Conference on Frontiers in Atomistic Simulations: from Physics to Chemistry and Biology | (smr 4098) (08-12 September 2025)

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Contribution List

Displaying 62 contributions out of 62

Universal Machine Learning Kohn-Sham Hamiltonian and its application

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A Symphony of Motion in Heterogeneous Catalysis: Moving Beyond the Active Site Paradigm

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Ab-initio Molecular Dynamics of Ferroelectrics

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Automatic Reaction Discovery by Biasing Deep-Learned Skewed Distributions

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- Giovanni_Maria_Piccini.pdf

Avoiding Rare Events: Insights into the Polymorphism of Molecular Crystals Without Sampling Phase Transitions

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Beyond the Debye-Hückel Limit: Towards a General Theoretical Framework for Concentrated Electrolytes

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Brain injury and cancer, two sides of the same coin?

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Buffer / Announcements

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Closing remarks

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Concluding Words

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Data-efficient Deep Potential for Enhanced Sampling Simulations of Complex Systems

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Effect of Collective Dynamics and Anharmonicity on Entropy in Heterogenous Catalysis: Building the Case for Advanced Molecular Simulations

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- Abstract-ICTP.docx

Electronic stopping in liquid water, vapor, ice, and DNA from TDDFT

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Enhanced sampling and ML potentials applied to surface chemistry from the lab next door

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Fast and Accurate Absolute Binding Free Energies of Ligand–Protein/RNA Complexes: From L-ABF to L-ABF-OPES

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Four Generations of High-Dimensional Neural Network Potentials

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From Global Potential Energy Surface to Generalized Global Neural Network Potential：A Path to AGI in Chemistry

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From Stability to Dissociation: Elucidating Unbinding Kinetics of Protein-Protein Complexes via Atomistic Simulations

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Have you tried turning it off and on again? Stochastic resetting for enhanced sampling

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- Barak_Hirshberg.pdf

Homage to Seymour Cray: Architect and Builder of Supercomputers

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- Abstract_-_Michael_L._Klein.pdf

ICTP Introduction

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Integrating Unbiased Path Sampling with Biased Enhanced Sampling for Rare-event Kinetics

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- DhimanRay.pdf

Integrative structural biology in the era of Artificial Intelligence

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Inverse Materials Design Enabled by Universal Machine Learning Potential

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Learning to react: transfer and active learning for interatomic potentials

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MD simulations of biological systems

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Machine Learning Potentials for Phase Change Materials for Electronic Memories

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- Marco-Bernasconi.pdf

Machine-Learned Potentials from Multireference Electronic Structure Calculations for Reaction Dynamics

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Machine-learned approaches to study the dynamic fluctuations local structure of actinides in molten salts

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- ICTP_Abstract-VAG.pdf

Making sense of biomolecular trajectories in the exascale era

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Modeling biomolecular structure and interactions in cellular condensates

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Modeling electrified oxide-electrolyte interfaces using machine learning simulations

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Molecular transport phenomena with metadynamics and beyond

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Needles or Platelets? How Temperature Shapes Ice Crystals

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PLUMED: A community project for enhanced sampling

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- Gareth_Tribello.pdf

Poster session

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Poster session

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Pushing the Frontier of Coarse-grained Modeling

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Quantum Light–Matter Effects in Chemistry: An Ab Initio QEDFT Approach

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Redox Versatility of [4Fe-4S] Clusters: A Computational and Statistical Inquiry

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- Simone_Raugei.pdf

Simulation recipes from the Parrinello family cookbook

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- Michele_Ceriotti.pdf

Structure, dynamics and photochemistry at ice surfaces

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The Unseen Architect: How Water Shapes Biomolecular Processes

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The weird and wonderful World of Catalysis and how I got there

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- Abstract_M.Parrinello.pdf

Towards fully dynamical docking via molecular dynamics and related methods

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Towards unified representation learning and sampling

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Uncovering Kinetic Pathways of Pressure-Induced Structural Phase Transitions by Metadynamics

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Understanding crystallization with ab initio machine learning simulation

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- PabloPiaggi.pdf

Understanding phase transition in materials through machine learning aided molecular simulation

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Unveiling the Functional Dynamics of G Protein-Coupled Receptors through Free-Energy Calculations

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What is the difference of the thermodynamics of a crystal under hydrostatic stress and a liquid?

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Organizers

Giovanni Bussi (SISSA), Paolo Carloni (FZJ), Alessandro Curioni (IBM Research Zurich), Marco De Vivo (Istituto Italiano di Tecnologia), Giulia Galli (The University of Chicago), Francesco Luigi Gervasio (University of Geneva), Xingao Gong (Fudan University), Alessandro Laio (SISSA), Vittorio Limongelli (USI Lugano), Carmen Rovira (University of Barcelona), Erio Tosatti (ICTP & SISSA), Local Organiser: Ali Hassanali (ICTP)

Co-sponsors

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