2026年03月23日に日本表面真空学会 #JVSS が【表面科学セミナー2026 実践!インフォマティクスと自律計測の基礎と応用】を開催。講演3件と個別相談会 (現地参加者のみ)。東京都大田区・大田区産業プラザPiOおよびオンラインにて。案内(PDF)は https://www.jvss.jp/_files/hyomen_seminar2026.pdf に、詳細は https://www.jvss.jp/ja/activities/06/detail/00024.html に。
#Seminar #SurfaceScience #MaterialsInformatics
Quick Knowledge Drop — Trend
🔍 What is #MaterialsInformatics?
➡️ Applying machine learning to discover, design & optimise materials
✅ Faster experimentation
✅ Less costly prototyping
✅ Smarter insights from massive datasets
Innovation starts here! 🚀
🌐 https://c2f.lovable.app/
Connected 2 Future - End-to-End Digital Solutions

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Should I use an LLM?, here is an interesting slide that was presented by Professor Anna-Lena Lamprecht in her talk entitled "Advancing Workflow Composition: A Semantic Approach" at the Materials Science and Engineering (MSE) Congress 2024.

#mse #llm #materialsinformatics #semantics

Excited to share our latest work presented at #SeMats2024 at #SEMANTiCS in #Amsterdam, offering valuable insights for #MSE experts to choose the right #ontology for their projects!

Link to the paper:

https://arxiv.org/abs/2408.06034

If you have an #ontology in the domain of #MaterialsScience and #Engineering and you'd like us to evaluate it, feel free to easily add it here:
https://ise-fizkarlsruhe.github.io/mseo.github.io/

#SemanticWeb #MaterialsInformatics #Ontologies #MSE #OntologyEvaluation

@fizise @lysander07 @joerg

The landscape of ontologies in materials science and engineering: A survey and evaluation

Ontologies are widely used in materials science to describe experiments, processes, material properties, and experimental and computational workflows. Numerous online platforms are available for accessing and sharing ontologies in Materials Science and Engineering (MSE). Additionally, several surveys of these ontologies have been conducted. However, these studies often lack comprehensive analysis and quality control metrics. This paper provides an overview of ontologies used in Materials Science and Engineering to assist domain experts in selecting the most suitable ontology for a given purpose. Sixty selected ontologies are analyzed and compared based on the requirements outlined in this paper. Statistical data on ontology reuse and key metrics are also presented. The evaluation results provide valuable insights into the strengths and weaknesses of the investigated MSE ontologies. This enables domain experts to select suitable ontologies and to incorporate relevant terms from existing resources.

arXiv.org

Next proposal submitted 😍.
It was a tiny bit stressful to write it (short deadline) but I actually love the outcome!

Let's hope it gets funded 😅.
#CompChem #MaterialsInformatics

Our group from BAM made a group trip to University of Jena and the group of Silvana Botti to discuss science. 😍 We have been discussing scicene in a hybrid mode for quite some while already!

It was a very exciting day.

#Jena #Science #CondensedMatterTheory #MaterialsInformatics