New projects secure almost half a million core.hours in Navigator cluster
Daniel Gouveia and Gerard Novell-Leruth awarded in the recent FCT Call for Advanced Computing Projects.

The Portuguese Foundation for Science and Technology, as a result of the Call for Advanced Computing Projects, 1st edition, FCT/CPCA/2020/01, has awarded approximately half a million core-hours of computation time to the projects “Epitaxial growth of multimetallic MXenes via nitrogen dissociation” and “Adsorption energies of corrosion inhibitors as smart data to search new protective solutions for aeronautical applications”, submitted by CICECO researchers José Daniel Gouveia and Gerard Novell-Leruth respectively. The CPU time will be available during the next six months and was granted on the Navigator cluster (5,216 cores) at the University of Coimbra, one of the largest in Portugal, which provided 5 million core-hours for this call.

daniel_news.pngDaniel’s project (project access, 420,480 core-hours) aims to model the epitaxial growth of bimetallic transition metal (M) carbide and nitride (X) surfaces (MXenes), by taking advantage of their demonstrated catalytic potential. MXenes are 2D materials discovered very few years ago by researchers at Drexel University, which have been finding application in a wide range of areas, e.g. catalysis, batteries, gas storage, and sensing to cite a few. MXenes can be bimetallic, with one metal element occupying the outer M layers and the other one occupying the remaining inner M layers. Daniel participated in another project that was awarded hundreds of thousands of CPU hours for its calculations, which were performed at the Mare Nostrum supercomputer (165,888 cores), the most powerful in the Iberian Peninsula. In that extensive study, which considered 18 M/X combinations, the researchers concluded that MXenes are excellent catalysts for nitrogen dissociation, strongly adsorbing N2 molecules and potentially reducing the energy required to activate this reaction by over 90 %. The present study will investigate two processes, again using first-principles computational methods: firstly, whether the successive adsorption of N2 in a nitrogen-filled atmosphere is able to create a full layer of nitrogen atoms on the MXenes, and secondly, whether this layer is reactive enough to allow the deposition of a single metallic layer on top of it. Ultimately, if the process described is found to be feasible, it may present itself as a method for experimentally growing multimetallic MXenes.

gerard_news.pngGerard’s project (preparatory access, 50,000 core-hours) aims to model the adsorption energies, over aluminium surfaces, of hundreds of organic molecules, from a database of corrosion inhibitors, to feed the DATACOR project. The DATACOR Project, which seeks to find new corrosion inhibitors for aeronautical applications, was conceived by Groups 3 and 6 of CICECO. A database of 102 potential molecules is considered, using several structural and computational descriptors, to build machine-learning (ML) models that can predict the performance of new systems, in the same way as in a previous publication. The new descriptor for the ML models considers the adsorption energy of each molecule in the database over the Al(111) surface from density functional theory (DFT) calculations. An initial automated screening of conformer adsorption of 102 molecules on the Al(111) surface was performed on the Argus cluster (1,756 cores), using the XTB package. Following this initial step, the researchers now intend to calculate the adsorption energies, using periodic DFT-based models. The efficiency of these calculations will be greatly boosted by employing the NAVIGATOR cluster. As a result, the new descriptor will be implemented in the model generated by artificial intelligence to find the best inhibitors.

These two research projects are in the scope of the activities envisaged for CICECO’s Group 6 in the period 2018-2022. The major goals of Group 6, Computer Simulation and Multiscale Modeling, are the prediction, interpretation and validation of properties of inorganic, organic and hybrid materials by consideration of quantum, classical and numerical simulations.

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