First principles characterization of defect states in emerging materials for next-generation technology

Information and communication technologies have been historically powered by silicon. The current major worldwide drive for big data, machine learning and quantum computing threatens to overwhelm Si-based resources and architectures. The search for alternative materials and technologies is therefore crucial and it represents a unique opportunity to explore and link materials’ properties and performances in unexplored architectures.

In this upcoming process, many of the emerging candidates for next-generation technology include disrupting solutions for in-memory computing and synaptic electronics, based on chalcogenides, metal-oxides and other non-Si-based materials in their crystalline, amorphous or disordered phases. Characteristic high densities of defect states play a pivotal role in transport in these systems – even more than in traditional electronics – such that defects and traps govern long-term stability and performances of devices. Therefore, describing, identifying, and controlling defect states is crucial to characterize properties of emerging materials and their interplay with non-standard device architectures, as well as to engineer already known materials to improve their application range.

In this colloquium I will present some of the work we have been carrying on in such direction within the European projects INTERSECT and OpenModel. In particular, I will focus on the study of stability, thermodynamics, diffusion and electronic properties of point defects in crystalline GeSe chalcogenide, a promising system for in-memory computing, and TiO₂, well-known material with a wide range of applications spanning form photocatalysis to electrochromics. The investigations have been performed by means of the Quantum ESPRESSO suite of codes and of state-of-the-art high-throughput workflows for first principles condensed matter simulations, part of the AiiDA automated infrastructure.

The seminar is realized in the framework of the funded projects INTERSECT (Grant n. 814487) and OpenModel (Grant n. 953167).