Interview with Academic Positions
Süleyman Er has recently been interviewed by Academic Positions, a trusted partner of over 2,500 organizations seeking to attract international academic talent. The interview, titled Supercharging Chemicals For Clean Energy, is available at the link here.
Presentation at the Forum on Artificial Intelligence in Research
Süleyman Er will present a talk titled The Use of AI for Autonomous Materials Discovery at the FAIR – Forum on Artificial Intelligence in Research on Wednesday, April 30, 2025. The Department of Materials Physics, Faculty of Sciences, at the Autonomous University of Madrid, Spain, is hosting the event, which will be held in Miraflores de la Sierra, Spain. FAIR offers a comprehensive, interdisciplinary perspective on artificial intelligence, exploring its various applications and implications in scientific research. More information and registration details can be found here.
Poster presentations at NWO ICT.OPEN 2025
Delaram Samani and Maas van Apeldoorn will present their posters, Emulating Self-Driving Labs: Enhancing Workflows and Minimizing Risks and Simulating Self-Driving Labs: Accelerating Research and Minimizing Risks, respectively, at the NWO ICT.OPEN 2025. The conference brings scientists from all ICT research disciplines and industries together to learn, share ideas, and network. The conference will be held at Jaarbeurs in Utrecht on April 16, 2025. You can find the program and registration link here.
Presentation at LabAutomation 2025
Süleyman Er will deliver a talk titled Simulating and Emulating Self-Driving Labs at the LabAutomation 2025. This event provides an excellent opportunity to stay informed and lead the way in these rapidly advancing techniques. FHI LabAutomation 2025 will be held on March 11, 2025, at Congress Center 1931 in Den Bosch, the Netherlands. More information and registration details can be found here.
Poster presentations at NWO Physics 2025
Ceren Tayran and Can Oğuz presented their posters at NWO Physics 2025, held on January 21, 2025, in Eindhoven. This major conference offers a comprehensive overview of physics research in the Netherlands. Their posters, titled Vanadium-Enhanced Tungsten for Fusion Reactors and AI-Driven Bimetal Catalyst Discovery for Green Hydrogen, attracted significant interest from attendees.
PhD Opportunities in Developing a Digital Infrastructure for Self-Driving Labs
2 x PhD Opportunities at DIFFER: Self-Driving Labs in Energy Materials Research – Machine Learning & Digital Twins! 🤖
➡️ Apply here:
PhD Position 1 in Machine Learning: https://www.differ.nl/vacancies/1132453
PhD Position 2 in Digital Twins : https://www.differ.nl/vacancies/1132486
Applications that are not submitted via DIFFER’s online portal will not be accepted.
Postdoc in Computational Modeling for Advanced Nuclear Materials
In our AMD group at DIFFER, we have an opening for a Postdoc in Computational Modeling for Advanced Nuclear Materials, available as of May 1st, 2025 and for a duration of 2 years. Please see the link here for the job description, requirements, and application details. The application deadline is December 31, 2024. Applications that are not submitted via our DIFFER online portal will not be accepted.
Publication in Chemistry-Methods
Our group introduces ChemPrice, an open software tool developed to streamline the process of collecting pricing data from over 100 chemical compound suppliers. ChemPrice ensures consistency in pricing units and provides comprehensive and best-available pricing information for the compounds being searched. In addition to the code highlight titled ChemPrice: A Python Package for Automated Chemical Price Search, published in Chemistry-Methods, we provide open-access source code, a user-friendly web application, and a comprehensive user manual.
Poster presentations at EIRES Energizing Day 2024
Ceren Tayran and Can Oğuz have presented their posters at the EIRES Energizing Day 2024, which took place on November 19, 2024, at Eindhoven University of Technology. Their posters are titled Vanadium-Enhanced Tungsten for Fusion Reactors and AI-Driven Bimetal Catalyst Discovery for Green Hydrogen, respectively. In addition, the day marked a special occasion: the formal integration of the Center for Computational Energy Research (CCER), a collaborative initiative between TU/e and DIFFER, into the EIRES.
Faculty Colloquium at TU Delft ChemE
Süleyman Er has presented at TU Delft ChemE Faculty Colloquium on November 18, 2024. His presentation titled Towards a Self-Driving Lab for Energy Materials Discovery has introduced an overview of our research projects that merge machine learning with high-throughput computational screening for identifying molecules and materials, which can potentially be used for energy conversion and storage. He also presented our new efforts to bridge the gap between virtual material discovery and real lab experiments by developing a self-driving lab for screening heterogeneous catalysts for e-fuels.
PhD Researcher in ML and Physics-Based Modeling for Efficient Electrocatalyst Discovery
In our AMD group at DIFFER, we have an opening for a PhD Researcher in Machine Learning and Physics-Based Modeling for Efficient Electrocatalyst Discovery, for a duration of 4 years. Please see the link here for the job description, requirements, and application details. The application deadline is November 2, 2024.
Presentation at MRS Fall Meeting 2024
Süleyman Er is invited present at the 2024 Materials Research Society (MRS) Fall Meeting in Boston, Massachusetts, USA. His presentation is titled Prediction of 2D materials for energy applications using computational methods. The presentation is part of MRS Symposium MT03-Synthesis of 2D Materials—Theory and Simulation, which focuses on theoretical, computational, and machine learning methods and tools that can assist and guide the design and synthesis of 2D materials beyond graphene.
Presentation at CECAM Flagship Workshop
Süleyman Er is invited present at the CECAM Workshop on Challenges and perspective in computational modelling for fusion reactors, which will take place on October 28 & 29 at the CECAM Headquarters in EPFL, Lausanne, Switzerland. The workshop focuses on the challenges of developing plasma-facing materials for nuclear fusion reactor, which are one of the most promising and sustainable options for providing mankind with a large-scale, carbon-free energy source.
Presentation at Materials Science and Engineering Congress
Süleyman Er will give an online presentation at the MSE Congress 2024, which is a leading international Materials Science and Engineering Congress in Germany. His presentation is titled AI-guided computational identification of 2D materials for energy and it will be broadcasted as part of the Modelling and Simulation session, track M06: Energy Materials Research Driven by Modelling and Simulation, on September 24, at 12:10 (CET). The interactive program of the event can be found here.
Tutorial at GCMAC Workshop
The German Canadian Materials Acceleration Centre is hosting a day-long training workshop on Friday August 9, at Accelerate 2024, focused on the Integration and Automation of Materials Characterization Techniques. The workshop will feature Süleyman Er (DIFFER) among experts who are working on the various aspects of Materials Acceleration Platforms.
Publication in Advanced Energy Materials
We applied a virtual discovery workflow, including machine learning, semi-empirical quantum mechanics, density functional theory, and molecular dynamics calculations, to search for suitable material candidates for lithium-ion battery cathode materials. Among the newly discovered materials, we synthesized one interesting candidate and validated its electrochemical performance. This compound exhibits a higher redox potential than any previously reported within the same group of sulfonamide redox materials. Further information can be found on our recent publication, which is titled Computational and machine learning-assisted discovery and experimental validation of conjugated sulfonamide cathodes for lithium-ion batteries and published in Advanced Energy Materials.
PhD defense: Yatong Wang
Yatong will his doctoral thesis titled Data-driven discovery of 2D materials as photocatalysts for water splitting on Monday July 1, 2024, at 13:30 in TU/e Atlas building room 0.710.
[AMD] welcomes new interns
We have launched four internship projects on the various topics of machine-learning assisted heterogenous electrocatalyst discovery. The projects will be carried out by Haiko Perrier de la Bathie, Nathan Polese, Samuel Mesquita, and Tom Thinel, who are junior researchers visiting our lab from Strasbourg University. We wish all of them success on their new research endeavors.