Computational Materials Science最新文献

{"title":"An advanced deep learning approach for energy absorption prediction in porous metals across diverse strain rate scenarios","authors":"Minghai Tang,&nbsp;Lei Wang,&nbsp;Junyong Song","doi":"10.1016/j.commatsci.2025.113862","DOIUrl":"10.1016/j.commatsci.2025.113862","url":null,"abstract":"<div><div>Different strain rates affect yield stresses, influencing energy absorption characteristics. Thus, analyzing porous metals requires considering both quasi-static and impact loads. Current methods, like experiments and finite element method, often fail to assess all factors quickly. Hence, this study introduces a deep learning model that integrates convolutional neural network (CNN) and long short-term memory network (LSTM) to analyze the energy absorption characteristics of different porous metals under various strain rates scenarios. Firstly, ABAQUS/Explicit is developed using Python for batch computing to construct the dataset. Three types of loads, quasi-static compression and impact loads (strain rates of <span><math><mrow><msup><mrow><mtext>92.59 s</mtext></mrow><mrow><mo>-</mo><mn>1</mn></mrow></msup></mrow></math></span> and <span><math><mrow><msup><mrow><mtext>231.21 s</mtext></mrow><mrow><mo>-</mo><mn>1</mn></mrow></msup></mrow></math></span>), are considered. Subsequently, the microstructure of porous metals, encoded with strain rate, is simultaneously fed into the CNN for feature extraction. Finally, the output of the CNN, in conjunction with the strain data, is utilized as input for the LSTM, which establishes the intrinsic correlation among microstructure, strain rate, and energy absorption characteristics. Results show that the CNN-LSTM model achieves an accurate and fast prediction of the energy absorption characteristics of porous metals with both random pores and circular pores in a wide range of strain rates. Additionally, the CNN-LSTM model assesses the time accumulation of energy absorption, enhancing the accuracy and comprehensiveness of the overall energy absorption evaluation. It is anticipated that a method based on deep learning can offer a fresh perspective on assessing the exceptional performance of intricate porous materials across diverse loading scenarios.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113862"},"PeriodicalIF":3.1,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760438","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":"Molecular dynamics study of nano-iron H2O reaction properties and the effect of ether encapsulation in high temperature environment","authors":"Lei Wang ,&nbsp;Xile Qian ,&nbsp;Tao Wang ,&nbsp;Pingan Liu","doi":"10.1016/j.commatsci.2025.113660","DOIUrl":"10.1016/j.commatsci.2025.113660","url":null,"abstract":"<div><div>In this study, the reactive molecular dynamics method was employed to investigate the FNP-H₂O, with the parameters analyzed including the proportion of crystalline atoms within the particles, the radial distribution function (RDF) of the key atom pairs, the mean-square displacements (MSD) of the shell and core atoms, the number of H₂O molecules adsorbed on the surface, the number of atomic displacements and the number of key atom pairs in the reaction process during the reaction process of iron nanoparticles (FNPs) of different particle sizes during the aqueous reaction process at different temperatures, and to characterize the FNP-H₂O reaction characteristics were investigated. The findings indicate that decreasing the particle size of FNP facilitates its entry into the pre-ignition state, thereby reducing the ignition delay time. The H₂O molecules adsorbed on the surface of FNP contribute to enhancing the structural stability of the amorphous atoms on the FNP surface before the temperature elevation to 907.2 K. The analysis of the reaction products reveals that Fe-O compounds and Fe-H compounds are the predominant components of the Fe-H₂O reaction products. The ether capping layer’s effect on the ignition mechanism of the FNP-H₂O reaction was also investigated, and the results showed that the ether molecules were directly involved in the whole ignition process of the FNP-H₂O reaction, and had an important influence on the ignition mechanism of the FNP-H₂O reaction. This study has enhanced our comprehension of the FNP-H₂O reaction mechanism and the influence of the ether coating layer, and it has played a guiding role in the subsequent enhancement of the ignition and combustion performance of FNP.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113660"},"PeriodicalIF":3.1,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760439","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":"A review on all-atom force fields capabilities to predict polymer properties: Case of poly(methyl methacrylate) and polyisobutylene polymer systems","authors":"R.L. Nkepsu Mbitou,&nbsp;F. Bedoui","doi":"10.1016/j.commatsci.2025.113861","DOIUrl":"10.1016/j.commatsci.2025.113861","url":null,"abstract":"<div><div>The strategy of this review is to list and discuss the most commonly used Class I and Class II atomistic force fields. The corresponding force-field parameters are detailed, and the functional form difference is mentioned in terms of each generation of the force field. The validity of each force field was checked by comparing the simulated properties values of two polymer test cases, with their experimental values. It was observed that Class II force fields are more convenient for predicting the thermomechanical properties of amorphous polymer systems, and they could be good candidates for molecular simulations of polymers reinforced by nanoparticles.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113861"},"PeriodicalIF":3.1,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760437","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}

{"title":"Magnetic phase transitions in (1−x)BiFeO3–xPbFe1/2Sb1/2O3 solid solutions studied by the Monte Carlo method","authors":"A.V. Motseyko ,&nbsp;A.V. Pushkarev ,&nbsp;N.M. Olekhnovich ,&nbsp;Y.V. Radyush ,&nbsp;N.V. Ter-Oganessian","doi":"10.1016/j.commatsci.2025.113860","DOIUrl":"10.1016/j.commatsci.2025.113860","url":null,"abstract":"<div><div>Bismuth ferrite (BiFeO<span><math><msub><mrow></mrow><mrow><mn>3</mn></mrow></msub></math></span>, BFO) and its solid solutions are promising multiferroic materials with both magnetic and ferroelectric orderings. One such solid solution is <span><math><mrow><mo>(</mo><mn>1</mn><mo>−</mo><mi>x</mi><mo>)</mo></mrow></math></span>BiFeO<span><math><msub><mrow></mrow><mrow><mn>3</mn></mrow></msub></math></span> – <span><math><mi>x</mi></math></span>PbFe<span><math><msub><mrow></mrow><mrow><mn>1</mn><mo>/</mo><mn>2</mn></mrow></msub></math></span>Sb<span><math><msub><mrow></mrow><mrow><mn>1</mn><mo>/</mo><mn>2</mn></mrow></msub></math></span>O<span><math><msub><mrow></mrow><mrow><mn>3</mn></mrow></msub></math></span>. PbFe<span><math><msub><mrow></mrow><mrow><mn>1</mn><mo>/</mo><mn>2</mn></mrow></msub></math></span>Sb<span><math><msub><mrow></mrow><mrow><mn>1</mn><mo>/</mo><mn>2</mn></mrow></msub></math></span>O₃ (PFS) is also considered multiferroic, exhibiting a high peak in the dielectric constant at 190 K and electric polarization loops below this temperature. However, the magnetic properties and the ground state of PFS remain subjects of debate. The magnetic behaviour is arguably further complicated by its strong tendency to form cation-ordered structures. In this study, we investigate the magnetism in the <span><math><mrow><mo>(</mo><mn>1</mn><mo>−</mo><mi>x</mi><mo>)</mo></mrow></math></span>BiFeO<span><math><msub><mrow></mrow><mrow><mn>3</mn></mrow></msub></math></span> – <span><math><mi>x</mi></math></span>PbFe<span><math><msub><mrow></mrow><mrow><mn>1</mn><mo>/</mo><mn>2</mn></mrow></msub></math></span>Sb<span><math><msub><mrow></mrow><mrow><mn>1</mn><mo>/</mo><mn>2</mn></mrow></msub></math></span>O<span><math><msub><mrow></mrow><mrow><mn>3</mn></mrow></msub></math></span> solid solutions using the Monte Carlo method. The evolution of the magnetic phase transition temperature and of the type of magnetic ordering with varying PFS concentration is examined. We consider different scenarios of Fe<span><math><mo>−</mo></math></span>Sb atomic ordering: disordered, clustered, or with varying degrees of ordering, and build phase diagrams providing insights into the magnetism of these solid solutions.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113860"},"PeriodicalIF":3.1,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760440","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":"Tensor equation of state for copper and aluminum","authors":"Boris A. Panchenko ,&nbsp;Eugenii V. Fomin ,&nbsp;Alexander E. Mayer","doi":"10.1016/j.commatsci.2025.113845","DOIUrl":"10.1016/j.commatsci.2025.113845","url":null,"abstract":"<div><div>Increasing the strain rate up to about 1/ns in the conditions of ultra-short-pulse powerful laser irradiation of thin metal foils of submicron thickness reveals very strong elastic precursors, for which decoupling of pressure and stress deviators is unreasonable. A nonlinear stress–strain relationship (tensor equation of state–TEOS) is required for establishing theoretical models of such dynamic processes and unsteady shock waves. We proposed an ANN-TEOS model, which adopts an artificial neural network (ANN) trained on the data of density functional theory (DFT) calculations for the cold curve and analytical form for thermal contributions fitted to molecular dynamics (MD) data. We showed the efficiency of feed-forward ANN in approximation of the cold curve. Besides, the range of applicability of Hooke’s law for approximation of the cold curve was examined. The DFT data were used to train a cold-curve ANN and to fit elastic constants of the Hooke’s law with nonlinear corrections for copper and aluminum. Whereas the ANN is applicable for a complex approximation within a wide range of deformed states, the Hooke’s law applicability is restricted to the strain level of about 0.1. MD simulations were used to construct and fit the thermal contributions. The developed ANN-TEOS model was applied to calculate the shock adiabats for both plastic shock wave (nearly hydrostatic omnidirectional loading) and elastic shock wave (uniaxial loading). Elastic shock Hugoniots lie above the plastic ones for both metals providing an opportunity for a shock wave to split into elastic precursor and plastic wave even for conditions, in which the plastic shock wave velocity exceeds the longitudinal sound speed. A simultaneous consideration of TEOS and plasticity model is required for the prediction of splitting and two-wave structure. Our comparison of several interatomic potentials with the stress sates calculated by means of DFT showed much higher precision of the classical force field in comparison with the examined machine-learning potentials for the considered problem of severe deformation. This result elucidates one more time the known problem of the restricted range of applicability of the machine-learning potentials and the need to include the required range of states in the training dataset for these potentials.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113845"},"PeriodicalIF":3.1,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761160","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":"Atomistic molecular dynamics simulations of the tensile strength properties of polymer-calcite systems","authors":"Keat Yung Hue ,&nbsp;Daniela Andrade Damasceno ,&nbsp;Myo Thant Maung Maung ,&nbsp;Paul F. Luckham ,&nbsp;Omar K. Matar ,&nbsp;Erich A. Müller","doi":"10.1016/j.commatsci.2025.113866","DOIUrl":"10.1016/j.commatsci.2025.113866","url":null,"abstract":"<div><div>The production of solids can occur in poorly consolidated carbonate rock reservoirs, leading to equipment damage and environmental waste. This issue can be mitigated by injecting formation-strengthening chemicals, and the performance of these chemicals can be assessed in terms of their tensile strength and interfacial interaction with calcite, the main component of carbonate formations. This study aims to investigate the tensile deformation behaviour of polymer-calcite systems. Classical atomistic molecular dynamics (MD) simulations are utilised to model the interaction of polyacrylamide-based polymer additives, including pure polyacrylamide (PAM), hydrolysed polyacrylamide (HPAM), and sulfonated polyacrylamide (SPAM) with a calcite (1 0 4) structure. Uniaxial tensile simulations demonstrate that the interfacial strength of the polymer-calcite system is significantly stronger than the corresponding bulk polymer strength, resulting in strong polymer adhesion at the calcite surface during deformation. HPAM exhibits high bulk polymer and interfacial strength, presumably due to the presence of the acrylate monomer in ionised form, making it an excellent formation-strengthening agent.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113866"},"PeriodicalIF":3.1,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747368","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}

{"title":"Atomistic simulations of short-range ordering with light interstitials in Inconel superalloys","authors":"Tyler D. Doležal ,&nbsp;Emre Tekoglu ,&nbsp;Jong-Soo Bae ,&nbsp;Gi-Dong Sim ,&nbsp;Rodrigo Freitas ,&nbsp;Ju Li","doi":"10.1016/j.commatsci.2025.113858","DOIUrl":"10.1016/j.commatsci.2025.113858","url":null,"abstract":"<div><div>This study employed hybrid Monte Carlo Molecular Dynamics simulations to investigate the short-range ordering behavior of Ni-based superalloys doped with boron or carbon. The simulations revealed that both boron and carbon dissociated from their host Ti atoms to achieve energetically favored ordering with Cr, Mo, and Nb. Boron clusters formed as B₂, surrounded by Mo, Nb, and Cr, while carbon preferentially clustered with Cr to form a Cr₂₃C₆ local motif and with Nb to form Nb₂C. Distinct preferences for interstitial sites were observed, with boron favoring tetrahedral sites and carbon occupying octahedral sites. In the presence of a vacancy, B₂ shifted from the tetrahedral site to the vacancy, where it remained coordinated with Mo, Nb, and Cr. Similarly, carbon utilized vacancies to form Nb₂C clusters. Excess energy calculations showed that B and C exhibited strong thermodynamic stability within their short-range ordered configurations. However, under Ti-rich conditions, C was more likely to segregate into TiC, despite preexisting ordering with Cr. This shift in stability suggests that increased Ti availability would alter carbide formation pathways, drawing C away from Cr-rich networks and promoting the development of TiC. Such redistribution may disrupt the continuity of Cr-based carbide networks, which play a critical role in stabilizing grain boundaries and impeding crack propagation. These effects further underscore the impact of interstitial-induced ordering on phase stability and microstructural evolution. This work provides an atomistic perspective on how boron- and carbon-induced ordering influences microstructure and mechanical properties. These findings highlight the critical role of interstitial-induced short-range ordering and demonstrate that this mechanism can be leveraged as a design principle to fine-tune alloy microstructures for specific engineering applications.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113858"},"PeriodicalIF":3.1,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747371","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":"Controlling grain boundary mobility in phase-field-crystal model","authors":"Zhanxin Xiao ,&nbsp;Xin Su ,&nbsp;Dan Mordehai ,&nbsp;Nan Wang","doi":"10.1016/j.commatsci.2025.113869","DOIUrl":"10.1016/j.commatsci.2025.113869","url":null,"abstract":"<div><div>Grain boundary (GB) mobility is a key parameter in modelling microstructure evolution of polycrystalline materials. It is well known that GB mobility depends on the misorientation and possibly other degrees of freedom of the GB. This misorientation dependence has been calculated in numerous previous studies using molecular dynamics (MD) for several materials. However, MD simulations are computationally demanding due to need to account for atomic fluctuations, where the recently developed phase-field-crystal (PFC) method is shown to overcome this shortcoming. Nonetheless, GB mobility was not extensively studied using PFC, and it is not clear if the mobility in the PFC method has a similar misorientation dependency as the one extracted from the MD simulation. This work addresses this issue by calculating the GB mobility for several GBs in Nickel using both the MD simulation and the PFC. It is found that the misorientation dependent GB mobility in the PFC follow similar behavior as in the MD results when the kinetic factor is tuned to depend on the local-averaged density order parameter in the PFC model.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113869"},"PeriodicalIF":3.1,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747370","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":"A decision transformer approach to grain boundary network optimization","authors":"Christopher W. Adair,&nbsp;Oliver K. Johnson","doi":"10.1016/j.commatsci.2025.113852","DOIUrl":"10.1016/j.commatsci.2025.113852","url":null,"abstract":"<div><div>As microstructure property models improve, additional information from crystallographic degrees of freedom and grain boundary networks (GBNs) can be included in microstructure design problems. However, the high-dimensional nature of including this information precludes the use of many common optimization approaches and requires less efficient methods to generate quality designs. Previous work demonstrated that human-in-the-loop optimization, instantiated as a video game, achieved high-quality, efficient solutions to these design problems. However, such data is expensive to obtain. In the present work, we show how a Decision Transformer machine learning (ML) model can be used to learn from the optimization trajectories generated by human players, and subsequently solve materials design problems. We compare the ML optimization trajectories against players and a common global optimization algorithm: simulated annealing (SA). We find that the ML model exhibits a validation accuracy of 84% against player decisions, and achieves solutions of comparable quality to SA (92%), but does so using three orders of magnitude fewer iterations. We find that the ML model generalizes in important and surprising ways, including the ability to train using a simple constitutive structure–property model and then solve microstructure design problems for a different, higher-fidelity, constitutive structure–property model without any retraining. These results demonstrate the potential of Decision Transformer models for the solution of materials design problems.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113852"},"PeriodicalIF":3.1,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747425","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":"First-principles study on local site preference of interstitial oxygen in Ti3Zr1.5NbVAl0.25 high-entropy alloy","authors":"Ruili Liu ,&nbsp;Ruizhi Lu ,&nbsp;Aimin Wang ,&nbsp;Zhengwang Zhu ,&nbsp;Hao Wang","doi":"10.1016/j.commatsci.2025.113867","DOIUrl":"10.1016/j.commatsci.2025.113867","url":null,"abstract":"<div><div>The occupancy of interstitial oxygen atoms in high-entropy alloy exhibits site preferences, thus affecting alloy properties. In this work, first-principles calculations were employed to investigate the physical origin of the local site preference of oxygen in Ti₃Zr_1.5NbVAl_0.25 high-entropy alloy. The results indicate that the formation energies are closely correlated with the coordinating atoms in the interstitial environment. Interstitial oxygen tends to occupy the coordination environment of Ti and Zr, which is not conducive to stabilizing the Al coordination environment. Such local site preference primarily depends on the amount of charge transfer and lattice distortion, which encourages interstitial oxygen to occupy Ti and Zr-rich environments. Conversely, minimal charge transfer between Al and oxygen hinders the solid solution of interstitial oxygen. The present work thus offers insights and theoretical guidance for the design of high-performance lightweight refractory high-entropy alloys.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113867"},"PeriodicalIF":3.1,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747369","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}