Computational Materials Science Laboratory - MEMTi

Laboratory of

Computational Material Science 

The Laboratory focuses on the computational study of novel materials for energy, environmental and bio-technologies, by combining molecular simulations and machine learning techniques.
 
Head (ad interim): Daniela Polino, PhD

SUPSI Image Focus

The Laboratory specializes in the use of computer models for studying and engineering novel materials for energy, environment, and biotechnologies. We develop multiscale molecular models and use advanced simulation techniques that allow the characterization of physico-chemical properties otherwise inaccessible with experimental approaches. 

We carry out the research activities of the laboratory exploiting cutting-edge techniques that range from sub-atomistic to macromolecular scales, which include:
  • quantum mechanics and density functional theory (DFT) calculations,
  • molecular dynamics (MD) simulations at multiple scales: ab initio, atomistic, and coarse-grained,
  • advanced simulation techniques: enhanced sampling, machine learning potentials, non-equilibrium approaches,
  • machine learning and data-driven optimization of models, materials, and processes.

The research of the Laboratory focuses on the understanding of the molecular mechanisms underpinning the technological development of new materials in the areas of energy, environment, and biotechnologies. 

Energy and Environment

  • challenges in the fields of catalysis for the sustainable production of green energy vectors such as hydrogen, ammonia, and synthetic fuels;
  • solid-liquid interface chemistry and physics for the technological development of batteries, electrolyzers, and sustainable omniphobic coatings;
  • chemistry and physics in confined spaces for the advancement of fine-chemistry applications (e.g. sensors, catalyzers, process sustainability improvement).

Biotechnology

  • pharmaceutical nanotechnologies such as the development of drug vectors for specific tissue targeting, as well as improvement of drug specificity;
  • agroalimentary technologies such as the design of new-generation insecticides for green crop preservation;
  • study and development of supramolecular materials and self-assembly towards tissue engineering, regenerative medicine, drug delivery, and molecular encapsulation.  

The main activities of the group range within:
  • quantum mechanics and ab initio MD simulations coupled with advanced simulation techniques which allow to capture the key mechanisms of chemical reactions in complex reactive systems including the dynamical effects of both reactants and environment,
  • classical all-atom (AA) and coarse-grained (CG) MD simulations are combined with enhanced sampling and out of equilibrium techniques to model the structure and dynamic properties of materials and interfaces,
  • machine learning and data-driven methodologies are used for the optimization of engineering processes, molecular models, and the screening of materials properties.

SUPSI Image Focus

SUPSI Image Focus

Hidden Widget