Computational Materials Science最新文献_第2页

First-principles study on local site preference of interstitial oxygen in Ti3Zr1.5NbVAl0.25 high-entropy alloy

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-03-31 DOI: 10.1016/j.commatsci.2025.113867

Ruili Liu , Ruizhi Lu , Aimin Wang , Zhengwang Zhu , Hao Wang

引用次数: 0

Structural and mechanical properties of W-Cu compounds characterized by a neural-network-based potential

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-03-29 DOI: 10.1016/j.commatsci.2025.113825

Jianchuan Liu , Tao Chen , Sheng Mao , Mohan Chen

引用次数: 0

Design of novel interpretable deep learning framework for microstructure–property relationships in nickel and cobalt based superalloys

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-03-29 DOI: 10.1016/j.commatsci.2025.113854

Aditya Gollapalli, Abhishek Kumar Singh

{"title":"Design of novel interpretable deep learning framework for microstructure–property relationships in nickel and cobalt based superalloys","authors":"Aditya Gollapalli, Abhishek Kumar Singh","doi":"10.1016/j.commatsci.2025.113854","DOIUrl":"10.1016/j.commatsci.2025.113854","url":null,"abstract":"<div><div>Featurization of microstructures is one of the most fundamental challenges in establishing microstructure–property relationships. Conventional machine learning and statistical methods require explicit featurization methods such as image processing, which are difficult to implement for complex and diverse sets of microstructures. To this end, deep learning methods such as convolution neural networks (CNNs) have been used to automate the featurization based on target properties. However, these CNNs do not include composition information limiting them to a single set of compositions. Moreover, these networks are complex and difficult to interpret. To overcome these challenges, a deep learning mixed input network consisting of a convolutional neural network (CNN) for microstructure input and an artificial neural network (ANN) for composition input is developed to predict the Vickers hardness of nickel and cobalt-based superalloys. A unique three-step optimization procedure is employed to reduce the complexity of the network. The network architecture is designed based on hardening models which allows the analysis of contributions of precipitation hardening and solid solution strengthening to the Vickers hardness. The network has been analyzed using synthetically generated controlled microstructures to understand the effect of microstructural features on the hardness. Furthermore, SHAPley additive explanations (SHAP) analysis has been used to understand the effect of composition and assess the interdependence between microstructure and composition in determining hardness.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113854"},"PeriodicalIF":3.1,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143734820","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}

引用次数: 0

A universal ML model for segregation in W

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-03-29 DOI: 10.1016/j.commatsci.2025.113847

Christoph Dösinger , Oleg E. Peil , Daniel Scheiber , Lorenz Romaner

{"title":"A universal ML model for segregation in W","authors":"Christoph Dösinger , Oleg E. Peil , Daniel Scheiber , Lorenz Romaner","doi":"10.1016/j.commatsci.2025.113847","DOIUrl":"10.1016/j.commatsci.2025.113847","url":null,"abstract":"<div><div>Segregation of solute elements to grain-boundaries (GB) in alloys is a key process controlling material properties. Examples are phase transformations, strength, or nanocrystalline stability. The central quantities to predict GB segregation are the site-specific segregation energies which can be accurately calculated using density functional theory (DFT). To reduce the computational cost, machine learning (ML) models are trained on DFT segregation data to predict the segregation energies. Here, we combine descriptors for the local structure of the segregation site with element-specific parameters for the solute element to train ML models that can predict the site-specific segregation energies for a wide range of elements. We use cross-validation and extrapolation scores to find the optimal set of descriptors for the model. The thus obtained model is then used to predict the segregation energies of solutes that are not in the data set. We apply our approach to segregation of transition metals in W. Both, cross-validation scores and comparison to literature data highlight excellent results of the ML approach. We make the model available by publishing the relevant codes and data.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113847"},"PeriodicalIF":3.1,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143726148","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}

引用次数: 0

Dislocation properties in BCC refractory compositionally complex alloys from atomistic simulations

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-03-28 DOI: 10.1016/j.commatsci.2025.113859

Juntan Li, Haixuan Xu

{"title":"Dislocation properties in BCC refractory compositionally complex alloys from atomistic simulations","authors":"Juntan Li, Haixuan Xu","doi":"10.1016/j.commatsci.2025.113859","DOIUrl":"10.1016/j.commatsci.2025.113859","url":null,"abstract":"<div><div>Body-centered cubic (BCC) refractory compositionally complex alloys (RCCAs) have emerged as promising candidates for aerospace, nuclear energy, and automotive applications due to their exceptional high-temperature strengths. It is well-known that dislocations play a critical role in the mechanical properties of refractory alloys. In this study, we examine the fundamental properties of edge and screw dislocations, including core energies and dislocation shear stresses (DSSs) in MoNbTi, NbMoTaW, and CrTaVW, at various temperatures using atomistic simulations with the state-of-the-art machine-learned interatomic potentials (MLIPs). Our findings reveal that at high temperatures, the DSS of edge dislocations exceed those of screw dislocations in MoNbTi and NbMoTaW alloys. This behavior is attributed to cross-kink diffusion and annihilation in screw dislocations, which leads to a more significant decrease in DSS as temperature increases. Furthermore, the DSS values of screw dislocations at low temperatures and those of edge dislocations at high temperatures closely align with experimental yield strengths. These results show that edge dislocations are primarily responsible for the high-temperature strengths of some of the RCCAs and are crucial for tuning their mechanical properties. Additionally, we observe that screw dislocations exhibit lower core energies than edge dislocations across all temperatures in the investigated alloys, indicating their greater thermodynamic stability. These findings underscore the importance of considering different types of dislocations at various temperature regimes in BCC RCCAs, which is essential for guiding alloy design within the vast compositional space.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113859"},"PeriodicalIF":3.1,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143715962","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}

引用次数: 0

Large language model-driven database for thermoelectric materials

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-03-28 DOI: 10.1016/j.commatsci.2025.113855

Suman Itani , Yibo Zhang , Jiadong Zang

{"title":"Large language model-driven database for thermoelectric materials","authors":"Suman Itani , Yibo Zhang , Jiadong Zang","doi":"10.1016/j.commatsci.2025.113855","DOIUrl":"10.1016/j.commatsci.2025.113855","url":null,"abstract":"<div><div>Thermoelectric materials have the ability to convert waste heat into electricity, offering a valuable solution for energy harvesting. However, their widespread use is hindered by low conversion efficiency, the reliance on expensive rare earth elements, and the environmental and regulatory concerns associated with lead-based materials. A fast and cost-effective way to identify highly efficient thermoelectric materials is through data-driven methods. These approaches rely on robust and comprehensive datasets to train models. Although there are several databases on thermoelectric materials, there is still a need to collect and integrate experimental data from peer-reviewed research articles to capture diverse compositions and properties of materials. Here we developed a comprehensive database of 7,123 thermoelectric compounds, containing key information such as chemical composition, structural detail, seebeck coefficient, electrical and thermal conductivity, power factor, and figure of merit (ZT). We used the GPTArticleExtractor workflow, powered by large language models (LLM), to extract and curate data automatically from the scientific literature published in Elsevier journals. This process enabled the creation of a structured database that addresses the challenges of manual data collection. The open access database could stimulate data-driven research and advance thermoelectric material analysis and discovery.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113855"},"PeriodicalIF":3.1,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716074","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}

引用次数: 0

Molecular dynamics simulation of interfacial thermal conductance in RDX/PVDF mixture explosives

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-03-27 DOI: 10.1016/j.commatsci.2025.113857

Meilin Lu , Zhaoyang Zheng , Yangyang Zeng , Yanqiang Yang

{"title":"Molecular dynamics simulation of interfacial thermal conductance in RDX/PVDF mixture explosives","authors":"Meilin Lu , Zhaoyang Zheng , Yangyang Zeng , Yanqiang Yang","doi":"10.1016/j.commatsci.2025.113857","DOIUrl":"10.1016/j.commatsci.2025.113857","url":null,"abstract":"<div><div>The interfacial thermal conductance of mixtures formed with hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) as the explosive and polyvinylidene fluoride (PVDF) as the binder were investigated through reverse non-equilibrium molecular dynamics (rNEMD) simulation. A combined force field, incorporating the modified Smith-Bharadwaj, PCFF, and RDX/polymer interfacial force fields, was employed to model the systems. The thermal conductance of six RDX/PVDF interfaces composed of PVDF (010), (001) and RDX (001), (010) and (100) crystal planes were calculated, respectively. The orientation-dependent thermal conductivities of both the RDX and PVDF crystals were determined. PVDF molecules in the three RDX/PVDF(001) structures tend to rotate and put shear stress on RDX crystal, causing a deformation of RDX emerged in (001) plane, which is known to exhibit the lowest stability against shear. Consequently, these structural changes influence the thermal conductivities of the corresponding bulk monocrystals. The interfaces in RDX/PVDF(001) structures are formed after the rearrangement of RDX and rotated PVDF molecules and act as mixed buffer layers which enhance their interfacial thermal conductance compared to those in RDX/PVDF(010) mixtures. Among the three RDX/PVDF(010) interfaces, the interfacial thermal conductance of RDX(001)/PVDF(010) is higher than the other two. Further analysis of the vibrational density of states and the interfacial atomic pair distribution function indicated that intermolecular hydrogen bonds, especially H (RDX)···F (PVDF) bonds, play a significant role in the thermal transport across the RDX/PVDF(010) interface.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113857"},"PeriodicalIF":3.1,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716073","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}

引用次数: 0

First-principles insights into the site occupancy of Ta–Fe–Al C14 laves phases

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-03-27 DOI: 10.1016/j.commatsci.2025.113856

Nisa Ulumuddin, Sandra Korte-Kerzel, Zhuocheng Xie

{"title":"First-principles insights into the site occupancy of Ta–Fe–Al C14 laves phases","authors":"Nisa Ulumuddin, Sandra Korte-Kerzel, Zhuocheng Xie","doi":"10.1016/j.commatsci.2025.113856","DOIUrl":"10.1016/j.commatsci.2025.113856","url":null,"abstract":"<div><div>This study investigates the site occupancy preferences of Al in Ta(Fe<span><math><msub><mrow></mrow><mrow><mn>1</mn><mo>−</mo><mi>x</mi></mrow></msub></math></span>Al<span><math><msub><mrow></mrow><mrow><mi>x</mi></mrow></msub></math></span>)<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> Laves phases using first-principles calculations, covering Al concentrations from 0 to 50 at.%. Al atoms exhibit a strong preference for <span><math><mrow><mn>2</mn><mi>a</mi></mrow></math></span> Wyckoff sites, with configurations becoming more energetically favorable as these sites reach full occupancy at high Al concentrations. Magnetic configurations were explored, revealing that anti-ferromagnetic ordering is the most favorable at ground states. A metastable defect phase diagram based on the chemical potential of Al was constructed to map site occupancy preferences, where Ta<span><math><msub><mrow></mrow><mrow><mn>4</mn></mrow></msub></math></span>Fe<span><math><msub><mrow></mrow><mrow><mn>6</mn></mrow></msub></math></span>Al<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> and Ta<span><math><msub><mrow></mrow><mrow><mn>4</mn></mrow></msub></math></span>Fe<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>Al<span><math><msub><mrow></mrow><mrow><mn>6</mn></mrow></msub></math></span> exhibit the widest chemical potential windows. The correlation between lattice distortions and site occupancy was examined, demonstrating that symmetric Al distributions enhance structural preference. These findings offer insights into the structural motifs of the Ta–Fe–Al system, providing a foundation for future investigations on structure–property relationships.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113856"},"PeriodicalIF":3.1,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716072","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}

引用次数: 0

First principles: Influence different parameters on the coefficient of thermal expansion

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-03-26 DOI: 10.1016/j.commatsci.2025.113843

Yiman Zhao , Zelong Gong , Zhibo Zhang , Guangyao Huang , Defeng Guo , Jinliang Ning , Kaihong Zheng

引用次数: 0

Band edge engineering of CsPbI3 by surface decoration of halogen and alkaline atoms

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-03-25 DOI: 10.1016/j.commatsci.2025.113863

Fahhad Alsubaie , Aijun Du , Lei Zhang

{"title":"Band edge engineering of CsPbI3 by surface decoration of halogen and alkaline atoms","authors":"Fahhad Alsubaie , Aijun Du , Lei Zhang","doi":"10.1016/j.commatsci.2025.113863","DOIUrl":"10.1016/j.commatsci.2025.113863","url":null,"abstract":"<div><div>The inorganic halide perovskite, CsPbI<sub>3</sub>, has emerged as a promising material for photovoltaic applications. Effective strategy to tune its band edges is crucial to realize rational interface design with charge transport layers. In this work, by first-principle calculations, we found that surface decoration with halogen and alkaline atoms can effectively tune the electronic properties of CsPbI<sub>3</sub>. The introduction of these adatoms breaks the centrosymmetry of the CsPbI<sub>3</sub> surface, resulting in the intrinsic electric dipole whose direction is determined by the charge transfer between the adatoms and the surface. The electric dipole then leads to a lateral electric field which redistribute the conduction and valence band edges to two opposite surfaces with a large electrostatic potential difference. Therefore, the electron and hole carriers are spatially separated, with the energy levels of band edges significantly shifted. Our work demonstrates surface decoration of halogen and alkaline atoms can effectively tailor the band edges of CsPbI<sub>3</sub> and unveils the critical role of induced electric dipole moments, offering new opportunities for optimizing CsPbI<sub>3</sub>-based solar cell interfaces.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"253 ","pages":"Article 113863"},"PeriodicalIF":3.1,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697001","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}

引用次数: 0