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In our research we use first-principles simulations based on the density-functional theory to understand or predict structural, electronic, optical and dynamical properties of materials. We exploit high-throughput screening techniques (i.e. the design of simulation funnels with increasingly complex steps , that starting from thousands of materials can progressively pinpoint the best materials for a target application) as well as machine learning methods to effectively explore and rationalize the materials space.
Our interests include quantum materials like superconductors and topological insulators especially in the low-dimensional limit (2D and 1D materials).
Contacts: Marco Bernasconi, Davide Campi
Selected bibliography
Selected bibliography
Searching for the thinnest metallic wire, C.Cignarella, D.Campi, N.Marzari, ACS nano 18 (25), 16101-16112 (2024).
High-throughput screening of Weyl semimetals, D.Grassano, N.Marzari, D.Campi, Physical Review Materials 8 (2), 024201 (2024).
Complementary screening for quantum spin Hall insulators in two-dimensional exfoliable materials, D.Grassano, D.Campi, A.Marrazzo, N.Marzari, Physical Review Materials 7 (9), 094202 (2023).
Expansion of the materials cloud 2D database, D.Campi, N.Mounet, M.Gibertini, G.Pizzi, N.Marzari, ACS nano 17 (12), 11268-11278 (2023).
Prediction of Phonon-Mediated Superconductivity with High Critical Temperature in the Two-Dimensional Topological Semimetal W2N3, D.Campi, S.Kumari, N.Marzari, Nano Letters 21 (8), 3435-3442 (2021).
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