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Professor Stefano Sanvito

Professor of Condensed Matter Theory (Physics)
Director of CRANN (CRANN)
 (3531896) 3065
CRANN
      
Profile Photo

Professor Stefano Sanvito

Professor of Condensed Matter Theory (Physics)
CRANN

 Stefano.Sanvito@tcd.ie

 3531896 3065

Director of CRANN (CRANN)

 (3531896) 3065


At the beginning of year 2002 I moved from University of California Santa Barbara to the Trinity College Dublin, creating the "Computational Spintronics Group" within the Physics Department. The main research focus of the group is to study theoretically spin transport at the nanscale level. The group at present comprises two postdoctoral researchers, six PhD students and several undergraduate and summer students. We established the "Computational Spintronics Lab." with nine state of the art PC workstations. The purchase of a large LinuX-based cluster is at present under tender. We maintain several collaborations locally and internationally with frequent visits to Dublin from our collaborators. In year 2003/2004 we host an equivalent of about two months visit. In the two years 2002-2004 we have published over ten publications in peer reviewed journals, two book chapters, several conference proceedings, and we have submitted an Irish patent. Recently we received fundings from Science Foundation of Ireland, Enterprise Ireland and the High Education Authority, for a total of about 1,5 Million Euro over the next five years. This ranks us as probably the largest and best funded single PI Computational Materials Science group in Ireland.
  Computer Modelling   Condensed Matter   Condensed Matter Theory   Electronic/Optical Materials   Magnetic Materials   Magnetics   Materials Sciences   Mathematical Modelling   Nanotechnology   Physics   Semiconductors   Theoretical Physics
Project Title
 Precise Scientific Information Extractor for accelerating materials discovery
From
25/09/2023
To
24/11/2023
Summary
The project aims at investigating the viability of a new spinout company that will develop a suit of natural language processing (NLP) algorithms for the precise extraction of materials properties from scientific literature. This will enable the creation of large datasets of materials properties and, most importantly, their interrelations, enabling the construction of large machine-learning (ML) models for materials design. The extracted data will be of a quality sufficient to enable downstream tasks, such as the construction of machine-learning models for materials design
Funding Agency
Enterprise Ireland
Programme
Feasibility Programme
Project Title
 InfoMatDesign: Precise Information Extraction through Natural Language Processing for Materials Design and Materials Market Intelligence
From
15/08/2024
To
14/08/2026
Summary
Precise Information Extraction through Natural Language Processing for Materials Design and Materials Market Intelligence
Funding Agency
Enterprise Ireland
Programme
Manufacturing, Energy and Food Commercialisation
Project Title
 Multiscale Corrosion Modeling for the Oil & Gas Industry
From
15/03/2020
To
15/03/2024
Summary
Funding Agency
Qatar National Research Fund ("QNRF")
Project Title
 ML-transport: machine-learning accelerators for quantum transport
From
02/09/2024
To
31/08/2028
Summary
In "ML-transport: machine-learning accelerators for quantum transport" we propose to combine machine-learning methods for predicting the charge density in a density functional theory (DFT) calculations with quantum transport theory. This will allow us to achieve a thousand-fold computational speedup, thus making the evaluation of finite-temperature transport possible
Funding Agency
Research Ireland
Programme
Government of Ireland Postgraduate Scholarship
Project Title
 Voltemag
From
01/11/2022
To
30/10/2024
Summary
Voltage-Controlled Electronic and Magnetic Phase Transitions in Nano-Devices based on Correlated Mott Materials
Funding Agency
EU
Programme
Marie Curie

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Language Skill Reading Skill Writing Skill Speaking
English Fluent Fluent Fluent
Italian Fluent Fluent Fluent
Details Date From Date To
Member of the Americal Physical Society
Organizer of the symposium on "spin injection into semiconductors" at JEMS 2004
Collaborator for Contemporary Physics
Reviewer for Physical Review B, Physical Review Letters, The European Physical Journal B, Europhysics Letters, Journal of Physics C: Condensed Matter, Semiconductor Science and Technology, Journal of Computational and Theoretical Nanoscience
Organizer of the "Magnetism and spin injection in semiconductors" symposium at the 2004 Joint European Magnetic Symposia (Dresden)
Member of the editorial board of "Journal of Computational and Theoretical Nanoscience"
Co-organizer of the "Spintronics" session at the 2003 Electronic Materials Conference
Declan Nell, Stefano Sanvito, Ivan Rungger, Andrea Droghetti, Effect of dynamical electron correlations on the tunnelling magnetoresistance of Fe/MgO/Fe(001) junctions, Physical Review B, 111, (3), 2025, Journal Article, PUBLISHED  DOI
Simonian, Tigran and Roy, Ahin and Bajaj, Akash and Dong, Rui and Lei, Zheng and Sofer, ZdenÄ k and Sanvito, Stefano and Nicolosi, Valeria, Elucidating the role of stacking faults in TlGaSe2 on its thermoelectric properties, npj 2D Materials and Applications, 9, (1), 2025, Notes: [Cited by: 0], Journal Article, PUBLISHED  DOI
Lin, Dongying and Zou, Jijie and Dong, Yangyu and Wang, Yudi and Wang, Yongfeng and Sanvito, Stefano and Hou, Shimin, Transformer-based deep learning structure-conductance relationships in gold and silver nanowires, Physical Chemistry Chemical Physics, 27, (15), 2025, p7728 â€" 7739 , Notes: [Cited by: 0], Journal Article, PUBLISHED  DOI
Benini, Mattia and Shumilin, Andrei and Kabanov, Viktor and Rakshit, Rajib Kumar and Sahoo, Antarjami and Halder, Anita and Droghetti, Andrea and Cugini, Francesco and Solzi, Massimo and Bisero, Diego and Graziosi, Patrizio and Riminucci, Alberto and Bergenti, Ilaria and Singh, Manju and Gnoli, Luca and Sanna, Samuele and Cinchetti, Mirko and Mertelj, Tomaz and Sanvito, Stefano and Dediu, Valentin Alek, Collapse of the standard ferromagnetic domain structure in hybrid Co/Molecule bilayers, Nature Communications, 16, (1), 2025, Notes: [Cited by: 0], Journal Article, PUBLISHED  DOI
Mitchell, Michael A. J. and Sanvito, Stefano and Jones, Lewys, Rapid eigenpatch utility classifier for image denoising, Scientific Reports, 15, (1), 2025, Notes: [Cited by: 0; All Open Access, Gold Open Access], Journal Article, PUBLISHED  DOI
Suman Hazra, Urvesh Patil, Stefano Sanvito, A charge-density machine-learning workflow for computing the infrared spectrum of molecules, The journal of Cheimcal Physics, 113, 2025, p174104-, Journal Article, PUBLISHED  DOI
Eoghan Cronin, Rajarshi Tiwari, Stefano Sanvito, Machine learning semilocal exchange-correlation functionals for Kohn-Sham density functional theory of the Hubbard model, Physical review B, 112, 2025, p195103-, Journal Article, PUBLISHED  DOI
Anita Halder, Durga Paudyal, Stefano Sanvito, Martin TakÃ¡Ä , Huseyin Ucar, Machine learning-driven discovery of hard magnetic materials using high-throughput computation and screening, Acta Materialia, 297, 2025, p121347-, Journal Article, PUBLISHED  DOI
Michelangelo Domina, Stefano Sanvito, General formalism for machine-learning models based on multipolar spherical harmonics, Physical Review B, 112, 2025, p085106-, Journal Article, PUBLISHED  DOI
Luke P. J. Gilligan, Matteo Cobelli, Valentin Taufour, Stefano Sanvito, Author Correction: A rule-free workflow for the automated generation of databases from scientific literature, npj Computational Materials, 10, (1), 2024, Journal Article, PUBLISHED  DOI  URL
  

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Peng Jiang, Lili Kang, Xiaohong Zheng, Zhi Zeng, and Stefano Sanvito, Computational prediction of a two-dimensional semiconductor SnO2 with negative Poisson's ratio and tunable magnetism by doping, Physical Review B, 2020, Journal Article, PUBLISHED
Aaron Hurley, Nadjib Baadji, Stefano Sanvito, A pertubative approach to the Kondo effect in magnetic atoms on nonmagnetic substrates, 2011, Journal Article, SUBMITTED
A. Filippetti, C. D. Pemmaraju, P. Delugas, D. Puggioni, V. Fiorentini, S. Sanvito, A variational pseudo-self-interaction correction approach: ab-initio description of correlated oxides and molecules, 2011, Journal Article, SUBMITTED

  


Award Date
Elected 'Cavaliere della Stella d'Italia', Knight of the Italian Star February 2017
Elected Member of the Royal Irish Academy May 2016
Fellow of the Institute of Physics (UK) April 2013
2007 IUPAP Young Scientist Prize in Computational Physics September 2007
Fellow of Trinity College April 2006
Spin-transport at the atomic scale Density functional study of electronic and transport properties of spintronics materials and in particular of III-V diluted magnetic semiconductors Development of analytical and numerical techniques for quantum electronic transport using ab initio methods Density functional theory methods for strongly correlated electrons Transport properties of magnetic hybrid systems and carbon nanotubes