3 citations · 4 across the 8 of their papers we have counts for
8 papers
Atomic Scale Ordering of Sulfur Vacancies Enhances Charge Transport in Monolayer MoS
Alessandro Pecchia, Andrea Lorenzoni, Alexander Croy +2
Defect engineering in two-dimensional semiconductors has primarily focused on controlling the nature and concentration of atomic defects. Here, we show that the spatial arrangement…
Materials Informatics Across the Length Scales
Jamal Abdul Nasir, Hamide Kavak, Oguzhan Der +8
Materials informatics is increasingly used to support modelling, analysis and design across the length scales of materials science, from atomistic simulations to microstructural ch…
MAMBO: a lightweight ontology for multiscale materials and applications
Fabio Le Piane, Matteo Baldoni, Mauro Gaspari +1
Advancements of both computational and experimental tools have recently led to significant progress in the development of new advanced and functional materials, paralleled by a qui…
Molecular and Materials Basic Ontology: development and first steps
Fabio Le Piane, Matteo Baldoni, Mauro Gaspari +1
Advanced materials and their applications have become a key field of research, and it looks like this trend is not going to change soon. For that reason, the need for systematic an…
Introducing MAMBO: Materials And Molecules Basic Ontology
Fabio Le Piane, Matteo Baldoni, Mauro Gaspari +1
Recent advances in computational and experimental technologies applied to the design and development of novel materials have brought out the need for systematic, rational and effic…
Novel two-dimensional materials for electronics: computational modelling as a tool to enable the use of phosphorene in real applications
Francesco Mercuri
Two-dimensional and layered materials, such as graphene, have emerged in recent years for their potential use in several applications in technology, for example in electronics, bio…
Predicting the properties of molecular materials: multiscale simulation workflows meet machine learning
Fabio Le Piane, Matteo Baldoni, Francesco Mercuri
Machine Learning tools are nowadays widely applied extensively to the prediction of the properties of molecular materials, using datasets extracted from high-throughput computation…
Early steps in the formation of the interface between organic molecular semiconductors and metals: a computational approach
Francesco Mercuri
A computational approach for predictive simulations of the nanoscale morphology in the early steps of the formation of the interface between metals and organic molecular semiconduc…