for Open Science Platforms Across Europe

View Full Paper

Ask AI

Bookmark

Share

Key Points

The project aims to enhance surface scattering data quality and accessibility using AI-driven workflows.
Development of AI-assisted workflows for data processing
Focus on reflectometry and grazing-incidence diffraction techniques
Integration of enhanced data into open science platforms
Improved data quality through AI enhancements
Increased accessibility of data for the scientific community
Support for FAIR (Findable, Accessible, Interoperable, Reusable) data principles

Implication

Poster presents AI-driven workflows improving surface scattering data integration for open science, indicating enhanced accessibility.

Abstract

Poster presenting the AI-SCOPE project, which develops AI-assisted workflows for reflectometry and grazing-incidence diffraction enabling FAIR surface scattering data and integration with open science platforms.

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Kowarik et al. (2026) studied this question.

synapsesocial.com/papers/69a67efaf353c071a6f0ab65 https://doi.org/10.5281/zenodo.18827597

View Full Paper

Ask AI

Bookmark

Share

AI-SCOPE Poster: AI-Driven Enhancement of Surface Scattering Data for Open Science Platforms Across Europe

Key Points

Implication

Abstract

Discussion

Cite This Study

AI-SCOPE Poster: AI-Driven Enhancement of Surface Scattering Data for Open Science Platforms Across Europe

Key Points

Implication

Abstract

Discussion

Cite This Study

Keep reading

Keep reading