2025

Artificial Intelligence and “Evolving” Databases: a Politecnico di Torino Study Proposes Thousands of New Materials for Energy Applications

We are pleased to share the official press release published by the Politecnico di Torino following the appearance of our peer-reviewed article in Energy and AI. This institutional announcement highlights the research conducted within the SMaLL – Multi-Scale Modeling Laboratory at DENERG and the creation of Energy-GNoME, an “evolving” AI-driven database for energy materials discovery.

Energy-GNoME Featured in Energy and AI

We are pleased to announce that our work "Energy-GNoME: A living database of selected materials for energy applications" has been published in the peer-reviewed journal Energy and AI.

This publication marks a key milestone in the development of Energy-GNoME, presenting the scientific foundation and methodology behind our open, AI-driven database for accelerated discovery of materials for energy applications.

Energy-GNoME Update: Improved Predictive Models for Thermoelectrics and Perovskites

We are excited to announce an update to the Energy-GNoME platform: enhanced machine learning models for both the Thermoelectric and Perovskite databases! These improvements mark a significant step forward in the predictive power and practical utility of our platform, enabling faster and more accurate discovery of high-performance materials.

AI Tools for Material Enhancement and Discovery in Energy Applications — Prof. Eliodoro Chiavazzo at NTU

On 21 May 2025, Prof. Eliodoro Chiavazzo delivered an invited lecture titled “AI Tools for Material Enhancement and Discovery in Energy Applications” at the IAS @ NTU STEM Graduate Colloquium, jointly organised by the Institute of Advanced Studies (IAS), Energy Research Institute @ NTU (ERI@N), and the Graduate Students' Club of MSE at NTU.

Introducing Material-Specific Web Pages in Energy-GNoME

We introduced a new feature that enhances the Energy-GNoME database's usability: dedicated web pages for individual materials! This update brings a significant step forward in how researchers and enthusiasts can explore materials, leveraging advanced visualization tools and property insights and enabling people who are not computational material experts to fully explore the database, alongside the dashboard.