“Modeling of the synthesis and subsequent growth of nanoparticles in dusty plasmas”. de Bleecker K, Bogaerts A, High temperature material processes 11, 21 (2007). http://doi.org/10.1615/HighTempMatProc.v11.i1.20
Keywords: A1 Journal article; Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
DOI: 10.1615/HighTempMatProc.v11.i1.20
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“Modeling and tackling resistivity scaling in metal nanowires”. Moors K, Sorée B, Magnus W, International Conference on Simulation of Semiconductor Processes and Devices : [proceedings]
T2 –, International Conference on Simulation of Semiconductor Processes and, Devices (SISPAD), SEP 09-11, 2015, Washington, DC , 222 (2015)
Abstract: A self-consistent analytical solution of the multi-subband Boltzmann transport equation with collision term describing grain boundary and surface roughness scattering is presented to study the resistivity scaling in metal nanowires. The different scattering mechanisms and the influence of their statistical parameters are analyzed. Instead of a simple power law relating the height or width of a nanowire to its resistivity, the picture appears to be more complicated due to quantum-mechanical scattering and quantization effects, especially for surface roughness scattering.
Keywords: P1 Proceeding; Condensed Matter Theory (CMT)
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“Self-consistent 30-band simulation approach for (non-)uniformly strained confined heterostructure tunnel field-effect transistors”. Verreck D, Verhulst AS, Van de Put ML, Sorée B, Magnus W, Collaert N, Mocuta A, Groeseneken G, Simulation of Semiconductor Processes and, Devices (SISPAD)AND DEVICES (SISPAD 2017) , 29 (2017)
Abstract: Heterostructures of III-V materials under a mechanical strain are being actively researched to enhance the performance of the tunnel field-effect transistor (TFET). In scaled III-V device structures, however, the interplay between the effects of strain and quantum confinement on the semiconductor band structure and hence the performance is highly non-trivial. We have therefore developed a computationally efficient quantum mechanical simulator Pharos, which enables self-consistent full-zone k.p-based simulations of III-V TFETs under a general non-uniform strain. We present the self-consistent procedure and demonstrate it on confined staggered bandgap GaAs0.5Sb0.5/In0.53Ga0.47As TFETs. We find a large performance degradation due to size-induced quantum confinement compared to non-confined devices. We show that some performance can be regained either by applying a uniform biaxial tensile strain or through the non-uniform strain profile at a lattice-mismatched heterostructure.
Keywords: P1 Proceeding; Condensed Matter Theory (CMT)
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“Ab initio modeling of few-layer dilute magnetic semiconductors”. Tiwari S, Van de Put ML, Sorée B, Vandenberghe WG, International Conference on Simulation of Semiconductor Processes and Devices : [proceedings]
T2 –, International Conference on Simulation of Semiconductor Processes and, Devices (SISPAD), SEP 27-29, 2021, Dallas, TX , 141 (2021). http://doi.org/10.1109/SISPAD54002.2021.9592535
Abstract: We present a computational model to model the magnetic structure of two-dimensional (2D) dilute-magnetic-semiconductors (DMS) both the monolayers and multilayers using first-principles density functional theory (DFT), as well as their magnetic phase transition as a function of temperature using Monte-Carlo simulations. Using our method, we model the magnetic structure of bulk, bilayer, and monolayer MoS2 substitutionally doped with Fe atoms. We find that the out-of-plane interaction in bilayer MoS2 is weakly ferromagnetic, whereas in bulk MoS2 it is strongly anti-ferromagnetic. Finally, we show that the magnetic order is more robust in bilayer Fe-doped MoS2 compared to the monolayer and results in a room-temperature FM at an atomic substitution of 14-16%.
Keywords: P1 Proceeding; Engineering sciences. Technology; Condensed Matter Theory (CMT)
DOI: 10.1109/SISPAD54002.2021.9592535
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“Ab-initio study of magnetically intercalated Tungsten diselenide”. Reyntjens PD, Tiwari S, Van de Put ML, Sorée B, Vandenberghe WG, International Conference on Simulation of Semiconductor Processes and Devices : [proceedings]
T2 –, International Conference on Simulation of Semiconductor Processes and, Devices (SISPAD), SEP 23-OCT 06, 2020 , 97 (2020). http://doi.org/10.23919/SISPAD49475.2020.9241592
Abstract: We theoretically investigate the effect of intercalation of third row transition metals (Co, Cr, Fe, Mn, Ti and V) in the layers of WSe2. Using density functional theory (DFT), we investigate the structural stability. We also compute the DFT energies of various magnetic spin configurations. Using these energies, we construct a Heisenberg Hamiltonian and perform a Monte Carlo study on each WSe2 + intercalant system to estimate the Curie or Neel temperature. We find ferromagnetic ground states for Ti and Cr intercalation, with Curie temperatures of 31K and 225K, respectively. In Fe-intercalated WSe2, we predict that antiferromagnetic ordering is present up to 564K. For V intercalation, we find that the system exhibits a double phase transition.
Keywords: P1 Proceeding; Condensed Matter Theory (CMT)
DOI: 10.23919/SISPAD49475.2020.9241592
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“Carrier transport in a two-dimensional topological insulator nanoribbon in the presence of vacancy defects”. Tiwari S, Van de Put ML, Sorée B, Vandenberghe WG, International Conference on Simulation of Semiconductor Processes and Devices : [proceedings]
T2 –, International Conference on Simulation of Semiconductor Processes and, Devices (SISPAD), SEP 24-26, 2018, Austin, TX , 92 (2018). http://doi.org/10.1109/SISPAD.2018.8551720
Abstract: We model transport through two-dimensional topological insulator (TI) nanoribbons. To model the quantum transport, we employ the non-equilibrium Green's function approach. With the presented approach, we study the effect of lattice imperfections on the carrier transport. We observe that the topologically protected edge states of TIs are robust against a high percentage (2%) of vacancy defects. We also investigate tunneling of the edge states in two decoupled TI nanoribbons.
Keywords: P1 Proceeding; Engineering sciences. Technology; Condensed Matter Theory (CMT)
DOI: 10.1109/SISPAD.2018.8551720
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“Characterization of colloidal and particulate matter transported by the Magela Creek system, Northern Australia”. Hart BT, Douglas GB, Beckett R, van Put A, Van Grieken R, Hydrological processes 7, 105 (1993)
Keywords: A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Patterns of damage in igneous and sedimentary rocks under conditions simulating sea-salt weathering”. Cardell C, Rivas T, Mosquera MJ, Birginie JM, Moropoulou A, Prieto B, Silva B, Van Grieken R, Earth surface processes and landforms 28, 1 (2003). http://doi.org/10.1002/ESP.408
Keywords: A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
DOI: 10.1002/ESP.408
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“Quantum transport study of contact resistance of edge- and top-contacted two-dimensional materials”. Deylgat E, Chen E, Sorée B, Vandenberghe WG, International Conference on Simulation of Semiconductor Processes and Devices : [proceedings]
T2 –, International Conference on Simulation of Semiconductor Processes and, Devices (SISPAD), SEP 27-29, 2023, Kobe, Japan , 45 (2023). http://doi.org/10.23919/SISPAD57422.2023.10319537
Abstract: We calculate the contact resistance for an edge- and top-contacted 2D semiconductor. The contact region consists of a metal contacting a monolayer of MoS2 which is otherwise surrounded by SiO2. We use the quantum transmitting boundary method to compute the contact resistance as a function of the 2D semiconductor doping concentration. An effective mass Hamiltonian is used to describe the properties of the various materials. The electrostatic potentials are obtained by solving the Poisson equation numerically. We incorporate the effects of the image-force barrier lowering on the Schottky barrier and examine the impact on the contact resistance. At low doping concentrations, the contact resistance of the top contact is lower compared to edge contact, while at high doping concentrations, the edge contact exhibits lower resistance.
Keywords: P1 Proceeding; Condensed Matter Theory (CMT)
DOI: 10.23919/SISPAD57422.2023.10319537
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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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