Researchers at Cnr Nano have developed a groundbreaking computational method that speeds up calculations in two-dimensional semiconductors. This new technique not only accelerates the process but also maintains high accuracy in predictions. The authors of the work published in Nature Computational Materials include Dr Andrea Ferretti and Dr Daniele Varsano, who play a prominent role in the MaX - MAterials design at the eXascale - European Centre of Excellence.
In simpler terms, the scientists have created a method that makes it easier and faster to calculate properties of materials like semiconductors, which are used in electronic devices. The technique combines stochastic averaging and interpolation of the screened potential to quickly achieve accurate results.
The research team tested the method on three prototypical monolayer semiconductors, MoS2, hBN, and phosphorene, and found that it significantly reduces the computational cost without compromising accuracy. This is a major step forward in the field, as it allows for more efficient calculations in materials science.
The new method has been implemented in the Yambo code, one of the MaX flagship codes. Furthermore, the researchers are considering the possibility of extending this methodology to metals and systems with different dimensionalities, such as 1D or 3D, in future research.
Read the full news article at Cnr Nano’s website.
Read the full article at Nature Computational Materials
Article reference:
Guandalini, A., D’Amico, P., Ferretti, A. et al. Efficient GW calculations in two dimensional materials through a stochastic integration of the screened potential. npj Comput Mater 9, 44 (2023).
[Image credit: Matthew Cherny]