Computational Materials Science最新文献

{"title":"Impacts of alkali and alkaline earth defects on the Electronic, magnetic properties and work function of 2H-CrS2","authors":"Xuejiao Wang,&nbsp;Xintao Li,&nbsp;Longhua Li","doi":"10.1016/j.commatsci.2025.113822","DOIUrl":"10.1016/j.commatsci.2025.113822","url":null,"abstract":"<div><div>The substitutional doping method offers a unique opportunity to engineer the electronic and magnetic properties of 2D materials, possible to design new materials for nanoelectronics. Herein, by means of density functional theory (DFT), we systematically studied the structure, electronic, magnetic properties and work function of ten alkali and alkaline earth metals (X) substitution for S doping CrS₂ (X_S-CrS₂). The formation and binding energy calculations indicate that the X_S-CrS₂ may be realized in experiments. The ab-initio molecular dynamics (AIMD) and elastic constants further suggest the stability of the doping structures. The electronic structures show that the electronic band gap is determined by the splitting energy of impurity states induced by X, creating pairs of electron and hole traps close to the Fermi level. The local magnetic moments of Cr are significantly enhanced by the X_S doping. In particular, it is found that the work functions of X_S-CrS₂ are asymmetric and linearly dependent on the atomic number of X. The alkali and alkaline earth metals reduce the work function on the top of the X_S-CrS₂ nanosheets by 0.4–1.7 eV compared to the pristine 2H-CrS₂. Moreover, the work function exhibits a linear relationship with the dipole moment of the nanosheet. All these findings provide insights in the defect behavior of alkali and alkaline earth metals and provide possibilities for electronics applications for X_S-CrS₂.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113822"},"PeriodicalIF":3.1,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Short-range order based ultra fast large-scale modeling of high-entropy alloys","authors":"Caimei Niu ,&nbsp;Lifeng Liu","doi":"10.1016/j.commatsci.2025.113792","DOIUrl":"10.1016/j.commatsci.2025.113792","url":null,"abstract":"<div><div>High-Entropy Alloys (HEAs) exhibit complex atomic interactions, with short-range order (SRO) playing a critical role in determining their properties. Traditional methods, such as Monte Carlo generator of Special Quasirandom Structures within the Alloy Theoretic Automated Toolkit (ATAT-mcsqs), Super-Cell Random APproximates (SCRAPs), and hybrid Monte Carlo-Molecular Dynamics (MC-MD)—are often hindered by limited system sizes and high computational costs. In response, we introduce PyHEA, a Python-based toolkit with a high-performance C++ core that leverages global and local search algorithms, incremental SRO computations, and GPU acceleration for unprecedented efficiency. When constructing random HEAs, PyHEA achieves speedups exceeding 333,000<span><math><mo>×</mo></math></span> and 13,900<span><math><mo>×</mo></math></span> over ATAT-mcsqs and SCRAPs, respectively, while maintaining high accuracy. PyHEA also offers a flexible workflow that allows users to incorporate target SRO values from external simulations (e.g., LAMMPS or density functional theory (DFT)), thereby enabling more realistic and customizable HEA models. As a proof of concept, PyHEA successfully replicated literature results for a 256,000-atom Fe–Mn–Cr–Co system within minutes—an order-of-magnitude improvement over hybrid MC-MD approaches. This dramatic acceleration opens new possibilities for bridging theoretical insights and practical applications, paving the way for the efficient design of next-generation HEAs.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113792"},"PeriodicalIF":3.1,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting the heat of formation and energy above convex hull of 2D MXenes using machine-learning methods","authors":"Umair Haider ,&nbsp;Gul Rahman ,&nbsp;Imen Kebaili ,&nbsp;Norah Alomayrah","doi":"10.1016/j.commatsci.2025.113790","DOIUrl":"10.1016/j.commatsci.2025.113790","url":null,"abstract":"<div><div>MXenes provide a high degree of compositional flexibility that can be used to provide adjustable mechanical, optical, and electrical properties. We provide a set of machine learning algorithms that are designed to forecast the heat of formation of MXenes and the energy above the convex hull. Our model is trained on 300 entries from the Computational 2D Materials Database (C2DB) using the fundamental chemical properties of the elements that make up MXene as features. The neural network model predicts the heat of formation using 12 different MXenes characteristics, with a mean absolute error (MAE) of 0.18 eV on training data and 0.21 eV on testing data. Characteristics of atoms terminating the MXene surface, including electronegativity, are important, according to feature importance analysis. Additionally, we employ a neural network model to estimate energy above the convex hull based on 14 characteristics. With a MAE of 0.03 eV on training data and 0.08 eV on testing data, the neural network model predicts the energy above the convex hull. We introduce reduced-order models comprising seven and four features. These reduced-order models exhibit easier transferability while exhibiting the same mean average error.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113790"},"PeriodicalIF":3.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143549338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Morphologies and interlayer delamination of multilayer graphene on rough Au substrate","authors":"Shuhong Dong ,&nbsp;Lin Yao ,&nbsp;Jiukang Fang","doi":"10.1016/j.commatsci.2025.113810","DOIUrl":"10.1016/j.commatsci.2025.113810","url":null,"abstract":"<div><div>Recently, Au-assisted exfoliation method [<em>Nat. Commun.</em>, 2020, 11(1): 2453; <em>Sci. Adv.</em>, 2020, 6(44): eabc6601] has been identified as a universal route for producing large-area graphene monolayers because of large interfacial adhesion between Au and graphene. However, atomically flat Au films are difficult to be prepared in available experiments. In this study, the effects of rough Au substrate on the configuration and interlayer delamination of multilayer graphene are analyzed by combining theoretical models with molecular dynamics simulations. The competition between interfacial van der Waals interaction and bending energy of multilayer graphene determines morphologies of graphene membranes. In particular, the interface delamination of multilayer graphene can be regulated by amplitudes and wavelengths of rough Au substrate. This study provides a deep understanding of bending behaviors of two-dimensional multilayer nanomaterials on rough substrate, which is of great importance for designing multilayer graphene-based electron devices.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"252 ","pages":"Article 113810"},"PeriodicalIF":3.1,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143549580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on spatiotemporal prediction model of grain microstructure evolution based on VMamba network","authors":"Li Jing-jie ,&nbsp;Chang-sheng Zhu ,&nbsp;Li Tian-yu ,&nbsp;Gao Zi-hao ,&nbsp;Liu Shuo ,&nbsp;Cao Hang ,&nbsp;Miao Jin-tao","doi":"10.1016/j.commatsci.2025.113793","DOIUrl":"10.1016/j.commatsci.2025.113793","url":null,"abstract":"<div><div>The evolution of microstructure is essentially a spatiotemporal prediction problem, so developing effective spatiotemporal models is crucial for accurately describing this process. It is of great significance to adopt deep learning techniques to accurately predict grain growth by learning the spatiotemporal characteristics of historical microstructure data, in order to address the problems of large computational complexity and high computational complexity in phase field method calculations. This study proposes a novel grain microstructure evolution prediction model, the Visual Mamba Grain Microstructure Evolution Prediction Model (VMmabaGP), which fully utilizes the powerful capabilities of VMamba Network and spatiotemporal attention mechanism to accurately predict the evolution process of grain microstructure. Based on this model, training was conducted on publicly available datasets for grain growth and self-made datasets for the microstructure evolution of Ni–Cu binary alloy dendrites. The dynamic evolution process of grain microstructure was predicted and the predicted results were compared and analyzed with the calculation results of traditional methods. The results showed that the grain growth prediction results were consistent with the phase field method calculation results. Comparing VMmabaGP with existing advanced models such as SimVP and TAU, the prediction performance was excellent, with an average MSE decrease of 57.4% and an average SSIM improvement of 43.7%, proving the high prediction accuracy and generalization ability of VMambaGP model on different datasets. The prediction results of the microstructure evolution of Ni–Cu binary alloy dendrites reveal the complex relationship between dendrite morphology and solid solute diffusion coefficient during the solidification process. In particular, this model has significantly improved computational efficiency, with a 400% increase compared to traditional phase field models. Therefore, it can solve the problems of high computational complexity and complexity in phase field calculations, demonstrating its enormous potential in multiple fields such as material design. The code dataset for this study can be obtained from the following URL <span><span>https://github.com/ljj123-wed/VMmabaGP</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"252 ","pages":"Article 113793"},"PeriodicalIF":3.1,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Theoretical investigation of the mechanical and thermodynamic properties of TiGN2 (G = Al, Hf and Ta) ceramics: Advanced TiN-based solid solutions","authors":"Nana Wan ,&nbsp;Meiyun zhang ,&nbsp;Hongying Li ,&nbsp;Xuyun Zhang ,&nbsp;Zhengke Chen ,&nbsp;Haiqing Wan ,&nbsp;Diyou Jiang","doi":"10.1016/j.commatsci.2025.113813","DOIUrl":"10.1016/j.commatsci.2025.113813","url":null,"abstract":"<div><div>This paper investigated the mechanical and thermodynamic properties of TiGN₂ (G = Al, Ta, and Hf) ceramics based on first principles methods. The results show that the C₁₁, bulk modulus, melting and B/G values of TiTaN₂ are as high as 680GPa, 340GPa, 3565 K and 1.902, which are obviously higher than TiN, TiAlN₂ and TiHfN₂, which shows excellent stiffness, strength, melting and ductility. In addition, the bulk modulus of TiTaN₂ is also obviously higher than that of TiN, TiAlN₂ and TiHfN₂ at high temperatures, showing high temperature strength properties. The thermal expansion coefficients of TiTaN₂ and TiHfN₂ are obviously smaller than that of TiN. In particular, TiTaN₂ at high temperatures exhibits thermal expansion suppression. The lattice thermal conductivity of TiAlN₂ is greater than that of TiN, while the lattice thermal conductivities of TiHfN₂ and TiTaN₂ are obviously smaller than TiN, indicating that doping Hf/Ta elements can reduce the thermal conductivity of TiN.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"252 ","pages":"Article 113813"},"PeriodicalIF":3.1,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Atomic-scale study of lattice distortion and oxygen-rich environment impact on the surface degradation dynamics of zinc-based alloys","authors":"Vladimir A. Bryzgalov ,&nbsp;Andrey A. Kistanov ,&nbsp;Artem A. Izosimov ,&nbsp;Elena A. Korznikova","doi":"10.1016/j.commatsci.2025.113797","DOIUrl":"10.1016/j.commatsci.2025.113797","url":null,"abstract":"<div><div>Mechanical stress and environmental conditions are main factors affecting the corrosion process of Zn-based alloys. In this work, density functional theory-based simulations are utilized to study the atomic-scale mechanism of degradation of the Zn-based alloys surface. Our findings suggest that lattice distortion promotes surface degradation of Zn-based alloys by increasing their surface reactivity and reducing work function, thus, decreasing O₂ adsorption energy. Oxygen adsorption on Zn surface can lead to the formation of a local dipole, which increases the work function of the surface. Notably, at a specific tensile strain of 1.5 % a reorientation of a local dipole induces an increase of the O₂ adsorption energy. These results highlight the significant impact of lattice distortion and the O₂ adsorption on the degradation dynamics of Zn-based alloys, offering valuable insights for the design of advanced biodegradable Zn-based alloys.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"252 ","pages":"Article 113797"},"PeriodicalIF":3.1,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation on the aggregation behavior and mechanical properties of silica-filled natural rubber composites: A coarse-grained molecular dynamics study","authors":"Hongyu Guo,&nbsp;Fanlin Zeng,&nbsp;Jianzheng Cui,&nbsp;Qing Li","doi":"10.1016/j.commatsci.2025.113815","DOIUrl":"10.1016/j.commatsci.2025.113815","url":null,"abstract":"<div><div>Understanding the particle aggregation behavior in filled rubber is crucial for developing high-performance composite materials. Herein, the effect of the spatial distribution of silica nanoparticles, the length of matrix molecular chains, and the crosslinking of the matrix on the mechanical properties of natural rubber (NR) composites were systematically investigated using coarse-grained molecular dynamics (CGMD) simulations. The results show that with the increase in the degree of silica nanoparticle aggregation, the stress level of the filled rubber in the small deformation stage is significantly increased, but in the large deformation stage, it is significantly reduced. The former can be attributed to the supporting effect of the high strength and rigidity of the particle network in the small deformation stage, while the latter can be attributed to the gradual failure of the particle network in the large deformation stage and the weakening of the adsorption of the particles on the rubber molecular chain. Moreover, it was found that longer molecular chains reduced particle aggregation by enhancing particle encapsulation and interface interactions, while crosslinked networks promoted aggregation behavior by restricting particle mobility through a cage structure. To explain in depth the inherent enhancement mechanism of nanoparticle-filled rubber, microstructure property analysis, such as mean square displacement, interaction energy, and bond orientation, has been implemented and discussed.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"252 ","pages":"Article 113815"},"PeriodicalIF":3.1,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mechanistic insights into nanoscale heat transfer on platinum surfaces using molecular dynamics simulations","authors":"Mukesh Kumar ,&nbsp;Anusree S. Chandran ,&nbsp;Manikantan R. Nair ,&nbsp;Tribeni Roy ,&nbsp;Santosh Kumar Tamang","doi":"10.1016/j.commatsci.2025.113817","DOIUrl":"10.1016/j.commatsci.2025.113817","url":null,"abstract":"<div><div>Cooling microelectronics devices is challenging, and phase change heat transfer at the nanoscale is considered an effective method to overcome this. However, designing heat transfer at the nanoscale requires a mechanistic understanding of the solid–liquid interface at the molecular level. Hence, this study focuses on investigating the interactions between liquid coolant (water nanodroplets) and solid surface (platinum) using molecular dynamics simulations, focusing on how varying energy coefficients (α) influence heat transfer. The simulation results indicate that the wettability of the platinum surface is significantly affected by variations in energy coefficients. At a high energy coefficient (α = 3.0), the contact angle is 49.09˚, indicating higher wettability, while a low energy coefficient (α = 0.1) results in lower wettability. Improved wettability indirectly corresponds to enhanced heat transfer, as higher wettability indicates a better surface area for heat transfer. Further, potential energy analysis conducted as part of the work shows a decreasing trend with increasing energy coefficient value, indicating the reason for improved wettability. From the study, it was also observed that higher wettability has contributed towards better heat transfer, and this has been analyzed using the changes in the heat flux concerning increasing energy coefficient values. From the results, an increasing trend in the values of average heat flux with a higher value of 1.6 × 10⁻⁵ Wm⁻² for α = 3.0 and a lesser value of −4.40 × 10⁻⁷ Wm⁻² for α = 0.1 was observed. This confirms that heat transfer is better at higher energy coefficients. This study highlights the pivotal role of energy coefficients in optimizing heat transfer at the nanoscale, providing valuable insights for designing advanced thermal management systems.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"252 ","pages":"Article 113817"},"PeriodicalIF":3.1,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143549579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Layered double hydroxides reinforced epoxy composites: Computational analysis of microstructure effect on strength","authors":"Sigitas Kilikevičius ,&nbsp;Leon Mishnaevsky Jr. ,&nbsp;Daiva Zeleniakiene","doi":"10.1016/j.commatsci.2025.113816","DOIUrl":"10.1016/j.commatsci.2025.113816","url":null,"abstract":"<div><div>This paper analyses the mechanical and damage behaviour of epoxy composites incorporating magnesium–aluminium layered double hydroxides (LDH), which have potential applications as corrosion protective coatings. The analysis of these composites was carried out by developing a computational model based on numerical homogenisation approach, employing the micromechanical finite element method. The influence of the elastic modulus, aspect ratio and weight fractions of the LDH particles on the mechanical and damage behaviour of epoxy/LDH composites was investigated. Damage modelling was performed, capturing both crack formation and evolution. Damage mechanisms such as crack pinning and crack deflection due to the LDH particles were observed. The modelling demonstrated that with an increase in the weight fraction of LDH, the composite became stiffer and more brittle. Adding up to 5 wt% LDH particles to epoxy increased the elastic modulus of the composite by nearly 20%. The strain at break was reduced to 2 %. The model was validated against experimental data, demonstrating its ability to predict the behaviour of epoxy/LDH composites. The findings indicate that epoxy/LDH composites exhibit enhanced stiffness, making them suitable for practical applications as corrosion-protective coatings.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"252 ","pages":"Article 113816"},"PeriodicalIF":3.1,"publicationDate":"2025-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143527129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}