Modelling and Simulation in Materials Science and Engineering最新文献

{"title":"Atomic thermal fluctuation reduction method for robust local lattice structure identification in finite-temperature molecular dynamics","authors":"Atsuo Hirano, Yosuke Tsunemoto and Akiyuki Takahashi","doi":"10.1088/1361-651x/ad5dd4","DOIUrl":"https://doi.org/10.1088/1361-651x/ad5dd4","url":null,"abstract":"Classical molecular dynamics (MD) is extensively employed to explore the properties, deformations, and fractures of materials at the atomic scale. Identifying local structures is crucial for understanding the mechanisms behind material deformation and fracture. Nevertheless, analyzing the local lattice structure at high temperatures poses challenges due to atomic thermal fluctuations, which act as noise and potentially lead to misjudgment of the local lattice structure. To date, various strategies have been implemented to circumvent this issue. However, they cannot be a solution because it is unable to reproduce phenomena unique to high temperatures, whereas others require significant computational resources. This paper introduces an innovative method to reduce atomic thermal fluctuations using a straightforward algorithm, thereby facilitating accurate identification of local lattice structures even at high temperatures. Our approach incorporates novel degrees of freedom, termed ‘Markers,’ that are linked to atoms. By reducing the thermal fluctuation of these Markers, precise analysis of the local lattice structure becomes feasible. The efficacy of this method is validated through its thermal reducibility and Markers trackabilities to atoms. Utilizing common neighbor analysis, the error rate for structure identification with our method is nearly 0% at temperatures up to 1200 K in Fe, in contrast to approximately 5% without it. Furthermore, the average distance between atoms and Markers remains below 0.1 Å. Applying our method to phase transformations, we successfully observed the transition from face-centered cubic to body-centered cubic structure in Fe at 1200 K. This method holds promise for expanding the capabilities of MD simulations at high temperatures.","PeriodicalId":18648,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"31 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141587983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Roadmap on data-centric materials science","authors":"Stefan Bauer, Peter Benner, Tristan Bereau, Volker Blum, Mario Boley, Christian Carbogno, C Richard A Catlow, Gerhard Dehm, Sebastian Eibl, Ralph Ernstorfer, Ádám Fekete, Lucas Foppa, Peter Fratzl, Christoph Freysoldt, Baptiste Gault, Luca M Ghiringhelli, Sajal K Giri, Anton Gladyshev, Pawan Goyal, Jason Hattrick-Simpers, Lara Kabalan, Petr Karpov, Mohammad S Khorrami, Christoph T. Koch, Sebastian Kokott, Thomas Kosch, Igor Kowalec, Kurt Kremer, Andreas Leitherer, Yue Li, Christian H Liebscher, Andrew J Logsdail, Zhongwei Lu, Felix Luong, Andreas Marek, Florian Merz, Jaber R Mianroodi, Jörg Neugebauer, Zongrui Pei, Thomas A R Purcell, Dierk Raabe, Markus Rampp, Mariana Rossi, Jan-Michael Rost, James Saal, Ulf Saalmann, Kasturi Narasimha Sasidhar, Alaukik Saxena, Luigi Sbailò, Markus Scheidgen, Marcel Schloz, Daniel F Schmidt, Simon Teshuva, Annette Trunschke, Ye Wei, Gerhard Weikum, R Patrick Xian, Yi Yao, Junqi Yin, Meng Zhao and Matthias Scheffler","doi":"10.1088/1361-651x/ad4d0d","DOIUrl":"https://doi.org/10.1088/1361-651x/ad4d0d","url":null,"abstract":"Science is and always has been based on data, but the terms ‘data-centric’ and the ‘4th paradigm’ of materials research indicate a radical change in how information is retrieved, handled and research is performed. It signifies a transformative shift towards managing vast data collections, digital repositories, and innovative data analytics methods. The integration of artificial intelligence and its subset machine learning, has become pivotal in addressing all these challenges. This Roadmap on Data-Centric Materials Science explores fundamental concepts and methodologies, illustrating diverse applications in electronic-structure theory, soft matter theory, microstructure research, and experimental techniques like photoemission, atom probe tomography, and electron microscopy. While the roadmap delves into specific areas within the broad interdisciplinary field of materials science, the provided examples elucidate key concepts applicable to a wider range of topics. The discussed instances offer insights into addressing the multifaceted challenges encountered in contemporary materials research.","PeriodicalId":18648,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"14 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141516485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SCAPS 1D based study of hole and electron transfer layers to improve MoS2–ZrS2 solar cell efficiency","authors":"Bhoomi S Shah, Jiten P Tailor, Sunil H Chaki and M P Deshpande","doi":"10.1088/1361-651x/ad5a2b","DOIUrl":"https://doi.org/10.1088/1361-651x/ad5a2b","url":null,"abstract":"In the realm of photovoltaic applications, scientists and technocrats are striving to maximize the solar cell input photon energy conversion to electricity. However, achieving optimal cell efficiency requires significant time and energy investment for each variation and optimization. To overcome this issue authors simulated and studied the fabricated cell for optimizing conditions, which can save time and efforts for the relatively better outcomes. The family of transition metal chalcogenides holds promise as a material that yield improved outcomes in optoelectronic applications, particularly in photovoltaics. These materials are employed in experimental investigations aimed at enhancing solar cell parameters, resulting in the development of the FTO/ZnO/ZrS2/MoS2/CuO/Au composite cell. Numerical simulations utilizing SCAPS-1D software is conducted, focusing on the significance of CuO as a hole transport layer (HTL), and ZnO as an electron transport layer (ETL). The investigation examines into the impact of various factors, including thickness, bandgap, and carrier densities for both HTL and ETL, on fundamental solar cell parameters. The study indicates that device parameters are influenced by factors such as recombination rate, photogenerated current, charge carrier length, and built-in-voltage. Optimized parameters for HTL, including thickness, bandgap, and carrier concentration, are determined to be 0⋅35 μm, 1⋅2 eV, and 1⋅0 × 1020 cm–3, respectively. For ETL, the optimized parameters are found to be 0⋅05 μm, 3⋅1 eV, and 1⋅0 × 1018 cm–3, respectively. With these optimized parameters, the efficiency of the solar cell reached 20⋅64%, accompanied by open circuit voltage, short circuit current density, and fill factor values of 0.836 V, 36.021 mA⋅cm–2, and 68⋅54%, respectively. The simulated results indicate that addition of two extra layers and the use of efficient binary materials in heterojunction formation can effectively enhance device parameters, offering advantages such as low-cost and large-scale fabrication.","PeriodicalId":18648,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"103 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 insights on the self-interstitial diffusion in α-Beryllium","authors":"Huiming Wang, Jianfeng Jin, Dongxin Wang, Demei Xu, Kaiqi Guo, Peijun Yang and Gaowu Qin","doi":"10.1088/1361-651x/ad5a2a","DOIUrl":"https://doi.org/10.1088/1361-651x/ad5a2a","url":null,"abstract":"Beryllium has some unique properties and plays a key role in many special applications. However, Beryllium (α-Be) is of close-packed hexagonal (HCP) crystal structure, which has a strong anisotropic feature and limits its applications. In this work, diffusion behaviors of the self-interstitial atom (SIA) in α-Be at the temperature of 300–1100 K are studied using molecular dynamics simulations. It is observed that the diffusion mechanisms are not only dominated by the SIA jumps among the BO and BS sites on the basal plane, but also by the jumps among the C and O sites along the c-axis, which strongly depend on temperature. Diffusion behaviors of SIA can be divided into two stages with the temperature of 300–800 K and 800–1100 K, respectively, in which diffusion coefficient component of the c-axis (Dc) is higher than that of the basal plane (Db) at first and then becomes closer to the Db after 800 K, in consistent with diffusion mechanisms. When the temperature rises from 300 K to 1100 K, the total diffusion coefficient of SIA (Dt) increases gradually from 0.34 × 10−4 cm2 s−1 to 1.13 × 10−4 cm2 s−1. With the temperature increasing from 300 K to 1100 K, the anisotropy factor (η = Dc/Db) of SIA diffusion drastically decreases from 1.76 to 1.01 in α-Be, while the η increases from 0.21 to 0.70 in α-Zr with the temperature from 500 K to 1100 K.","PeriodicalId":18648,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"43 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 DFT study on structural, electronic, and optical properties of cubic perovskite semiconductors InXF3 (X = Be and Ca) for optoelectronic applications","authors":"M Mohammed Shoaib Hussain, N Syed Kaleemullah, G Ajay and M Mohamed Sheik Sirajuddeen","doi":"10.1088/1361-651x/ad5a2c","DOIUrl":"https://doi.org/10.1088/1361-651x/ad5a2c","url":null,"abstract":"First principles calculations were employed to study the structural, electronic and optical properties of Indium based cubic perovskite materials, specifically focusing on InBeF3 and InCaF3 compounds. The generalized gradient approximation Perdew–Burke–Ernzerhof (GGA_PBE) approximation and Tran–Blaha modified Becke–Johnson (TB-mBJ) approximations were used to study and compare the electronic and optical properties. The compound InBeF3 is predicted to have an indirect band gap of 2.51 eV in GGA_PBE and 2.96 eV in TB-mBJ. InCaF3 is found to have a direct wide band gap of 3.61 eV in GGA_PBE and 4.37 eV in TB-mBJ approximation. The partial density of states predicts the significance of In-5p and F-2p states in the conduction and valence bands, respectively. The dielectric constants decrease under the TB-mBJ approximation, with InCaF3 demonstrating lower values owing to its larger band gap. Optical activity analysis indicates transparency for both compounds with notable absorption peaks, suggesting potential applications in transparent coatings. Refractive indices decrease with photon energy, with values dropping below 1.0 in the TB-mBJ approximation, indicating superluminal behavior in wave propagation. The drop in refractive index value below1.0 is earlier for InCaF3 than InBeF3. Examination of the extinction coefficient reveals UV absorption peaks, indicating potential for optoelectronic applications. From this study it can be noticed that the compounds under study can be used for optoelectronic applications, supported by their predicted structural and optical properties study.","PeriodicalId":18648,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"5 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141516546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 machine learning framework for the prediction of grain boundary segregation in chemically complex environments","authors":"Doruk Aksoy, Jian Luo, Penghui Cao and Timothy J Rupert","doi":"10.1088/1361-651x/ad585f","DOIUrl":"https://doi.org/10.1088/1361-651x/ad585f","url":null,"abstract":"The discovery of complex concentrated alloys (CCA) has unveiled materials with diverse atomic environments, prompting the exploration of solute segregation beyond dilute alloys. However, the vast number of possible elemental interactions means a computationally prohibitive number of simulations are needed for comprehensive segregation energy spectrum analysis. Data-driven methods offer promising solutions for overcoming such limitations for modeling segregation in such chemically complex environments (CCEs), and are employed in this study to understand segregation behavior of a refractory CCA, NbMoTaW. A flexible methodology is developed that uses composable computational modules, with different arrangements of these modules employed to obtain site availabilities at absolute zero and the corresponding density of states beyond the dilute limit, resulting in an extremely large dataset containing 10 million data points. The artificial neural network developed here can rely solely on descriptions of local atomic environments to predict behavior at the dilute limit with very small errors, while the addition of negative segregation instance classification allows any solute concentration from zero up to the equiatomic concentration for ternary or quaternary alloys to be modeled at room temperature. The machine learning model thus achieves a significant speed advantage over traditional atomistic simulations, being four orders of magnitude faster, while only experiencing a minimal reduction in accuracy. This efficiency presents a powerful tool for rapid microstructural and interfacial design in unseen domains. Scientifically, our approach reveals a transition in the segregation behavior of Mo from unfavorable in simple systems to favorable in complex environments. Additionally, increasing solute concentration was observed to cause anti-segregation sites to begin to fill, challenging conventional understanding and highlighting the complexity of segregation dynamics in CCEs.","PeriodicalId":18648,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"227 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141516544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The property of CrCoNiFeMnAl x (x=0, 0.5, and 1) high-entropy alloys on rapid cooling: insights from ab initio molecular dynamics","authors":"Luyu Wang, Xinxin Liu and Zhibin Gao","doi":"10.1088/1361-651x/ad585e","DOIUrl":"https://doi.org/10.1088/1361-651x/ad585e","url":null,"abstract":"High-entropy alloys (HEAs) are currently the subject of extensive research. Despite this, the effects of rapid cooling on their performance have yet to be investigated. This study uses ab initio molecular dynamics to investigate the CrCoFeNiMnAlx (x =0, 0.5 and 1) HEAs under a rapid cooling process. It has been observed that the three HEAs all form metallic glass at 300 K under a constant cooling rate of 1.25 × 102 K ps−1, mainly composed of icosahedron and face-centered cubic clusters. Secondly, the glass transition temperatures (Tg) are predicted to be 1658 K for CrCoFeNiMn, 1667 K for CrCoFeNiMnAl0.5, and 1687 K for CrCoFeNiMnAl, respectively. It can be seen the Tg of HEAs increases with the content of Al increasing. Eventually, a relationship between structure and dynamics is established by using the five-fold local symmetry parameters and shear viscosity, which proves that structural evolution is the fundamental reason for dynamic deceleration. The present results contribute to understanding the evolution of the local structure of CrCoFeNiMnAlx and provide a new perspective for studying the structural mechanism of dynamic retardation in HEAs.","PeriodicalId":18648,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"29 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simulation of taper heating and variable pressing rate to improve extrusion performance for high-strength aluminum alloys","authors":"Vladimir N Danilin, Alexander S Aleshchenko, Andrei V Danilin and Alexander N Koshmin","doi":"10.1088/1361-651x/ad56a6","DOIUrl":"https://doi.org/10.1088/1361-651x/ad56a6","url":null,"abstract":"The main process parameters of direct and indirect extrusion of aluminum alloys were studied using FE-modeling in this article. The subject of the study was the use of billets taper heating and variable pressing rate as compared to the standard extrusion conditions. Extrusion of AA2024 grade alloy and experimental Al-2%Cu-1.5%Mn-1%Mg-1%Zn alloy was considered. The flow stress-on-strain dependences within the 350 °C–450 °C range at strain rates of 0.1–10 s−1 were determined for the experimental alloy. Considering the time of billet transportation to the extrusion equipment, its optimum temperature gradient was determined to be 500 °C at the front end and 140 °C at the tail end. Direct extrusion of taper heated billets at the variable rate and elongation of 7 allowed increasing the process performance by 5.6 times (from 1.8 mm s−1 to an average of 10 mm s−1, in case uniformly heated billets are extruded at the constant rate). In case of pressing at high elongations (15 and 25), the performance increase was about 2 times. It was found that the use of taper heating, both in case of grade alloy and model alloy extrusion, in all the considered conditions, allows achieving a significant increase in performance. However, these results are considered to be most effective in case of direct extrusion at small elongation ratios.","PeriodicalId":18648,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"179 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141516545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Crystal orbital overlap population based on all-electron ab initio simulation with numeric atom-centered orbitals and its application to chemical-bonding analysis in Li-intercalated layered materials","authors":"Izumi Takahara, Kiyou Shibata, Teruyasu Mizoguchi","doi":"10.1088/1361-651x/ad4c82","DOIUrl":"https://doi.org/10.1088/1361-651x/ad4c82","url":null,"abstract":"Crystal orbital overlap population (COOP) is one of the effective tools for chemical-bonding analysis, and thus it has been utilized in the materials development and characterization. In this study, we developed a code to perform the COOP-based chemical-bonding analysis based on the wave function obtained from a first principles all-electron calculation with numeric atom-centered orbitals. The chemical-bonding analysis using the developed code was demonstrated for F₂, Si, CaC₆, and metals including Ti and Nb. Furthermore, we applied the method to analyze the chemical-bonding changes associated with a Li intercalation in three representative layered materials: graphite, MoS₂, and ZrNCl, because of their great industrial importance, particularly for the applications in battery and superconducting materials. The COOP analysis provided some insights for understanding the intercalation mechanism and the stability of the intercalated materials from a chemical-bonding viewpoint.","PeriodicalId":18648,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"56 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141546735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adsorption structure and properties of Ni/Fe electrodeposition interface: a DFT study","authors":"Shiqing Yang, Guoxing Liang, Yonggui Huang, Xinhui Hao, Jian Zhao and Ming Lv","doi":"10.1088/1361-651x/ad4b4d","DOIUrl":"https://doi.org/10.1088/1361-651x/ad4b4d","url":null,"abstract":"The density functional theory calculations of the adsorption model of NiCl2, Ni, and Cl on the Fe surface, as well as interface electronic properties, provide theoretical guidance for improving the Ni electrodeposition process. The adsorption properties of these three species on the Fe (100) crystal surface at different coverages, and the adsorption properties of the single Ni on three different crystal surfaces of Fe (100), Fe (110), and Fe (111), were studied through calculations of adsorption energy, charge density, charge occupancy, and DOS. The results indicate that the H sites are the most favorable for the adsorption of Ni and Cl on the Fe (100) surface. T sites, B sites, and H sites are all potential adsorption sites for NiCl2. The order of adsorption strength is Ni > Cl > NiCl2. In response to changes in charge, the adsorption effect exhibits a negative correlation with surface coverage. In addition, the hybridization of Ni’s 3d orbitals, Cl’s 3p orbitals, and Fe’s 3d orbitals changes the distribution of the interface charge, resulting in an increase of the charge in the Fe surface. Ni exhibits better adsorption performance on Fe (100) surface, driven by the lattice structure, surface electron configuration, and Ni–Fe atomic interactions.","PeriodicalId":18648,"journal":{"name":"Modelling and Simulation in Materials Science and Engineering","volume":"4 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141258603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}