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Publication in Artificial Intelligence Chemistry

Publication in Artificial Intelligence Chemistry

Publication in Artificial Intelligence Chemistry

Our research paper titled RedPred, a machine learning model for the prediction of redox reaction energies of the aqueous organic electrolytes is published in Artificial Intelligence Chemistry. In this study, we present RedPred, an ML model that predicts the redox reaction energies of molecules. RedPred comprises an ensemble of Artificial Neural Networks, Random Forests, and Graph Convolutional Networks, trained using the RedDB database. In addition, we released a user-friendly web tool with open-source code to promote software sustainability and broad use.

Presentation at Symposium: ‘Circularity: The New Shape of Chemistry’

Presentation at Symposium: ‘Circularity: The New Shape of Chemistry’

Presentation at Symposium: ‘Circularity: The New Shape of Chemistry’

Süleyman will present at the Symposium: ‘Circularity: The New Shape of Chemistry’ on May 21, 2024, 09:00-17:45 at TU/e Auditorium, Blauwe Zaal. His presentation is titled Exploring the chemical space through computational screening and AI to discover molecules for energy storage. This special event is organized by T.S.V. ‘Jan Pieter Minckelers’, also known as ‘Japie’, which is the study association of the department of Chemical Engineering and Chemistry at the University of Technology Eindhoven. Japie is an association run by and for students in order to look after the interests of the students of the department and to provide them with the opportunity to develop themselves. Event link is here.

Colloquium at AMOLF

Colloquium at AMOLF

Colloquium at AMOLF

Süleyman will present at the AMOLF Colloquium on Monday, April 8, 2024 at 13:00-14:30. His presentation is titled Towards Autonomous Discovery of Energy Materials. The presentation will provide an overview of our group’s various research projects that merge AI with computational screening for identifying molecules and materials, which can potentially be used for energy conversion and storage.

4TU.High-Tech Materials Workshop

4TU.High-Tech Materials Workshop

4TU.High-Tech Materials Workshop

Süleyman will present at the Role of Machine Learning in Molecular Discovery & Scientific Understanding workshop at TU Delft on March 21st, 2024. His presentation is titled Towards Autonomous Discovery of Energy Materials. The event will focus on exploring theoretical machine learning research and their real-world applications in molecular and material discovery. You can find the full program and register on the event page here.

Poster presentations at MPIE in Germany

Poster presentations at MPIE in Germany

Poster presentations at MPIE in Germany

Xuan Zhou and Yatong Wang have presented their posters titled: High-throughput computational screening of organic cathode materials for Li/Na-ion batteries and ML-aided computational screening of 2D materials for photocatalytic water splitting, respectively, at the New Horizons in Materials Design Workshop organized by Max-Planck-Institut für Eisenforschung (MPIE) in Düsseldorf, Germany, on 17-18 August 2023. Their posters have received attention from several researchers working on the theory and experiments aimed at the design of materials to address the challenges of the 21st century.

Presentation at DIFFER PhD colloquium

Presentation at DIFFER PhD colloquium

Presentation at DIFFER PhD colloquium

PhD researcher Yatong Wang from our group has given a presentation titled ML-aided computational screening of 2D materials for photocatalytic water splitting at the DIFFER PhD colloquium on June 14th at DIFFER. Yatong’s presentation has received substantial interest from DIFFER researchers of all levels. The research findings are currently under review and will soon be published publicly.

Publication in Digital Discovery

Publication in Digital Discovery

Publication in Digital Discovery

Our manuscript titled Discovery of lead quinone cathode materials for Li-ion batteries has been published in Digital Discovery from the Royal Society of Chemistry (RSC). In this study, we applied machine learning and semi-empirical quantum mechanical methods to study a chemical space of approximately 200,000 compounds for use as cathode materials in Li-ion batteries. Additionally, by performing an automated search on a commercial vendor database, computing battery-relevant properties, and evaluating the structural integrity upon the lithiation process, a total of 349 molecules were identified as potentially high-performing cathode materials for Li-ion batteries. Furthermore, one example of a candidate compound was tested through cyclic voltammetry experiments, which showed highly promising results. 

Publication in Energy Advances

Publication in Energy Advances

Publication in Energy Advances

Our manuscript titled Virtual Screening of Organic Quinones as Cathode Materials for Sodium-Ion Batteries has been published in Energy Advances from the Royal Society of Chemistry (RSC). In this study, we applied a DFT-empowered high-throughput virtual screening study that reckoned with the most essential battery-relevant properties of 448,658 molecules. Among them, we identified 17 highly promising compounds for validation as candidate cathode materials in sodium-ion batteries, which are seen as alternatives to lithium-ion batteries because of the natural abundance, low cost, and high safety of sodium when compared to lithium.

Postdoc AI for Energy Materials

Postdoc AI for Energy Materials

Postdoc AI for Energy Materials

We have open postdoctoral positions for researchers who wish to apply their expertise in machine learning for the design of high-tech energy materials. You will have the opportunity to collaborate with several researchers at DIFFER and to explore novel ideas that will have direct impact on energy transition. See the job description and apply at the DIFFER job portal. For more information concerning the position you may contact [AMD] Group Leader Dr. Süleyman Er. Kindly note that applications must be submitted exclusively via the DIFFER job portal.

Poster presentation at NWO Physics

Poster presentation at NWO Physics

Poster presentation at NWO Physics

Yatong Wang, who is a PhD researcher at our [AMD] group, has presented a poster at the annual Dutch Research Council (NWO) Physics Conference on April 4th, 2023. Yatong’s poster had the title of ML-assisted computational discovery of 2D materials for H2 production. The poster has been well-received though a broad community of researchers and visitors of the conference.