Posters list

Below is the final poster list as submitted by the Project Leaders. In case something is wrong or missing, please check first with your Project Leader, who is the person responsible for each poster list. Only the name of the first author is listed here.

Design & Discovery Project 1: Organic Crystals

• Addressing molecular flexiblity of amino acids with machine learning — Edgar A. Engel (COSMO, EPFL)
• An assessment of approximate methods for determining anharmonic free energies — Venkat Kapil (COSMO, EPFL)
• ShiftML: Machine-learning of isotropic chemical shifts — Felix Musil (COSMO, EPFL)
• A transferable machine-learning model of the electron density — Alberto Fabrizio (LCMD, EPFL)
• DORI reveals the influence of noncovalent interactions on covalent bonding patterns in molecular crystals under pressure — Benjamin Meyer (LCMD, EPFL)
• Funnel hopping Monte Carlo: an efficient method to overcome broken ergodicity — Jonas Finkler (University of Basel)
• Molecular dynamics simulations of CO₂ crystallization — Julieta Agustina Trapé (Università della Svizzera Italiana)

Design & Discovery Project 2: Metal Alloys

• Orowan looping in Al-Mg-Si alloys — Yi Hu (LAMMM, EPFL)
• A neural network potential for magnesium — Markus Stricker (LAMMM, EPFL)
• Fast, accurate, modeling of precipitates in Cu containing aluminum alloys with neural network potentials — Daniel Marchand (LAMMM, EPFL)
• High-temperature thermodynamics of Ni alloys with machine learning — Nataliya Lopanitsyna (COSMO, EPFL)
• A look into the ordering at the Ga/GaAs interface with a machine learning potential — Giulio Imbalzano (COSMO, EPFL)
• Kinetic Monte Carlo for complex alloys using machine learning — Albert Glensk (LAMMM, EPFL)
• Efficient computation of many-body density-based atomic descriptors — Max Veit (COSMO, EPFL)

Design & Discovery Project 3: Low Dimensional Materials

• Scattering in 2-D materials: from mobility calculation to device characteristics — Youseung Lee (ETHZ)
• Ab initio simulation of field-effect transistors with novel 2-D material channels — Cedric Klinkert (ETHZ)
• Discovery of novel two-dimensional topological insulators: synergies between simulations and experiments — Antimo Marrazzo (THEOS, EPFL)
• Expansion and characterization of the MARVEL portfolio of 2D materials: high-mobility semiconductors, photocatalysts, membranes, superconductors — Davide Campi (THEOS, EPFL)
• Device integration of low-bandgap graphene nanoribbons — Gabriela Borin Barin (Empa)
• Massive Dirac fermion behavior in a low bandgap graphene nanoribbon near a topological phase boundary — Qiang Sun (Empa)
• Contact engineering and developments in transport theory — Guido Gandus (Empa)

Design & Discovery Project 4: Nanoporous Materials

• Using AiiDA for gas adsorption: open-source, reproducibility and automation — Daniele Ongari (LSMO, EPFL)
• Assessment of a tight-binding method for nanoporous materials — Daniele Ongari (LSMO, EPFL)
• Towards large scale screening for excited states in nanoporous materials — Anna Hehn (University of Zurich)
• Advanced electronic structure methods for nanoporous materials properties calculations — Augustin Bussy (University of Zurich)
• Computational screening of metal-organic-frameworks for applications in photocatalysis — Maria Fumanal (EPFL/IBM)

Design & Discovery Project 5: Correlated Oxides

• Mott solar cells — Francesco Petocchi (University of Fribourg)
• Strain-controlled dimensionality of interface metallicity in LaVO₃/LaTiO₃ multilayers — Sophie Beck (ETHZ)
• DFT+U+V and DFT+DMFT description of defects in SrTiO₃ — Chiara Ricca (University of Bern)
• The coupled structural and electronic metal-insulator transition in rare earth nickelates — Alexander Hampel (ETHZ)
• RNiO₃ perovskites: exploring the T_MIT --> 0 limit — Maximilian Klein (PSI)
• AiiDA workflows to explore functional effects in oxide heterostructures — Chiara Ricca (University of Bern)
• Stabilizing room-temperature magnetic spirals with disorder-induced frustrating defects — Marisa Medarde (PSI)

Design & Discovery Project 6: Topological Materials

• Classification and properties of composite Weyl fermions — Daniel Gosalbez Martinez (C3MP, EPFL)
• Recent developments in WannierTools — Quansheng Wu (C3MP, EPFL)
• Computational prediction of novel bismuth halide topological materials — Shiyu Deng (EPFL/ETHZ)
• Anisotropic exchange interactions in Kitaev materials Na₃Co₂SbO₆ and Na₂Co₂TeO₆ — Vamshi Katukuri (C3MP, EPFL)
• Tight-binding Hamiltonian for twisted bilayer graphene from ab-initio calculations and its twelve-band projection to the basis of Wannier orbitals — Arkadiy Davydov (University of Zurich)
• Observation of type-II Weyl nodes in WP₂ — Sandy Adhitia Ekahana (PSI)
• Spin fluctuation induced Weyl semimetal state in the paramagnetic phase of EuCd₂As₂ — Junzhang Ma (PSI)

Incubator Project 1: Solid-State Ionics

• The solid-state Li-ion conductor Li₇TaO₆: from a computational screening to its experimental characterization — Xi Cheng (PSI)
• Li_4-xGe_1-xP_xO₄ pellet and thin films: a theoretical and experimental study of the Lithium ion conductivity — Elisa Gilardi (PSI)
• Modeling and screening Li-ion conductors for solid-state electrolytes — Leonid Kahle (THEOS, EPFL)
• Sulfide and oxide LGPS-type superionics from first-principles simulations and experimental characterization: conductivity and elastic properties — Giuliana Materzanini (THEOS, EPFL)
• Computational methods for solid-state electrolyte characterization — Aris Marcolongo (IBM Research - Zurich)
• AiiDA workflows for solid-state electrolyte characterization — Tobias Binninger (IBM Research - Zurich)

Incubator Project 2: Machine Learning

• Learning property-invariant chemical subspaces for molecule screening — Mario Wieser (University of Basel)
• Structured exploration of the chemical space with deep archetypes — Mario Wieser (University of Basel)
• QML: a Python framework for Quantum Machine Learning — Anders Christensen (University of Basel)
• Operators in machine learning: response properties in chemical space — Anders Christensen (University of Basel)
• Alchemical and structural distribution based representation for universal quantum machine learning — Felix Faber (University of Basel)
• Correcting the non-covalent interaction errors of density functionals by conventional and machine learning methods —Pál Dániel Mezei (University of Basel)
• Atom-density representations for atomistic machine learning — Michael Willatt (COSMO, EPFL)

Open Science Platform

• AiiDA - Towards exascale computing through automated workflows with full data provenance — Casper W. Andersen (THEOS, EPFL)
• Materials Cloud: A web portal to foster Open Science in MARVEL and beyond — Snehal Kumbhar (THEOS, EPFL)
• AiiDA lab - a cloud collaborative environment to develop, execute and share scientific workflows — Aliaksandr Yakutovich (LSMO/THEOS, EPFL)
• Examples of on surface chemistry within AiiDA lab — Kristjan Eimre (Empa)
• Charged excitations and band structures from Koopmans spectral functionals — Nicola Colonna (PSI)
• Hubbard interactions from density-functional perturbation theory and application to complex oxides — Iurii Timrov (THEOS, EPFL)

HPC and Future Architectures

• SIRIUS: a domains specific library for GPU accelerated DFT — Anton Kozhevnikov (CSCS/ETHZ)
• Exploring robust optimization: combining rapid prototyping in Python with GPU accelerated backends — Simon Pintarelli (CSCS/ETHZ)
• Curated database of crystal structures through high-throughput DFT computation — Sebastiaan Huber (THEOS, EPFL)