Tungsten carbide-based(WC-based)cemented carbides are widely recognized as high-performance tool materials.Traditionally,single metals such as cobalt(Co)or nickel(Ni)serve as the binder phase,providing toughness and s...Tungsten carbide-based(WC-based)cemented carbides are widely recognized as high-performance tool materials.Traditionally,single metals such as cobalt(Co)or nickel(Ni)serve as the binder phase,providing toughness and structural integrity.Replacing this phase with high-entropy alloys(HEAs)offers a promising approach to enhancing mechanical properties and addressing sustainability challenges.However,the complex multi-element composition of HEAs complicates conventional experimental design,making it difficult to explore the vast compositional space efficiently.Traditional trial-and-error methods are time-consuming,resource-intensive,and often ineffective in identifying optimal compositions.In contrast,artificial intelligence(AI)-driven approaches enable rapid screening and optimization of alloy compositions,significantly improving predictive accuracy and interpretability.Feature selection techniques were employed to identify key alloying elements influencing hardness,toughness,and wear resistance.To enhance model interpretability,explainable artificial intelligence(XAI)techniques—SHapley Additive exPlanations(SHAP)and Local Interpretable Model-agnostic Explanations(LIME)—were applied to quantify the contributions of individual elements and uncover complex elemental interactions.Furthermore,a high-throughput machine learning(ML)–driven screening approach was implemented to optimize the binder phase composition,facilitating the discovery of HEAs with superiormechanical properties.Experimental validation demonstrated strong agreement between model predictions and measured performance,confirming the reliability of the ML framework.This study underscores the potential of integrating ML and XAI for data-driven materials design,providing a novel strategy for optimizing high-entropy cemented carbides.展开更多
In the present work,the structure and microwave dielectric properties of(Ba,Sr,Ca)HfO_(3)ceramics were systematically investigated to understand the general mechanism of tuning the temperature coefficient of resonant ...In the present work,the structure and microwave dielectric properties of(Ba,Sr,Ca)HfO_(3)ceramics were systematically investigated to understand the general mechanism of tuning the temperature coefficient of resonant frequency,tf in perovskite ceramics.Ba1_(-x-y)Sr_(x)Ca_(y)HfO_(3)and Sr_(1-y)Ca_(y)HfO_(3)could form continuous solid solutions while the solid solubility of Ca in Ba1_(-x-y)Sr_(x)Ca_(y)HfO_(3)was about 20%(in mole).tf changed nonlinearly with increasing tolerance factor as the result of competition between the increase in the restoring force on the ions and the increase in polarizability.Under the guidance of three microscopic mechanisms affecting tf,a preliminary attempt was made to explore the suitable parameters to predict the variation trend of tf.Normalized ionic radii and the tf values of the end members were selected as independent variables,and tf was calculated by using multiple linear regression method.For Ba1_(-x-y)Sr_(x)Ca_(y)HfO_(3)and Sr_(1-y)Ca_(y)HfO_(3)with orthorhombic structures,the root mean square error between the calculated and measured tf was only 6.8×10℃^(-1).The good agreement between the calculated tf values and the measured ones in Ba1_(-x-y)Sr_(x)Ca_(y)HfO_(3)ceramics confirmed its validity where three elements jointly occupy A-site,but it only works when there is no structural phase transition.Progresses in this researchfield would not only deepen our understanding of mechanism of regulating properties in multi-ion solid solutions,but also boost the developments of closely relatedfields such as machine learning-assisted design and high-entropy ceramics.Finally,a good combination of microwave dielectric properties was achieved in Sr_(0.15)Ca_(0.85)Hf_(0.96)Ti_(0.040)O_(3):εr=27.8,Qf=36,470 GHz,τf=+5×10^(-6)℃^(-1).展开更多
A high thermal-stable jet fuel design method was developed using composition-properties relations and basic specification properties of jet fuel. Tannery diagrams were provided to visualize relationships among three m...A high thermal-stable jet fuel design method was developed using composition-properties relations and basic specification properties of jet fuel. Tannery diagrams were provided to visualize relationships among three main components (n-paraffins, iso-paraffins, cycloparaffins, or aromatics) with four major specification properties (density, flash point, freezing point, net heat of combustion) and thermal sta- bility. An optimum chemical composition was established to meet performance requirements: n-paraffins 25%-45%, iso-paraffins 15%-30%, cycloparaffins 30%-50%, and aromatics 5%. The thermal stability test on four fuel samples with and without optimal composition indicated that the thermal stabilities of fuel samples with optimal composition are higher than RP-3 jet fuel, and that the theoretical design method is a reliable method to screen the basic oil for the high thermal-stable jet fuel.展开更多
Double-metallic lead-free halide perovskites,Cs_(2)B^(I)B^(III)X_(6),sharing three-dimensional crystal structure,have been under the spotlight as the promising alternatives for the toxic and instable lead-based counte...Double-metallic lead-free halide perovskites,Cs_(2)B^(I)B^(III)X_(6),sharing three-dimensional crystal structure,have been under the spotlight as the promising alternatives for the toxic and instable lead-based counterparts.Interest in Cs_(2)B^(I)B^(III)X_(6)motivates intense research into their colloidal nanocrystals(NCs).Recently,Cs_(2)B^(I)B^(III)X_(6)NCs have made great progress in the optical performance via alloying or doping,but there are still great challenges for optoelectronic applications.In this review,the latest advances of Cs_(2)B^(I)B^(III)X_(6)NCs in synthesis approaches,bandgap engineering,photoluminescence(PL)optimization,and applications are summarized.The focus is put upon the composition-property relationships of Cs_(2)B^(I)B^(III)X_(6)NCs,which is approached by discussing the influences of composition variation on the electronic states,carrier dynamics,and optical properties.The challenges and the corresponding improving strategies in the development of high-effective and stable Cs_(2)B^(I)B^(III)X_(6)NCs for device applications are also highlighted.It is believed that this review can deepen the understanding on this burgeoning material system and shed light on their future research directions.展开更多
文摘Tungsten carbide-based(WC-based)cemented carbides are widely recognized as high-performance tool materials.Traditionally,single metals such as cobalt(Co)or nickel(Ni)serve as the binder phase,providing toughness and structural integrity.Replacing this phase with high-entropy alloys(HEAs)offers a promising approach to enhancing mechanical properties and addressing sustainability challenges.However,the complex multi-element composition of HEAs complicates conventional experimental design,making it difficult to explore the vast compositional space efficiently.Traditional trial-and-error methods are time-consuming,resource-intensive,and often ineffective in identifying optimal compositions.In contrast,artificial intelligence(AI)-driven approaches enable rapid screening and optimization of alloy compositions,significantly improving predictive accuracy and interpretability.Feature selection techniques were employed to identify key alloying elements influencing hardness,toughness,and wear resistance.To enhance model interpretability,explainable artificial intelligence(XAI)techniques—SHapley Additive exPlanations(SHAP)and Local Interpretable Model-agnostic Explanations(LIME)—were applied to quantify the contributions of individual elements and uncover complex elemental interactions.Furthermore,a high-throughput machine learning(ML)–driven screening approach was implemented to optimize the binder phase composition,facilitating the discovery of HEAs with superiormechanical properties.Experimental validation demonstrated strong agreement between model predictions and measured performance,confirming the reliability of the ML framework.This study underscores the potential of integrating ML and XAI for data-driven materials design,providing a novel strategy for optimizing high-entropy cemented carbides.
基金by National Natural Foundation of China under grant Nos.U20A2024352372127.
文摘In the present work,the structure and microwave dielectric properties of(Ba,Sr,Ca)HfO_(3)ceramics were systematically investigated to understand the general mechanism of tuning the temperature coefficient of resonant frequency,tf in perovskite ceramics.Ba1_(-x-y)Sr_(x)Ca_(y)HfO_(3)and Sr_(1-y)Ca_(y)HfO_(3)could form continuous solid solutions while the solid solubility of Ca in Ba1_(-x-y)Sr_(x)Ca_(y)HfO_(3)was about 20%(in mole).tf changed nonlinearly with increasing tolerance factor as the result of competition between the increase in the restoring force on the ions and the increase in polarizability.Under the guidance of three microscopic mechanisms affecting tf,a preliminary attempt was made to explore the suitable parameters to predict the variation trend of tf.Normalized ionic radii and the tf values of the end members were selected as independent variables,and tf was calculated by using multiple linear regression method.For Ba1_(-x-y)Sr_(x)Ca_(y)HfO_(3)and Sr_(1-y)Ca_(y)HfO_(3)with orthorhombic structures,the root mean square error between the calculated and measured tf was only 6.8×10℃^(-1).The good agreement between the calculated tf values and the measured ones in Ba1_(-x-y)Sr_(x)Ca_(y)HfO_(3)ceramics confirmed its validity where three elements jointly occupy A-site,but it only works when there is no structural phase transition.Progresses in this researchfield would not only deepen our understanding of mechanism of regulating properties in multi-ion solid solutions,but also boost the developments of closely relatedfields such as machine learning-assisted design and high-entropy ceramics.Finally,a good combination of microwave dielectric properties was achieved in Sr_(0.15)Ca_(0.85)Hf_(0.96)Ti_(0.040)O_(3):εr=27.8,Qf=36,470 GHz,τf=+5×10^(-6)℃^(-1).
基金National Hi-Tech Research and Development 863 Program of China (No. 2005AA723101)China Postdoctoral Science Foundation (No. 2005AA723101)Innovative Research Project of Petrochina Co. Ltd
文摘A high thermal-stable jet fuel design method was developed using composition-properties relations and basic specification properties of jet fuel. Tannery diagrams were provided to visualize relationships among three main components (n-paraffins, iso-paraffins, cycloparaffins, or aromatics) with four major specification properties (density, flash point, freezing point, net heat of combustion) and thermal sta- bility. An optimum chemical composition was established to meet performance requirements: n-paraffins 25%-45%, iso-paraffins 15%-30%, cycloparaffins 30%-50%, and aromatics 5%. The thermal stability test on four fuel samples with and without optimal composition indicated that the thermal stabilities of fuel samples with optimal composition are higher than RP-3 jet fuel, and that the theoretical design method is a reliable method to screen the basic oil for the high thermal-stable jet fuel.
基金supported by the Natural Science Foundation of Fujian Province(No.2021J01315)Quanzhou Scientific Research Project(No.2021GZ4).
文摘Double-metallic lead-free halide perovskites,Cs_(2)B^(I)B^(III)X_(6),sharing three-dimensional crystal structure,have been under the spotlight as the promising alternatives for the toxic and instable lead-based counterparts.Interest in Cs_(2)B^(I)B^(III)X_(6)motivates intense research into their colloidal nanocrystals(NCs).Recently,Cs_(2)B^(I)B^(III)X_(6)NCs have made great progress in the optical performance via alloying or doping,but there are still great challenges for optoelectronic applications.In this review,the latest advances of Cs_(2)B^(I)B^(III)X_(6)NCs in synthesis approaches,bandgap engineering,photoluminescence(PL)optimization,and applications are summarized.The focus is put upon the composition-property relationships of Cs_(2)B^(I)B^(III)X_(6)NCs,which is approached by discussing the influences of composition variation on the electronic states,carrier dynamics,and optical properties.The challenges and the corresponding improving strategies in the development of high-effective and stable Cs_(2)B^(I)B^(III)X_(6)NCs for device applications are also highlighted.It is believed that this review can deepen the understanding on this burgeoning material system and shed light on their future research directions.
