Simone Di Cataldo

Pubblicazioni

Le pubblicazioni dell'autore sono raggiungibili sul catalogo IRIS tramite il seguente link

ERC

  • PE3_1
  • PE3_6

KET

  • Advanced materials

Interessi di ricerca

More about me: https://dicatals.wordpress.com

I am a condensed matter theorist and non-tenured assistant professor at Sapienza University of Rome, where I study superconductivity, crystal structures, and advanced materials using first-principles simulations.
About me
I started studying physics because I loved solving difficult problems. As I grew up, I also felt a strong urge to contribute, in my own way, to the challenges of climate change and the energy transition. Fascinated by solar panels, I chose to specialize in condensed matter physics during my master’s degree. Later, I had the opportunity to switch to superconductivity—a field that combined my passion for difficult, century-old scientific puzzles (like the quest for room-temperature superconductivity) with coding and the potential to revolutionize energy technologies.
Since then, this motivation has guided my research. I’ve tried to avoid the “when all you have is a hammer, everything is a nail” trap by constantly learning new tools. Over the years, I’ve worked with a variety of computational techniques—Density Functional Theory, Dynamical Mean Field Theory, and ab initio Molecular Dynamics—to study an equally diverse range of materials.
My PhD research focused on high-pressure hydride superconductors, but my interests have expanded to include hydrogen hydrates (complex materials relevant for hydrogen storage with a fascinating phase diagram), nickelates (the first correlated superconductors with a quantitative theory for their phase diagram), and even thermoelectric materials.
Of all aspects of my work, nothing excites me more than hearing from an experimentalist that a material I predicted has been synthesized—and that it shows the properties we anticipated. So far, this has happened four times, and counting.

Keywords

superconductivity
materials science
crystal structure prediction
computational chemistry

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