We are excited to share the recordings of users' talks and invited speakers' presentations from our latest Users Meeting last November! The full playlist includes:

• FAIR Research Data Management with FAIRmat and NOMAD – Ahmed Mansour
• The FAIRification of PV research data – Eva Unger
• Enabling high-throughput materials discovery of phosphosulfides by developments in FAIR data management, visualization and analysis in NOMAD – Lena Mittmann
• Martignac: Computational workflows for reproducible, traceable, and composable coarse-grained Martini simulations – Tristan Bereau
• Achieving semantic interoperability in materials science data and simulation workflows – Abril Azocar Guzman
• An overview of NFDI4Cat´4 services and tools with a special focus on Voc4Cat the shared vocabularies for catalysis and related disciplines – David Linke

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Last week, the FAIRmat team participated in Love Data Week 2025, an international campaign promoting research data and effective data management.

Siamak Nakhaie and Ahmed Mansour hosted insightful coffee talks on researchers' rights to the data they create and the challenges of managing diverse, large datasets. Both talks are available on our YouTube channel.

Meanwhile, our colleague Julia Schumann participated as an invited speaker at the NFDI4Cat consortium workshop, exploring various RDM solutions for catalysis research.

Let’s keep the spirit of Love Data Week alive and celebrate our passion for data all year round!

Our work on the symmetry-based clustering for efficient and accurate classification of atomistic structures has now been published in the journal npg Computational Materials.

The publication, titled “Automated identification of bulk structures, two-dimensional materials, and interfaces using symmetry-based clustering” presents a novel symmetry-based clustering (SBC) algorithm for the automated identification and classification of atomistic structures, including bulk materials, two-dimensional materials, and interfaces. Unlike machine learning approaches, SBC requires no prior training, relying instead on the recognition of common unit cells within atomic systems. The publication is authored by FAIRmat members: Thea Denell, Lauri Himanen, Markus Scheidgen, and Claudia Draxl.

SBC is an iterative approach that decomposes complex structures into distinct components based on their symmetry properties, allowing for a comprehensive material description. It finds repeating patterns within the atomistic structure by selecting an atom of choice, searching its neighborhood for repetitions of the same atomic species, and then constructing the most likely unit cell. When the unit cell is found, all atoms that can be replicated by repeating that unit cell are assigned to a single component.

It's implemented in the MatID Python package, which is part of the NOMAD platform, and has been benchmarked against stacked 2D structures and grain boundaries, showing high accuracy and robustness even with noisy data. SBC effectively streamlines the exploration of large materials datasets by providing precise labeling of structural component, ensuring reproducible and consistent results, and offering versatility across diverse materials research applications.

On January 15-16, our colleague Andrea Albino (Area A: Synthesis) led a two-day workshop on the topic “On-boarding of New Users for the Customization of NOMAD Oasis.” The workshop introduced PhD students and researchers from Italian CNR institutes and universities to the essential features of the NOMAD platform and its local counterpart, NOMAD Oasis. The event aimed to provide practical guidance on how to use NOMAD for efficient research data management (RDM), and to equip scientists with the tools and knowledge to streamline data workflows in their experimental and computational research.

The workshop struck a perfect balance between theoretical concepts and practical sessions. It began with an exploration of NOMAD's schemas, including base sections, community standards, and custom YAML schemas. Participants received detailed guidance on extending existing schemas to align with specific experimental workflows. Another key topic was the development of parsers to populate NOMAD with experimental and computational data. Using template repositories, researchers created Python-based plugins for data processing.

Hands-on sessions reinforced theoretical knowledge, focusing on setting up the dedicated environment for NOMAD plugin development. A significant part of the workshop showcased real-life examples of extending data schemas, automating data processing workflows (available here), and integrating NOMAD into existing RDM frameworks.

By creating a collaborative environment and emphasizing practical learning, the workshop catalyzed participants' adoption of the platform. Additionally, their integration into the broader NOMAD community through its Discord channel ensures continued knowledge exchange and innovation, contributing to the platform's growth and development.

The recording of the workshop is available on FAIRmat’s YouTube channel.

The 6th edition of the FAIRmat newsletter is now available for download! Stay up to date with the latest project developments, enjoy an insightful interview with NOMAD user Lena Mittmann, and explore more exciting articles from the FAIRmat community. Download it now from our website!

Due to the great public interest in the Fourth FAIRmat Users Meeting at the FAU in Erlangen, we are excited to share the recordings of users' talks and invited speakers' presentations on the FAIRmat and NOMAD YouTube channel! The full playlist includes:

• Research Data Management in Collaborative Research Centres by Brit Redöhl
• Designing RDM in collaborative funding schemes by Heiko Weber
• Knowledge management and online AI training in NOMAD by Ta-Shun Chou
• Advancing Catalysis Research by Julia Schumann
• Low-scaling algorithms developed in NOMAD by Antonio Delesma Diaz
• Taylored RDM with NOMAD by Lauri Himanen
• Employing NOMAD CAMELS in an atom beam experiment by Carina Kanitz

You can read more about the event and see the contributions here.

We're happy to announce that our tutorial on structured data extraction with large language models (LLMs) has been published in Chemical Society Reviews!

The publication, titled 'From Text to Insight: Large Language Models for Chemical Data Extraction,' provides an in-depth overview of LLM-based structured data extraction in materials science and chemistry, synthesizing current knowledge and exploring future directions. It is a product of the FAIRmat AI Toolkit task led by Kevin Maik Jablonka, with contributions from Mara Schilling-Wilhelmi (Friedrich Schiller University Jena), Martiño Ríos-García and María Victoria Gil (CSIC, Oviedo), Sherjeel Shabih, Christoph T. Koch, and José A. Márquez (Humboldt-Universität zu Berlin), and Santiago Miret (Intel Labs).

To improve interactivity and applicability, we've created a Jupyter book with practical examples tailored to chemistry and materials science. These examples can now be run directly using the Jupyter4NFDI service provided by Base4NFDI - Basic Services for the NFDI.

• Read the online book.
• Run it in Jupyter4NFDI.

The annual DGKK + DEMBE workshop took place in Berlin on December 11-13, hosted by the Paul-Drude-Institut für Festkörperelektronik (PDI) and the Fraunhofer Heinrich-Hertz-Institut (HHI). This event combined the expertise of the Deutsche Gesellschaft für Kristallwachstum und Kristallzüchtung (DGKK), focusing on the epitaxy of III-V semiconductors, with the German MBE workshop (DEMBE), bringing together leading experts and researchers in crystal growth and thin film science.

NOMAD was represented by Andrea Albino and Sebastian Brückner (Area A: Synthesis), who showcased their advancements in Research Data Management (RDM) tailored to the needs of the communities addressed in the workshop. On the opening day, they presented a poster highlighting implemented use cases for Metal-Organic Vapor Phase Epitaxy (MOVPE) and Molecular Beam Epitaxy (MBE), as well as a poster detailing the approach of FAIRmat Area A and its community plugins, which bridge the gap in adopting the FAIR principles in RDM. Additionally, Sebastian Brückner participated in a panel discussion alongside experts from academia and industry, offering insights on improving RDM practices in experimental science. The discussion addressed existing bottlenecks and explored new avenues for development, including AI-based real-time analysis for monitoring and prompt corrections during the growth process.

Throughout the event, attendees engaged with Andrea and Sebastian at the FAIRmat booth in the exhibition area. Here, they explored how FAIRmat and NOMAD tools and resources streamline research data workflows, ensuring data are Findable, Accessible, Interoperable, and Reusable (FAIR). These solutions are specifically designed to meet the needs of researchers in thin film science and crystal growth.

A significant point of interest was the reusability of the tools and data structures developed so far, which enable new use cases with minimal modeling effort. This approach strengthens shared standards within the community, fostering collaboration and ease of adoption for new users.

The workshop also attracted the attention of technology partners providing instruments for this research field. These partners showed strong interest in the RDM solutions offered by FAIRmat and engaged in productive discussions about the needs of the community and their potential role in advancing RDM practices.

On November 27, 2024, the FAIRmat community met in Berlin for the Fifth FAIRmat Users Meeting. The event focused on community building, integrating all stakeholders, and fostering collaboration with the FAIRmat consortium. It brought together researchers, data management experts, and our FAIRmat domain experts to discuss the advancements in research data management and our NOMAD tool.

During the morning session, the Users Meeting featured several invited talks by our users and collaborators, showcasing inspiring and practical applications of NOMAD, as well as collaborative efforts alongside tour sibling consortia NFDI4Cat and NFDI-MatWerk. Invited talks have been given by:

• Eva Unger (Helmholtz-Zentrum Berlin and Humboldt-Universität zu Berlin) – „The FAIRification of PV research data“
• Lena Mittmann (Technical University of Denmark) - “Enabling high-throughput materials discovery of phosphosulfides by developments in FAIR data management, visualization, and analysis in NOMAD“
• Tristan Bereau (Universtät Heidelberg) – “Martignac: Computational workflows for reproducible, traceable, and composable coarse-grained Martini simulations”
• Abril Azocar Guzman (NFDI-MatWerk) – „Achieving semantic interoperability in materials science data and simulation workflows“
• David Linke (NFDI4Cat) – “An overview of NFDI4Cat services and tools with a special focus on Voc4Cat the shared vocabularies for catalysis and related disciplines”

In the following weeks, the recordings of all invited talks will be available on our FAIRmat and NOMAD YouTube channel.

The afternoon program included two interactive workshops and a dedicated Users Help Desk. The workshops were designed to provide hands-on guidance on our NOMAD tool, aimed to empower participants to start and work with NOMAD and address user-specific challenges.

The Fifth FAIRmat Users Meeting showcased the growing community committed to research data management according to the FAIR data principles. We are thankful to all participants for their active engagement and contributions. We look forward to further collaborations and are available for support and discussion beyond the Users Meeting. Join our Discord channel to stay connected!

We are excited to see you all again at the 2025 edition of the Users Meeting.

Recordings of FAIRmat Tutorial 15 are now available on the FAIRmat and NOMAD YouTube channel! The full playlist includes:

• FAIR data management
• NeXus data modeling
• Data conversion and verification using pynxtools
• Data in NOMAD

You can read more about the FAIRmat hands-on tutorial series here. The event page has all the learning material for Tutorial 15.