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AI Materials MDPI

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AI Materials MDPI

Kontaktinformationen, Karte und Wegbeschreibungen, Kontaktformulare, Öffnungszeiten, Dienstleistungen, Bewertungen, Fotos, Videos und Ankündigungen von AI Materials MDPI, Herausgeber, Basel.

AI Materials (ISSN 3042-6715) is an international, peer-reviewed, open access journal dedicated to advancing the interdisciplinary frontier of applications between artificial intelligence (AI) and materials science.

03/06/2026

🎉 Welcome our new Editorial Board Member

We are pleased to welcome Prof. Dr. Qing Wang as a new Editorial Board Member of AI Materials MDPI!
https://www.mdpi.com/journal/aimater/editors

📍 Prof. Dr. Qing Wang is affiliated with Dalian University of Technology in Dalian, China.

📍 Her expertise will play a key role in enhancing the journal’s impact and maintaining its high standards.

Please join us in welcoming Prof. Dr. Qing Wang to our Editorial Board. We are excited for this collaboration! 🤝

01/06/2026

🥁 Big news for —we’re thrilled to reveal that Prof. Dr. Danqing Liu, from TU Eindhoven, is our second Plenary Speaker! 🌷

📚 With her broad background in various disciplines (electrical, mechanical, and chemical engineering), Prof. Liu develops materials that sense, feel, and communicate with humans or machines. 📡

🎓 Shortly before joining the TU/e Chemical Engineering and Chemistry department, she also received the Michi Nakata Prize for Early Career Achievements from the International Liquid Crystal Society. 💎

https://brnw.ch/21x2SFa 🔗 Join her from 16–18 September for the 6th International Conference on Materials: From Innovation to Translation. Submit your abstract to be in for actionable insights and long-lasting collaborations! 🤝

28/05/2026

🎉 Welcome our new Editorial Board Member

We are pleased to welcome Dr. José R. B. Gomes as a new Editorial Board Member of AI Materials MDPI!
https://bit.ly/4vdu1OM

📍Dr. José R. B. Gomes is affiliated with CICECO - Aveiro Institute of Materials, Department of Chemistry, University of Aveiro in Aveiro, Portugal

📍His expertise will play an important role in maintaining the high standards and continued growth of the journal.

We are pleased to have Dr. José R. B. Gomes join our Editorial Board and look forward to working together. 🤝

22/05/2026

In a career? Good news! With escalating interest and responses, we're pleased to share that has a new Abstract Submission Deadline—30 June 2026. ⌚

👉 Discover more and submit your abstract here: https://brnw.ch/21x2Hoi

Showcase your stellar work to industry professionals and experts in the field, at a far-reaching event in dazzling ! ⚽

💡 If your submission is nearly there or your just needs a bit more time before sharing it with the public, jump on this final chance to present, connect, and ready for the future of this academic community.

19/05/2026

🎉Welcome our new Editorial Board Member

We are pleased to welcome Prof. Dr. Stephan Roche as a new Editorial Board Member of AI Materials MDPI!
https://bit.ly/3RfYzAJ

Professor Roche is affiliated with CSIC-UAB-GC—Instituto Catalán de Nanociencia y Nanotecnología (ICN2), Spain.

Professor Roche brings valuable expertise and insights, strengthening our efforts to advance high-quality research published in our journal.

We look forward to working together to support the journal’s development and the research community. 🤝

14/05/2026

🥁 Another exciting reveal for : We're thrilled to welcome Prof. Dr. Radha Boya from The University of Manchester as a Keynote Speaker! 🎊

🔬 Exploring the fundamentals and applications of atomic-scale nanocapillaries as a The Royal Society University Research and Kathleen Ollerenshaw fellow, it doesn’t stop there on prestigious international fellowships she’s received. ✨

🏆 In addition to other accolades, Prof. Boya was recognized with a Royal Society of Chemistry Marlow award, and named as an inventor in MIT Technology Review's "Innovators under 35" list. 🔎

https://brnw.ch/21x2sHU 📌 Be sure to catch her powerful insights—Submit your abstract before time runs out to meet her at !

11/05/2026

🎉 Welcome our new Editorial Board Member

We are pleased to welcome Prof. Dr. Doo Yeol Yoo as a new Editorial Board Member of AI Materials MDPI!
https://www.mdpi.com/journal/aimater/editors

Professor Yoo is affiliated with the Department of Architecture and Architectural Engineering, Yonsei University, Republic of Korea

Professor Yoo brings valuable expertise and insights, strengthening our efforts to advance high-quality research published in our journal.

We look forward to working together to support the journal’s development and the research community. 🤝

07/05/2026

🛑 Heads up enthusiasts—the submission deadline on 17 May is just around the corner! 🏁

➡️ Submit your here: https://brnw.ch/21x2fqF

🎮 Join fellow gamechangers in the field by presenting your as a Talk or Poster, and gain an inside scoop into advancements from our Plenary and Keynote Speakers. 💫

🎁 With awards and a publication opportunity available, attendees are in store for an international event with lasting impact, not to mention the host city to enjoy! 🌆

04/05/2026

🌙 We’re over the moon to unveil our next Invited Speaker at , Prof. Dr. Markus Gallei, from Germany’s Universität des Saarlandes - Saarland University! 🦉

🔬 At the Gallei Lab, research is inspired by structures from nature and their outstanding ability to create macroscopic functions by molecular and hierarchically structured design. 📝

📚 His team uses an interdisciplinary concept to create new nanomaterials, which can serve as building blocks for advanced technologies such as photonics, smart membranes, and ceramic templates. 📟

https://brnw.ch/21x25hA 👈 Submit your abstract today to catch his talk and present your own impactful work among thought leaders like him!

27/04/2026

Read the second published paper in AI Materials MDPI!

Spatial Prediction of Electronic Wavefunctions from Reciprocal Lattices: Visualization of Electronic Properties of 2D Materials Using Deep Convolutional Neural Networks
https://bit.ly/4d7QFlr

This research introduces a deep convolutional neural network to predict electronic wavefunctions in real space for 2D materials, achieving prediction accuracies between 62% and 92%. The method is significantly faster than traditional DFT calculations, providing an efficient means to visualize electronic properties and assess local charge density and molecular orbitals in crystalline systems.

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