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Machine Learning Assisted Atomistic Modelling of Materials and Proteins (MALAMP)

Project
MALAMP aims at bringing together a scientific team of diverse experience in condensed matter physics, chemistry, and biochemistry, with the goal developing new ML interatomic potentials: one is the Cu-Mn-Fe-Co-Ni high-entropy alloy (HEA), which is a more sustainable variant of the well-known Cantor HEA; the second concerns ionic fluorine diffusion in cathodes and solid electrolytes, which could constitute future replacement of lithium in next-generation batteries. A third branch of MALAMP will focus on protein-protein interaction, to identify which specific interface residues of protein–protein complexes form the hot spots, which is critical for understanding the principles of protein interactions.
Machine Learning Assisted Atomistic Modelling of Materials and Proteins (MALAMP)
  • Overview
  • Research Areas

Overview

Contributors (3)

EBERINI IVANO   Scientific Manager  
GUERRA ROBERTO   Scientific Manager  
MARTINAZZO ROCCO   Scientific Manager  

Departments involved (3)

Dipartimento di Fisica Aldo Pontremoli   Principale  
Dipartimento di Chimica   Aggregata  
Dipartimento di Scienze Farmacologiche e Biomolecolari Rodolfo Paoletti   Aggregata  

Type

Progetti PNRR - Bandi a Cascata

Funder

CONSIGLIO NAZIONALE DELLE RICERCHE - CNR
External Organization Funding Organization

Date/time interval

December 16, 2024 - November 30, 2025

Project duration

11 months

Research Areas

Concepts


Settore PHYS-04/A - Fisica teorica della materia, modelli, metodi matematici e applicazioni
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