Integrating high-performance computing, machine learning, data management workflows, and infrastructures for multiscale simulations and nanomaterials technologies

• Fabio Le Piane,
• Mario Vozza,
• Matteo Baldoni and
• Francesco Mercuri

Beilstein J. Nanotechnol. 2024, 15, 1498–1521, doi:10.3762/bjnano.15.119

• digital methodologies in advanced research. Keywords: artificial intelligence; high-performance computing; HPC; machine learning; materials modelling; multiscale modelling; nanomaterials; semantic data management; Introduction Digital technologies have ushered in a new era of materials science, enabling

• infrastructures [41][56]. Multiscale modelling constitutes one of the crucial ingredients for linking a physical description of materials to new digital and data-intensive technologies. Accordingly, multiscale modelling has recently gained popularity as the approach of choice in several application domains where

• relatively low throughput of multiscale modelling approaches in current scenarios. In recent years, however, we have begun to witness the success of AI and ML for materials development [7][13]. This is particularly evident, for example, in the application of AI-related methods for the prediction of structure

Multiscale modelling of biomolecular corona formation on metallic surfaces

• Parinaz Mosaddeghi Amini,
• Ian Rouse,
• Julia Subbotina and
• Vladimir Lobaskin

Beilstein J. Nanotechnol. 2024, 15, 215–229, doi:10.3762/bjnano.15.21

• , particularly concerning its interaction with the most abundant milk proteins and lactose. By employing a multiscale modelling approach, we simulated the interaction between metallic aluminum surfaces and the proteins and lactose, considering different crystallographic orientations. The results of our study

• provide valuable insights into the mechanisms of lactose and protein deposition on aluminum surfaces, which can aid in the general understanding of protein corona formation. Keywords: all atomistic; aluminum; bionano interface; coarse grained model; lactose; milk protein; multiscale modelling; protein

• properties of the nanomaterial, the characteristics of the surrounding medium, and the biological factors at play. A dataflow scheme of the multiscale modelling approach implemented in this study, including an all-atom model of surface and AAs, a CG UnitedAtom model for the entire protein-surface interaction