Article
Chemistry, Physical
Ziqing Zhou, Yinghui Shang, Xiaodi Liu, Yong Yang
Summary: Researchers have developed a generative deep learning framework to directly generate compositionally complex bulk metallic glasses (BMGs), such as high entropy BMGs. The framework is capable of producing composition-property mappings, which paves the way for the inverse design of BMGs.
NPJ COMPUTATIONAL MATERIALS
(2023)
Article
Materials Science, Multidisciplinary
Tao Long, Zhilin Long, Zheng Peng
Summary: In this study, a deep forest (DF) model with few hyperparameters and non-excessive dependence on super parameter regulation was used to predict the glass-forming ability (GFA) of bulk metallic glasses (BMGs). The results showed that our suggested DF model improved the determination coefficient (R-2) by 10.4%-74.2% compared to mainstream machine learning models. The analysis of the obtained parameter U using the SHapley Additive exPlanations (SHAP) method can guide the design and development of BMGs. Finally, a design and development scheme for BMGs that meets the expected requirements is provided using parameter U and the constructed DF model.
JOURNAL OF MATERIALS SCIENCE
(2023)
Review
Materials Science, Multidisciplinary
Zhichao Lu, Yibo Zhang, Wenyue Li, Jinyue Wang, Xiongjun Liu, Yuan Wu, Hui Wang, Dong Ma, Zhaoping Lu
Summary: Metallic glasses have unique chemical, physical, and mechanical properties, making them attractive for various engineering applications. Understanding the structure-property relationships is crucial for the development of new metallic glasses with desirable performance. This paper provides an overview of recent advances, challenges, and future opportunities in the field, including high-throughput preparation and characterization of metallic glasses, as well as data-driven machine learning strategies for accelerating their development. The paper also proposes future research directions and perspectives for MGI-assisted design of metallic glasses.
JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
(2023)
Article
Materials Science, Multidisciplinary
Hongzhen Li, Zhen Li, Jian Yang, Hai Bo Ke, Baoan Sun, Chen Chen Yuan, Jiang Ma, Jun Shen, Wei Hua Wang
Summary: Developing materials with excellent properties has always been a relentless pursuit of mankind. Metallic glasses (MGs) could be the ideal metallic materials if their size could be scaled up to be comparable to traditional metals. Various methods have been attempted to address this challenge, including thermodynamics-based alloy, 3D printing, and the recent artificial intelligence-guided optimal alloy. In this study, a simple and flexible approach was demonstrated to manufacture giant MGs (GMGs) with diameters more than 100 mm through the thermo-joining process. The jointed GMG samples exhibit almost the same performance as the as-cast ones, and the ability to manufacture complex 3D components such as the Chinese Zodiacs was also demonstrated. This approach may overcome the longstanding problem of glass forming ability (GFA) limitations in alloy systems and pave the way for fabricating size unlimited MGs.
SCIENCE CHINA-MATERIALS
(2021)
Article
Materials Science, Multidisciplinary
Xin Li, Guangcun Shan, Shujie Pang, Chan-Hung Shek
Summary: A multi-stage optimization strategy based on machine learning (ML) was proposed to accelerate the rational design of magnetic high-entropy metallic glasses (HE-MGs), and new HE-MGs with balanced magnetic properties and entropy were successfully developed.
APPLIED MATERIALS TODAY
(2023)
Article
Materials Science, Ceramics
Xiang Xu, Jingyi Hu
Summary: Metallic glass has attracted attention due to its unique properties, but the complex composition design space poses challenges for traditional experimental methods. This paper proposes a novel approach using a generative adversarial network (GAN) to generate hypothetical metallic glass compositions quickly. The GAN-generated samples were evaluated for validity, novelty, and uniqueness. Results show high validity rates and demonstrate the novelty and uniqueness of the generated samples through distribution comparison. The GAN model is expected to improve sampling efficiency and shorten the development cycle of metallic glass.
JOURNAL OF NON-CRYSTALLINE SOLIDS
(2023)
Article
Materials Science, Multidisciplinary
Junhyub Jeon, Namhyuk Seo, Hwi-Jun Kim, Min-Ha Lee, Hyun-Kyu Lim, Seung Bae Son, Seok-Jae Lee
Summary: An artificial neural network was trained to predict the thermal properties of Fe-based BMGs, with alloy compositions as the input data. The models were used with particle swarm optimization to design BMGs with desired thermal properties. The fabricated alloys were evaluated using X-ray diffraction and differential thermal analysis tests.
Article
Multidisciplinary Sciences
Sailan Shui, Pablo Gainza, Leo Scheller, Che Yang, Yoichi Kurumida, Stephane Rosset, Sandrine Georgeon, Raphael B. Di Roberto, Rocio Castellanos-Rueda, Sai T. Reddy, Bruno E. Correia
Summary: Small-molecule responsive protein switches are crucial for controlling synthetic cellular activities. A computational protein design strategy was presented to repurpose drug-inhibited protein-protein interactions into OFF- and ON-switches active in cells.
NATURE COMMUNICATIONS
(2021)
Article
Materials Science, Multidisciplinary
Anurag Bajpai, Jatin Bhatt, Nilesh P. Gurao, Krishanu Biswas
Summary: This study proposes a modified Mendeleev Number (MNp) element scale based on important elemental properties to predict Multicomponent Metallic Glasses (MMGs) using machine learning. The results show that the proposed MNp is a significant attribute for predicting MMGs with an accuracy of 87.8% in cross-validation. Additionally, the mean square variation in the MNp of the alloy constituents provides a delineated zone for glass forming multicomponent alloys.
PHILOSOPHICAL MAGAZINE
(2022)
Article
Chemistry, Multidisciplinary
Hailong Yuan, Luyuan Qi, Michael Paris, Fei Chen, Qiang Shen, Eric Faulques, Florian Massuyeau, Romain Gautier
Summary: Designing new single-phase white phosphors for solid-state lighting is a challenging trial-error process that requires navigation in a multidimensional space. With the guidance of machine learning models, a series of luminescent hybrid lead halides with ultra-high color rendering have been precisely designed.
Article
Biochemistry & Molecular Biology
Anthony Marchand, Lucia Bonati, Sailan Shui, Leo Scheller, Pablo Gainza, Steiphane Rosset, Sandrine Georgeon, Li Tang, Bruno E. Correia
Summary: Protein-based therapeutics, such as monoclonal antibodies and cytokines, are important treatments for various diseases, but their wide application is often limited by toxicities and adverse effects. In this study, researchers have designed and applied small-molecule-controlled switchable protein therapeutics by utilizing an OFF-switch system. By optimizing the affinity between B-cell lymphoma 2 protein and a designed protein partner, the addition of a competing drug can efficiently disrupt the protein function in vitro and lead to fast clearance in vivo. This study provides a proof-of-concept for the controllable design of protein-based therapeutics by introducing a drug-induced OFF-switch.
ACS CHEMICAL BIOLOGY
(2023)
Review
Chemistry, Multidisciplinary
Ali Hussain Motagamwala, James A. Dumesic
Summary: Microkinetic modeling is a useful tool for understanding surface kinetics in heterogeneous catalyst design. It helps identify key reaction intermediates and rate-determining elementary reactions, as well as ensuring thermodynamic consistency of the model and adjusting parameters for catalyst heterogeneity. The incorporation of Bronsted-Evans-Polanyi relations and scaling relations in microkinetic models has significant effects on catalytic performance and formation of volcano curves.
Article
Chemistry, Multidisciplinary
Rayan Chakraborty, Parikshit Kumar Rajput, Gokul M. Anilkumar, Shabnum Maqbool, Ranjan Das, Atikur Rahman, Pankaj Mandal, Angshuman Nag
Summary: Structural non-centrosymmetry in semiconducting organic-inorganic hybrid halide perovskites introduces functionalities like anomalous photovoltaics and nonlinear optical properties. By creating dissimilar non-covalent interactions at the organic-inorganic interface, Pb- and Bi-based two- and one-dimensional hybrid perovskites with polar non-centrosymmetric space groups can be designed. The non-centrosymmetry results in visible to infrared tunable nonlinear optical properties and anomalous photovoltaic effect in (MIPA)2PbI4 and (H3N-(CH2)3-NH(CH3)2)BiI5.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2023)
Article
Nanoscience & Nanotechnology
Jianan Huang, Yifan Gao, Peng Ding, Xuhong Guo, Martien A. Cohen Stuart, Junyou Wang
Summary: In this study, a new assembly system was designed to regulate the structure and functionality of polyelectrolyte assembly-based polyion complex (PIC) vesicles, enabling better applications and encapsulation and release of hydrophilic molecules.
ACS APPLIED MATERIALS & INTERFACES
(2022)
Article
Engineering, Mechanical
Chenglin Dong, Haitao Liu, Juliang Xiao, Tian Huang
Summary: This paper presents a dynamic modeling and design approach for a novel hybrid robot for machining, investigating the influences of design variables on performance indices and developing a full-size prototype machine that meets the essential requirements for robot machining.
MECHANISM AND MACHINE THEORY
(2021)
Article
Materials Science, Multidisciplinary
Shaofei Liu, Guma Yeli, Da Chen, Weitong Lin, Yilu Zhao, Junhua Luan, Shijun Zhao, Tao Yang, Ji-jung Kai
Summary: In this study, three NiCoCr-based medium-entropy alloys (MEAs) were irradiated with helium ions to investigate radiation hardening and He-induced cavity growth. The results showed that NiCoCr-based MEAs exhibited mitigated radiation hardening at 400°C and significant cavity growth at 700°C, in contrast to FeCoNiCr. Among the studied alloys, NiCoCrW0.1 showed the best radiation hardening resistance, while NiCoCrTi0.1 presented the strongest tolerance in He cavity growth. These findings demonstrate the potential of NiCoCr-based MEAs as critical nuclear structural components at different temperatures.
JOURNAL OF NUCLEAR MATERIALS
(2023)
Article
Materials Science, Multidisciplinary
Guhui Gao, Miao Liu, Xiaolu Gui, Jie Hu, Junhua Luan, Zengbao Jiao, Xi Wang, Bingzhe Bai, Zhigang Yang
Summary: The failures of conventional pearlitic rail steels are influenced by the formation of hard and brittle white and brown etching layers (WEL and BEL) on the rail raceway during service. This study reports the formation of a unique multilayer heterostructured WEL/BEL in a field-tested bainitic rail. The WEL is composed of fine-grained martensite or ferrite and retained austenite, while the BEL contains nanocrystalline martensite or ferrite, retained austenite, cementite, and oxide or O-rich particles.
Article
Materials Science, Multidisciplinary
Hao Jie Kong, Tao Yang, Rong Chen, Zengbao Jiao, Tianlong Zhang, Boxuan Cao, Junhua Luan, Shaofei Liu, Anding Wang, Jacob Chih-Ching Huang, Xun-Li Wang, Chain Tsuan Liu
Summary: High-performance, low-cost structural materials with nanoscale precipitations are essential for advanced industry systems. Traditional nucleation mechanisms have limitations in achieving fine dispersion of nanoscale precipitates. However, a revolutionary approach of ultra-strong iron-based alloys has successfully resolved these issues through non-classical nanoscale precipitations and multi-elemental partitioning. This strategy allows for control of nanoscale precipitates with low solute supersaturation, resulting in enhanced strength and ductility, superior fabricability, and post-weld properties.
Article
Engineering, Multidisciplinary
Lu Yang, Chengxia Wei, Dingshan Liang, Feilong Jiang, Zhuo Cheng, Junhua Luan, Zengbao Jiao, Fuzeng Ren
Summary: In this study, the friction and wear behaviors of CoCrNi2(Al0.2Nb0.2) alloy with high-density coherent L1(2) nanoprecipitates during sliding at room and elevated temperatures were systematically investigated. The results showed that the alloy exhibited low wear rate and excellent wear resistance at room temperature, attributed to the precipitation strengthening and dynamic workhardening. At elevated temperature, the reduced wear rates and coefficients of friction were associated with the formation of glaze layer and high resistance to thermal softening. This work provides significant insight into the sliding-induced microstructure evolution and deformation mechanism of L1(2)-strengthened high-entropy alloys during sliding wear.
COMPOSITES PART B-ENGINEERING
(2023)
Article
Engineering, Mechanical
F. Zhu, G. H. Xing, G. J. Lyu, L. T. Zhang, Yun-Jiang Wang, Y. Yang, J. M. Pelletier, J. C. Qiao
Summary: Dynamic mechanical relaxation is an important metric for studying viscoelastic amorphous solids. The relaxation behavior of amorphous solids, due to their heterogeneous microstructure, often deviates from the Debye relaxation. The distribution of relaxation time based on the stretched exponential function or power law is commonly used to describe non-Debye relaxation, but its applicability to real amorphous materials is still under discussion.
INTERNATIONAL JOURNAL OF PLASTICITY
(2023)
Article
Physics, Applied
H. Wang, Q. F. He, A. D. Wang, Y. Yang
Summary: We fabricated severely distorted high-entropy Elinvar alloys through micro-alloying of (CoNi)(50-x)(TiZrHf)(50)Fe-x (in atomic percentage). Our experiments demonstrate a tunable Elinvar effect that is positively correlated with overall lattice distortion in single-phase B2 high entropy alloys. Additionally, we propose a simple physical model that captures the general trend of our experimental findings.
JOURNAL OF APPLIED PHYSICS
(2023)
Article
Materials Science, Multidisciplinary
S. Shuang, G. J. Lyu, D. Chung, X. Z. Wang, X. Gao, H. H. Mao, W. P. Li, Q. F. He, B. S. Guo, X. Y. Zhong, Y. J. Wang, Y. Yang
Summary: In this study, we developed a series of medium-entropy alloys (MEAs) with high strength, superior fracture toughness, and ultra-high corrosion resistance. Interestingly, our MEAs exhibit an unusual anti-corrosion behavior as their corrosion resistance increases with increasing acidity. This behavior can be attributed to the surface chemical complexity of our MEAs, which facilitates the formation of metastable medium entropy passive films.
JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
(2023)
Article
Materials Science, Multidisciplinary
D. H. Chung, J. Lee, Q. F. He, Y. K. Kim, K. R. Lim, H. S. Kim, Y. Yang, Y. S. Na
Summary: The study investigates the toughening/strengthening mechanisms of heterostructured eutectic high-entropy alloys (EHEAs) and discovers that fully eutectic HEAs show superior performance in both yield stress and fracture toughness due to the high hetero-deformation-induced (HDI) strengthening/toughening associated with a high misorientation angle at the grain/phase boundaries.
JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
(2023)
Article
Materials Science, Multidisciplinary
Xinghao Wei, Lixin Sun, Zhongwu Zhang, Yang Zhang, Junhua Luan, Zengbao Jiao, Chain Tsuan Liu, Gang Zhao
Summary: In this study, the effects of aging treatments at 500 and 550 degrees C on the impact performance of a Cu precipitation-strengthened steel at a low temperature of -80 degrees C were investigated. The main factor controlling the low-temperature toughness was found to be solute segregation at lath boundaries. Excellent impact performance of -180 J at -80 degrees C, along with high yield strength of -1050 MPa and total elongation of 19%, can be achieved by controlling the segregation of solute elements, specifically Mo and Mn, at the lath boundaries. The evolution of matrix and precipitates during aging treatments and the strengthening and toughening mechanisms were also discussed.
JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T
(2023)
Article
Materials Science, Multidisciplinary
M. C. Niu, C. J. Chen, W. Li, K. Yang, J. H. Luan, W. Wang, Z. B. Jiao
Summary: Understanding the solute interaction effects on grain boundary segregation, precipitation, and fracture of Fe-Ni-Ti-(Mo) maraging steels is crucial for the development of improved steel performance. The addition of Mo effectively suppresses intergranular embrittlement by reducing the segregation of Ni and Ti, inhibiting the formation of coarse Ni3Ti precipitates and precipitate-free zones at grain boundaries, and enhancing grain boundary cohesion.
Article
Materials Science, Multidisciplinary
L. T. Zhang, Yun-Jiang Wang, Y. Yang, J. C. Qiao
Summary: In this study, the rejuvenation of metallic glasses through the training of the beta relaxation process is demonstrated. The transition from structural relaxation to rejuvenation is observed with increasing training frequency. Surprisingly, rejuvenation can be achieved at a relatively small cyclic strain of 0.2%. Rejuvenation increases relaxation enthalpy and promotes decoupling of the beta relaxation process and relaxation process. A cluster of beta relaxation time curves is formulated to describe energetic states between ultrastable and ultimately rejuvenated metallic glasses. Additionally, rejuvenation expands the distribution of the beta relaxation process, anelastic, and viscoplastic components during deformation.
JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
(2023)
Letter
Materials Science, Multidisciplinary
Bo Xiao, Jixun Zhang, Shaofei Liu, Yilu Zhao, Lianyong Xu, C. T. Liu, Tao Yang
JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
(2023)
Article
Materials Science, Multidisciplinary
Rui Zhou, Wenyu Chen, Wanpeng Li, Tzu-Hsiu Chou, Yen-Hsiang Chen, Xiaopeng Liang, Junhua Luan, Yuntian Zhu, J. C. Huang, Yong Liu
Summary: Traditional methods to improve corrosion resistance of alloys often sacrifice mechanical properties. However, we demonstrate that selective laser melting (SLM) can double the corrosion resistance of a N-doped CoCrFeNi HEA while maintaining good mechanical properties. The SLM process creates a heterogeneous microstructure with 3D dislocation cells, promoting Cr outward segregation and forming a thick protective Cr oxide layer for excellent corrosion resistance. Furthermore, Cr segregation along cell boundaries provides nucleation sites for oxides and stabilizes the cell structure for good mechanical properties. This strategy may be applicable to other HEAs with multiple strengthening mechanisms.
NPJ MATERIALS DEGRADATION
(2023)