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Wed 20 |
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Thu 21 |
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Parallel Session – PhD Students I - Room C & Auditorium - Computational Materials Modeling & Simulation |
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Chairperson: Christina Schenk (IMDEA Materials Institute, Spain) |
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08:30-08:40 |
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Balance between precision and scalability: Kinetic Monte Carlo Simulation of Electrodeposition Processes |
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Efe Mehmet Peker,
Bundesanstalt für Materialforschung und-prüfung (BAM), Germany |
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08:40-08:50 |
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From Oligomers to entangled Polymers: How transferable are Machine Learning Interatomic Potentials? |
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Mirko Fischer,
University of Münster / Institute for Physical Chemistry, Germany |
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08:50-09:00 |
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Towards Scalable Gallium Selenide Epitaxy on Graphene: A Multiscale DFT-KMC Framework for Optimizing Growth Conditions |
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Rayen Ben Ismail,
University of Nottingham, UK |
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09:00-09:10 |
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Screening Energetically Stable Structures in Solid-State Ionics Applications |
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Alex Teruel,
Basque Center for Applied Mathematics, Spain |
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09:10-09:20 |
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Data-Driven Exploration of Thermal and Elastic Properties in Covalent Organic Frameworks |
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Aleksander Szewczyk,
TU Dresden, Germany |
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09:20-09:30 |
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Limitations of cluster-trained MLIPs for liquid density and diffusivity |
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Viktor Svahn,
Uppsala university, Sweden |
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09:30-09:40 |
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Predicting Crystal Structures and Ionic Conductivities in Li3YCl6−xBrx Halide Solid Electrolytes Using a Fine-Tuned Machine Learning Interatomic Potential |
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Jonas Böhm,
ICMCB-CNRS, France |
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09:40-09:50 |
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Fine-Tuned Ab Initio–Trained MACE Model for Predictive Mechanical Modeling of Graphene Oxide |
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Sara Shahbazi Fashtali,
Sapienza Università di Roma, Italy |
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09:50-10:00 |
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A Multi-Scale Mixture of Experts Model for Structural Prediction of Cu Nanoparticles |
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Yunyu Zhang,
University College London, UK |
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10:00-10:10 |
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Discovery and recovery of crystalline materials with property-conditioned transformers |
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Cyprien Bone,
University College London, UK |
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10:10-10:20 |
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Fourier Transformers for Latent Crystallographic Diffusion and Generative Modeling |
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Elohan Veillon,
Université d´Artois, France |
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Parallel Session – PhD Students II - Room María Fernández del Amo - Machine Learning, Optimization & Predictive Properties |
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Chairperson: Joaquín Muñoz Rodríguez (Bird & Bird LLP, Spain) |
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08:30-08:40 |
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ML-SAPIE: An Autonomous Workflow Bridging High-Throughput DFT and Machine Learning for Surface Interface Discovery |
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Mary Tabut,
Sorbonne University, France |
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08:40-08:50 |
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MAD-SURF: a general machine-learning interatomic potential for molecular adsorption on metal surfaces |
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Manuel González Lastre,
Universidad Autónoma de Madrid, Spain |
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08:50-09:00 |
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Benchmarking Bandgap Prediction in Semiconductors under Experimental and Realistic Evaluation Settings |
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Haolin Wang,
University of Sheffield, UK |
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09:00-09:10 |
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Generative Pseudo-Force Fields for Structure Generation |
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Stefaan Hessmann,
TU Berlin, Germany |
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09:10-09:20 |
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Machine learning aided, closed-loop optimization of electrodeposition processes in a Material Acceleration Platform |
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Mert Ozan,
Federal Institute for Materials Research and Testing(BAM), Germany |
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09:20-09:30 |
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From Prompt to Protocol: Fast Charging Batteries with Large Language Models |
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Ge Lei,
Imperial College London, UK |
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09:30-09:40 |
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MAESTRO: An AI agent orchestrator for battery materials discovery |
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Sheares Toh,
Imperial College London, UK |
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09:40-09:50 |
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Lattice thermal conductivity on argyrodite compounds Ag8TS6 (T= Si, Ge and Sn): Experimental and Theoretical approach |
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Joana Cecibel Bustamante Pineda,
Federal Institute for Materials Research and Testing (BAM), Germany |
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09:50-10:00 |
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LeMat-Rho: High-Fidelity Charge Density Dataset for Machine Learning and Atomistic Materials Modeling |
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Mathilde Franckel,
Imperial College London, UK |
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10:00-10:10 |
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Machine Learning driven insight into Bonding Heterogeneity Effects on Thermal Conductivity |
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Aakash Ashok Naik,
Federal Institute for Materials Research and Testing (Bundesanstalt für Materialforschung und -prüfung), Germany |
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10:10-10:20 |
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Machine Learning Accelerators for Quantum Transport |
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Luke Keenan,
Trinity College DUblin, Ireland |
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10:20-10:30 |
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Generative Artificial Intelligence for Inverse Materials Design |
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Junwu Chen,
EPFL, Switzerland |
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10:30-11:00 |
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Coffee Break / Poster Session /Exhibition |
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Plenary Session - Auditorium |
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Chairperson: Milica Todorovic (University of Turku, Finland) |
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11:00-11:20 |
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INVITED |
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Helium Effect on Self-Healing at Tungsten Grain Boundaries Using a DFT-Based Machine Learning Interatomic Potential |
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Roberto Luis Iglesias Pastrana,
Universidad de Oviedo, Spain |
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11:20-11:35 |
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Modelling the interplay between vibrations and disorder in crystalline materials |
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Kasper Tolborg,
Aalborg University, Denmark |
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11:35-11:50 |
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Digital experiments for molecular passivation of hybrid perovskite surfaces |
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Laura-Bianca Pasca,
University of Oxford, UK |
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11:50-12:10 |
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INVITED |
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MaterialEyes — Seeing the Invisible using Experiment, Theory, and AI |
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Maria K. Chan,
Argonne National Laboratory, USA |
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12:10-12:25 |
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Multi-Modal Artificial Intelligence for Molecular Structure Identification using Infrared and Raman Spectroscopy |
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Javier Heras Domingo,
Universitat de Barcelona, Spain |
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12:25-12:40 |
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Predictions and/or insight? - ML and physics-based NMR and IR spectroscopy for water in, and on, crystals |
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Jolla Kullgren,
Chemistry - Ångström, Uppsala University, Sweden |
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12:40-12:55 |
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TriForces: Augmenting Atomistic GNNs for Transferable Representations |
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Joseph Musielewicz,
Entalpic, France |
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12:55-13:15 |
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INVITED |
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Machine-learning materials science |
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Miguel Marques,
Ruhr Universitat Bochum, Germany |
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13:15-13:35 |
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INVITED |
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Deformation-trained Deep Potential model for superionic water ice: transferability from stress-strain data to phase equilibria |
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Maurice de Koning,
Instituto de Física Gleb Wataghin, Brazil |
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13:35 |
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Closing & AI4AM2027 announcement |
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