Acta Materialia最新文献

{"title":"Biomimetic Structural Foil Anode with Toughened Fracture Mechanism for High Energy Density Lithium-Ion Batteries","authors":"Song Sun, Shukai Chen, Jinhui Zhao, Xin Zhang, Huiyang Gou, Gongkai Wang","doi":"10.1016/j.actamat.2025.121192","DOIUrl":"https://doi.org/10.1016/j.actamat.2025.121192","url":null,"abstract":"Mechanical fracture is a critical failure mode in lithium-ion batteries (LIBs), with crack propagation—central to the fracture mechanism—posing significant challenging in control. This issue is particularly pronounced in alloy-type anodes, which exhibit limited stress tolerance, constraining advancements toward higher energy densities in LIBs. Herein, we introduce a biomimetic laminated structure alloy-type foil anode by compositing Sn foil with single-walled carbon nanotubes that enables cyclic stability and high energy density. By modulating the crack propagation mechanism at multiple length scales, the biomimetic structure effectively raises the energy release threshold and facilitates the delocalization of electrochemically induced stress concentration, significantly delaying the onset of mechanical fracture during cycling. Consequently, the full-cell paired with LiFePO₄ and LiNi_0.8Co_0.1Mn_0.1O₂ cathodes achieve stable hundreds of cycles at practically relevant areal capacities. In particular, the full-cell with LiNi_0.8Co_0.1Mn_0.1O₂ at high loading of 10 mAh cm⁻² delivers a volumetric energy density of 1127.2 Wh L⁻¹, offering a promising pathway for advancing alloy-type foil anodes in high-energy LIBs.","PeriodicalId":238,"journal":{"name":"Acta Materialia","volume":"41 1","pages":"121192"},"PeriodicalIF":9.4,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144183755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Elucidating the thermal properties and anomalous transport in the 18R polytype of SnSe2","authors":"Wilarachchige D.C.B. Gunatilleke, Oluwagbemiga P. Ojo, Winnie Wong-Ng, Tieyan Chan, Yu-Sheng Chen, Joshua Martin, Adam J. Biacchi, George S. Nolas","doi":"10.1016/j.actamat.2025.121190","DOIUrl":"https://doi.org/10.1016/j.actamat.2025.121190","url":null,"abstract":"The 18R polytype of SnSe₂ possesses unique structural features that can directly impact the transport properties and potential applications of interest; however, a comprehensive understanding of the intrinsic physical properties is lacking. We grew large crystals in order to investigate the thermal and electrical properties of this SnSe₂ polytype and reveal the anomalous electronic transport for this material. High-resolution single-crystal synchrotron, as well as powder X-ray diffraction on crushed crystals, were employed elucidating the long-period stacking sequence and octahedral layering along the <em>c</em>-axis separated by weak van der Waals bonds forming the rhombohedral lattice structure. Temperature-dependent Hall, resistivity, and Seebeck coefficient measurements were employed in investigating the atypical electrical transport this polytype possesses, which has a 1.1 eV indirect band gap as revealed from our optical spectroscopy investigations. Analyses and modelling of the temperature-dependent thermal properties revealed a low Debye temperature and average speed of sound, with minimal lattice anharmonicity resulting in relatively high thermal conductivity. Our findings will also aid research on other materials with similar layered structure types in exploring their suitability for technological applications.","PeriodicalId":238,"journal":{"name":"Acta Materialia","volume":"2 1","pages":""},"PeriodicalIF":9.4,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144176797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In situ atomic-scale observation of diffusion-assisted pure sliding of coherent twin boundary in Pt","authors":"Zhanxin Wang, Jiao Teng, Yizhong Guo, Chengpeng Yang, Yan Ma, Zhipeng Li, Haibo Long, Shengcheng Mao, Ze Zhang, Xin Yan, Jian Wang, Lihua Wang, Xiaodong Han","doi":"10.1016/j.actamat.2025.121188","DOIUrl":"https://doi.org/10.1016/j.actamat.2025.121188","url":null,"abstract":"Coherent twin boundary (CTB) can markedly enhance the strength of metallic materials because thermally stable CTBs act as strong barriers for blocking dislocation motion. CTB sliding should rarely happen because twinning dislocations (TDs) nucleate with a lower activation energy than a full dislocation while the gliding of TDs migrates the CTB. Here, the atomic-scale sliding process of CTB was in situ captured in a twin-structured Pt, involving two TDs that glide toward each other on two non-coplanar (111) planes separated by the CTB. They meet and then exchange their sliding planes assisted by short-range atomic diffusion to continue gliding, resulting in pure sliding across the CTB without migration of the CTB. Repeat of this pure sliding process requires the assistance of atoms diffusion to annihilate the created vacancies. This sliding mechanism enriches CTB-related plastic deformation mechanisms.","PeriodicalId":238,"journal":{"name":"Acta Materialia","volume":"5 1","pages":""},"PeriodicalIF":9.4,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144176849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Photovoltaic effect of TiO2 films with large photoelectric responsivity","authors":"Wenjing Hua, Wenyue Zhao, Ruilin Mao, Zhao Wang, Yazhou Peng, Lei Shi, Jie Wang, Xiaoxia Yang, Yuqi Zhang, Peng Gao, Weidong Fei, Yu Zhao","doi":"10.1016/j.actamat.2025.121189","DOIUrl":"https://doi.org/10.1016/j.actamat.2025.121189","url":null,"abstract":"Ferroelectric photovoltaic effects usually exhibit low photocurrent, which limits their wide application. Here, we report the discovery of a photovoltaic effect with high photocurrent in TiO₂ films prepared by sol-gel method. It is found that an open circuit voltage of 0.58 V and a short circuit current density of 0.64 mA/cm² (26 mA/W) are achieved in the TiO₂ film annealed at 850 °C. Based on the experiment and calculation results, a possible mechanism is put forward to explain the photovoltaic effect in the TiO₂ films. The self-polarization is caused by the electric field generated by the gradient distribution of Ti³⁺ ions in the TiO₂ film. Ferroelectricity in microscopic regions in the TiO₂ film was confirmed by both piezoelectric force microscope analysis and density function theory calculation. In addition, the TiO₂ film annealed at 750 °C exhibits high photoresponse stability over a long time (&gt;6800 s) and excellent self-powered photodetection performances with a rising time of 1.5 ms, a falling time of 5.9 ms, an optical responsivity of 15.8 mA/W, and a specific detection rate of 1.06×10¹² Jones under 365 nm light (25 mW/cm²) at 0 V bias. This work not only provides an economically effective approach for designing high performance FePV films devices, but also further guides the application of ferroelectric films in self-powered photodetection and other optoelectronic fields.","PeriodicalId":238,"journal":{"name":"Acta Materialia","volume":"6 1","pages":""},"PeriodicalIF":9.4,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144177295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Initiation of dusting corrosion in high-temperature alloys under CO exposure","authors":"Shyam Bharatkumar Patel, Jianyu Wang, Chaoran Li, Abdullah Al-Mahboob, Dario Stacchiola, Jerzy T. Sadowski, Guangwen Zhou","doi":"10.1016/j.actamat.2025.121178","DOIUrl":"https://doi.org/10.1016/j.actamat.2025.121178","url":null,"abstract":"Carbon monoxide is commonly encountered in energy systems, yet its reactivity with structural alloys—critical heat-resistant components in these systems—has been largely overlooked compared to the well-documented effects of oxidizing gases. In contrast, we demonstrate the high-temperature reaction of CO with NiAl using in-situ low-energy electron microscopy and X-ray photoemission electron microscopy. Our results show that CO dissociates into atomic oxygen and carbon, resulting in two concurrent reactions: selective oxidation of aluminum to form Al₂O₃ and the initiation of dusting corrosion through carbon dissolution into the alloy and subsequent carbon deposition on the surface. These reactions produce spatially distinct surface products, preventing the formation of a continuous protective Al oxide layer. These results reveal a preference for the dissociative pathway of CO over the classic Boudouard disproportionation reaction that forms CO₂. These insights not only advance our understanding of CO-induced alloy degradation but also highlight the practical implications for managing alloy stability and optimizing catalysis in carbon-rich environments, such as those in petrochemical processing and hydrocarbon combustion.","PeriodicalId":238,"journal":{"name":"Acta Materialia","volume":"19 1","pages":""},"PeriodicalIF":9.4,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144176798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning pipeline for Structure–Property modeling in Mg-alloys using microstructure and texture descriptors","authors":"Mahish K. Guru ,&nbsp;Jan Bohlen ,&nbsp;Roland C. Aydin ,&nbsp;Noomane Ben Khalifa","doi":"10.1016/j.actamat.2025.121132","DOIUrl":"10.1016/j.actamat.2025.121132","url":null,"abstract":"<div><div>Identifying the relationships between material structure and mechanical properties has been crucial for accelerating the exploration of the material design space for advanced alloys. However, traditional approaches for magnesium (Mg) alloys often fall short in providing quantitative and broadly applicable structure–property linkages. To address this challenge, a comprehensive machine learning pipeline is presented for structure–property modeling in extruded Mg-alloys, leveraging both microstructure and texture descriptors derived from experimental data. The pipeline encompasses a robust workflow for data extraction from optical microscopy and X-ray diffraction, advanced image processing and deep learning techniques for microstructure binarization and grain statistics, and the computation of statistical descriptors including n-point spatial correlations, gram matrices for microstructure, and generalized spherical harmonics (GSH) for texture. Dimensionality reduction techniques such as principal component analysis (PCA), isomap, and autoencoders are employed to manage the high-dimensionality of the descriptor space. Subsequently, non-linear regression models—Gaussian Process, XGBoost, and Multi-Layer Perceptron regressors—are evaluated to predict mechanical properties, specifically strain hardening exponent (<span><math><mi>n</mi></math></span>) and yield stress (<span><math><msub><mrow><mi>σ</mi></mrow><mrow><mi>y</mi></mrow></msub></math></span>). Our results demonstrate that XGBoost consistently outperforms other regressors, achieving a notably low mean absolute percentage error (MAPE) of 6.67% for strain hardening exponent and 7.01% for yield stress, using a combination of PCA-reduced 3-point spatial correlations and isomap-reduced gram matrices as microstructure descriptors, and isomap-reduced GSH coefficients as texture descriptors at a <span><math><mrow><mn>150</mn><mspace></mspace><mi>μ</mi><mtext>m</mtext></mrow></math></span> length scale. Shapley Additive exPlanations (SHAP) analysis further reveals that texture descriptors and aspect ratio distribution are the most influential features in predicting mechanical properties. This established ML framework for structure–property modeling in Mg-alloys, surpasses state-of-the-art benchmarks and provides a valuable template for materials design and discovery.</div></div>","PeriodicalId":238,"journal":{"name":"Acta Materialia","volume":"295 ","pages":"Article 121132"},"PeriodicalIF":8.3,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144165045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design strategy of Ti-Zr-Hf-Nb high-entropy alloys based on first principles computations","authors":"Bohua Yu, Ning Ding, Hongmei Chen, Xinxin Yang, Huaijin Wang, Jie Chen, Zeyun Cai, Guoqiang Xie","doi":"10.1016/j.actamat.2025.121183","DOIUrl":"https://doi.org/10.1016/j.actamat.2025.121183","url":null,"abstract":"High-entropy alloys (HEAs) have emerged as promising biomaterials owing to their favorable properties. The propensity of Ti-Zr and Hf-Nb atomic pairs within the Ti-Zr-Hf-Nb system was exploited to generate predictive design strategy utilizing the CALPHAD and first-principles calculations. The Ti₃₀Zr₃₀Hf₂₀Nb₂₀ (TZ6) and Ti₃₅Zr₃₅Hf₁₅Nb₁₅ (TZ7) alloys exhibited an optimal balance between strength, ductility, and Young’s modulus. TZ6 alloy possessed a yield strength of 694.5 ± 5.6 MPa and an elongation of 20.7 ± 1.7% in tensile test, with Young’s modulus of 79.8 ± 1.9 GPa. TZ7 alloy was characterized by a yield strength of 676.3 ± 5.6 MPa and an elongation of 19.0 ± 1.7%, with Young’s modulus of 70.3 ± 1.5 GPa. Due to the increased proportion of Ti-Zr pair in the alloy, which destabilized the electronic structure, the Young’s modulus was subsequently diminished. Concurrently, the reduction in dislocation nucleation energy significantly enhanced the ductility. Notably, the Young’s modulus of the TZ6 and TZ7 alloy is reduced by 11.1% and 21.7 %, respectively, compared to equimolar TiZrHfNb (TZ5) HEA. Additionally, TZ6 and TZ7 can be classified as a Class 0 non-cytotoxic material, demonstrating superior cell compatibility compared to Ti6Al4V and TZ5 alloys. The theoretical predictions were in well agreement with the experimental results, which provided a paradigm for the design of comprehensive balanced performance in biomedical HEAs.","PeriodicalId":238,"journal":{"name":"Acta Materialia","volume":"82 1","pages":""},"PeriodicalIF":9.4,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144165042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Steady state negative capacitance in p-n ferroelectric junctions","authors":"Andra Georgia Boni, Cristina Florentina Chirila, Lucian Dragos Filip, Mihaela Ioana Botea, Cristian Radu, Dana Georgeta Popescu, Marius Adrian Husanu, Luminita Hrib, Lucian Trupina, Ioana Pintilie, Lucian Pintilie","doi":"10.1016/j.actamat.2025.121177","DOIUrl":"https://doi.org/10.1016/j.actamat.2025.121177","url":null,"abstract":"Despite the promise of high-k dielectrics, inherent limitations persist in transistor scaling and enhancing energy efficiency, including a fundamental threshold of 60 mV/dec for increasing drain current by an order of magnitude. Proposed solutions involve negative capacitance at the gate oxide to overcome this barrier using ferroelectric structures. Efforts to understand and regulate the switching dynamics and intricate electrostatic configurations of ferroelectric structures towards achieving negative capacitance regimes have intensified. While standalone ferroelectric capacitors cannot stabilize negative capacitance without external fields, multilayered thin films offer a promising solution. Typically, ferroelectric layers are paired with dielectrics/insulator, demonstrating steady-state negative capacitance, often at nanoscale or specific temperature domains. This study aims to stabilize negative capacitance in ferroelectric structures by inducing internal electric fields, aligning the system near coercivity, particularly in bilayer structures formed by two ferroelectric layers with slight differences in polarization values, such as p-n heterojunctions using Pb (Zr,Ti)O₃ PZT) with different doping as Fe, Nb, Bi. Most of these structures exhibit evident amplification of capacitance compared to the equivalent series-connected capacitance, across a large temperature domain. The complex capacitance-frequency characteristic of these structures indicates a complex equivalent circuit. Analysis of these complex circuits compared with simple component layers concludes that at least one of the FE layers in these bilayer structures is in a negative capacitance (NC) state.","PeriodicalId":238,"journal":{"name":"Acta Materialia","volume":"26 1","pages":""},"PeriodicalIF":9.4,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144165043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing thermal-mechanical processes for high in-plane texture and thermoelectric performance of n-type Bi2Te3","authors":"Jianghe Feng, Ping Yang, Ali Li, Hao Li, Erbiao Min, Fangjian Li, Hongcheng Zhang, Juan Li, Pengyang Zhao, Rong Sun, Ruiheng Liu","doi":"10.1016/j.actamat.2025.121185","DOIUrl":"https://doi.org/10.1016/j.actamat.2025.121185","url":null,"abstract":"The layered Bi₂Te₃ is currently the only commercialized thermoelectric material whose performance is highly contingent on the in-plane crystallographic texture, particularly for the n-type Bi₂Te₃. In recent years, the demand for robust mechanical strength in practical applications has driven advancements in hot extrusion techniques for material fabrication but with considerable room for texture optimization. Herein, the primary slip systems activated during the plastic deformation of Bi₂Te₃ were firstly identified, and a Taylor model to simulate the texture evolution of the hot-extruded samples under various conditions was developed. Subsequently, by simply aligning the extrusion direction with the initial in-plane texture, we achieved at least a doubling of the texture degree, resulting in the extremely high room temperature carrier mobility 263 cm²V^-1s^-1 and power factor ∼47.3 μWcm^-1K^-2, which contributes to the high dimensionless figure of merit ∼1.05@ 375K. Under the guidance of the same method, another hierarchical Bi₂Te_2.7Se_0.3 with a high 1.08@ 450 K was also achieved, based on which a segmented thermoelectric generator module was fabricated and realized a high conversion efficiency of 7.6 % at a temperature difference of 293 K. Therefore, these results underscore that the fabrication of target microstructures based on an understanding of microstructure evolution and prediction will significantly propel the development of thermoelectric materials.","PeriodicalId":238,"journal":{"name":"Acta Materialia","volume":"49 1","pages":""},"PeriodicalIF":9.4,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144153797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictive modeling of the bainite start temperature using Bayesian inference","authors":"Bernd Schuscha, Dominik Brandl, Lorenz Romaner, Ernst Kozeschnik, Reinhold Ebner, Aurélie Jacob, Peter Presoly, Daniel Scheiber","doi":"10.1016/j.actamat.2025.121131","DOIUrl":"https://doi.org/10.1016/j.actamat.2025.121131","url":null,"abstract":"The prediction of the bainite start temperature (&lt;span&gt;&lt;span&gt;&lt;math&gt;&lt;msub is=\"true\"&gt;&lt;mrow is=\"true\"&gt;&lt;mi is=\"true\"&gt;B&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow is=\"true\"&gt;&lt;mtext is=\"true\"&gt;S&lt;/mtext&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt;&lt;script type=\"math/mml\"&gt;&lt;math&gt;&lt;msub is=\"true\"&gt;&lt;mrow is=\"true\"&gt;&lt;mi is=\"true\"&gt;B&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow is=\"true\"&gt;&lt;mtext is=\"true\"&gt;S&lt;/mtext&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/script&gt;&lt;/span&gt;) is key to modelling the bainitic phase transformations in steels. The present work employs Bayesian inference on various existing models and presents enhanced models that allow for accurate prediction of bainite start temperatures. In a first step, a meticulously curated dataset is generated and accompanied by additional experimental &lt;span&gt;&lt;span&gt;&lt;math&gt;&lt;msub is=\"true\"&gt;&lt;mrow is=\"true\"&gt;&lt;mi is=\"true\"&gt;B&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow is=\"true\"&gt;&lt;mtext is=\"true\"&gt;S&lt;/mtext&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt;&lt;script type=\"math/mml\"&gt;&lt;math&gt;&lt;msub is=\"true\"&gt;&lt;mrow is=\"true\"&gt;&lt;mi is=\"true\"&gt;B&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow is=\"true\"&gt;&lt;mtext is=\"true\"&gt;S&lt;/mtext&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/script&gt;&lt;/span&gt; temperatures. Several physics-based models based on energy criteria (one diffusive and some displacive models) and a linear regression model are used to predict &lt;span&gt;&lt;span&gt;&lt;math&gt;&lt;msub is=\"true\"&gt;&lt;mrow is=\"true\"&gt;&lt;mi is=\"true\"&gt;B&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow is=\"true\"&gt;&lt;mtext is=\"true\"&gt;S&lt;/mtext&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt;&lt;script type=\"math/mml\"&gt;&lt;math&gt;&lt;msub is=\"true\"&gt;&lt;mrow is=\"true\"&gt;&lt;mi is=\"true\"&gt;B&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow is=\"true\"&gt;&lt;mtext is=\"true\"&gt;S&lt;/mtext&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/script&gt;&lt;/span&gt;. Adaptation and enhancement of the available models are evaluated in the framework of Bayesian inference including uncertainties, and the predictive performance is compared between the models. The concentration-dependent Gibbs energies are calculated using three different thermodynamic databases, and the models are parameterized regarding the best possible prediction of &lt;span&gt;&lt;span&gt;&lt;math&gt;&lt;msub is=\"true\"&gt;&lt;mrow is=\"true\"&gt;&lt;mi is=\"true\"&gt;B&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow is=\"true\"&gt;&lt;mtext is=\"true\"&gt;S&lt;/mtext&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt;&lt;script type=\"math/mml\"&gt;&lt;math&gt;&lt;msub is=\"true\"&gt;&lt;mrow is=\"true\"&gt;&lt;mi is=\"true\"&gt;B&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow is=\"true\"&gt;&lt;mtext is=\"true\"&gt;S&lt;/mtext&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/script&gt;&lt;/span&gt;. The obtained parameterization for a diffusive, some displacive and a linear regression model is used to analyze the uncertainty in the model parameters and to quantify the influence of the most important steel alloying elements on &lt;span&gt;&lt;span&gt;&lt;math&gt;&lt;msub is=\"true\"&gt;&lt;mrow is=\"true\"&gt;&lt;mi is=\"true\"&gt;B&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow is=\"true\"&gt;&lt;mtext is=\"true\"&gt;S&lt;/mtext&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt;&lt;script type=\"math/mml\"&gt;&lt;math&gt;&lt;msub is=\"true\"&gt;&lt;mrow is=\"true\"&gt;&lt;mi is=\"true\"&gt;B&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow is=\"true\"&gt;&lt;mtext is=\"true\"&gt;S&lt;/mtext&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/script&gt;&lt;/span&gt;. Results show that there is little difference between displacive, diffusive and data-driven approaches for prediction of &lt;span&gt;&lt;span&gt;&lt;math&gt;&lt;msub is=\"true\"&gt;&lt;mrow is=\"true\"&gt;&lt;mi is=\"true\"&gt;B&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow is=\"true\"&gt;&lt;mtext is=\"true\"&gt;S&lt;/mtext&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt;","PeriodicalId":238,"journal":{"name":"Acta Materialia","volume":"44 1","pages":""},"PeriodicalIF":9.4,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144145832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}