Call for papers: Special Issue on

Semantic Materials Science and Engineering (SMSE)

Materials Science and Engineering (MSE) is currently navigating a profound transformation, often described as the shift toward Industry 5.0 and Materials 4.0. While high-throughput experimentation and multi-scale modeling have generated an unprecedented volume of data, the discipline faces a critical bottleneck: data fragmentation and lack of interoperability. The focus of this special issue lies in the transition from data-driven to knowledge-driven materials science. Current approaches often rely on black-box Machine Learning models that, while powerful, lack explainability and physical context.

Semantic MSE (SMSE) proposes a symbiotic integration where:

• Semantic Web technologies provide the backbone for interoperability, reasoning, and adherence to FAIR (Findable, Accessible, Interoperable, Reusable) principles.
• Domain knowledge is formalized via ontologies, ensuring that data retains its physical meaning across scales - from quantum mechanical calculations to macroscopic continuum mechanics.

As robotic platforms begin to automate the synthesis and characterization of materials, the need for machine-interpretable communication protocols is no longer theoretical, it is an engineering necessity. Furthermore, the advent of Large Language Models (LLMs) offers new opportunities to populate Knowledge Graphs (KGs) or derive ontologies from unstructured literature, provided these probabilistic models can be grounded in rigorous semantic frameworks to prevent hallucinations.

This special issue aims to address these questions, among others, by seeking new methods, models, and resources that advance research in semantic materials science and engineering.

Relevant topics include, but are not limited to:

• Ontological Architectures for Multiscale Physics: The development and alignment of domain ontologies (e.g., crystallography, defects, thermodynamics) or ontology design patterns with top-level or mid-level frameworks (e.g., BFO, EMMO, PMDco) to support cross-domain interoperability.
• Neurosymbolic Material Discovery: Methods that combine KGs with Deep Learning to improve , as e.g., property prediction accuracy.
• Semantic Interoperability in Manufacturing: Utilization of AAS (Asset Administration Shell) and semantic digital twins to map the “Processing-Structure-Property-Performance" (PSPP) interdependencies in real-time industrial environments.
• Automated Knowledge Extraction: Novel pipelines utilizing Natural Language Processing (NLP) and LLMs to extract structured material data (e.g., synthesis recipes, phase diagrams) and ontologies from unstructured scientific text and patents.
• Autonomous Neurosymbolic Research Assistants: Agentic systems that combine LLMs with KGs/ontologies to support or automate materials R&D workflows (e.g., hypothesis generation, experiment planning, literature-to-KG curation, and closed-loop optimization), with semantic grounding, provenance tracking, and verification/guardrails to ensure trustworthy outputs.
• Decentralized Data Marketplaces: Architectures leveraging Linked Data and Solid pods to facilitate the secure, sovereign exchange of proprietary material data between academic and industrial stakeholders.

Submission Guidelines

Submission deadline: December 16, 2026. Papers submitted before the deadline will be reviewed upon receipt.

Submissions should be made through the Semantic Web Journal website at http://www.semantic-web-journal.net. Authors must take notice of the submission guidelines posted at http://www.semantic-web-journal.net/authors.

Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this special issue. Authors can extend previously published conference or workshop papers (cf submission guidelines). Please indicate in the cover letter that it is for the Special Issue on “Semantic Materials Science and Engineering (SMSE)." All manuscripts will be reviewed based on the SWJ open and transparent review policy and will be made available online during the review process.

Also note that the Semantic Web journal is open access and all submissions rely on an open and transparent review process. There is an APC of $2,250. Please see FAQ 3 for more information.

Guest Editors:

• Dr. Ozan Dernek, SDLE Research Center, Case Western Reserve University, Cleveland OH, USA
• Dr. Jennifer D’Souza, Data Science & Digital Libraries Research Group, TIB - Leibniz Information Center for Science and Technology, Hannover, Germany
• Dr. Huanyu Li, Department of Computer and Information Science, Linköping University, Linköping, Sweden
• Prof. Roger H. French, Department of Materials Science and Engineering, Case Western Reserve University, Cleveland OH, USA
• Prof. Patrick Lambrix, Department of Computer and Information Science, Linköping University, Sweden
• Prof. Harald Sack, Department of Information Service Engineering, FIZ Karlsruhe - Leibniz Institute for Information Infrastructure & Karlsruhe Institute of Technology, Karlsruhe, Germany

Guest Editorial Board

• Toshihiro Ashino, Toyo University & NIMS, Japan
• Bernd Bayerlein, BAM, Germany
• Owain Beynon, University College London, UK
• Hossein Beygi Nasrabadi, FIZ Karlsruhe, Germany
• Diego Collorana, Fraunhofer FIT, Germany
• Martin Thomas Horsch, Norwegian University of Life Sciences, Norway
• Emanuele Ghedini, University of Bologna, Italy
• Gerhard Goldbeck, Goldbeck Consulting, UK
• Abril Azocar Guzman, Forschungszentrum Jülich, Germany
• Adham Hashibon, University College London, UK
• Jesper Friis, SINTEF, Norway
• Philipp von Hartrott, Fraunhofer IWM, Germany
• Lars Vogt, Leibniz IABC, Germany
• Markus Schilling, BAM, Germany
• Jörg Waitelonis, FIZ Karlsruhe, Germany
• He Tan, Jönköping University, Sweden
• Patrik Schneider, Siemens AG, Germany & TU Wien, Vienna, Austria
• Anmol Sain, Wright State University, USAi