Cardiovascular diseases(CVDs)are one of the most serious diseases threatening human health in the world.Therefore,effective monitoring and treatment of CVDs are urgently needed.Compared with traditional rigid devices,...Cardiovascular diseases(CVDs)are one of the most serious diseases threatening human health in the world.Therefore,effective monitoring and treatment of CVDs are urgently needed.Compared with traditional rigid devices,nanomaterials based flexible devices open up new opportunities for further development beneficial from the unique properties of nanomaterials which contribute to excellent performance to better prevent and treat CVDs.This review summarizes recent advances of nanomaterials based flexible devices for the monitoring and treatment of CVDs.First,we review the outstanding characteristics of nanomaterials.Next,we introduce flexible devices based on nanomaterials for practical use in CVDs including in vivo,ex vivo,and in vitro methods.At last,we make a conclusion and discuss the further development needed for nanomaterials and monitoring and treatment devices to better care CVDs.展开更多
Cardiovascular disease(CVD)has gradually become one of the main causes of harm to the life and health of residents.Exploring the influencing factors and risk assessment methods of CVD has become a general trend.In thi...Cardiovascular disease(CVD)has gradually become one of the main causes of harm to the life and health of residents.Exploring the influencing factors and risk assessment methods of CVD has become a general trend.In this paper,a machine learning-based decision-making mechanism for risk assessment of CVD is designed.In this mechanism,the logistics regression analysismethod and factor analysismodel are used to select age,obesity degree,blood pressure,blood fat,blood sugar,smoking status,drinking status,and exercise status as the main pathogenic factors of CVD,and an index systemof risk assessment for CVD is established.Then,a two-stage model combining K-means cluster analysis and random forest(RF)is proposed to evaluate and predict the risk of CVD,and the predicted results are compared with the methods of Bayesian discrimination,K-means cluster analysis and RF.The results show that thepredictioneffect of theproposedtwo-stagemodel is better than that of the comparedmethods.Moreover,several suggestions for the government,the medical industry and the public are provided based on the research results.展开更多
The growth of high-quality germanium tin(Ge_(1–y)Sn_(y))binary alloys on a Si substrate using chemical vapor deposition(CVD)techniques holds immense potential for advancing electronics and optoelectronics application...The growth of high-quality germanium tin(Ge_(1–y)Sn_(y))binary alloys on a Si substrate using chemical vapor deposition(CVD)techniques holds immense potential for advancing electronics and optoelectronics applications,including the development of efficient and low-cost mid-infrared detectors and light sources.However,achieving precise control over the Sn concentration and strain relaxation of the Ge_(1–y)Sn_(y)epilayer,which directly influence its optical and electrical properties,remain a significant challenge.In this research,the effect of strain relaxation on the growth rate of Ge_(1–y)Sn_(y)epilayers,with Sn concentration>11at.%,is investigated.It is successfully demonstrated that the growth rate slows down by~55%due to strain relaxation after passing its critical thickness,which suggests a reduction in the incorporation of Ge into Ge_(1–y)Sn_(y)growing layers.Despite the increase in Sn concentration as a result of the decrease in the growth rate,it has been found that the Sn incorporation rate into Ge_(1–y)Sn_(y)growing layers has also decreased due to strain relaxation.Such valuable insights could offer a foundation for the development of innovative growth techniques aimed at achieving high-quality Ge_(1–y)Sn_(y)epilayers with tuned Sn concentration and strain relaxation.展开更多
Graphene(Gr)has unique properties including high electrical conductivity;Thus,graphene/copper(Gr/Cu)composites have attracted increasing attention to replace traditional Cu for electrical applications. However,the pro...Graphene(Gr)has unique properties including high electrical conductivity;Thus,graphene/copper(Gr/Cu)composites have attracted increasing attention to replace traditional Cu for electrical applications. However,the problem of how to control graphene to form desired Gr/Cu composite is not well solved. This paper aims at exploring the best parameters for preparing graphene with different layers on Cu foil by chemical vapor deposition(CVD)method and studying the effects of different layers graphene on Gr/Cu composite’s electrical conductivity. Graphene grown on single-sided and double-sided copper was prepared for Gr/Cu and Gr/Cu/Gr composites. The resultant electrical conductivity of Gr/Cu composites increased with decreasing graphene layers and increasing graphene volume fraction. The Gr/Cu/Gr composite with monolayer graphene owns volume fraction of less than 0.002%,producing the best electrical conductivity up to59.8 ×10^(6)S/m,equivalent to 104.5% IACS and 105.3% pure Cu foil.展开更多
基金supported by the National Key R&D Program of China(No.2018YFA0108100)the National Natural Science Foundation of China(No.62104009).
文摘Cardiovascular diseases(CVDs)are one of the most serious diseases threatening human health in the world.Therefore,effective monitoring and treatment of CVDs are urgently needed.Compared with traditional rigid devices,nanomaterials based flexible devices open up new opportunities for further development beneficial from the unique properties of nanomaterials which contribute to excellent performance to better prevent and treat CVDs.This review summarizes recent advances of nanomaterials based flexible devices for the monitoring and treatment of CVDs.First,we review the outstanding characteristics of nanomaterials.Next,we introduce flexible devices based on nanomaterials for practical use in CVDs including in vivo,ex vivo,and in vitro methods.At last,we make a conclusion and discuss the further development needed for nanomaterials and monitoring and treatment devices to better care CVDs.
基金This work is supported by the National Natural Science Foundation of China(Nos.72071150,71871174).
文摘Cardiovascular disease(CVD)has gradually become one of the main causes of harm to the life and health of residents.Exploring the influencing factors and risk assessment methods of CVD has become a general trend.In this paper,a machine learning-based decision-making mechanism for risk assessment of CVD is designed.In this mechanism,the logistics regression analysismethod and factor analysismodel are used to select age,obesity degree,blood pressure,blood fat,blood sugar,smoking status,drinking status,and exercise status as the main pathogenic factors of CVD,and an index systemof risk assessment for CVD is established.Then,a two-stage model combining K-means cluster analysis and random forest(RF)is proposed to evaluate and predict the risk of CVD,and the predicted results are compared with the methods of Bayesian discrimination,K-means cluster analysis and RF.The results show that thepredictioneffect of theproposedtwo-stagemodel is better than that of the comparedmethods.Moreover,several suggestions for the government,the medical industry and the public are provided based on the research results.
文摘The growth of high-quality germanium tin(Ge_(1–y)Sn_(y))binary alloys on a Si substrate using chemical vapor deposition(CVD)techniques holds immense potential for advancing electronics and optoelectronics applications,including the development of efficient and low-cost mid-infrared detectors and light sources.However,achieving precise control over the Sn concentration and strain relaxation of the Ge_(1–y)Sn_(y)epilayer,which directly influence its optical and electrical properties,remain a significant challenge.In this research,the effect of strain relaxation on the growth rate of Ge_(1–y)Sn_(y)epilayers,with Sn concentration>11at.%,is investigated.It is successfully demonstrated that the growth rate slows down by~55%due to strain relaxation after passing its critical thickness,which suggests a reduction in the incorporation of Ge into Ge_(1–y)Sn_(y)growing layers.Despite the increase in Sn concentration as a result of the decrease in the growth rate,it has been found that the Sn incorporation rate into Ge_(1–y)Sn_(y)growing layers has also decreased due to strain relaxation.Such valuable insights could offer a foundation for the development of innovative growth techniques aimed at achieving high-quality Ge_(1–y)Sn_(y)epilayers with tuned Sn concentration and strain relaxation.
基金supported substantially by the Southwest Jiaotong University for Material and Financial Support。
文摘Graphene(Gr)has unique properties including high electrical conductivity;Thus,graphene/copper(Gr/Cu)composites have attracted increasing attention to replace traditional Cu for electrical applications. However,the problem of how to control graphene to form desired Gr/Cu composite is not well solved. This paper aims at exploring the best parameters for preparing graphene with different layers on Cu foil by chemical vapor deposition(CVD)method and studying the effects of different layers graphene on Gr/Cu composite’s electrical conductivity. Graphene grown on single-sided and double-sided copper was prepared for Gr/Cu and Gr/Cu/Gr composites. The resultant electrical conductivity of Gr/Cu composites increased with decreasing graphene layers and increasing graphene volume fraction. The Gr/Cu/Gr composite with monolayer graphene owns volume fraction of less than 0.002%,producing the best electrical conductivity up to59.8 ×10^(6)S/m,equivalent to 104.5% IACS and 105.3% pure Cu foil.
