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Computational Study of Nanomaterials
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Computational Study of Nanomaterials

A special issue of Nanomaterials (ISSN 2079-4991). This special issue belongs to the section "Theory and Simulation of Nanostructures".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 47332

Special Issue Editor

Dr. Guang-Ping Zheng

E-Mail Website
Guest Editor
Department of Mechanical Engineering, Hong Kong Polytechnic University, Kowloon 10000, Hong Kong, China
Interests: computational materials science; computational materials design; functional nanomaterials
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Computational study of nanomaterials is a young but fast-growing field. Already, it has risen to being the third most used approach applied to materials, following experimental and theoretical studies. Coupled with materials informatics, the “Computational Study of Nanomaterials” will lay a solid foundation for apprehending the nanomaterials for structural and functional applications. This Special Issue aims to publish research work that is related to understanding the mechanical, electronic and chemical properties of nanomaterial by using multiscale modeling techniques (e.g., ab-initio method, molecular dynamics, Monte Carlo method, phase-field modeling, finite element methods), and machine learning algorithms. The nanomaterials in the works may include nano-scale materials (e.g., nanoparticles, nanowires and two-dimensional materials) and nanostructured advanced materials (e.g., nanocomposites, nanocrystalline materials, high-entropy materials, metallic nano-glasses, etc).

You are cordinally invited to submit research articles with the following topics to this Special Issue, and any research work related to computational study of nanomaterials are welcome.

  1. First-principles prediction on novel physical and chemical properties of nanomaterials.
  2. Studies on physical and chemical properties of novel nanomaterials by machine learning.
  3. Computational studies on structure–property relationships in nanomaterials.
  4. Atomistic (ab-initio, molecular dynamics) simulation on mechanical properties of nanomaterials.
  5. Studies on nanomechanics by multiscale simulation approaches.

Dr. Guang-Ping Zheng
Guest Editor

Manuscript Submission Information

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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. Nanomaterials 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 2900 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

  • First-principles prediction
  • Structure–property relationship
  • Atomistic simulation
  • Multiscale modeling and simulation
  • Machine learning

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Published Papers (19 papers)

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Research

21 pages, 25124 KiB  
Article
Sensitivity Analysis of the Catalysis Recombination Mechanism on Nanoscale Silica Surfaces
by Lichao He, Zhiliang Cui, Xiangchun Sun, Jin Zhao and Dongsheng Wen
Nanomaterials 2022, 12(14), 2370; https://doi.org/10.3390/nano12142370 - 11 Jul 2022
Cited by 8 | Viewed by 1837
Abstract
A deep understanding of surface catalysis recombination characteristics is significant for accurately predicting the aeroheating between hypersonic non-equilibrium flow and thermal protection materials, while a de-coupling sensitivity analysis of various influential factors is still lacking. A gas–solid interface (GSI) model with a hyperthermal [...] Read more.
A deep understanding of surface catalysis recombination characteristics is significant for accurately predicting the aeroheating between hypersonic non-equilibrium flow and thermal protection materials, while a de-coupling sensitivity analysis of various influential factors is still lacking. A gas–solid interface (GSI) model with a hyperthermal flux boundary was established to investigate the surface catalysis recombination mechanisms on nanoscale silica surfaces. Using the reactive molecular dynamics (RMD) simulation method, the effects of solid surface temperature, gas incident angle, and translational energy on the silica surface catalysis recombination were qualified under hyperthermal atomic oxygen (AO), atomic nitrogen (AN), and various AN/AO gas mixtures’ influence. It can be found that, though the Eley–Rideal (E–R) recombination mechanism plays a dominant role over the Langmuir–Hinshelwood (L–H) mechanism for all the sensitivity analyses, a non-linear increasing pattern of AO recombination coefficient γO2 with the increase in incident angle θin and translational energy Ek is observed. Compared with the surface catalysis under hyperthermal AO impact, the AN surface adsorption fraction shows an inverse trend with the increase in surface temperature, which suggests the potential inadequacy of the traditional proportional relationship assumptions between the surface adsorption concentration and the surface catalysis recombination coefficient for other species’ impact instead of AOs. For the incoming bi-component AO/AN gas mixtures, the corresponding surface catalysis coefficient is not the simple superposition of the effects of individual gases but is affected by both the intramolecular bond energies (e.g., O2, N2) and intermolecular energies (e.g., Si/N, Si/O). Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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20 pages, 1742 KiB  
Article
Application of the Higher-Order Hamilton Approach to the Nonlinear Free Vibrations Analysis of Porous FG Nano-Beams in a Hygrothermal Environment Based on a Local/Nonlocal Stress Gradient Model of Elasticity
by Rosa Penna, Luciano Feo, Giuseppe Lovisi and Francesco Fabbrocino
Nanomaterials 2022, 12(12), 2098; https://doi.org/10.3390/nano12122098 - 17 Jun 2022
Cited by 13 | Viewed by 2129
Abstract
Nonlinear transverse free vibrations of porous functionally-graded (FG) Bernoulli–Euler nanobeams in hygrothermal environments through the local/nonlocal stress gradient theory of elasticity were studied. By using the Galerkin method, the governing equations were reduced to a nonlinear ordinary differential equation. The closed form analytical [...] Read more.
Nonlinear transverse free vibrations of porous functionally-graded (FG) Bernoulli–Euler nanobeams in hygrothermal environments through the local/nonlocal stress gradient theory of elasticity were studied. By using the Galerkin method, the governing equations were reduced to a nonlinear ordinary differential equation. The closed form analytical solution of the nonlinear natural flexural frequency was then established using the higher-order Hamiltonian approach to nonlinear oscillators. A numerical investigation was developed to analyze the influence of different parameters both on the thermo-elastic material properties and the structural response, such as material gradient index, porosity volume fraction, nonlocal parameter, gradient length parameter, mixture parameter, and the amplitude of the nonlinear oscillator on the nonlinear flexural vibrations of metal–ceramic FG porous Bernoulli–Euler nano-beams. Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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12 pages, 3609 KiB  
Article
Effect of the Interface on the Compressibility of Substances with Spherical Nano-Inhomogeneities on the Example of Al/C60
by Viktor Reshetniak, Olga Reshetniak, Artemiy Aborkin, Vladimir Nederkin and Anatoliy Filippov
Nanomaterials 2022, 12(12), 2045; https://doi.org/10.3390/nano12122045 - 14 Jun 2022
Cited by 6 | Viewed by 1580
Abstract
The paper examines the compressibility of media with nano-inhomogeneities using the example of an aluminum melt and C60 fullerenes immersed in it. The results of molecular dynamics simulations indicate a significant effect of the interface on the effective compressibility of a heterogeneous [...] Read more.
The paper examines the compressibility of media with nano-inhomogeneities using the example of an aluminum melt and C60 fullerenes immersed in it. The results of molecular dynamics simulations indicate a significant effect of the interface on the effective compressibility of a heterogeneous medium. It is found that the application of the rule of mixture for the Al/C60 system results in an incorrect qualitative picture of the dependence of compressibility on the concentration of fullerenes. To explain this effect, an analytical model is proposed that takes into account the reduction in distances between atoms of different components during compression. The model makes it possible to estimate the effective mechanical characteristics of a liquid with nano-inhomogeneities within the framework of the mechanical approach, and correctly predicts the nature of the change in the dependence of compressibility on concentration. Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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10 pages, 9011 KiB  
Article
Spin-Orbit Coupling Electronic Structures of Organic-Group Functionalized Sb and Bi Topological Monolayers
by Qi Gong and Guiling Zhang
Nanomaterials 2022, 12(12), 2041; https://doi.org/10.3390/nano12122041 - 14 Jun 2022
Cited by 4 | Viewed by 2054
Abstract
Electronic band-gap is a key factor in applying two-dimensional (2D) topological insulators into room-temperature quantum spin Hall effect (QSH) spintronic devices. Employing pseudopotential plane-wave first-principles calculations, we investigate spin-orbit coupling (SOC) electronic structures of the novel 2D topological insulator series of antimony (Sb) [...] Read more.
Electronic band-gap is a key factor in applying two-dimensional (2D) topological insulators into room-temperature quantum spin Hall effect (QSH) spintronic devices. Employing pseudopotential plane-wave first-principles calculations, we investigate spin-orbit coupling (SOC) electronic structures of the novel 2D topological insulator series of antimony (Sb) and bismuth (Bi) monolayers (isolated double atomic layers) functionalized by organic-groups (methyl, amino and hydroxyl). Cohesive energies and phonon frequency dispersion spectra indicate that these organic-group decorated Sb and Bi monolayers possess structural stability in both energetic statics and lattice dynamics. The giant electronic band-gaps adequate for room-temperature applications are attributed to the effective SOC enhancement of group functionalization. The nontrivial topology of these novel 2D monolayer materials is verified by the Z2 invariant derived from wave-function parity and edge-states of their nanoribbons, which is prospective for QSH spintronic devices. The chemical functional group changes the p-orbital component of Fermi level electrons, leading to strong intra-layer spin-orbit coupling, opening a large band-gap of approaching 1.4 eV at Dirac-cone point and resulting in a global indirect band-gap of 0.75 eV, which, even underestimated, is adequate for room-temperature operations. Sb and Bi monolayers functionalized by organic groups are also predicted to maintain stable nontrivial topology under in-layer biaxial strain, which is suitable for epitaxy technology to realize QSH spintronic devices. Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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15 pages, 2929 KiB  
Article
Disordered Rock-Salt Type Li2TiS3 as Novel Cathode for LIBs: A Computational Point of View
by Riccardo Rocca, Mauro Francesco Sgroi, Bruno Camino, Maddalena D’Amore and Anna Maria Ferrari
Nanomaterials 2022, 12(11), 1832; https://doi.org/10.3390/nano12111832 - 27 May 2022
Cited by 6 | Viewed by 2322
Abstract
The development of high-energy cathode materials for lithium-ion batteries with low content of critical raw materials, such as cobalt and nickel, plays a key role in the progress of lithium-ion batteries technology. In recent works, a novel and promising family of lithium-rich sulfides [...] Read more.
The development of high-energy cathode materials for lithium-ion batteries with low content of critical raw materials, such as cobalt and nickel, plays a key role in the progress of lithium-ion batteries technology. In recent works, a novel and promising family of lithium-rich sulfides has received attention. Among the possible structures and arrangement, cubic disordered Li2TiS3 has shown interesting properties, also for the formulation of new cell for all-solid-state batteries. In this work, a computational approach based on DFT hybrid Hamiltonian, localized basis functions and the use of the periodic CRYSTAL code, has been set up. The main goal of the present study is to determine accurate structural, electronic, and spectroscopic properties for this class of materials. Li2TiS3 precursors as Li2S, TiS2, and TiS3 alongside other formulations and structures such as LiTiS2 and monoclinic Li2TiS3 have been selected as benchmark systems and used to build up a consistent and robust predictive scheme. Raman spectra, XRD patterns, electronic band structures, and density of states have been simulated and compared to available literature data. Disordered rock-salt type Li2TiS3 structures have been derived via a solid solution method as implemented into the CRYSTAL code. Representative structures were extensively characterized through the calculations of their electronic and vibrational properties. Furthermore, the correlation between structure and Raman fingerprint was established. Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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11 pages, 18331 KiB  
Article
Molecular Dynamics Analysis of Graphene Nanoelectromechanical Resonators Based on Vacancy Defects
by Wenhua Li and Wenchao Tian
Nanomaterials 2022, 12(10), 1722; https://doi.org/10.3390/nano12101722 - 18 May 2022
Cited by 4 | Viewed by 1768
Abstract
Due to the limitation of graphene processing technology, the prepared graphene inevitably contains various defects. The defects will have a particular influence on the macroscopic characteristics of the graphene. In this paper, the defect-based graphene nanoresonators are studied. In this study, the resonant [...] Read more.
Due to the limitation of graphene processing technology, the prepared graphene inevitably contains various defects. The defects will have a particular influence on the macroscopic characteristics of the graphene. In this paper, the defect-based graphene nanoresonators are studied. In this study, the resonant properties of graphene were investigated via molecular dynamic simulations. The effect of vacancy defects and hole defects at different positions, numbers, and concentrations on the resonance frequency of graphene nanoribbons was studied. The results indicated that single monatomic vacancy has no effect on graphene resonant frequency, and the concentration of the resonant frequency of graphene decreases almost linearly with the increase of single-atom vacancy concentration. When the vacancy concentration is 5%, the resonance frequency is reduced by 12.77% compared to the perfect graphene. Holes on the graphene cause the resonance frequency to decrease. As the circular hole defect is closer to the center of the graphene nanoribbon, not only does its resonant frequency increase, but the tuning range is also expanded accordingly. Under the external force of 10.715 nN, the resonant frequency of graphene reaches 429.57 GHz when the circular hole is located at the center of the graphene nanoribbon, which is 40 GHz lower than that of single vacancy defect graphene. When the circular hole is close to the fixed end of graphene, the resonant frequency is 379.62 GHz, which is 90 GHz lower than that of single vacancy graphene. When the hole defect is at the center of nanoribbon, the frequency tunable range of graphene reaches 120 GHz. The tunable frequency range of graphene is 100.12 GHz when the hole defect is near the fixed ends of the graphene nanoribbon. This work is of great significance for design and performance optimization of graphene-based nanoelectro-mechanical system (NEMS) resonators. Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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9 pages, 1446 KiB  
Article
Stability Trends in Mono-Metallic 3d Layered Double Hydroxides
by Saeedeh Mohammadi, Ayoub Esmailpour, Esmail Doustkhah and Mohammad Hussein Naseef Assadi
Nanomaterials 2022, 12(8), 1339; https://doi.org/10.3390/nano12081339 - 13 Apr 2022
Cited by 6 | Viewed by 2153
Abstract
Layered double hydroxides (LDHs) constitute a unique group of 2D materials that can deliver exceptional catalytic, optical, and electronic performance. However, they usually suffer from low stability compared to their oxide counterparts. Using density functional calculations, we quantitatively demonstrate the crucial impact of [...] Read more.
Layered double hydroxides (LDHs) constitute a unique group of 2D materials that can deliver exceptional catalytic, optical, and electronic performance. However, they usually suffer from low stability compared to their oxide counterparts. Using density functional calculations, we quantitatively demonstrate the crucial impact of the intercalants (i.e., water, lactate, and carbonate) on the stability of a series of common LDHs based on Mn, Fe, and Co. We found that intercalation with the singly charged lactate results in higher stability in all these LDH compounds, compared to neutral water and doubly charged carbonate. Furthermore, we show that the dispersion effect aids the stability of these LDH compounds. This investigation reveals that certain intercalants enhance LDH stability and alter the bandgap favourably. Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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18 pages, 22898 KiB  
Article
The Theoretical Study of Kink Deformation in Graphite Based on Differential Geometric Method
by Xiao-Wen Lei, Shungo Shimizu and Jin-Xing Shi
Nanomaterials 2022, 12(6), 903; https://doi.org/10.3390/nano12060903 - 9 Mar 2022
Cited by 6 | Viewed by 2492
Abstract
Kink deformation is often observed in materials with laminated layers. Graphite composed of stacked graphene layers has the unique laminated structure of carbon nanomaterials. In this study, we performed the interlayer deformation of graphite under compression using a simulation of molecular dynamics and [...] Read more.
Kink deformation is often observed in materials with laminated layers. Graphite composed of stacked graphene layers has the unique laminated structure of carbon nanomaterials. In this study, we performed the interlayer deformation of graphite under compression using a simulation of molecular dynamics and proposed a differential geometrical method to evaluate the kink deformation. We employed “mean curvature” for the representativeness of the geometrical properties to explore the mechanism of kink deformation and the mechanical behaviors of graphite in nanoscale. The effect of the number of graphene layers and the lattice chirality of each graphene layer on kink deformation and stress–strain diagrams of compressed graphite are discussed in detail. The results showed that kink deformation occurred in compressed graphite when the strain was approximately equal to 0.02, and the potential energy of the compressed graphite proportionately increased with the increasing compressive strain. The proposed differential geometric method can not only be applied to kink deformation in nanoscale graphite, but could also be extended to solving and predicting interlayer deformation that occurs in micro- and macro-scale material structures with laminated layers. Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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36 pages, 5208 KiB  
Article
Quantitative Features Analysis of Water Carrying Nanoparticles of Alumina over a Uniform Surface
by Abdul Hamid Ganie, Fazlullah Fazal, Carlos Andrés Tavera Romero and Muhammad Sulaiman
Nanomaterials 2022, 12(5), 878; https://doi.org/10.3390/nano12050878 - 6 Mar 2022
Cited by 4 | Viewed by 2246
Abstract
Little is known about the rising impacts of Coriolis force and volume fraction of nanoparticles in industrial, mechanical, and biological domains, with an emphasis on water conveying 47 nm nanoparticles of alumina nanoparticles. We explored the impact of the volume fraction and rotation [...] Read more.
Little is known about the rising impacts of Coriolis force and volume fraction of nanoparticles in industrial, mechanical, and biological domains, with an emphasis on water conveying 47 nm nanoparticles of alumina nanoparticles. We explored the impact of the volume fraction and rotation parameter on water conveying 47 nm of alumina nanoparticles across a uniform surface in this study. The Levenberg–Marquardt backpropagated neural network (LMB-NN) architecture was used to examine the transport phenomena of 47 nm conveying nanoparticles. The partial differential equations (PDEs) are converted into a system of Ordinary Differential Equations (ODEs). To assess our soft-computing process, we used the RK4 method to acquire reference solutions. The problem is investigated using two situations, each with three sub-cases for the change of the rotation parameter K and the volume fraction ϕ. Our simulation results are compared to the reference solutions. It has been proven that our technique is superior to the current state-of-the-art. For further explanation, error histograms, regression graphs, and fitness values are graphically displayed. Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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20 pages, 12730 KiB  
Article
Virtual Vibrational Spectrometry of Stable Radicals—Necklaced Graphene Molecules
by Elena F. Sheka
Nanomaterials 2022, 12(4), 597; https://doi.org/10.3390/nano12040597 - 10 Feb 2022
Cited by 9 | Viewed by 1513
Abstract
The article presents results of an extended virtual experiment on graphene molecules performed using the virtual vibrational spectrometer HF Spectrodyn that exploits semiempirical Hartree–Fock approximation. The molecules are composed of flat graphene domains surrounded with heteroatom necklaces. Not existing individually, these molecules are [...] Read more.
The article presents results of an extended virtual experiment on graphene molecules performed using the virtual vibrational spectrometer HF Spectrodyn that exploits semiempirical Hartree–Fock approximation. The molecules are composed of flat graphene domains surrounded with heteroatom necklaces. Not existing individually, these molecules are met in practice as basic structure units of complex multilevel structure of all sp2 amorphous carbons. This circumstance deprives the solids’ in vitro spectroscopy of revealing the individual character of basic structural elements, and in silico spectrometry fills this shortcoming. The obtained virtual vibrational spectra allow for drawing first conclusions about the specific features of the vibrational dynamics of the necklaced graphene molecules, caused by spatial structure and packing of their graphene domains as well as by chemical composition of the relevant necklaces. As shown, IR absorption spectra of the molecules are strongly necklace dependent, once becoming a distinct spectral signature of the amorphous body origin. Otherwise, Raman spectra are a spectral mark of the graphene domain’s size and packing, thus disclosing the mystery of their universal D-G-band standard related to graphene-containing materials of various origins. Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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14 pages, 1461 KiB  
Article
Simulating and Predicting Adsorption of Organic Pollutants onto Black Phosphorus Nanomaterials
by Lihao Su, Ya Wang, Zhongyu Wang, Siyu Zhang, Zijun Xiao, Deming Xia and Jingwen Chen
Nanomaterials 2022, 12(4), 590; https://doi.org/10.3390/nano12040590 - 9 Feb 2022
Cited by 8 | Viewed by 2521
Abstract
Layered black phosphorus (BP) has exhibited exciting application prospects in diverse fields. Adsorption of organics onto BP may influence environmental behavior and toxicities of both organic pollutants and BP nanomaterials. However, contributions of various intermolecular interactions to the adsorption remain unclear, and values [...] Read more.
Layered black phosphorus (BP) has exhibited exciting application prospects in diverse fields. Adsorption of organics onto BP may influence environmental behavior and toxicities of both organic pollutants and BP nanomaterials. However, contributions of various intermolecular interactions to the adsorption remain unclear, and values of adsorption parameters such as adsorption energies (Ead) and adsorption equilibrium constants (K) are lacking. Herein, molecular dynamic (MD) and density functional theory (DFT) was adopted to calculate Ead and K values. The calculated Ead and K values for organics adsorbed onto graphene were compared with experimental ones, so as to confirm the reliability of the calculation methods. Polyparameter linear free energy relationship (pp-LFER) models on Ead and logK were developed to estimate contributions of different intermolecular interactions to the adsorption. The adsorption in the gaseous phase was found to be more favorable than in the aqueous phase, as the adsorbates need to overcome cohesive energies of water molecules onto BP. The affinity of the aromatics to BP was comparable to that of graphene. The pp-LFER models performed well for predicting the Ead and K values, with external explained variance ranging from 0.90 to 0.97, and can serve as effective tools to rank adsorption capacities of organics onto BP. Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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7 pages, 1846 KiB  
Communication
Investigation of SERS and Electron Transport Properties of Oligomer Phenylacetyne-3 Trapped in Gold Junctions
by Ziyu Liu, Tingting Hu, Muwafag Osman Adam Balila, Jihui Zhang, Yujin Zhang and Wei Hu
Nanomaterials 2022, 12(3), 571; https://doi.org/10.3390/nano12030571 - 7 Feb 2022
Cited by 1 | Viewed by 1883
Abstract
Molecular junctions hold great potential for future microelectronics and attract people’s attention. Here, we used density functional theory calculations (DFT) to investigate the surface-enhanced Raman spectroscopy (SERS) and electron transport properties of fully π-conjugated oligomers (phenylacetylene)-3 (OPE-3) trapped in gold junctions. The effects [...] Read more.
Molecular junctions hold great potential for future microelectronics and attract people’s attention. Here, we used density functional theory calculations (DFT) to investigate the surface-enhanced Raman spectroscopy (SERS) and electron transport properties of fully π-conjugated oligomers (phenylacetylene)-3 (OPE-3) trapped in gold junctions. The effects of charge injection, an applied electric field, and molecular deformation are considered. We found that a new Raman peak located at around 1400 cm−1 appears after the injection of a charge, which agrees well with the experiment. The external electric field and configurational deformation hardly affect the Raman spectra, indicating that the electronic rather than the geometrical structure determines the Raman response. Nonequilibrium Green’s function (NEGF) calculations show that both the rotation of the benzene groups and an increased electrode distance largely reduced the conductivity of the studied molecular junctions. The present investigations provide valuable information on the effect of charging, electric field, and deformation on the SERS and conductivity of molecular junctions, helping the development of molecular devices. Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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13 pages, 3898 KiB  
Article
Non-Restoring Array Divider Using Optimized CAS Cells Based on Quantum-Dot Cellular Automata with Minimized Latency and Power Dissipation for Quantum Computing
by Hyun-Il Kim and Jun-Cheol Jeon
Nanomaterials 2022, 12(3), 540; https://doi.org/10.3390/nano12030540 - 4 Feb 2022
Cited by 8 | Viewed by 2390
Abstract
Many studies have addressed the physical limitations of complementary metal-oxide semi-conductor (CMOS) technology and the need for next-generation technologies, and quantum-dot cellular automata (QCA) are emerging as a replacement for nanotechnology. Meanwhile, the divider is the most-used circuit in arithmetic operations with squares [...] Read more.
Many studies have addressed the physical limitations of complementary metal-oxide semi-conductor (CMOS) technology and the need for next-generation technologies, and quantum-dot cellular automata (QCA) are emerging as a replacement for nanotechnology. Meanwhile, the divider is the most-used circuit in arithmetic operations with squares and multipliers, and the development of effective dividers is crucial for improving the efficiency of inversion and exponentiation, which is known as the most complex operation. In most public-key cryptography systems, the corresponding operations are used by applying algebraic structures such as fields or groups. In this paper, an improved design of a non-restoring array divider (N-RAD) is proposed based on the promising technology of QCA. Our QCA design is focused on the optimization of dividers using controlled add/subtract (CAS) cells composed of an XOR and full adder. We propose a new CAS cell using a full adder that is designed to be very stable and compact so that power dissipation is minimized. The proposed design is considerably improved in many ways compared with the best existing N-RADs and is verified through simulations using QCADesigner and QCAPro. The proposed full adder reduces the energy loss rate by at least 25% compared to the existing structures, and the divider has about 23%~4.5% lower latency compared to the latest coplanar and multilayer structures. Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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19 pages, 6455 KiB  
Article
Inverse Identification of Single-Crystal Plasticity Parameters of HCP Zinc from Nanoindentation Curves and Residual Topographies
by Pham T. N. Nguyen, Fazilay Abbès, Jean-Sébastien Lecomte, Christophe Schuman and Boussad Abbès
Nanomaterials 2022, 12(3), 300; https://doi.org/10.3390/nano12030300 - 18 Jan 2022
Cited by 7 | Viewed by 2399
Abstract
This paper investigates the orientation-dependent characteristics of pure zinc under localized loading using nanoindentation experiments and crystal plasticity finite element (CPFEM) simulations. Nanoindentation experiments on different grain orientations exhibited distinct load–depth responses. Atomic force microscopy revealed two-fold unsymmetrical material pile-up patterns. Obtaining crystal [...] Read more.
This paper investigates the orientation-dependent characteristics of pure zinc under localized loading using nanoindentation experiments and crystal plasticity finite element (CPFEM) simulations. Nanoindentation experiments on different grain orientations exhibited distinct load–depth responses. Atomic force microscopy revealed two-fold unsymmetrical material pile-up patterns. Obtaining crystal plasticity model parameters usually requires time-consuming micromechanical tests. Inverse analysis using experimental and simulated loading–unloading nanoindentation curves of individual grains is commonly used, however the solution to the inverse identification problem is not necessarily unique. In this study, an approach is presented allowing the identification of CPFEM constitutive parameters from nanoindentation curves and residual topographies. The proposed approach combines the response surface methodology together with a genetic algorithm to determine an optimal set of parameters. The CPFEM simulations corroborate with measured nanoindentation curves and residual profiles and reveal the evolution of deformation activity underneath the indenter. Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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18 pages, 16530 KiB  
Article
Multi-Scale Modelling of Aggregation of TiO2 Nanoparticle Suspensions in Water
by Giulia Mancardi, Matteo Alberghini, Neus Aguilera-Porta, Monica Calatayud, Pietro Asinari and Eliodoro Chiavazzo
Nanomaterials 2022, 12(2), 217; https://doi.org/10.3390/nano12020217 - 10 Jan 2022
Cited by 8 | Viewed by 3507
Abstract
Titanium dioxide nanoparticles have risen concerns about their possible toxicity and the European Food Safety Authority recently banned the use of TiO2 nano-additive in food products. Following the intent of relating nanomaterials atomic structure with their toxicity without having to conduct large-scale [...] Read more.
Titanium dioxide nanoparticles have risen concerns about their possible toxicity and the European Food Safety Authority recently banned the use of TiO2 nano-additive in food products. Following the intent of relating nanomaterials atomic structure with their toxicity without having to conduct large-scale experiments on living organisms, we investigate the aggregation of titanium dioxide nanoparticles using a multi-scale technique: starting from ab initio Density Functional Theory to get an accurate determination of the energetics and electronic structure, we switch to classical Molecular Dynamics simulations to calculate the Potential of Mean Force for the connection of two identical nanoparticles in water; the fitting of the latter by a set of mathematical equations is the key for the upscale. Lastly, we perform Brownian Dynamics simulations where each nanoparticle is a spherical bead. This coarsening strategy allows studying the aggregation of a few thousand nanoparticles. Applying this novel procedure, we find three new molecular descriptors, namely, the aggregation free energy and two numerical parameters used to correct the observed deviation from the aggregation kinetics described by the Smoluchowski theory. Ultimately, molecular descriptors can be fed into QSAR models to predict the toxicity of a material knowing its physicochemical properties, enabling safe design strategies. Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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14 pages, 5178 KiB  
Article
Computational Prediction and Experimental Values of Mechanical Properties of Carbon Nanotube Reinforced Cement
by Carlos Talayero, Omar Aït-Salem, Pedro Gallego, Alicia Páez-Pavón, Rosario G. Merodio-Perea and Isabel Lado-Touriño
Nanomaterials 2021, 11(11), 2997; https://doi.org/10.3390/nano11112997 - 8 Nov 2021
Cited by 14 | Viewed by 2492
Abstract
The main objective of this study is to create a rigorous computer model of carbon nanotube composites to predict their mechanical properties before they are manufactured and to reduce the number of physical tests. A detailed comparison between experimental and computational results of [...] Read more.
The main objective of this study is to create a rigorous computer model of carbon nanotube composites to predict their mechanical properties before they are manufactured and to reduce the number of physical tests. A detailed comparison between experimental and computational results of a cement-based composite is made to match data and find the most significant parameters. It is also shown how the properties of the nanotubes (Young’s modulus, aspect ratio, quantity, directionality, clustering) and the cement (Young’s modulus) affect the composite properties. This paper tries to focus on the problem of modeling carbon nanotube composites computationally, and further study proposals are given. Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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12 pages, 2400 KiB  
Article
Electromechanical Characteristics by a Vertical Flip of C70 Fullerene Prolate Spheroid in a Single-Electron Transistor: Hybrid Density Functional Methods
by Jong Woan Choi, Changhoon Lee, Eiji Osawa, Ji Young Lee, Jung Chul Sur and Kee Hag Lee
Nanomaterials 2021, 11(11), 2995; https://doi.org/10.3390/nano11112995 - 8 Nov 2021
Cited by 1 | Viewed by 1573
Abstract
In this study, the B3LYP hybrid density functional theory was used to investigate the electromechanical characteristics of C70 fullerene with and without point charges to model the effect of the surface of the gate electrode in a C70 single-electron transistor (SET). [...] Read more.
In this study, the B3LYP hybrid density functional theory was used to investigate the electromechanical characteristics of C70 fullerene with and without point charges to model the effect of the surface of the gate electrode in a C70 single-electron transistor (SET). To understand electron tunneling through C70 fullerene species in a single-C70 transistor, descriptors of geometrical atomic structures and frontier molecular orbitals were analyzed. The findings regarding the node planes of the lowest unoccupied molecular orbitals (LUMOs) of C70 and both the highest occupied molecular orbitals (HOMOs) and the LUMO of the C70 anion suggest that electron tunneling of pristine C70 prolate spheroidal fullerene could be better in the major axis orientation when facing the gate electrode than in the major (longer) axis orientation when facing the Au source and drain electrodes. In addition, we explored the effect on the geometrical atomic structure of C70 by a single-electron addition, in which the maximum change for the distance between two carbon sites of C70 is 0.02 Å. Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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21 pages, 9357 KiB  
Article
Computational Study of Quenching Effects on Growth Processes and Size Distributions of Silicon Nanoparticles at a Thermal Plasma Tail
by Masaya Shigeta, Yusuke Hirayama and Emanuele Ghedini
Nanomaterials 2021, 11(6), 1370; https://doi.org/10.3390/nano11061370 - 21 May 2021
Cited by 17 | Viewed by 3949
Abstract
In this paper, quenching effects on silicon nanoparticle growth processes and size distributions at a typical range of cooling rates in a thermal plasma tail are investigated computationally. We used a nodal-type model that expresses a size distribution evolving temporally with simultaneous homogeneous [...] Read more.
In this paper, quenching effects on silicon nanoparticle growth processes and size distributions at a typical range of cooling rates in a thermal plasma tail are investigated computationally. We used a nodal-type model that expresses a size distribution evolving temporally with simultaneous homogeneous nucleation, heterogeneous condensation, interparticle coagulation, and melting point depression. The numerically obtained size distributions exhibit similar size ranges and tendencies to those of experiment results obtained with and without quenching. In a highly supersaturated state, 40–50% of the vapor atoms are converted rapidly to nanoparticles. After most vapor atoms are consumed, the nanoparticles grow by coagulation, which occurs much more slowly than condensation. At higher cooling rates, one obtains greater total number density, smaller size, and smaller standard deviation. Quenching in thermal plasma fabrication is effectual, but it presents limitations for controlling nanoparticle characteristics. Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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14 pages, 27701 KiB  
Article
Artificial Neural Network-Based Prediction of the Optical Properties of Spherical Core–Shell Plasmonic Metastructures
by Ehsan Vahidzadeh and Karthik Shankar
Nanomaterials 2021, 11(3), 633; https://doi.org/10.3390/nano11030633 - 4 Mar 2021
Cited by 14 | Viewed by 4018
Abstract
The substitution of time- and labor-intensive empirical research as well as slow finite difference time domain (FDTD) simulations with revolutionary techniques such as artificial neural network (ANN)-based predictive modeling is the next trend in the field of nanophotonics. In this work, we demonstrated [...] Read more.
The substitution of time- and labor-intensive empirical research as well as slow finite difference time domain (FDTD) simulations with revolutionary techniques such as artificial neural network (ANN)-based predictive modeling is the next trend in the field of nanophotonics. In this work, we demonstrated that neural networks with proper architectures can rapidly predict the far-field optical response of core–shell plasmonic metastructures. The results obtained with artificial neural networks are comparable with FDTD simulations in accuracy but the speed of obtaining them is between 100–1000 times faster than FDTD simulations. Further, we have proven that ANNs does not have problems associated with FDTD simulations such as dependency of the speed of convergence on the size of the structure. The other trend in photonics is the inverse design problem, where the far-field optical response of a spherical core–shell metastructure can be linked to the design parameters such as type of the material(s), core radius, and shell thickness using a neural network. The findings of this paper provide evidence that machine learning (ML) techniques such as artificial neural networks can potentially replace time-consuming finite domain methods in the future. Full article
(This article belongs to the Special Issue Computational Study of Nanomaterials)
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