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Modelling Materials and Devices at Atomistic Level

A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Materials Simulation and Design".

Deadline for manuscript submissions: closed (10 November 2022) | Viewed by 3289

Special Issue Editor


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Guest Editor
Horia Hulubei National Institute for Physics and Nuclear Engineering, Magurele, Romania
Interests: perovskite materials; graphene and related materials; density functional theory; nanoelectronic devices; machine learning techniques

Special Issue Information

Dear Colleagues,

In the past few years, atomistic simulations have become essential tools for exploring new materials and nanostructures, as well as for investigating the working principles of novel electronic devices. The success of ab initio methods based on the density functional theory (DFT) and its extensions in predicting material properties ensures valuable guidance for the synthesis of proper candidates. First-principle calculations are typically employed in the study of bulk materials and low-dimensional systems and interfaces, providing an accurate description of opto-electronic, magnetic, mechanic, and other derived properties. Moreover, coupling DFT to transport methods such as the non-equilibrium Green’s functions (NEGF), one may describe spin and charge transport in atomic-scale devices such as molecular junctions, spinfilters, and nanosensors.

Complementary, molecular dynamics simulations are able to cover mechanical properties at significantly larger timescales and system sizes, as compared to DFT calculations. In addition, in recent years, machine learning (ML) techniques combined with atomistic descriptions have boosted the search for new materials and the optimization of device properties. 

This Special Issue shall cover topics concerning the modeling of materials and devices at atomistic level. These shall be focused but not limited to materials and interfaces for opto-electronic applications, spin and charge transport in atomic-scale devices, and novel ML approaches coupled to ab initio approaches.

Dr. George Alexandru Nemnes
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Materials is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • density functional theory
  • electronic structure calculations
  • molecular dynamics
  • machine learning
  • spin and charge transport
  • atomic-scale devices
  • ab initio modeling of interfaces
  • molecular dynamics simulations

Published Papers (2 papers)

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Research

10 pages, 3042 KiB  
Article
CO2 Adsorption over 3d Transition-Metal Nanoclusters Supported on Pyridinic N3-Doped Graphene: A DFT Investigation
by Fernando Montejo-Alvaro, Jesus A. Martínez-Espinosa, Hugo Rojas-Chávez, Diana C. Navarro-Ibarra, Heriberto Cruz-Martínez and Dora I. Medina
Materials 2022, 15(17), 6136; https://0-doi-org.brum.beds.ac.uk/10.3390/ma15176136 - 04 Sep 2022
Cited by 3 | Viewed by 1614
Abstract
CO2 adsorption on bare 3d transition-metal nanoclusters and 3d transition-metal nanoclusters supported on pyridinic N3-doped graphene (PNG) was investigated by employing the density functional theory. First, the interaction of Co13 and Cu13 with PNG was analyzed [...] Read more.
CO2 adsorption on bare 3d transition-metal nanoclusters and 3d transition-metal nanoclusters supported on pyridinic N3-doped graphene (PNG) was investigated by employing the density functional theory. First, the interaction of Co13 and Cu13 with PNG was analyzed by spin densities, interaction energies, charge transfers, and HUMO-LUMO gaps. According to the interaction energies, the Co13 nanocluster was adsorbed more efficiently than Cu13 on the PNG. The charge transfer indicated that the Co13 nanocluster donated more charges to the PNG nanoflake than the Cu13 nanocluster. The HUMO-LUMO gap calculations showed that the PNG improved the chemical reactivity of both Co13 and Cu13 nanoclusters. When the CO2 was adsorbed on the bare 3d transition-metal nanoclusters and 3d transition-metal nanoclusters supported on the PNG, it experienced a bond elongation and angle bending in both systems. In addition, the charge transfer from the nanoclusters to the CO2 molecule was observed. This study proved that Co13/PNG and Cu13/PNG composites are adequate candidates for CO2 adsorption and activation. Full article
(This article belongs to the Special Issue Modelling Materials and Devices at Atomistic Level)
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9 pages, 6718 KiB  
Article
Molecular Dynamics Investigation of Spreading Performance of Physiological Saline on Surface
by Jianhua Pan and Xiao Wang
Materials 2022, 15(11), 3925; https://0-doi-org.brum.beds.ac.uk/10.3390/ma15113925 - 31 May 2022
Cited by 1 | Viewed by 1303
Abstract
Physiological saline is an indispensable element for maintaining the functions of life. The spreading performance of physiological saline droplets on the surface of graphene under different NaCl concentrations and electric field intensities was studied in the present work. The results show that the [...] Read more.
Physiological saline is an indispensable element for maintaining the functions of life. The spreading performance of physiological saline droplets on the surface of graphene under different NaCl concentrations and electric field intensities was studied in the present work. The results show that the increase in NaCl concentration reduces the displacement vector value of molecules in droplets. In addition, NaCl is easy to aggregate on the surface of graphene. The increase in NaCl concentration makes it more difficult for droplets to penetrate the surface of graphene, and the penetration angle of droplets increases with the rise in NaCl concentration. With the increase in electric field intensity, the wetting effect of droplets is more obvious. The greater the electric field intensity is, the smaller the penetration angle is, which is mainly due to the polarity of water molecules. This study has reference significance for the study of body fluid volatilization on the human surface. Full article
(This article belongs to the Special Issue Modelling Materials and Devices at Atomistic Level)
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