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Physics, Accuracy and Machine Learning: Towards the next-generation of Molecular Potentials

Project description

Gaining a stronger understanding of weak intermolecular interactions

Experts in chemical physics, intermolecular interactions, simulation, and machine learning will come together to develop accurate molecular potentials that can impact a wide range of applications, including protein folding, charge transfer, and interstellar gas clouds. This will be carried out by the PHYMOL project, with the support of the Marie Skłodowska-Curie Actions programme. PHYMOL aims to improve our understanding of weak intermolecular interactions in significant physical-chemical processes and provide a comprehensive training programme in this field. Overall, the project is a significant step towards providing a much needed training programme for the next generation of researchers capable of developing accurate molecular potentials.

Objective

Weak intermolecular interactions are the driving force of relevant processes including protein folding, charge transfer through solid state junctions in solar cells and collisions in interstellar gas clouds. Understanding the nature of these forces is essential to achieve better control and optimization of these processes. Nowadays, modelling has become an essential tool for unravelling experiments and aiding materials design. However, the accurate description of weak interactions is plenty of challenges for many theoretical approaches. Atomistic simulations can help decipher the mechanisms underlying complex processes nonetheless precise molecular potentials are required to achieve a quantitative and qualitative description of these physical-chemical processes.

Despite the importance of this field, there is, at present, no systematic and comprehensive training in this subject, particularly in the fundamentals of the theory, method development, techniques to rigorously test the theory using experimental data, and the creation of new models using detailed physical understanding combined with machine-learning. The PHYMOL network aims to fill in this fill this gap by bringing together a group of experts in the field of chemical physics, intermolecular interactions, simulation and machine-learning with several industrial and academic partners. This program will exploit the synergies between an accurate description of intermolecular interactions and the use of machine learning techniques towards the generation of new molecular potentials. Combining scientific investigation with an intensive training program PHYMOL will help shape a new generation of researchers with the capability of developing accurate molecular potentials impacting a broad range of applications.

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Topic(s)

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HORIZON-TMA-MSCA-DN - HORIZON TMA MSCA Doctoral Networks

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Call for proposal

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(opens in new window) HORIZON-MSCA-2021-DN-01

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Coordinator

UNIWERSYTET MIKOLAJA KOPERNIKA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 453 024,00
Address
UL. JURIJA GAGARINA 11
87-100 TORUN
Poland

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Region
Makroregion północny Kujawsko-pomorskie Bydgosko-toruński
Activity type
Higher or Secondary Education Establishments
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Total cost

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Participants (8)

Partners (12)

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