AFM Data for the Community: Towards Reproducible, Interoperable, and Open Science

In 2026, the scientific community celebrates 40 years of Atomic Force Microscopy (AFM), a transformative technology pioneered by Gerd Binnig, Calvin Quate, and Christoph Gerber. Over four decades, AFM has evolved from laboratory prototype to an indispensable instrument for materials science, biology, and semiconductor research. It now generates increasingly complex datasets, ranging from simple topographical images to mechanical, chemical, and magnetic maps, across diverse applications.

Despite its central role, AFM data is often fragmented, inconsistently documented, or stored in proprietary formats, limiting interoperability, reproducibility, and reuse. As AFM enters its fifth decade, there is a timely opportunity to align scientific publication with robust, community-driven data infrastructure.

The goal of this article collection is to advance AFM research by positioning high-quality, reusable datasets as integral scientific outputs. Developed in collaboration with the Physical Sciences Data Infrastructure (PSDI), this Research Topic aims to connect peer-reviewed research with open, FAIR-compliant data sharing. It will do so through integration with PSDI’s Community Data Collections, Atomic Force Microscopy Database (AFMDB). By linking publications with structured and accessible datasets, this initiative seeks to strengthen reproducibility, enable cross-study comparison, and support new data-driven discoveries in nanoscience.

PSDI accelerates research in the physical sciences by supporting communities in chemistry, materials science, and related disciplines, building on the data systems researchers already use. It provides access to diverse data sources, services, and tools, alongside guidance and training for researchers and the professionals who support them. Through this collaborative infrastructure, the initiative promotes best practices in data management, sharing, and reuse across the AFM community.

Ultimately, this Research Topic aims to foster a culture of open and reproducible science, encouraging researchers to contribute well-documented datasets alongside their scientific findings. By strengthening connections between publications, data, and community infrastructure, the collection will help create a sustainable ecosystem for interoperable AFM data that accelerates discovery and maximizes the scientific impact of four decades of AFM innovation.

This article collection welcomes submissions across the broad spectrum of AFM applications, including materials science, nanobiology, nanoelectronics, nanofabrication, and surface characterization. Contributions may include Original Research Articles, Brief Research Reports, Methods papers, Reviews, or Perspectives that present new scientific insights, methodological developments, or critical evaluations of current practices in AFM research and data management.

Authors are encouraged to make associated datasets openly available through one of two options. First, authors can utilize the FAIR2 DATA Direct Submission. More information about word counts and offerings can be found at this webpage.

Second, authors can utilize the PSDI Community Data Collection, a collaborative, subject-focused research data repository within the PSDI. The repository supports the publication, sharing, discovery, and reuse of valuable research data. It follows FAIR principles through a comprehensive metadata schema that combines widely adopted standards with domain-specific scientific descriptors. Metadata and deposited datasets are openly accessible to all users, supporting transparency and long-term data usability.

For AFM-related studies, datasets can be deposited in the Atomic Force Microscopy Database (AFMDB), a dedicated collection within PSDI Community Data Collection. AFMDB accepts AFM data in any instrument file format together with processed image outputs. Contributors are encouraged to use TopoStats, an open-source image processing tool available through PSDI, to support standardized analysis workflows and improve interoperability across studies. While dataset deposition is not mandatory, authors with relevant datasets are strongly encouraged to deposit them to enhance reproducibility and enable broader reuse by the AFM and nanotechnology communities.

Key subthemes of this Research Topic include (but are not limited to):
• Standardization, metadata, and FAIR data principles for AFM
• Reproducibility and benchmarking of AFM measurements and workflows
• Open data infrastructure, databases, and community-driven resources for AFM
• Data formats, interoperability, and software tools for AFM analysis
• High-throughput and multimodal AFM data acquisition and management
• Integration of AFM datasets with machine learning and data-driven discovery approaches
• Best practices for data sharing, curation, and long-term reuse in nanoscience
• Cross-disciplinary applications of AFM supported by reusable datasets (materials, biology, nanoelectronics, nanofabrication)

Topic Editor Dr. Mansoor Nellikkal is employed by PSDI, which is overseen by the University of Southampton. The other Topic Editors report no competing interests related to this Research Topic.