Email: alessandro.fortunelli@cnr.it
Phone: +39 050 315 2447
Site: Pisa
Address: Area della Ricerca CNR di Pisa, Via Moruzzi 1, 56124 Pisa
Education: PhD in Chemistry at Scuola Normale Superiore Pisa (2012); Degree in Chemistry at Scuola Normale Superiore and University of Pisa (1978-1983).
Work Experience: Research Director at National Research Council (CNR), with previous positions at CNR since 1984.
Management: Coordinator and unit leader in the ESF EUROCORES SONS SSATMN project (2003 – 2006); Coordinator and unit leader in the EC FP6 NMP STREP GSOMEN project (2004 – 2007); Unit leader in the ERC-AG SEPON project (2008 – 2013); Member of the Management Committee of the COST Action MP0903 on “Nanoalloys” (2010 – 2014); Unit leader in the EC FP7 NMP LARGE HELM project (2012 – 2016); Unit leader in the EC H2020 FET-Open QUEFORMAL project (2019 –present); Work Package leader in the EC H2020 ITN BIKE project (2019 – present).
Visiting Scientist: California Institute of Technology (Caltech), CA, USA (2003-2004); University of California at Los Angeles (UCLA), CA, USA (2001).
Visiting Associate: California Institute of Technology (Caltech), CA, USA (2012-present).
Tutoring: Member of 5 PhD Committee (UK, 2 Denmark, France, Ireland); scientific evaluator of 12 PhD Thesis (UK, 2 Denmark, France, Ireland, 3 India, 4 Austria).
Other Activities: Peer-reviewer for 22 international journals, including Physical Review Letters, Journal of the Americal Chemical Society, Angewandte Chemie, Nature Chemistry, Nature Communications, Nature Nanotechnology, Chemical Reviews.
Publications: 280+ peer-reviewed publications, 6 book chapters, 1 book edited, 1 special issue edited.
Bibliometric data (WOS, 01/02/2022) results: 294; total citations: 8992; citing articles: 5590; h-index: 46.
Research Interests: theoretical materials science: metal(oxide) nanoclusters/alloys: supported, ligand-protected, in other environments; emergent phenomena in 2D oxides; electrocatalysis; amorphous carbon; transport in 2D materials; CVD/CVI growth. My goal is a predictive computational science of structural, catalytic, magneto-optical, mechanical, and transport properties, with applications in the field of energy and environment.