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| 1 | Oxidation behavior of Mo-Si-B alloys at medium-to-high temperatures显示文摘Continuous exploration of high-temperature structural materials is being driven by the needs of gasturbine engines capable of withstanding the high-temperature environment.Relatively low melting points of currently applied superalloys restrain the further improvement of service tempe ratures.With higher melting tempe ratures above 2000℃,Mo-Si-B alloys are regarded as a new generation of ultrahightemperature structural materials.However,oxidation is a concern for the industrial application of Mo-Si-B alloys.Therefore,an in-depth understanding of the oxidation mechanisms may contribute to solving this issue,whereas relevant reviews about their recent advances are lacking.In the current work,a comprehensively systematic review about the oxidation behaviors of Mo-Si-B alloys is described for this purpose. | Kunming Pan Yanping Yang Shizhong Wei Honghui Wu Zhili Dong Yuan Wu Shuize Wang Laiqi Zhang Junping Lin Xinping Mao | 2021 | Journal of Materials Science & Technology2021，，1： | 5 |
| 2 | Tribological properties of high-entropy alloys:A review显示文摘Tribology,which is the study of friction,wear,and lubrication,largely deals with the service performance of structural materials.For example,newly emerging high-entropy alloys(HEAs),which exhibit excellent hardness,anti-oxidation,anti-softening ability,and other prop-erties,enrich the wear-resistance alloy family.To demonstrate the tribological behavior of HEAs systematically,this review first describes the basic tribological characteristics of single-,dual-,and multi-phase HEAs and HEA composites at room temperature.Then,it summarizes the strategies that improve the tribological property of HEAs.This review also discusses the tribological performance at elevated temperatures and provides a brief perspective on the future development of HEAs for tribological applications. | Zhuo Cheng Shuize Wang Guilin Wu Junheng Gao Xusheng Yang Honghui Wu | 2022 | International Journal of Minerals,Metallurgy and Materials2022，29，3： | 2 |
| 3 | Polymer-/Ceramic-based Dielectric Composites for Energy Storage and Conversion显示文摘Dielectric composites boost the family of energy storage and conversion materials as they can take full advantage of both the matrix and filler.This review aims at summarizing the recent progress in developing highperformance polymer-and ceramic-based dielectric composites,and emphases are placed on capacitive energy storage and harvesting,solid-state cooling,temperature stability,electromechanical energy interconversion,and high-power applications.Emerging fabrication techniques of dielectric composites such as 3D printing,electrospinning,and cold sintering are addressed,following by highlighted challenges and future research opportunities.The advantages and limitations of the typical theoretical calculation methods,such as finite-element,phase-field model,and machine learning methods,for designing high-performance dielectric composites are discussed.This review is concluded by providing a brief perspective on the future development of composite dielectrics toward energy and electronic devices. | Honghui Wu Fangping Zhuo Huimin Qiao Lalitha Kodumudi Venkataraman Mupeng Zheng Shuize Wang He Huang Bo Li Xinping Mao Qiaobao Zhang | 2022 | Energy & Environmental Materials2022，5，2： | 2 |
| 4 | Martensitic twinning transformation mechanism in a metastable IVB element-based body-centered cubic high-entropy alloy with high strength and high work hardening rate显示文摘Realizing high work hardening and thus elevated strength–ductility synergy are prerequisites for the practical usage of body-centered-cubic high entropy alloys(BCC-HEAs).In this study,we report a novel dynamic strengthening mechanism,martensitic twinning transformation mechanism in a metastable refractory element-based BCC-HEA(TiZrHf)Ta(at.%)that can profoundly enhance the work hardening capability,leading to a large uniform ductility and high strength simultaneously.Different from conventional transformation induced plasticity(TRIP)and twinning induced plasticity(TWIP)strengthening mechanisms,the martensitic twinning transformation strengthening mechanism combines the best characteristics of both TRIP and TWIP strengthening mechanisms,which greatly alleviates the strengthductility trade-off that ubiquitously observed in BCC structural alloys.Microstructure characterization,carried out using X-ray diffraction(XRD)and electron back-scatter diffraction(EBSD)shows that,upon straining,α”(orthorhombic)martensite transformation,self-accommodation(SA)α”twinning and mechanicalα”twinning were activated sequentially.Transmission electron microscopy(TEM)analyses reveal that continuous twinning activation is inherited from nucleating mechanical{351}type I twins within SA“{351}”<■11>typeⅡtwinnedα”variants on{351}twinning plane by twinning transformation through simple shear,thereby accommodating the excessive plastic strain through the twinning shear while concurrently refining the grain structure.Consequently,consistent high work hardening rates of 2–12.5 GPa were achieved during the entire plastic deformation,leading to a high tensile strength of 1.3 GPa and uniform elongation of 24%.Alloy development guidelines for activating such martensitic twinning transformation strengthening mechanism were proposed,which could be important in developing new BCC-HEAs with optimal mechanical performance. | Yuhe Huang Junheng Gao Vassili Vorontsov Dikai Guan Russell Goodall David Dye Shuize Wang Qiang Zhu W.Mark Rainforth Iain Todd | 2022 | Journal of Materials Science & Technology2022，，29： | 1 |
| 5 | Perspective on antiferroelectrics for energy storage and conversion applications显示文摘As a close relative of ferroelectricity,antiferroelectricity has received a recent resurgence of interest driven by technological aspirations in energy-efficient applications,such as energy storage capacitors,solid-state cooling devices,explosive energy conversion,and displacement transducers.Though prolonged efforts in this area have led to certain progress and the discovery of more than 100 antiferroelectric materials over the last 70 years,some scientific and technological issues remain unresolved.Herein,we provide perspectives on the development of antiferroelectrics for energy storage and conversion applications,as well as a comprehensive understanding of the structural origin of antiferroelectricity and field-induced phase transitions,followed by design strategies for new lead-free antiferroelectrics.We also envision unprecedented challenges in the development of promising antiferroelectric materials that bridge materials design and real applications.Future research in these directions will open up new possibilities in resolving the mystery of antiferroelectricity,provide opportunities for comprehending structure-property correlation and developing antiferroelectric/ferroelectric theories,and suggest an approach to the manipulation of phase transitions for real-world applications. | Fangping Zhuo Huimin Qiao Jiaming Zhu Shuize Wang Yang Bai Xinping Mao Hong-Hui Wu | 2021 | Chinese Chemical Letters2021，32，7： | 0 |
| 6 | Atomic-scale simulations in multi-component alloys and compounds:A review on advances in interatomic potential显示文摘Multi-component alloys have demonstrated excellent performance in various applications,but the vast range of possible compositions and microstructures makes it challenging to identify optimized alloys for specific purposes.To overcome this challenge,large-scale atomic simulation techniques have been widely used for the design and optimization of multi-component alloys.The capability and reliability of large-scale atomic simulations essentially rely on the quality of interatomic potentials that describe the interactions between atoms.This work provides a comprehensive summary of the latest advances in atomic simulation techniques for multi-component alloys.The focus is on interatomic potentials,including both conventional empirical potentials and newly developed machine learning potentials(MLPs).The fitting processes for different types of interatomic potentials applied to multi-component alloys are also discussed.Finally,the challenges and future perspectives in developing MLPs are thoroughly addressed.Overall,this review provides a valuable resource for researchers interested in developing optimized multicomponent alloys using atomic simulation techniques. | Feiyang Wang Hong-Hui Wu Linshuo Dong Guangfei Pan Xiaoye Zhou Shuize Wang Ruiqiang Guo Guilin Wu Junheng Gao Fu-Zhi Dai Xinping Mao | 2023 | Journal of Materials Science & Technology2023，，34： | 0 |
| 7 | Advances in machine learning-and artificial intelligence-assisted material design of steels显示文摘With the rapid development of artificial intelligence technology and increasing material data,machine learning-and artificial intelligence-assisted design of high-performance steel materials is becoming a mainstream paradigm in materials science.Machine learning methods,based on an interdisciplinary discipline between computer science,statistics and material science,are good at discovering correlations between numerous data points.Compared with the traditional physical modeling method in material science,the main advantage of machine learning is that it overcomes the complex physical mechanisms of the material itself and provides a new perspective for the research and development of novel materials.This review starts with data preprocessing and the introduction of different machine learning models,including algorithm selection and model evaluation.Then,some successful cases of applying machine learning methods in the field of steel research are reviewed based on the main theme of optimizing composition,structure,processing,and performance.The application of machine learning methods to the performance-oriented inverse design of material composition and detection of steel defects is also reviewed.Finally,the applicability and limitations of machine learning in the material field are summarized,and future directions and prospects are discussed. | Guangfei Pan Feiyang Wang Chunlei Shang Honghui Wu Guilin Wu Junheng Gao Shuize Wang Zhijun Gao Xiaoye Zhou Xinping Mao | 2023 | International Journal of Minerals,Metallurgy and Materials2023，30，6： | 0 |
| 8 | A hybrid machine learning model for predicting continuous cooling transformation diagrams in welding heat-affected zone of low alloy steels显示文摘Continuous cooling transformation diagrams in synthetic weld heat-affected zone(SH-CCT diagrams)show the phase transition temperature and hardness at different cooling rates,which is an important basis for formulating the welding process or predicting the performance of welding heat-affected zone.However,the experimental determination of SH-CCT diagrams is a time-consuming and costly process,which does not conform to the development trend of new materials.In addition,the prediction of SHCCT diagrams using metallurgical models remains a challenge due to the complexity of alloying elements and welding processes.So,in this study,a hybrid machine learning model consisting of multilayer perceptron classifier,k-Nearest Neighbors and random forest is established to predict the phase transformation temperature and hardness of low alloy steel using chemical composition and cooling rate.Then the SH-CCT diagrams of 6 kinds of steels are calculated by the hybrid machine learning model.The results show that the accuracy of the classification model is up to 100%,the predicted values of the regression models are in good agreement with the experimental results,with high correlation coefficient and low error value.Moreover,the mathematical expressions of hardness in welding heat-affected zone of low alloy steel are calculated by symbolic regression,which can quantitatively express the relationship between alloy composition,cooling time and hardness.This study demonstrates the great potential of the material informatics in the field of welding technology. | Xiaoxiao Geng Xinping Mao Hong-Hui Wu Shuize Wang Weihua Xue Guanzhen Zhang Asad Ullah Hao Wang | 2022 | Journal of Materials Science & Technology2022，，12： | 0 |
| 9 | Distribution behavior of inclusions in compact-strip-produced martensitic steel and its influence on mechanical properties显示文摘The distribution behavior of inclusions in martensitic steel produced by compact strip production process(CSP-MS)and its influence on mechanical properties were systematically investigated.The inclusions in the CSP-MS specimen are mainly composed of spherical Al_(2)O_(3)-CaO-CaS,MnS with high aspect ratio and small-sized TiN,whereas many coarse cuboidal TiN inclusions do exist in conventional martensitic steel(Con-MS).The high inclusion density of the CSP-MS specimen resulted in lower total elongation and impact toughness,and the MnS inclusions with high aspect ratio led to significantly stronger mechanical anisotropy than that for Con-MS specimen.The in-situ tensile results indicated that when the fracture direction is parallel to MnS direction,the microcracks induced by MnS inclusions tend to propagate into the matrix,leading to the formation of valley-like features,which significantly deteriorate the properties such as the total elongation and impact toughness.The microcracks caused by TiN inclusions are sharper than those caused by spherical Al_(2)O_(3)-CaO-CaS inclusions,and are easy to propagate into the matrix.This work is expected to guide the optimization of the mechanical properties of martensitic steels produced by CSP process and provide a theoretical basis for the CSP process design. | Jing Wang Peng Xue Laiqi Zhang Li You Xiaodong Zhu Shuize Wang Yong Zhong Xinping Mao | 2023 | Journal of Materials Science & Technology2023，，11： | 0 |
| 10 | Recent research progress on the phase-field model of microstructural evolution during metal solidification显示文摘Solidification structure is a key aspect for understanding the mechanical performance of metal alloys,wherein composition and casting parameters considerably influence solidification and determine the unique microstructure of the alloys.By following the principle of free energy minimization,the phase-field method eliminates the need for tracking the solid/liquid phase interface and has greatly accelerated the research and development efforts geared toward optimizing metal solidification microstructures.The recent progress in the application of phasefield simulation to investigate the effect of alloy composition and casting process parameters on the solidification structure of metals is summarized in this review.The effects of several typical elements and process parameters,including carbon,boron,silicon,cooling rate,pulling speed,scanning speed,anisotropy,and gravity,on the solidification structure are discussed.The present work also addresses the future prospects of phase-field simulation and aims to facilitate the widespread applications of phase-field approaches in the simulation of microstructures during solidification. | Kaiyang Wang Shaojie Lv Honghui Wu Guilin Wu Shuize Wang Junheng Gao Jiaming Zhu Xusheng Yang Xinping Mao | 2023 | International Journal of Minerals,Metallurgy and Materials2023，30，11： | 0 |
| 11 | Improved data-driven performance of Charpy impact toughness via literature-assisted production data in pipeline steel显示文摘Pipeline transportation is one of the most economical ways to transport crude oil and natural gas over long distances.High toughness is one of the important qualities of pipeline steel to ensure safe transportation,wherein a key factor characterizing toughness is Charpy impact toughness(CIT).In this work,according to the production line data provided by a steel mill and the experimental data collected in literature,two machine learning model construction strategies were proposed.One was based solely on the production line dataset,and the other was based on the production line dataset together with the literature dataset.In these two strategies,the random forest model displayed the best prediction results,the accuracy of strategy I was 0.58,and the accuracy of strategy II was 0.90,wherein literature data effectively improved the CIT prediction accuracy.Finally,an optimized CIT model based on machine learning algorithms was established.The proposed strategy of literature data-assisted production line data provides a new perspective for optimizing and predicting the performance of traditional structural materials. | SHANG ChunLei WANG ChuanJun WU HongHui LIU WenYue CHEN YiMian PAN GuangFei WANG ShuiZe WU GuiLin GAO JunHeng ZHAO HaiTao ZHANG ChaoLei MAO XinPing | 2023 | Science China(Technological Sciences)2023，66，7： | 0 |
| 12 | Titanium microalloying of steel:A review of its effects on processing,microstructure and mechanical properties显示文摘Carbon neutrality of the steel industry requires the development of high-strength steel.The mechanical properties of low-alloy steel can be considerably improved at a low cost by adding a small amount of titanium(Ti)element,namely Ti microalloying,whose performance is related to Ti-contained second phase particles including inclusions and precipitates.By proper controlling the precipitation behaviors of these particles during different stages of steel manufacture,fine-grained microstructure and strong precipitation strengthening effects can be obtained in low-alloy steel.Thus,Ti microalloying can be widely applied to produce high strength steel,which can replace low strength steels heavily used in various areas currently.This article reviews the characteristics of the chemical and physical metallurgies of Ti microalloying and the effects of Ti microalloying on the phase formation,microstructural evolution,precipitation behavior of low-carbon steel during the steel making process,especially the thin slab casting and continuous rolling process and the mechanical properties of final steel products.Future development of Ti microalloying is also proposed to further promote the application of Ti microalloying technology in steel to meet the requirement of low-carbon economy. | Shuize Wang Zhijun Gao Guilin Wu Xinping Mao | 2022 | International Journal of Minerals,Metallurgy and Materials2022，29，4： | 0 |
| 13 | Enhanced nanocrystalline stability of BCC iron via copper segregation显示文摘Nanocrystalline alloys are known for their high density of grain boundaries(GBs),which results in low thermal stability and a tendency for coarsening.In this work,we investigated Fe–Cu alloys to explore the effects of Cu concentration on the thermal stability of nanocrystalline samples.Using hybrid molecular dynamics(MD)and Monte Carlo(MC)simulations,annealing treatments of nanocrystalline samples with varied Cu concentrations were conducted.The simulation results revealed that Cu atoms tended to accumulate at GBs.Subsequently,the model with Cu segregation was subjected to mechanical creep loading at various temperatures.Through the analysis of atomic structure evolution during creep deformation,it was found that Cu segregation efficiently stabilizes GBs and restricts their movement.The present findings highlight that the thermal stability of nanocrystalline Fe–Cu alloys can be effectively improved by introducing suitable Cu segregation at GBs. | Feiyang Wang Linshuo Dong Hong-Hui Wu Penghui Bai Shuize Wang Guilin Wu Junheng Gao Jiaming Zhu Xiaoye Zhou Xinping Mao | 2023 | Progress in Natural Science:Materials International2023，33，2： | 0 |
| 14 | Enhanced Hydrogen Embrittlement Resistance via Cr Segregation in Nanocrystalline Fe-Cr Alloys显示文摘Hydrogen is a clean fuel with numerous sources,yet the hydrogen industry is plagued by hydrogen embrittlement(HE)issues during the storage,transportation,and usage of hydrogen gas.HE can compromise material performance during service,leading to significant safety hazards and economic losses.In the current work,the influence of element Cr on the HE resistance of nanocrystalline Fe-Cr alloys under different hydrogen concentrations and strain rates was evaluated.With hybrid Monte Carlo(MC)and molecular dynamics(MD)simulations,it was found that Cr atoms were segregated at grain boundaries(GB)and inhibited the GB decohesion.Correspondingly,Cr segregation improved the strength and plasticity of the nanocrystalline Fe-Cr alloys,especially the HE resistance.Moreover,the Cr segregation reduced the diffusion coefficient of hydrogen and inhibited hydrogen-induced cracking.This work provided new insight into the development of iron-based alloys with high HE resistance in the future. | Linshuo Dong Feiyang Wang Hong-Hui Wu Mengjie Gao Penghui Bai Shuize Wang Guilin Wu Junheng Gao Xiaoye Zhou Xinping Mao | 2023 | Acta Metallurgica Sinica(English Letters)2023，36，12： | 0 |
| 15 | Identifying facile material descriptors for Charpy impact toughness in low-alloy steel via machine learning显示文摘High toughness is highly desired for low-alloy steel in engineering structure applications,wherein Charpy impact toughness(CIT)is a critical factor determining the toughness performance.In the current work,CIT data of low-alloy steel were collected,and then CIT prediction models based on machine learning(ML)algorithms were established.Three feature construction strategies were proposed.One is solely based on alloy composition,another is based on alloy composition and heat treatment parameters,and the last one is based on alloy composition,heat treatment parameters,and physical features.A series of ML methods were used to effectively select models and material descriptors from a large number of al-ternatives.Compared with the strategy solely based on the alloy composition,the strategy based on alloy composition,heat treatment parameters together with physical features perform much better.Finally,a genetic programming(GP)based symbolic regression(SR)approach was developed to establish a physical meaningful formula between the selected features and targeted CIT data. | Yimian Chen Shuize Wang Jie Xiong Guilin Wu Junheng Gao Yuan Wu Guoqiang Ma Hong-Hui Wu Xinping Mao | 2023 | Journal of Materials Science & Technology2023，，1： | 0 |
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