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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 September 2022) | Viewed by 20055

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Prof. Dr. Seung Geol Lee

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Department of Materials Science and Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
Interests: battery/super capacitor/fuel-cell; CCS (carbon dioxide capture & sequestration); super absorbent polymer; hybrid interface design for composites
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Dear Colleagues,

In the future, research on high-value-added products with new functions using materials created by the fusion of science and technology will be widely and actively conducted. Related industrial fields are expected to be reorganized in accordance with the appearance of new industries. Although nanomaterials have been researched and their activated surface shows more unique attributes than the existing materials, there are constraints to applying them to the industry due to difficulty in materializing other complex functions with them and their small volumes. Hybridization of heterogeneous materials or heterogeneous scales is a new materials technology that has been assessed as new technology to create various functional materials. Computational materials science enables the functional interface and surface to design, invent, and forecast nanomaterials properties using computer simulation techniques such as density functional theory (DFT), molecular dynamics (MD), Monte Carlo (MC) method, finite element methods (FEM), and machine learning (ML) approaches. All topics potentially falling into the category of computational materials science will be considered, including inorganic materials (metals, ceramics, composites, semiconductors, nanostructures, 2D materials, metamaterials, etc.), organic materials (polymers, liquid crystals, surfactants, emulsions, etc.) and hybrid materials of inorganic and organic components. Both original research articles, in the form of full papers or communications, and reviews are welcome.

Prof. Dr. Seung Geol Lee
Guest Editor

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Keywords

functional materials
functional interfaces and surfaces
computational materials science
first principle calculations
density functional theory (DFT)
molecular dynamics (MD)
Monte Carlo (MC) method
mesoscale simulations
finite element methods (FEM)
multiscale simulations
machine learning (ML)

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Related Special Issue

Advances in Computational Materials Science on Functional Interfaces and Surfaces, Volume II in Nanomaterials (1 article)

Published Papers (12 papers)

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Research

11 pages, 3591 KiB

Open AccessArticle

Tuning the Magnetic Properties of Cr₂TiC₂T_x through Surface Terminations: A Theoretical Study

by Shaozheng Zhang, Yuanting Zhou, Xing Liang, Yulin Wang, Tong Wang, Jianhui Yang and Liang Lv

Nanomaterials 2022, 12(24), 4364; https://doi.org/10.3390/nano12244364 - 7 Dec 2022

Cited by 4 | Viewed by 1569

Abstract

Recently, magnetic two-dimensional Cr₂TiC₂T_x MXenes with promising applications in spin electronics have been experimentally confirmed. However, the underlying magnetic mechanism needs to be further investigated. Along these lines, in this work, the magnetic properties of Cr₂TiC₂O_n/4F_2−n/4 and Cr₂TiC₂O_n/4 structures were simulated through first-principle calculations using the GGA+U approach. The values of 4.1 and 3.1 eV were calculated for the Hubbard U of Cr and Ti, respectively, by applying the linear response method. Interestingly, the Cr₂TiC₂O_n/4F_2−n/4-based configurations with low O content (n ≤ 4) exhibit antiferromagnetic behavior, while the majority of the respective configurations with high O content (n ≥ 5) are ferromagnetic. As far as the Cr₂TiC₂O_5/4F_3/4 structure (n = 5) is concerned, the value of about 2.64 μ_B was estimated for the magnetic moment of the Cr atom. On top of that, the Curie temperature lies within the range of 10~47 K. The extracted theoretical results are in good agreement with experimental outcomes of the Cr₂TiC₂O_1.3F_0.8-based structure. From the simulated results, it can be also argued that the magnetic moment of Cr atoms and the Neel temperature can be directly tuned by the active content of O atoms. The conductivity of both Cr₂TiC₂O_n/4F_2−n/4 and Cr₂TiC₂O_n/4 configurations can be regulated by the externally applied magnetic field, while the density of states around the Fermi level shifted significantly between ferromagnetic and antiferromagnetic arrangements. The acquired results provide important theoretical insights to tuning the magnetic properties of Cr₂TiC₂T_x-based structures through surface termination mechanisms, which are quite significant for their potential applications in spin electronics. Full article

(This article belongs to the Special Issue Advances in Computational Materials Science on Functional Interfaces and Surfaces)

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15 pages, 6543 KiB

Open AccessArticle

Molecular Dynamics and Experimental Investigation on the Interfacial Binding Mechanism in the Fe/Cu_1−x-Ni_x Bimetallic Interface

by Guowei Zhang, Mingjie Wang, Huan Yu, Hong Xu and An Wan

Nanomaterials 2022, 12(18), 3245; https://doi.org/10.3390/nano12183245 - 19 Sep 2022

Cited by 2 | Viewed by 1947

Abstract

To systematically investigate the diffusion behavior of Fe/Cu bimetallic materials and the influence of the Ni element on the diffusion and mechanical properties of the Fe/Cu bimetallic interface, the diffusion distance, diffusion coefficient, and strain–stress process based on molecular dynamics (MD) calculations and experimental testing were analyzed. All simulation results indicated that the liquid Cu matrix had a higher diffusion coefficient but hardly diffused into the Fe matrix, and the solid Fe matrix had a smaller diffusion coefficient but diffused deep into the Cu matrix at the same temperature. Compared with the initial state, the addition of nickel atoms to the Cu matrix favored the improvement of the diffusion coefficient and the diffusion distance of Fe/Cu bimetallic materials. Moreover, we found that the diffusion distance and the yield strength simultaneously increased and then decreased with the increase in Ni atoms, which is in agreement with the experimental test results. These improvements in the diffusion and mechanical properties were attributed to the enrichment of Ni atoms at the interface, but excessive Ni content resulted in deteriorated properties. Finally, our research described the enhancement mechanism of the addition of nickel atoms to the Fe/Cu bimetallic diffusion system. An analysis of the contributions of the diffusion distance, the diffusion coefficient, and the yield strength revealed that the diffusion properties of nickel atoms play an important role in Fe/Cu bimetallic materials. Full article

(This article belongs to the Special Issue Advances in Computational Materials Science on Functional Interfaces and Surfaces)

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13 pages, 2729 KiB

Open AccessArticle

Predicting the Properties of High-Performance Epoxy Resin by Machine Learning Using Molecular Dynamics Simulations

by Joohee Choi, Haisu Kang, Ji Hee Lee, Sung Hyun Kwon and Seung Geol Lee

Nanomaterials 2022, 12(14), 2353; https://doi.org/10.3390/nano12142353 - 9 Jul 2022

Cited by 6 | Viewed by 3929

Abstract

Epoxy resin is an of the most widely used adhesives for various applications owing to its outstanding properties. The performance of epoxy systems varies significantly depending on the composition of the base resin and curing agent. However, there are limitations in exploring numerous formulations of epoxy resins to optimize adhesive properties because of the expense and time-consuming nature of the trial-and-error process. Herein, molecular dynamics (MD) simulations and machine learning (ML) methods were used to overcome these challenges and predict the adhesive properties of epoxy resin. Datasets for diverse epoxy adhesive formulations were constructed by considering the degree of crosslinking, density, free volume, cohesive energy density, modulus, and glass transition temperature. A linear correlation analysis demonstrated that the content of the curing agents, especially dicyandiamide (DICY), had the greatest correlation with the cohesive energy density. Moreover, the content of tetraglycidyl methylene dianiline (TGMDA) had the highest correlation with the modulus, and the content of diglycidyl ether of bisphenol A (DGEBA) had the highest correlation with the glass transition temperature. An optimized artificial neural network (ANN) model was constructed using test sets divided from MD datasets through error and linear regression analyses. The root mean square error (RMSE) and correlation coefficient (R²) showed the potential of each model in predicting epoxy properties, with high linear correlations (0.835–0.986). This technique can be extended for optimizing the composition of other epoxy resin systems. Full article

(This article belongs to the Special Issue Advances in Computational Materials Science on Functional Interfaces and Surfaces)

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10 pages, 2113 KiB

Open AccessArticle

Near-Infrared Absorption Properties of Neutral Bis(1,2-dithiolene) Platinum(II) Complexes Using Density Functional Theory

by Xuan-Hoang Luong, Nguyet N. T. Pham, Kyoung-Lyong An, Seong Uk Lee, Shi Surk Kim, Jong S. Park and Seung Geol Lee

Nanomaterials 2022, 12(10), 1704; https://doi.org/10.3390/nano12101704 - 17 May 2022

Cited by 6 | Viewed by 2204

Abstract

Small metal complexes are highly interesting for bioimaging because of their excellent near-infrared (NIR) absorption properties. In this study, neutral complexes of platinum(II) connected to two monoreduced 1,3-diisopropylimidazoline-2,4,5-trithione ligands—namely, [Pt(iPr₂timdt)₂]—were investigated. Theoretical studies using the density functional theory (DFT) and GW-BSE approximation verified the effects of the geometry of the isopropyl moieties on the NIR absorption spectra. The calculated absorption spectra showed excellent correspondence with the experimental results. The geometry of the isopropyl groups considerably influenced the electronic structures of the metal complexes, which altered the absorption profiles of the respective geometries, as demonstrated in this research. Full article

(This article belongs to the Special Issue Advances in Computational Materials Science on Functional Interfaces and Surfaces)

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13 pages, 5321 KiB

Open AccessArticle

The Effects of the Temperature and Termination(-O) on the Friction and Adhesion Properties of MXenes Using Molecular Dynamics Simulation

by Yao Deng, Yu Chen, Hanxu Liu and Xin Yan

Nanomaterials 2022, 12(5), 798; https://doi.org/10.3390/nano12050798 - 26 Feb 2022

Cited by 7 | Viewed by 2730

Abstract

Two-dimensional transition metal carbides and nitrides (MXenes) are widely applied in the fields of electrochemistry, energy storage, electromagnetism, etc., due to their extremely excellent properties, including mechanical performance, thermal stability, photothermal conversion and abundant surface properties. Usually, the surfaces of the MXenes are terminated by –OH, –F, –O or other functional groups and these functional groups of MXenes are related surface properties and reported to affect the mechanical properties of MXenes. Thus, understanding the effects of surface terminal groups on the properties of MXenes is crucial for device fabrication as well as composite synthesis using MXenes. In this paper, using molecular dynamics (MD) simulation, we study the adhesion and friction properties of Ti₂C and Ti₂CO₂, including the indentation strength, adhesion energy and dynamics of friction. Our indentation fracture simulation reveals that there are many unbroken bonds and large residual stresses due to the oxidation of oxygen atoms on the surface of Ti₂CO₂. By contrast, the cracks of Ti₂C keep clean at all temperatures. In addition, we calculate the elastic constants of Ti₂C and Ti₂CO₂ by the fitting force–displacement curves with elastic plate theory and demonstrate that the elastic module of Ti₂CO₂ is higher. Although the temperature had a significant effect on the indentation fracture process, it hardly influences maximum adhesion. The adhesion energies of Ti₂C and Ti₂CO₂ were calculated to be 0.3 J/m² and 0.5 J/m² according to Maugis–Dugdale theory. In the friction simulation, the stick-slip atomic scale phenomenon is clearly observed. The friction force and roughness (Ra) of Ti₂C and Ti₂CO₂ at different temperatures are analyzed. Our study provides a comprehensive insight into the mechanical behavior of nanoindentation and the surface properties of oxygen functionalized MXenes, and the results are beneficial for the further design of nanodevices and composites. Full article

(This article belongs to the Special Issue Advances in Computational Materials Science on Functional Interfaces and Surfaces)

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10 pages, 32853 KiB

Open AccessArticle

Permeability of a Zinc-Methacrylate-Based Self-Polishing Copolymer for Use in Antifouling Coating Materials by Molecular Dynamics Simulations

by Sung Hyun Kwon, Inwon Lee, Hyun Park and Seung Geol Lee

Nanomaterials 2021, 11(11), 3141; https://doi.org/10.3390/nano11113141 - 21 Nov 2021

Cited by 3 | Viewed by 2089

Abstract

Molecular dynamics simulations were used to investigate the solubility and permeability of H₂O in a self-polishing copolymer (SPC) with two zinc methacrylate (ZMA) contents (Z2: 2 mol% ZMA; Z16: 16 mol% ZMA) and ethyl acrylate, methyl methacrylate, 2-methoxyethyl acrylate, and butyl acrylate as antifouling agents. Water was found to be more soluble in hydrated Z16 than Z2 because ZMA interacts strongly with H₂O. In contrast, the diffusion coefficient of H₂O in Z16 is lower than that of Z2 because H₂O molecules are more constrained in the former due to strong ZMA/H₂O interactions. Z16 was found to be significantly more permeable than Z2 over time. The SPC hydrated region in Z2 tends to expand toward the SPC region, while the analogous region in Z16 swelled toward both the SPC and H₂O regions to leach SPC owing to the higher permeation of H2O into the SPC. These results reveal that H₂O permeability can be controlled by adjusting the ZMA content, which provides insight into antifouling performance. Full article

(This article belongs to the Special Issue Advances in Computational Materials Science on Functional Interfaces and Surfaces)

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10 pages, 9063 KiB

Open AccessArticle

Analysis of Ionicity-Magnetism Competition in 2D-MX3 Halides towards a Low-Dimensional Materials Study Based on GPU-Enabled Computational Systems

by Alexey Kartsev, Sergey Malkovsky and Andrey Chibisov

Nanomaterials 2021, 11(11), 2967; https://doi.org/10.3390/nano11112967 - 5 Nov 2021

Cited by 10 | Viewed by 2258

Abstract

The acceleration of parallel high-throughput first-principle calculations in the context of 3D (three dimensional) periodic boundary conditions for low-dimensional systems, and particularly 2D materials, is an important issue for new material design. Where the scalability rapidly deflated due to the use of large void unit cells along with a significant number of atoms, which should mimic layered structures in the vacuum space. In this report, we explored the scalability and performance of the Quantum ESPRESSO package in the hybrid central processing unit - graphics processing unit (CPU-GPU) environment. The study carried out in the comparison to CPU-based systems for simulations of 2D magnets where significant improvement of computational speed was achieved based on the IBM ESSL SMP CUDA library. As an example of physics-related results, we have computed and discussed the ionicity-covalency and related ferro- (FM) and antiferro-magnetic (AFM) exchange competitions computed for some CrX

_{3}

compounds. Further, it has been demonstrated how this exchange interplay leads to high-order effects for the magnetism of the 1L-RuCl

_{3}

compound. Full article

(This article belongs to the Special Issue Advances in Computational Materials Science on Functional Interfaces and Surfaces)

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16 pages, 10093 KiB

Open AccessArticle

Using Dissipative Particle Dynamics to Model Effects of Chemical Reactions Occurring within Hydrogels

by Ya Liu, Joanna Aizenberg and Anna C. Balazs

Nanomaterials 2021, 11(10), 2764; https://doi.org/10.3390/nano11102764 - 19 Oct 2021

Cited by 5 | Viewed by 2550

Abstract

Computational models that reveal the structural response of polymer gels to changing, dissolved reactive chemical species would provide useful information about dynamically evolving environments. However, it remains challenging to devise one computational approach that can capture all the interconnected chemical events and responsive structural changes involved in this multi-stage, multi-component process. Here, we augment the dissipative particle dynamics (DPD) method to simulate the reaction of a gel with diffusing, dissolved chemicals to form kinetically stable complexes, which in turn cause concentration-dependent deformation of the gel. Using this model, we also examine how the addition of new chemical stimuli and subsequent reactions cause the gel to exhibit additional concentration-dependent structural changes. Through these DPD simulations, we show that the gel forms multiple latent states (not just the “on/off”) that indicate changes in the chemical composition of the fluidic environment. Hence, the gel can actuate a range of motion within the system, not just movements corresponding to the equilibrated swollen or collapsed states. Moreover, the system can be used as a sensor, since the structure of the layer effectively indicates the presence of chemical stimuli. Full article

(This article belongs to the Special Issue Advances in Computational Materials Science on Functional Interfaces and Surfaces)

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12 pages, 1924 KiB

Open AccessArticle

Optical and Electronic Properties of Organic NIR-II Fluorophores by Time-Dependent Density Functional Theory and Many-Body Perturbation Theory: GW-BSE Approaches

by Nguyet N. T. Pham, Seong Hun Han, Jong S. Park and Seung Geol Lee

Nanomaterials 2021, 11(9), 2293; https://doi.org/10.3390/nano11092293 - 3 Sep 2021

Cited by 6 | Viewed by 2937

Abstract

Organic-molecule fluorophores with emission wavelengths in the second near-infrared window (NIR-II, 1000–1700 nm) have attracted substantial attention in the life sciences and in biomedical applications because of their excellent resolution and sensitivity. However, adequate theoretical levels to provide efficient and accurate estimations of the optical and electronic properties of organic NIR-II fluorophores are lacking. The standard approach for these calculations has been time-dependent density functional theory (TDDFT). However, the size and large excitonic energies of these compounds pose challenges with respect to computational cost and time. In this study, we used the GW approximation combined with the Bethe-Salpeter equation (GW-BSE) implemented in many-body perturbation theory approaches based on density functional theory. This method was used to perform calculations of the excited states of two NIR molecular fluorophores (BTC980 and BTC1070), going beyond TDDFT. In this study, the optical absorption spectra and frontier molecular orbitals of these compounds were compared using TDDFT and GW-BSE calculations. The GW-BSE estimates showed excellent agreement with previously reported experimental results. Full article

(This article belongs to the Special Issue Advances in Computational Materials Science on Functional Interfaces and Surfaces)

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26 pages, 3389 KiB

Open AccessEditor’s ChoiceArticle

Coupling between Polymer Conformations and Dynamics Near Amorphous Silica Surfaces: A Direct Insight from Atomistic Simulations

by Petra Bačová, Wei Li, Alireza F. Behbahani, Craig Burkhart, Patrycja Polińska, Manolis Doxastakis and Vagelis Harmandaris

Nanomaterials 2021, 11(8), 2075; https://doi.org/10.3390/nano11082075 - 16 Aug 2021

Cited by 13 | Viewed by 2943

Abstract

The dynamics of polymer chains in the polymer/solid interphase region have been a point of debate in recent years. Its understanding is the first step towards the description and the prediction of the properties of a wide family of commercially used polymeric-based nanostructured materials. Here, we present a detailed investigation of the conformational and dynamical features of unentangled and mildly entangled cis-1,4-polybutadiene melts in the vicinity of amorphous silica surface via atomistic simulations. Accounting for the roughness of the surface, we analyze the properties of the polymer chains as a function of their distance from the silica slab, their conformations and the chain molecular weight. Unlike the case of perfectly flat and homogeneous surfaces, the monomeric translational motion parallel to the surface was affected by the presence of the silica slab up to distances comparable with the extension of the density fluctuations. In addition, the intramolecular dynamical heterogeneities in adsorbed chains were revealed by linking the conformations and the structure of the adsorbed chains with their dynamical properties. Strong dynamical heterogeneities within the adsorbed layer are found, with the chains possessing longer sequences of adsorbed segments (“trains”) exhibiting slower dynamics than the adsorbed chains with short ones. Our results suggest that, apart from the density-dynamics correlation, the configurational entropy plays an important role in the dynamical response of the polymers confined between the silica slabs. Full article

(This article belongs to the Special Issue Advances in Computational Materials Science on Functional Interfaces and Surfaces)

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14 pages, 4947 KiB

Open AccessArticle

Experimental Investigation and Molecular Dynamics Simulation on the Anti-Adhesion Behavior of Alkanethiols on Nickel Insert in Micro Injection Molding

by Can Weng, Jiachen Chen, Jin Yang, Mingyong Zhou and Bingyan Jiang

Nanomaterials 2021, 11(7), 1834; https://doi.org/10.3390/nano11071834 - 14 Jul 2021

Cited by 2 | Viewed by 2104

Abstract

Due to the adhesion between the polymer melt and nickel (Ni) mold insert in the micro injection molding process, deformation defects frequently occur when the microstructures are demolded from the insert. In this study, self-assembled alkanethiols were applied to modify the surface of Ni mold insert to reduce its surface energy. Experimental trials were undertaken to explore the effect of alkanethiols coating on the replication quality. After that, molecular dynamics (MD) simulation was then used to investigate the adhesion behavior between the self-assembled coating and polypropylene (PP) by establishing three different types of alkanethiol material. The interaction energy, the potential energy change and radial distribution function were calculated to study the anti-adhesion mechanism. Experimental results show that all the three coatings can effectively decrease the adhesion and therefore promote the replication fidelity. It is demonstrated in MD simulation that the adhesion mainly comes from the van der Waals (vdW) force at the interface. The arrangement of sulfur atom on the Ni surface results in different absorbing behaviors. Compared with that of the PP–Ni interface, the interfacial energy and adhesion work after surface treatment is significantly reduced. Full article

(This article belongs to the Special Issue Advances in Computational Materials Science on Functional Interfaces and Surfaces)

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13 pages, 2533 KiB

Open AccessArticle

Prediction of Lap Shear Strength and Impact Peel Strength of Epoxy Adhesive by Machine Learning Approach

by Haisu Kang, Ji Hee Lee, Youngson Choe and Seung Geol Lee

Nanomaterials 2021, 11(4), 872; https://doi.org/10.3390/nano11040872 - 30 Mar 2021

Cited by 19 | Viewed by 4869

Abstract

In this study, an artificial neural network (ANN), which is a machine learning (ML) method, is used to predict the adhesion strength of structural epoxy adhesives. The data sets were obtained by testing the lap shear strength at room temperature and the impact peel strength at −40 °C for specimens of various epoxy adhesive formulations. The linear correlation analysis showed that the content of the catalyst, flexibilizer, and the curing agent in the epoxy formulation exhibited the highest correlation with the lap shear strength. Using the analyzed data sets, we constructed an ANN model and optimized it with the selection set and training set divided from the data sets. The obtained root mean square error (RMSE) and R² values confirmed that each model was a suitable predictive model. The change of the lap shear strength and impact peel strength was predicted according to the change in the content of components shown to have a high linear correlation with the lap shear strength and the impact peel strength. Consequently, the contents of the formulation components that resulted in the optimum adhesive strength of epoxy were obtained by our prediction model. Full article

(This article belongs to the Special Issue Advances in Computational Materials Science on Functional Interfaces and Surfaces)

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