S. Cottenier

Reactivity of Single Transition Metal Atoms on a Hydroxylated Amorphous Silica Surface: A Periodic Conceptual DFT Investigation

X. Deraet, J. Turek, M. Alonso, F. Tielens, S. Cottenier, P.W. Ayers, B.M. Weckhuysen, F. De Proft
Chemistry - A European Journal
27, 19 , 6050-6063
2021
A1

Abstract 

The drive to develop maximal atom-efficient catalysts coupled to the continuous striving for more sustainable reactions has led to an ever-increasing interest in single-atom catalysis. Based on a periodic conceptual density functional theory (cDFT) approach, fundamental insights into the reactivity and adsorption of single late transition metal atoms supported on a fully hydroxylated amorphous silica surface have been acquired. In particular, this investigation revealed that the influence of van der Waals dispersion forces is especially significant for a silver (98 %) or gold (78 %) atom, whereas the oxophilicity of the Group 8-10 transition metals plays a major role in the interaction strength of these atoms on the irreducible SiO2 support. The adsorption energies for the less-electronegative row 4 elements (Fe, Co, Ni) ranged from -1.40 to -1.92 eV, whereas for the heavier row 5 and 6 metals, with the exception of Pd, these values are between -2.20 and -2.92 eV. The deviating behavior of Pd can be attributed to a fully filled d-shell and, hence, the absence of the hybridization effects. Through a systematic analysis of cDFT descriptors determined by using three different theoretical schemes, the Fermi weighted density of states approach was identified as the most suitable for describing the reactivity of the studied systems. The main advantage of this scheme is the fact that it is not influenced by fictitious Coulomb interactions between successive, charged reciprocal cells. Moreover, the contribution of the energy levels to the reactivity is simultaneously scaled based on their position relative to the Fermi level. Finally, the obtained Fermi weighted density of states reactivity trends show a good agreement with the chemical characteristics of the investigated metal atoms as well as the experimental data.

DOI 

http://dx.doi.org/10.1002/chem.202004660

Hg adatoms on graphene: A first-principles study

A.S. Fenta, C.O. Amorim, J.N. Goncalvez, N. Fortunato, M.B. Barbosa, J.P. Araujo, M. Houssa, S. Cottenier, M.J. Van Bael, J.G. Correia, V.S. Amaral, L.M.C. Pereira
Journal of Physics-Materials
Volume 4 Issue1
2021
A1

Abstract 

The interest in understanding the interaction between graphene and atoms that are adsorbed on its surface (adatoms) spans a wide range of research fields and applications, for example, to controllably change the properties of graphene in electronic devices or to detect those changes in graphene-based sensors. We present a density functional theory study of the interaction between graphene and Hg adatoms. Binding energy, electronic structure and electric field gradient (EFG) were calculated for various high-symmetry atomic configurations, from isolated adatoms to a continuous Hg monolayer. Hg as isolated adatom was found to be the most stable configuration, with a binding energy of 188 meV. Whereas isolated adatoms have a minor effect on the electronic structure of graphene (small acceptor effect), Hg monolayer configurations induce a metallic state, with the Fermi level moving well above the Dirac point (donor behavior). Based on the EFG calculated for the various configurations, we discuss how hyperfine techniques (perturbed angular correlation spectroscopy, in particular) can be used to experimentally study Hg adsorption on graphene.

DOI 

http://dx.doi.org/10.1088/2515-7639/abc31c

Race against the Machine: can deep learning recognize microstructures as well as the trained human eye?

M. Larmuseau, M. Sluydts, K. Theuwissen, L. Duprez, T. Dhaene, S. Cottenier
Scripta Materialia
193, 33-37
2021
A1

Abstract 

The promising results of deep learning in image recognition suggest a huge potential for microscopic analyses in materials science. One major challenge for its adoption in the study of materials is the limited number of images that are available to train models on. Herein, we present a methodology to create accurate image recognition models with small datasets. By explicitly taking into account the magnification and by introducing appropriate transformations, we incorporate as many insights from material science in the model as possible. This allows for a highly data-efficient training of complex deep learning models. Our results indicate that a model trained with the presented methodology is able to outperform human experts.

DOI 

https://dx.doi.org/10.1016/j.scriptamat.2020.10.026

Compact representations of microstructure images using triplet networks

M. Larmuseau, M. Sluydts, K. Theuwissen, L. Duprez, T. Dhaene, S. Cottenier
npj Computational Materials
6, 156
2020
A1

Abstract 

The microstructure of a material, typically characterized through a set of microscopy images of two-dimensional cross-sections, is a valuable source of information about the material and its properties. Every pixel of the image is a degree of freedom causing the dimensionality of the information space to be extremely high. This makes it difficult to recognize and extract all relevant information from the images. Human experts circumvent this by manually creating a lower-dimensional representation of the microstructure. However, the question of how a microstructure image can be best represented remains open. From the field of deep learning, we present triplet networks as a method to build highly compact representations of the microstructure, condensing the relevant information into a much smaller number of dimensions. We demonstrate that these representations can be created even with a limited amount of example images, and that they are able to distinguish between visually very similar microstructures. We discuss the interpretability and generalization of the representations. Having compact microstructure representations, it becomes easier to establish processing–structure–property links that are key to rational materials design.

Open Access version available at UGent repository

DOI 

https://dx.doi.org/10.1038/s41524-020-00423-2

The ABINIT project: Impact, environment and recent developments

X. Gonze, B. Amadon, G. Antonius, F. Arnardi, L. Baguet, J.-M. Beuken, J. Bieder, F. Bottin, J. Bouchet, E. Bousquet, N. Brouwer, F. Bruneval, G. Brunin, T. Cavignac, J.-B. Charraud, W. Chen, M. Côté, S. Cottenier, J. Denier, G. Geneste, P. Ghosez, M. Giantomassi, Y. Gillet, O. Gingras, D.R. Hamann, G. Hautier, X. He, N. Helbig, N.A.W. Holzwarth, Y. Jia, F. Jollet, W. Lafargue-Dit-Hauret, K. Lejaeghere, M.A.L. Marques, A. Martin, C. Martins, H.P.C. Miranda, F. Naccarato, K. Persson, G. Petretto, V. Planes, Y. Pouillon, S. Prokhorenko, F. Ricci, G.-M. Rignanese, A.H. Romero, M.M. Schmitt, M. Torrent, M.J. van Setten, B. Van Troeye, M.J. Verstraete, G. Zérah, J.W. Zwanziger
Computer Physics Communications
248, 107042
2020
A1

Abstract 

Abinit is a material- and nanostructure-oriented package that implements density-functional theory (DFT) and many-body perturbation theory (MBPT) to find, from first principles, numerous properties including total energy, electronic structure, vibrational and thermodynamic properties, different dielectric and non-linear optical properties, and related spectra. In the special issue to celebrate the 40th anniversary of CPC, published in 2009, a detailed account of Abinit was included [Gonze et al. (2009)], and has been amply cited. The present article comes as a follow-up to this 2009 publication. It includes an analysis of the impact that Abinit has had, through for example the bibliometric indicators of the 2009 publication. Links with several other computational materials science projects are described. This article also covers the new capabilities of Abinit that have been implemented during the last three years, complementing a recent update of the 2009 article published in 2016. Physical and technical developments inside the abinit application are covered, as well as developments provided with the Abinit package, such as the multibinit and a-tdep projects, and related Abinit organization developments such as AbiPy . The new developments are described with relevant references, input variables, tests, and tutorials.

DOI 

https://doi.org/10.1016/j.cpc.2019.107042

210Po production in the European DEMO fusion reactor

M.A.J. Mertens, U. Fischer, P. Pereslavtsev, R. Stieglitz, J.-M. Noterdaeme, S. Cottenier
Nuclear Fusion
59 (10), 106029
2019
A1

Abstract 

The radionuclide inventory plays a central role in the safety of nuclear installations both during operation and their decommissioning. In nuclear fusion reactors using Pb-Li tritium breeding blankets, the undesired production of radiotoxic 210Po is still an unresolved safety issue. In this work, neutron transport calculations and inventory calculations are combined to predict the 210Po inventory in a DEMO fusion reactor using either a Helium Cooled Lithium Lead or a Water Cooled Lithium Lead breeding blanket. In order to guarantee that the environmental 210Po release associated with an ex-vessel leak-of-PbLi accident remains below the no-evacuation limit, the 210Po concentration in the Pb-Li should be kept below 1500 appt. It was found that no Pb-Li purification is required to keep the 210Po concentration in DEMO below this limit. However, in case the Pb-Li makes direct contact with water, more volatile Po-containing (oxy-)hydroxides could form. If these species increase the 210Po release rate by more than a factor two, safety measures will be required. Therefore, 210Po generation in DEMO does not pose a hazard in case of a regular ex-vessel leak-of-PbLi accident, unless possibly in case the Pb-Li makes contact with water.

DOI 

http://dx.doi.org/10.1088/1741-4326/ab36aa

Po-Containing Molecules in Fusion and Fission Reactors

M.A.J. Mertens, A. Aerts, I. Infante, J. Neuhausen, S. Cottenier
Journal of Physical Chemistry Letters
10 (11), 2879-2884
2019
A1

Abstract 

Fission and fusion reactors can only play a role in the future energy landscape if they are inherently safe by design. For some reactor concepts, a major remaining issue is the undesired production of radiotoxic 210Po. To filter out the volatile Po species, information on their molecular composition is needed. An experimental characterization is very challenging due to the large required amount of radioactive Po. An alternative quantum chemistry approach was taken to predict the temperature-dependent stability of relevant diatomic Po-containing molecules. Experimental data on lighter analogue molecules was used to establish a well-founded methodology. The relative occurrence of the Po species was estimated in the cover gas of (i) the lead–bismuth eutectic coolant in the accelerator-driven MYRRHA fission reactor and (ii) the Pb–Li eutectic tritium breeder in the DEMO fusion reactor. In both systems, Po is found to occur mainly as PbPo molecules and atomic Po.

DOI 

http://dx.doi.org/10.1021/acs.jpclett.9b00824

Density functional theory study on the B doping and B/P codoping of Si nanocrystals embedded in SiO2

Z.Y. Ni, X.D. Pi, S. Cottenier, D.R. Yang
Physical Review B
95 (7), 075307
2017
A1

Abstract 

Doping silicon nanocrystals (Si NCs) embedded in silicon dioxide (SiO2) with boron (B) and phosphorus (P) is a promising way of tuning the properties of Si NCs. Here we take advantage of density functional theory to investigate the dependence of the structural and electronic properties of Si NCs embedded in SiO2 on the doping of B and P. The locations and energy-level schemes are examined for singularly B-doped or B/P-codoped Si NCs embedded in SiO2 with a perfect or defective Si/SiO2 interface at which a Si dangling bond exists. A dangling bond plays an important role in the doping of Si NCs with B or B/P. The doping behavior of B in Si NCs embedded in SiO2 vastly differs from that of P. The electronic structure of a B/P-codoped Si NC largely depends on the distribution of the dopants in the NC.

Green Open Access

DOI 

http://dx.doi.org/10.1103/PhysRevB.95.075307

Formation, Structures and Electronic Properties of Silicene Oxides on Ag(111)

M. Ali, Z.Y. Ni, S. Cottenier, Y. Liu, X.D. Pi, D.R. Yang
Journal of Materials Science & Technology
33 (7), 751-757
2017
A1

Abstract 

The formation, structural and electronic properties of silicene oxides (SOs) that result from the oxidation of silicene on Ag(111) surface have been investigated in the framework of density functional theory (DFT). It is found that the honeycomb lattice of silicene on the Ag(111) surface changes after the oxidation. SOs are strongly hybridized with the Ag(111) surface so that they possess metallic band structures. Charge accumulation between SOs and the Ag(111) surface indicates strong chemical bonding, which dramatically affects the electronic properties of SOs. When SOs are peeled off the Ag(111) surface, however, they may become semiconductors.

DOI 

http://dx.doi.org/10.1016/j.jmst.2016.08.020

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