Correlation-Based Framework for Extraction of Insights from Quantum Chemistry Databases: Applications for Nanoclusters. Journal of Chemical Information and Modeling, 2021, 61 (3), 1125-1135. DOI: 10.1021/acs.jcim.0c01267
Machine Learning Prediction of Nine Molecular Properties Based on the SMILES Representation of the QM9 Quantum-Chemistry Dataset. The Journal of Physical Chemistry A, 2020, 124 (47), 9854-9866. DOI: 10.1021/acs.jpca.0c05969
Methane dehydrogenation on 3d 13-atom transition-metal clusters: A density functional theory investigation combined with Spearman rank correlation analysis. Fuel, 2020, 275, 117790. DOI: 10.1016/j.fuel.2020.117790
Ab Initio Insights Into the Formation Mechanisms of 55-Atom Pt-Based Core-Shell Nanoalloys. The Journal of Physical Chemistry, 2020, 124, 1, 1158-1164. DOI: 10.1021/acs.jpcc.9b09561
Ab initio insights into the structural, energetic, electronic, and stability properties of mixed CenZr15-nO30 nanoclusters, Physical Chemistry Chemical Physics, 2019, 21, 26637-26646. DOI: 10.1039/C9CP04762J
Understanding the interplay between π-π and cation-π interactions in [janusene-Ag]+ host-guest systems: a computational approach, Dalton Transactions, 2019, 48, 13281-13292. DOI: 10.1039/C9DT02307K
Ab initio investigation of the formation of ZrO2-like structures upon the adsorption of Zrn on the CeO2(111) surface, The Journal of Chemical Physics, 2018, 149, 244702. DOI: 10.1063/1.5063732
From Bulk CeO2 to Transition-Metal Clusters Supported on the CeO2(111) Surface: A Critical Discussion. In book: Encyclopedia of Interfacial Chemistry, Surface Science and Electrochemistry, 2018, 452-459. DOI: 10.1016/B978-0-12-409547-2.14196-4
