“Direct visualization of irreducible ferrielectricity in crystals”. Du K, Guo L, Peng J, Chen X, Zhou Z-N, Zhang Y, Zheng T, Liang Y-P, Lu J-P, Ni Z-H, Wang S-S, Van Tendeloo G, Zhang Z, Dong S, Tian H, npj Quantum Materials 5, 49 (2020). http://doi.org/10.1038/S41535-020-00252-Y
Abstract: In solids, charge polarity can one-to-one correspond to spin polarity phenomenologically, e.g., ferroelectricity/ferromagnetism, antiferroelectricity/antiferromagnetism, and even dipole-vortex/magnetic-vortex, but ferrielectricity/ferrimagnetism kept telling a disparate story in microscopic level. Since the definition of a charge dipole involves more than one ion, there may be multiple choices for a dipole unit, which makes most ferrielectric orders equivalent to ferroelectric ones, i.e., this ferrielectricity is not necessary to be a real independent branch of polarity. In this work, by using the spherical aberration-corrected scanning transmission electron microscope, we visualize a nontrivial ferrielectric structural evolution in BaFe2Se3, in which the development of two polar sub-lattices is out-of-sync, for which we term it as irreducible ferrielectricity. Such irreducible ferrielectricity leads to a non-monotonic behavior for the temperature-dependent polarization, and even a compensation point in the ordered state. Our finding unambiguously distinguishes ferrielectrics from ferroelectrics in solids.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
DOI: 10.1038/S41535-020-00252-Y
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“Burning questions of plasma catalysis: Answers by modeling”. Bogaerts A, Zhang Q-Z, Zhang Y-R, Van Laer K, Wang W, Catalysis today 337, 3 (2019). http://doi.org/10.1016/j.cattod.2019.04.077
Abstract: Plasma catalysis is promising for various environmental, energy and chemical synthesis applications, but the underlying mechanisms are far from understood. Modeling can help to obtain a better insight in these mechanisms. Some burning questions relate to the plasma behavior inside packed bed reactors and whether plasma can penetrate into catalyst pores. In this paper, we try to provide answers to these questions, by means of both fluid modeling and particle-in-cell/Monte Carlo collision simulations. We present a short overview of recent findings obtained in our group by means of modeling, i.e., the enhanced electric field near the contact points and the streamer propagation through the packing in packed bed reactors, as well as the plasma behavior in catalyst pores, to determine the minimum pore size in which plasma streamers can penetrate.
Keywords: A1 Journal article; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
Impact Factor: 4.636
Times cited: 7
DOI: 10.1016/j.cattod.2019.04.077
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“Pd/Lewis acid synergy in macroporous Pd@Na-ZSM-5 for enhancing selective conversion of biomass”. Liu J-W, Wu S-M, Wang L-Y, Tian G, Qin Y, Wu J-X, Zhao X-F, Zhang Y-X, Chang G-G, Wu L, Zhang Y-X, Li Z-F, Guo C-Y, Janiak C, Lenaerts S, Yang X-Y, Chemcatchem , 1 (2020). http://doi.org/10.1002/CCTC.202000868
Abstract: Pd nanometal particles encapsulated in macroporous Na-ZSM-5 with only Lewis acid sites have been successfully synthesized by a steam-thermal approach. The synergistic effect of Pd and Lewis acid sites have been investigated for significant enhancement of the catalytic selectivity towards furfural alcohol in furfural hydroconversion.
Keywords: A1 Journal article; Sustainable Energy, Air and Water Technology (DuEL)
Impact Factor: 4.5
Times cited: 1
DOI: 10.1002/CCTC.202000868
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“Unveiling the interaction mechanisms of cold atmospheric plasma and amino acids by machine learning”. Chai Z-N, Wang X-C, Yusupov M, Zhang Y-T, Plasma processes and polymers , 1 (2024). http://doi.org/10.1002/PPAP.202300230
Abstract: Plasma medicine has attracted tremendous interest in a variety of medical conditions, ranging from wound healing to antimicrobial applications, even in cancer treatment, through the interactions of cold atmospheric plasma (CAP) and various biological tissues directly or indirectly. The underlying mechanisms of CAP treatment are still poorly understood although the oxidative effects of CAP with amino acids, peptides, and proteins have been explored experimentally. In this study, machine learning (ML) technology is introduced to efficiently unveil the interaction mechanisms of amino acids and reactive oxygen species (ROS) in seconds based on the data obtained from the reactive molecular dynamics (MD) simulations, which are performed to probe the interaction of five types of amino acids with various ROS on the timescale of hundreds of picoseconds but with the huge computational load of several days. The oxidative reactions typically start with H-abstraction, and the details of the breaking and formation of chemical bonds are revealed; the modification types, such as nitrosylation, hydroxylation, and carbonylation, can be observed. The dose effects of ROS are also investigated by varying the number of ROS in the simulation box, indicating agreement with the experimental observation. To overcome the limits of timescales and the size of molecular systems in reactive MD simulations, a deep neural network (DNN) with five hidden layers is constructed according to the reaction data and employed to predict the type of oxidative modification and the probability of occurrence only in seconds as the dose of ROS varies. The well-trained DNN can effectively and accurately predict the oxidative processes and productions, which greatly improves the computational efficiency by almost ten orders of magnitude compared with the reactive MD simulation. This study shows the great potential of ML technology to efficiently unveil the underpinning mechanisms in plasma medicine based on the data from reactive MD simulations or experimental measurements. In this study, since reactive molecular dynamics simulation can currently only describe interactions between a few hundred atoms in a few hundred picoseconds, deep neural networks (DNN) are introduced to enhance the simulation results by predicting more data efficiently. image
Keywords: A1 Journal article; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
Impact Factor: 3.5
DOI: 10.1002/PPAP.202300230
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Zhang Y, Grü,newald L, Cao X, Abdelbarey D, Zheng X, Rugeramigabo EP, Zopf M, Verbeeck J, Ding F (2024) Supplementary Information and Data for “Unveiling the 3D Morphology of Epitaxial GaAs/AlGaAs Quantum Dots”
Abstract: Raw and processed TEM and AFM data for the article Unveiling the 3D Morphology of Epitaxial GaAs/AlGaAs Quantum Dots.
Keywords: Dataset; Engineering sciences. Technology; Electron microscopy for materials research (EMAT)
DOI: 10.5281/ZENODO.11449864
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