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Exfoliation of bulk 2H-MoS_(2)into bilayer 1T-phase nanosheets via ether-induced superlattices

Nano Research 2024年第6期17卷 5705-5711页

作者： Xiuling Shi Dongmei Lin Zhuorui Xiao yibo Weng Hanxiang Zhou Xiaoying Long Zhiyu Ding Fuyuan Liang Yan Huang Guohua Chen Kaikai Li tong-yi zhang School of Materials Science and Engineering Harbin Institute of TechnologyShenzhen 518055China Department of Mechanical Engineering Research Institute for Smart EnergyThe Hong Kong Polytechnic UniversityHong KongChina School of Energy and Environment City University of Hong KongTat Chee AvenueKowloonHong KongChina The Hong Kong University of Science and Technology(Guangzhou) Guangzhou Municipal Key Laboratory of Materials InformaticsAdvanced Materials Thrust and Sustainable Energy and Environment ThrustNanshaGuangzhou 511400China

The exfoliation of bulk 2H-molybdenum disulfide(2H-MoS_(2))into few-layer nanosheets with 1T-phase and controlled layers represents a daunting challenge towards the device applications of MoS_(2).Conventional ion intercalation assisted exfoliation needs the use of hazardous n-butyllithium and/or elaborate control of the intercalation potential to avoid the decomposition of the MoS_(2).This work reports a facile strategy by intercalating Li ions electrochemically with ether-based electrolyte into the van der Waals(vdW)channels of MoS_(2),which successfully avoids the decomposition of MoS_(2)at low *** co-intercalation of Li+and the ether solvent into MoS_(2)makes a first-order phase transformation,forming a superlattice phase,which preserves the layered structure and hence enables the exfoliation of bulk 2H-MoS_(2)into bilayer nanosheets with *** with the pristine 2H-MoS_(2),the bilayer 1T-MoS_(2)nanosheets exhibit better electrocatalytic performance for the hydrogen evolution reaction(HER).This facile method should be easily extended to the exfoliation of various transition metal dichalcogenides(TMDs).

关键词： exfoliation of MoS_(2) phase transformations superlattices ether electrolyte hydrogen evolution reaction(HER)

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Data-driven glass-forming ability criterion for bulk amorphous metals with data augmentation

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Journal of Materials Science & Technology 2022年第26期121卷 99-104页

作者： Jie Xiong tong-yi zhang School of Materials Science and Engineering Harbin Institute of TechnologyShenzhen 518000China Hong Kong University of Science and Technology(Guangzhou) Guangzhou 511400China Material Genome Institute Shanghai UniversityShanghai 200444China

A data augmentation technique is employed in the current work on a training dataset of 610 bulk metallic glasses(BMGs),which are randomly selected from 762 collected *** ensemble machine learning(ML)model is developed on augmented training dataset and tested by the rest 152 *** result shows that ML model has the ability to predict the maximal diameter Dmaxof BMGs more accurate than all reported ML *** addition,the novel ML model gives the glass forming ability(GFA)rules:average atomic radius ranging from 140 pm to 165 pm,the value of TT/(T-T)(T-T)being higher than 2.5,the entropy of mixing being higher than 10 J/K/mol,and the enthalpy of mixing ranging from-32 k J/mol to-26 k J/*** model is interpretative,thereby deepening the understanding of GFA.

关键词： Materials informatics Glass-forming ability Data augmentation Model interpretation Meta-ensemble model

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Machine learning of phases and mechanical properties in complex concentrated alloys

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Journal of Materials Science & Technology 2021年第28期87卷 133-142页

作者： Jie Xiong San-Qiang Shi tong-yi zhang School of Materials Science and Engineering Harbin Institute of TechnologyShenzhenChina Department of Mechanical Engineering The Hong Kong Polytechnic UniversityHong KongChina Shenzhen Research Institute The Hong Kong Polytechnic UniversityShenzhenChina Material Genome Institute Shanghai UniversityShanghaiChina

The mechanical properties of complex concentrated alloys(CCAs)depend on their formed phases and corresponding *** data-driven prediction of the phase formation and associated mechanical properties is essential to discovering novel *** present work collects 557 samples of various chemical compositions,comprising 61 amorphous,167 single-phase crystalline,and 329 multiphases crystalline *** classification models are developed with high accuracies to category and understand the formed phases of ***,two regression models are constructed to predict the hardness and ultimate tensile strength of CCAs,and the correlation coefficient of the random forest regression model is greater than 0.9 for both of two targeted ***,the Shapley additive explanation(SHAP)values are calculated,and accordingly four most important features are identified.A significant finding in the SHAP values is that there exists a critical value in each of the top four features,which provides an easy and fast assessment in the design of improved mechanical properties of *** present work demonstrates the great potential of machine learning in the design of advanced CCAs.

关键词： Materials informatics SHAP Complex concentrated alloys High entropy alloys

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Grain boundary segregation and relaxation in nano-grained polycrystalline alloys

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Science China(Physics,Mechanics & Astronomy) 2021年第2期64卷 72-90页

作者： tong-yi zhang ying-Xin Gao Sheng Sun Materials Genome Institute Shanghai UniversityShanghai200444China

The present study carries out systematic thermodynamics analysis of Grain Boundary(GB)segregation and relaxation in NanoGrained(NG)polycrystalline *** segregation and relaxation is an internal process towards thermodynamic equilibrium,which occurs naturally in NG alloys without any applied loads,causes deformation and generates internal *** analysis comprehensively investigates the multiple coupling effects among chemical concentrations and mechanical stresses in GBs and grains.A hybrid approach of eigenstress and eigenstrain is developed herein to solve the multiple coupling *** analysis results indicate that the GB stress and grain stress induced by GB segregation and relaxation can be extremely high in NG alloys,reaching the GPa level,which play an important role in the thermal stability of NG alloys,especially via the coupling terms between stress and *** present theoretic analysis proposes a novel criterion of thermal stability for NG alloys,which is determined by the difference in molar free energy between a NG alloy and its reference single crystal with the same nominal chemical *** the difference at a temperature is negative or zero,the NG alloy is thermal stable at that temperature,otherwise unstable.

关键词： nano-grained alloys thermal stability grain boundary segregation eigenstress eigenstrain

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Data driven discovery of an analytic formula for the life prediction of Lithium-ion batteries

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Progress in Natural Science:Materials International 2022年第6期32卷 793-799页

作者： Jie Xiong tong-Xing Lei Da-Meng Fu Jun-Wei Wu tong-yi zhang School of Materials Science and Engineering Harbin Institute of Technology Hong Kong University of Science and Technology (Guangzhou)

Predicting the cycle life of Lithium-Ion Batteries(LIBs) remains a great challenge due to their complicated degradation *** present work employs an interpretative machine learning of symbolic regression(SR) to discover an analytic formula for LIB life prediction with newly defined *** novel features are based on the discharging energies under the constant-current(CC) and constant-voltage(CV) modes at every five cycles *** cycle life is affected by the CC-discharging energy at the 15th cycle(E15-CCD) and the difference between the CC-discharging energies at the 45th cycle and 95th cycle(Δ45-95).The cycle life highly correlates with a simple indicator(E15-CCD-3)/Δ45-95with a Pearson correlation coefficient of *** machine learning tools provide a rapid and accurate prediction of cycle life at the early stage.

关键词： Symbolic regression Machine learning Cycle life prediction Lithium-ion batteries

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Gaussian process regressions on hot deformation behaviors of FGH98 nickel-based powder superalloy

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Journal of Materials Science & Technology 2023年第15期146卷 177-185页

作者： Jie Xiong Jian-Chao He Xue-Song Leng tong-yi zhang School of Materials Science and Engineering Harbin Institute of TechnologyShenzhen 518055China Institute of Special Environment Physical Sciences Harbin Institute of TechnologyShenzhen 518055China Hong Kong University of Science and Technology(Guangzhou) Guangzhou 511400China

The hot deformation behaviors of FGH98 nickel-based powder superalloy were experimentally investigated and theoretically analyzed by Arrhenius models and machine learning(ML).Hot compression tests were conducted with a Gleeble-3800 thermo-mechanical simulation machine on the FGH98 superalloy at strain rates of 0.001–1 s–1 and temperatures of 1025–1175℃.The peak stresses under different deformation conditions were analyzed via the Sellars model and an ML-inspired Gaussian process regression(GPR)*** prediction of the GPR model outperformed that from the Sellars *** addition,the stress-strain responses were predicted by the GPR model and tested by experimentally measured stress-strain *** results indicate that the developed GPR model has great power with wide generalization capability in the prediction of hot deformation behaviors of FGH98 superalloy,as evidenced by the R2 value higher than 0.99 on the test dataset.

关键词： Hot compressive deformation Nickel-based powder superalloy Activation energy Gaussian process regression

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miR-222 targets ACOX1, promotes triglyceride accumulation in hepatocytes

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Hepatobiliary & Pancreatic Diseases International 2019年第4期18卷 360-365页

作者： Jing-Jie Wang yi-tong zhang Yu Jen Tseng Jun zhang Department of Digestive Diseases Huashan Hospital Fudan University

Background:Non-alcoholic fatty liver disease(NAFLD)is one of the most prevalent chronic liver ***,the exact pathogenesis of NAFLD remains to be *** the association with tumors and cardiovascular diseases,the role of miR-222 in NAFLD remains *** present study was to investigate the role of miR-222 in ***:Wild-type C57BL/6 mice were fed a high-fat diet for 12 weeks to induce *** human liver cell line(L02)was cultured with free fatty acid(FFA)-containing medium to stimulate cell *** mRNA levels of miR-222 and acyl Coenzyme A xidase 1(ACOX1)were detected by quantitative-PCR(Q-PCR).The prediction of ACOX1 as the target gene for miR-222 was conducted via *** overexpression or inhibition of miR-222 was mediated by miR-222 mimics or antagomir,and intracellular triglyceride levels were measured using a triglyceride *** reporter assays verified ACOX1 as the target gene for ***:miR-222 was significantly elevated in both the in vivo and in vitro NAFLD *** of miR-222 significantly increased triglyceride content in the L02 cells,while inhibition of miR-222 expression restricted the accumulation of *** of miR-222 significantly inhibited ACOX1 *** transfection assays verified that ACOX1 3-UTR luciferase reporter activity could be inhibited by miR-222 ***:The present study suggested that miR-222 promotes the accumulation of triglycerides by inhibiting ACOX1.

关键词： ACOX1 Hepatocyte steatosis miR-222 NAFLD β-hydroxybutyrate

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Symbolic regression in materials science via dimension-synchronous-computation

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Journal of Materials Science & Technology 2022年第27期122卷 77-83页

作者： Changxin Wang Yan zhang Cheng Wen Mingli Yang Turab Lookman Yanjing Su tong-yi zhang Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology BeijingBeijing 100083China Corrosion and Protection Center University of Science and Technology BeijingBeijing 100083China Research Center for Materials Genome Engineering Sichuan UniversityChengdu 610065China Ai Materials Research LLC Santa FeNM 87501United States of America School of Materials Science and Engineering Harbin Institute of TechnologyShenzhenChina Materials Genome Institute Shanghai University333 Nanchen RoadShanghai 200444China

There is growing interest in applying machine learning techniques in the field of materials ***,the interpretation and knowledge extracted from machine learning models is a major concern,particularly as formulating an explicit model that provides insight into physics is the goal of *** the present study,we propose a framework that utilizes the filtering ability of feature engineering,in conjunction with symbolic regression to extract explicit,quantitative expressions for the band gap energy from materials *** propose enhancements to genetic programming with dimensional consistency and artificial constraints to improve the search efficiency of symbolic *** show how two descriptors attributed to volumetric and electronic factors,from 32 possible candidates,explicitly express the band gap energy of Na Cl-type *** approach provides a basis to capture underlying physical relationships between materials descriptors and target properties.

关键词： Symbolic regression Band gap Dimensional calculation

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Discovering a formula for the high temperature oxidation behavior of FeCrAlCoNi based high entropy alloys by domain knowledge-guided machine learning

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Journal of Materials Science & Technology 2023年第18期149卷 237-246页

作者： Qinghua Wei Bin Cao Lucheng Deng Ankang Sun Ziqiang Dong tong-yi zhang Materials Genome Institute Shanghai UniversityShanghai 200444China Hong Kong University of Science and Technology(Guangzhou) Guangzhou 511458China

A mathematical formula of high physical interpretation,and accurate prediction and large generaliza-tion power is highly desirable for science,technology and *** this study,we performed a domain knowledge-guided machine learning to discover high interpretive formula describing the high-temperature oxidation behavior of FeCrAlCoNi-based high entropy alloys(HEAs).The domain knowledge suggests that the exposure time dependent and thermally activated oxidation behavior can be described by the synergy formula of power law multiplying Arrhenius *** pre-factor,time exponent(m),and activation energy(Q)are dependent on the chemical compositions of eight elements in the FeCrAlCoNi-based *** Tree-Classifier for Linear Regression(TCLR)algorithm utilizes the two exper-imental features of exposure time(t)and temperature(T)to extract the spectrums of activation energy(Q)and time exponent(m)from the complex and high dimensional feature space,which automatically gives the spectrum of *** three spectrums are assembled by using the element features,which leads to a general and interpretive formula with high prediction accuracy of the determination coefficient R^(2)=*** role of each chemical element in the high-temperature oxidation behavior is analytically illustrated in the three spectrums,thereby the discovered interpretative formula provides a guidance to the inverse design of HEAs against high-temperature *** present work demonstrates the sig-nificance of domain knowledge in the development of materials informatics.

关键词： Domain knowledge Interpretive formula High entropy alloys Oxidation

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Chemical Strain of Graphite-Based Anode during Lithiation and Delithiation at Various Temperatures

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Research 2021年第1期2021卷 1255-1265页

作者： Zeyu Xu Xiuling Shi Xiaoqiang Zhuang Zihan Wang Sheng Sun Kaikai Li tong-yi zhang Materials Genome Institute Shanghai University333 Nanchen RoadShanghai 200444China School of Materials Science and Engineering Harbin Institute of TechnologyShenzhenChina

Electrochemical lithiation/delithiation of electrodes induces chemical strain cycling that causes fatigue and other harmful influences on lithium-ion *** this work,a homemade in situ measurement device was used to characterize simultaneously chemical strain and nominal state of charge,especially residual chemical strain and residual nominal state of charge,in graphite-based electrodes at various *** measurements indicate that raising the testing temperature from 20℃ to 60℃ decreases the chemical strain at the same nominal state of charge during cycling,while residual chemical strain and residual nominal state of charge increase with the increase of ***,a novel electrochemicalmechanical model is developed to evaluate quantitatively the chemical strain caused by a solid electrolyte interface(SEI)and the partial molar volume of Li in the SEI at different *** present study will definitely stimulate future investigations on the electro-chemo-mechanics coupling behaviors in lithium-ion batteries.

关键词： nominal cycling lithium

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