Abstract A quantitative investigation of poly(vinyl) chloride (PVC) de-chlorination using Fe2O3, together with the impact of SiO2 addition on the co-pyrolysis of PVC and Fe2O3, was conducted below 673 K in an Ar atmosphere aiming to cut the emission of gaseous Cl⁻ products. It was found that chlorine in PVC can be fixed in FeCl2 by the reaction between PVC and Fe2O3. The co-pyrolysis of PVC and Fe2O3 proceeds in two stages with a temperature boundary of around 543 K. Below 543 K, a direct reaction occurs between PVC and Fe2O3, resulting in a small mass loss ratio and some extent of chlorine fixing ratio in FeCl2. However, above 543 K, PVC starts to decompose to release gaseous H2, HCl, etc., which react with Fe2O3 through two possible pathways to form FeCl2. In Pathway 1, first Fe2O3 is reduced to Fe3O4 by H2, followed by the chlorination of Fe3O4 to FeCl2 by HCl. In Pathway 2, first Fe2O3 is chlorinated to FeCl3 by HCl, followed by the reduction of FeCl3 to FeCl2 by H2. The chlorine fixing ratio in FeCl2 and the volatile generation ratio increase with decreasing PVC content in the initial mixtures. The addition of SiO2 promotes the chlorine fixing ratio in FeCl2 and volatile generation, and the impact gets stronger with decreasing PVC content in the mixtures. The chlorine fixing ratio is increased from 70.8 to 82.6% by SiO2 addition for the mixtures containing 25% PVC, whereas the difference in the chlorine fixing ratio in FeCl2 caused by SiO2 addition is negligible for the mixtures containing 90% PVC. Fayalite (Fe2SiO4) was not detected in the solid residues after the experiments. After separating FeCl2 using water leaching, the filter residue, a composite of iron oxide and conjugated polyene, can be used as a raw material for iron-making.
{"title":"De-chlorination of poly(vinyl) chloride using Fe2O3 and the improvement of chlorine fixing ratio in FeCl2 by SiO2 addition","authors":"Lan Hong, Tai-lin Li, Lin-hai Ye","doi":"10.1515/htmp-2022-0299","DOIUrl":"https://doi.org/10.1515/htmp-2022-0299","url":null,"abstract":"Abstract A quantitative investigation of poly(vinyl) chloride (PVC) de-chlorination using Fe2O3, together with the impact of SiO2 addition on the co-pyrolysis of PVC and Fe2O3, was conducted below 673 K in an Ar atmosphere aiming to cut the emission of gaseous Cl⁻ products. It was found that chlorine in PVC can be fixed in FeCl2 by the reaction between PVC and Fe2O3. The co-pyrolysis of PVC and Fe2O3 proceeds in two stages with a temperature boundary of around 543 K. Below 543 K, a direct reaction occurs between PVC and Fe2O3, resulting in a small mass loss ratio and some extent of chlorine fixing ratio in FeCl2. However, above 543 K, PVC starts to decompose to release gaseous H2, HCl, etc., which react with Fe2O3 through two possible pathways to form FeCl2. In Pathway 1, first Fe2O3 is reduced to Fe3O4 by H2, followed by the chlorination of Fe3O4 to FeCl2 by HCl. In Pathway 2, first Fe2O3 is chlorinated to FeCl3 by HCl, followed by the reduction of FeCl3 to FeCl2 by H2. The chlorine fixing ratio in FeCl2 and the volatile generation ratio increase with decreasing PVC content in the initial mixtures. The addition of SiO2 promotes the chlorine fixing ratio in FeCl2 and volatile generation, and the impact gets stronger with decreasing PVC content in the mixtures. The chlorine fixing ratio is increased from 70.8 to 82.6% by SiO2 addition for the mixtures containing 25% PVC, whereas the difference in the chlorine fixing ratio in FeCl2 caused by SiO2 addition is negligible for the mixtures containing 90% PVC. Fayalite (Fe2SiO4) was not detected in the solid residues after the experiments. After separating FeCl2 using water leaching, the filter residue, a composite of iron oxide and conjugated polyene, can be used as a raw material for iron-making.","PeriodicalId":12966,"journal":{"name":"High Temperature Materials and Processes","volume":"6 10","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139455548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hongbo Liu, Rongyuan Xie, Min Li, CaiDong Zhang, Hong-Liang Yao, Zhiqiang Tian, Hai Yang, Zhanlian Liu, Qian Wang, Junyang Kang
Abstract The number density, size and composition of inclusions in U75V heavy rail steel during ladle furnace (LF)–RH refining process were studied by an Aztec-Feature inclusion automatic software which equipped with a field emission microscope. The results showed that the MnO–SiO2–Al2O3-type inclusions were the main inclusions at LF start. The MnO–SiO2–Al2O3-type inclusions were transformed into the CaO–SiO2–Al2O3-type inclusions during the LF refining process because of the Ca and Al elements which were brought by ferroalloy. At the RH start stage, the main inclusions were CaO–SiO2–Al2O3-type inclusions with low melting temperature and CaO–MgO–Al2O3-type inclusions with high melting temperature in the sample. And, the CaO–MgO–Al2O3-type inclusions were obviously removed during RH vacuum treatment. The average compositions of CaO–SiO2–Al2O3-type inclusions had no obvious change from RH vacuum holding for 15 min, RH vacuum break to RH soft blowing.
{"title":"Analysis of the evolution law of oxide inclusions in U75V heavy rail steel during the LF–RH refining process","authors":"Hongbo Liu, Rongyuan Xie, Min Li, CaiDong Zhang, Hong-Liang Yao, Zhiqiang Tian, Hai Yang, Zhanlian Liu, Qian Wang, Junyang Kang","doi":"10.1515/htmp-2022-0257","DOIUrl":"https://doi.org/10.1515/htmp-2022-0257","url":null,"abstract":"Abstract The number density, size and composition of inclusions in U75V heavy rail steel during ladle furnace (LF)–RH refining process were studied by an Aztec-Feature inclusion automatic software which equipped with a field emission microscope. The results showed that the MnO–SiO2–Al2O3-type inclusions were the main inclusions at LF start. The MnO–SiO2–Al2O3-type inclusions were transformed into the CaO–SiO2–Al2O3-type inclusions during the LF refining process because of the Ca and Al elements which were brought by ferroalloy. At the RH start stage, the main inclusions were CaO–SiO2–Al2O3-type inclusions with low melting temperature and CaO–MgO–Al2O3-type inclusions with high melting temperature in the sample. And, the CaO–MgO–Al2O3-type inclusions were obviously removed during RH vacuum treatment. The average compositions of CaO–SiO2–Al2O3-type inclusions had no obvious change from RH vacuum holding for 15 min, RH vacuum break to RH soft blowing.","PeriodicalId":12966,"journal":{"name":"High Temperature Materials and Processes","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44059001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract The difficulty of endpoint determination in basic oxygen furnace (BOF) steelmaking lies in achieving accurate real-time measurements of carbon content and temperature. For the characteristics of serious nonlinearity between process data, deep learning can perform excellent nonlinear feature representation for complex structural data. However, there is a process drift phenomenon in BOF steelmaking, and the existing deep learning-based soft sensor models cannot adapt to changes in the characteristics of samples, which may lead to their performance degradation. To deal with this problem, considering the characteristics of multimode distribution of process data, an adaptive updating deep learning model based on von-Mises Fisher (vMF) mixture model and weighted stacked autoencoder is proposed. First, the stacked autoencoder (SAE) and vMF mixture model are constructed for complex structural data, which can initially establish nonlinear mapping relationships and division of different distributions. Second, for each query sample, the basic SAE network will perform online adaptive fine-tuning according to its data with the same distribution to achieve dynamic updating. Moreover, each sample is assigned a weight according to its similarity with the query sample. Through the designed weighted loss function, the updated deep network will better match the working conditions of the query sample. Experimental studies with numerical examples and actual BOF steelmaking process data are provided to demonstrate the effectiveness of the proposed method.
{"title":"Soft sensor method of multimode BOF steelmaking endpoint carbon content and temperature based on vMF-WSAE dynamic deep learning","authors":"Luan Yang, Hui Liu, Fugang Chen","doi":"10.1515/htmp-2022-0270","DOIUrl":"https://doi.org/10.1515/htmp-2022-0270","url":null,"abstract":"Abstract The difficulty of endpoint determination in basic oxygen furnace (BOF) steelmaking lies in achieving accurate real-time measurements of carbon content and temperature. For the characteristics of serious nonlinearity between process data, deep learning can perform excellent nonlinear feature representation for complex structural data. However, there is a process drift phenomenon in BOF steelmaking, and the existing deep learning-based soft sensor models cannot adapt to changes in the characteristics of samples, which may lead to their performance degradation. To deal with this problem, considering the characteristics of multimode distribution of process data, an adaptive updating deep learning model based on von-Mises Fisher (vMF) mixture model and weighted stacked autoencoder is proposed. First, the stacked autoencoder (SAE) and vMF mixture model are constructed for complex structural data, which can initially establish nonlinear mapping relationships and division of different distributions. Second, for each query sample, the basic SAE network will perform online adaptive fine-tuning according to its data with the same distribution to achieve dynamic updating. Moreover, each sample is assigned a weight according to its similarity with the query sample. Through the designed weighted loss function, the updated deep network will better match the working conditions of the query sample. Experimental studies with numerical examples and actual BOF steelmaking process data are provided to demonstrate the effectiveness of the proposed method.","PeriodicalId":12966,"journal":{"name":"High Temperature Materials and Processes","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49019243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Production data from a vanadium (V)-containing titaniferous magnetite (VTM) smelting blast furnace (BF) ironmaking plant and a V-recovering basic oxygen furnace (BOF) shop were collected over a period of 1 year. The corresponding thermodynamics was analyzed in terms of V reduction in the BF operation and V oxidation in the BOF operation. The thermodynamic calculations were performed using the software Multi-Phase Equilibrium (MPE), in which generalized central atom model was introduced into the description of molten slag and applied for the slag database. The effects of operating conditions on V distribution ratios between slag and hot metal/semi-steel were analyzed and compared with the plant data. The simulated results could reproduce the variation of V distribution ratios with slag temperature and composition and provide the guidance for operators to control V distribution behavior for the better process operation.
{"title":"Thermodynamic analysis of vanadium distribution behavior in blast furnaces and basic oxygen furnaces","authors":"Yang He, Chunlin Chen, Xiaodong Yang","doi":"10.1515/htmp-2022-0259","DOIUrl":"https://doi.org/10.1515/htmp-2022-0259","url":null,"abstract":"Abstract Production data from a vanadium (V)-containing titaniferous magnetite (VTM) smelting blast furnace (BF) ironmaking plant and a V-recovering basic oxygen furnace (BOF) shop were collected over a period of 1 year. The corresponding thermodynamics was analyzed in terms of V reduction in the BF operation and V oxidation in the BOF operation. The thermodynamic calculations were performed using the software Multi-Phase Equilibrium (MPE), in which generalized central atom model was introduced into the description of molten slag and applied for the slag database. The effects of operating conditions on V distribution ratios between slag and hot metal/semi-steel were analyzed and compared with the plant data. The simulated results could reproduce the variation of V distribution ratios with slag temperature and composition and provide the guidance for operators to control V distribution behavior for the better process operation.","PeriodicalId":12966,"journal":{"name":"High Temperature Materials and Processes","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43695877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract The use of aluminum in chassis, bumper, and crash boxes has increased in the last 10 years with an increase in the production of electric vehicles in the automotive industry. The extrusion process has also gained importance because it allows mass production. While basic 6xxx series aluminum alloys such as 6060 and 6063 were used in the early stages of the process, later on, 6005A and 6082 alloys, which provide higher strength, have been used. Alloys with higher strength and crash ability are needed with an increase in safety requirements in automotive. In this study, the effect of chemical composition and heat treatment on the intergranular corrosion strength of 6056 alloys was examined. Another aim of this study is not only to produce high strength and ductility alloy but also to provide good corrosion resistance as automotives are used in different environments for several decades. The 6056 alloys are potential candidate materials for the new-generation electrical vehicles in the automobile industry due to their high strength, weldability, machinability, and impact resistance. Therefore, in our work, we produced 6056 alloy samples in a billet form using the direct chill casting method. Then they were homogenized, and billets were extruded as a box profile. Experimental studies were carried out on 6056 alloys with two different chemical compositions and three different heat treatment conditions (T42, T62, and T76) using Method B of EN ISO 11846 standard for corrosion testing. Crack sizes of metallographic sections from corroded areas were calculated g using a scanning electron microscope. As a result, we found that the addition of Mg to 6056 alloys improves corrosion resistance, while copper reduces it. When Zn is added to the alloys, Mg starts to react with it and forms MgZn2, which increases the corrosion progress. Moreover, when heat treatment is applied at T76 conditions, the alloys demonstrate high corrosion resistance.
摘要在过去10年中，随着汽车行业电动汽车产量的增加，铝在底盘、保险杠和防撞箱中的使用有所增加。挤压工艺也变得越来越重要，因为它允许大规模生产。虽然在工艺的早期阶段使用了基本的6xxx系列铝合金，如6060和6063，但后来使用了提供更高强度的6005A和6082合金。随着汽车安全要求的提高，需要具有更高强度和碰撞能力的合金。本研究考察了化学成分和热处理对6056合金晶间腐蚀强度的影响。这项研究的另一个目的不仅是生产高强度和延展性的合金，而且在汽车在不同环境中使用几十年时提供良好的耐腐蚀性。6056合金由于其高强度、可焊接性、机械加工性和抗冲击性，是汽车行业新一代电动汽车的潜在候选材料。因此，在我们的工作中，我们使用直接冷铸法生产了6056个坯料形式的合金样品。然后将它们均化，并将坯料挤压成箱形型材。采用EN ISO 11846标准的方法B对具有两种不同化学成分和三种不同热处理条件（T42、T62和T76）的6056合金进行了腐蚀试验研究。使用扫描电子显微镜计算腐蚀区域金相切片的裂纹尺寸g。因此，我们发现在6056合金中添加Mg可以提高耐腐蚀性，而铜可以降低耐腐蚀性。当向合金中添加Zn时，Mg开始与之反应并形成MgZn2，从而增加了腐蚀进度。此外，当在T76条件下进行热处理时，合金表现出高的耐腐蚀性。
{"title":"Effect of chemical composition and heat treatment on intergranular corrosion and strength of AlMgSiCu alloys","authors":"O. H. Çelik, O. Yücel","doi":"10.1515/htmp-2022-0284","DOIUrl":"https://doi.org/10.1515/htmp-2022-0284","url":null,"abstract":"Abstract The use of aluminum in chassis, bumper, and crash boxes has increased in the last 10 years with an increase in the production of electric vehicles in the automotive industry. The extrusion process has also gained importance because it allows mass production. While basic 6xxx series aluminum alloys such as 6060 and 6063 were used in the early stages of the process, later on, 6005A and 6082 alloys, which provide higher strength, have been used. Alloys with higher strength and crash ability are needed with an increase in safety requirements in automotive. In this study, the effect of chemical composition and heat treatment on the intergranular corrosion strength of 6056 alloys was examined. Another aim of this study is not only to produce high strength and ductility alloy but also to provide good corrosion resistance as automotives are used in different environments for several decades. The 6056 alloys are potential candidate materials for the new-generation electrical vehicles in the automobile industry due to their high strength, weldability, machinability, and impact resistance. Therefore, in our work, we produced 6056 alloy samples in a billet form using the direct chill casting method. Then they were homogenized, and billets were extruded as a box profile. Experimental studies were carried out on 6056 alloys with two different chemical compositions and three different heat treatment conditions (T42, T62, and T76) using Method B of EN ISO 11846 standard for corrosion testing. Crack sizes of metallographic sections from corroded areas were calculated g using a scanning electron microscope. As a result, we found that the addition of Mg to 6056 alloys improves corrosion resistance, while copper reduces it. When Zn is added to the alloys, Mg starts to react with it and forms MgZn2, which increases the corrosion progress. Moreover, when heat treatment is applied at T76 conditions, the alloys demonstrate high corrosion resistance.","PeriodicalId":12966,"journal":{"name":"High Temperature Materials and Processes","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43288498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract In order to improve the high temperature melting characteristics of bituminous coal with low ash melting point, three kinds of anthracites were used to improve the ash melting characteristics of blended coal to meet the requirement of blast furnace injection. The complete melting temperature of pulverized coal ash had been calculated by using FactSage thermodynamic calculation software. The results showed that after adding different proportions of anthracite with high ash melting point, the deformation temperature, softening temperature, hemispherical temperature, and flow temperature of the blended coal increased. After adding different proportions of Yang Quan anthracite, compared to Bu Lian Ta bituminous coal, the ash melting point of blended coal increased by 98, 136, 149, and 170 K, respectively. The relationship between the ash melting point of pulverized coal and the calculated value of ash complete melting temperature was obtained as: TST = 0.7098TC + 257.98.
{"title":"Improvement and prediction on high temperature melting characteristics of coal ash","authors":"Yifan Chai, Xing Gao, Yanfeng Liang, Junjie Wang, Wen-ting Hu, Yi-ci Wang","doi":"10.1515/htmp-2022-0039","DOIUrl":"https://doi.org/10.1515/htmp-2022-0039","url":null,"abstract":"Abstract In order to improve the high temperature melting characteristics of bituminous coal with low ash melting point, three kinds of anthracites were used to improve the ash melting characteristics of blended coal to meet the requirement of blast furnace injection. The complete melting temperature of pulverized coal ash had been calculated by using FactSage thermodynamic calculation software. The results showed that after adding different proportions of anthracite with high ash melting point, the deformation temperature, softening temperature, hemispherical temperature, and flow temperature of the blended coal increased. After adding different proportions of Yang Quan anthracite, compared to Bu Lian Ta bituminous coal, the ash melting point of blended coal increased by 98, 136, 149, and 170 K, respectively. The relationship between the ash melting point of pulverized coal and the calculated value of ash complete melting temperature was obtained as: TST = 0.7098TC + 257.98.","PeriodicalId":12966,"journal":{"name":"High Temperature Materials and Processes","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43233372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract The accurate control of the endpoint in converter steelmaking is of great significance and value for energy saving, emission reduction, and steel quality improvement. The key to endpoint control lies in accurately predicting the carbon content and temperature. Converter steelmaking is a dynamic process with a large fluctuation of samples, and traditional ensemble learning methods ignore the differences among the query samples and use all the sub-models to predict. The different performances of each sub-model lead to the performance degradation of ensemble learning. To address this issue, we propose a soft sensor method based on multi-cluster dynamic adaptive selection (MC-DAS) ensemble learning for converter steelmaking endpoint carbon content and temperature prediction. First, to ensure the diversity of the ensemble learning base model, we propose a clustering algorithm with different data partition characteristics to construct a pool of diverse base models. Second, a model adaptive selection strategy is proposed, which involves constructing diverse similarity regions for individual query samples and assessing the model’s performance in these regions to identify the most suitable model and weight combination for each respective query sample. Compared with the traditional ensemble learning method, the simulation results of actual converter steelmaking process data show that the prediction accuracy of carbon content within ±0.02% error range reaches 92.8%, and temperature within ±10°C error range reaches 91.6%.
{"title":"Soft sensor method for endpoint carbon content and temperature of BOF based on multi-cluster dynamic adaptive selection ensemble learning","authors":"Bin Shao, Hui Liu, Fu-gang Chen","doi":"10.1515/htmp-2022-0287","DOIUrl":"https://doi.org/10.1515/htmp-2022-0287","url":null,"abstract":"Abstract The accurate control of the endpoint in converter steelmaking is of great significance and value for energy saving, emission reduction, and steel quality improvement. The key to endpoint control lies in accurately predicting the carbon content and temperature. Converter steelmaking is a dynamic process with a large fluctuation of samples, and traditional ensemble learning methods ignore the differences among the query samples and use all the sub-models to predict. The different performances of each sub-model lead to the performance degradation of ensemble learning. To address this issue, we propose a soft sensor method based on multi-cluster dynamic adaptive selection (MC-DAS) ensemble learning for converter steelmaking endpoint carbon content and temperature prediction. First, to ensure the diversity of the ensemble learning base model, we propose a clustering algorithm with different data partition characteristics to construct a pool of diverse base models. Second, a model adaptive selection strategy is proposed, which involves constructing diverse similarity regions for individual query samples and assessing the model’s performance in these regions to identify the most suitable model and weight combination for each respective query sample. Compared with the traditional ensemble learning method, the simulation results of actual converter steelmaking process data show that the prediction accuracy of carbon content within ±0.02% error range reaches 92.8%, and temperature within ±10°C error range reaches 91.6%.","PeriodicalId":12966,"journal":{"name":"High Temperature Materials and Processes","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135442917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract The mayenite Ca 12 Al 14 O 33 material, owing to its oxide ion conducting behavior and the low cost of raw materials, has the potential of being applied in solid oxide fuel cells as an electrolyte. However, suffering from the relatively low oxide ion conductivity, there is still a long way to go for its practical application. To enhance the oxide ion conduction in Ca 12 Al 14 O 33 , many efforts have been endowed to this from different research groups but hardly succeeded. In this work, the Ca 12 Al 14 O 33 -based materials with Y, In, and Cu-doping on the Ca or Al sites were fabricated through a traditional solid-state reaction method (for Y-doping on Ca and Cu-doping on Al) or a glass-crystallization method (for In-doping on Al), with their electrical conductivities being studied. The results revealed that the solid solution regions of Ca 12− x Y x Al 14 O 33+ δ , Ca 12 Al 14− x In x O 33 , and Ca 12 Al 14− x Cu x O 33− δ were 0 ≤ x ≤ 0.15, 0 ≤ x ≤ 0.1, and 0 ≤ x ≤ 0.3, respectively. The electrical conductivities of all these doped materials were investigated.
摘要/ Abstract摘要:mayenite ca12al14o33材料由于具有良好的氧化离子导电性能和低廉的原材料成本，在固体氧化物燃料电池中具有作为电解质的应用潜力。然而，由于氧化离子电导率相对较低，其实际应用还有很长的路要走。为了提高ca12al14o33的氧化离子导电性，不同的研究小组做了很多努力，但很少成功。本文通过传统的固相反应法(Y掺杂在Ca上，cu掺杂在Al上)或玻璃结晶法(In掺杂在Al上)制备了在Ca或Al上掺杂Y、In和cu的Ca - 12al - 14o33基材料，并对其电导率进行了研究。结果表明，Ca 12−x Y x Al 14 O 33+ δ、Ca 12 Al 14−x In x O 33和Ca 12 Al 14−x Cu x O 33−δ的固溶体区分别为0≤x≤0.15、0≤x≤0.1和0≤x≤0.3。研究了这些掺杂材料的电导率。
{"title":"Cation-doping effects on the conductivities of the mayenite Ca<sub>12</sub>Al<sub>14</sub>O<sub>33</sub>","authors":"Xingping Song, Yaqiong Guo, Wenzhuo Chen, Keke Hou, Xiaoxu Duan, Jungu Xu","doi":"10.1515/htmp-2022-0295","DOIUrl":"https://doi.org/10.1515/htmp-2022-0295","url":null,"abstract":"Abstract The mayenite Ca 12 Al 14 O 33 material, owing to its oxide ion conducting behavior and the low cost of raw materials, has the potential of being applied in solid oxide fuel cells as an electrolyte. However, suffering from the relatively low oxide ion conductivity, there is still a long way to go for its practical application. To enhance the oxide ion conduction in Ca 12 Al 14 O 33 , many efforts have been endowed to this from different research groups but hardly succeeded. In this work, the Ca 12 Al 14 O 33 -based materials with Y, In, and Cu-doping on the Ca or Al sites were fabricated through a traditional solid-state reaction method (for Y-doping on Ca and Cu-doping on Al) or a glass-crystallization method (for In-doping on Al), with their electrical conductivities being studied. The results revealed that the solid solution regions of Ca 12− x Y x Al 14 O 33+ δ , Ca 12 Al 14− x In x O 33 , and Ca 12 Al 14− x Cu x O 33− δ were 0 ≤ x ≤ 0.15, 0 ≤ x ≤ 0.1, and 0 ≤ x ≤ 0.3, respectively. The electrical conductivities of all these doped materials were investigated.","PeriodicalId":12966,"journal":{"name":"High Temperature Materials and Processes","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135610967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Li Min, Liu Hongbo, Xie Rongyuan, Che Xiaorui, Liu Ying, Xu Hao, Zhang Caidong, Tian Zhiqiang
Abstract The liquidus temperature and temperature drop coefficients of medium manganese steel were systematically studied using Factsage and differential scanning calorimetry (DSC) experiments. The results indicated that the temperature drop coefficients of C, Mn, Cr, Si, and Al were complex, while the coefficients of Mo, V, and Nb were of a constant value. Based on the temperature drop coefficients, the empirical formula for calculating the liquidus temperature of medium manganese steel was established. The liquidus temperature calculated using the empirical formula was 1422.7°C, while that obtained by the DSC experiment was 1422.9°C. By comparison with different calculation formulas, the liquidus temperature obtained from the formula that was constructed in this study was much closer to the experiment one, indicating the high accuracy of the empirical formula in predicting the liquidus temperature of medium manganese steel.
{"title":"Investigation of the liquidus temperature calculation method for medium manganese steel","authors":"Li Min, Liu Hongbo, Xie Rongyuan, Che Xiaorui, Liu Ying, Xu Hao, Zhang Caidong, Tian Zhiqiang","doi":"10.1515/htmp-2022-0285","DOIUrl":"https://doi.org/10.1515/htmp-2022-0285","url":null,"abstract":"Abstract The liquidus temperature and temperature drop coefficients of medium manganese steel were systematically studied using Factsage and differential scanning calorimetry (DSC) experiments. The results indicated that the temperature drop coefficients of C, Mn, Cr, Si, and Al were complex, while the coefficients of Mo, V, and Nb were of a constant value. Based on the temperature drop coefficients, the empirical formula for calculating the liquidus temperature of medium manganese steel was established. The liquidus temperature calculated using the empirical formula was 1422.7°C, while that obtained by the DSC experiment was 1422.9°C. By comparison with different calculation formulas, the liquidus temperature obtained from the formula that was constructed in this study was much closer to the experiment one, indicating the high accuracy of the empirical formula in predicting the liquidus temperature of medium manganese steel.","PeriodicalId":12966,"journal":{"name":"High Temperature Materials and Processes","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135954983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1615/hightempmatproc.v27.i3.50
A. Shvedov, V. Elinson, P. Shchur
This paper presents the results of studies conducted on coatings based on thin fluorocarbon films obtained by plasma-enhanced chemical vapor deposition using low-frequency plasmatron and low-temperature plasma at atmospheric pressure. The possibility of forming thin fluorocarbon layers by supplying a cyclohexane/carbon tetrafluoride gas mixture to substrates made of polymeric materials (polyethylene terephthalate and polystyrene) has been demonstrated and the main technological modes of deposition process have been established. The absorption spectra of the obtained coatings were studied, the influence of the gas discharge energy contribution on the concentration of fluorocarbon compounds was established, and the band gap was calculated using the Tauc method. The surface relief of the obtained structures was considered using atomic force microscopy and the root-mean-square deviation of the surface roughness was calculated, which reached a maximum of 36 ± 3 nm. Using the Oliver-Pharr method, the nanohardness and Young's modulus of elasticity of the obtained coatings were calculated, which amounted to 0.447 ± 0.025 and 6.10 ± 0.39 GPa, respectively.
{"title":"SURFACE PROPERTIES OF FLUOROCARBON COATINGS PRODUCED BY LOW-FREQUENCY PLASMATRON AT ATMOSPHERIC PRESSURE","authors":"A. Shvedov, V. Elinson, P. Shchur","doi":"10.1615/hightempmatproc.v27.i3.50","DOIUrl":"https://doi.org/10.1615/hightempmatproc.v27.i3.50","url":null,"abstract":"This paper presents the results of studies conducted on coatings based on thin fluorocarbon films obtained by plasma-enhanced chemical vapor deposition using low-frequency plasmatron and low-temperature plasma at atmospheric pressure. The possibility of forming thin fluorocarbon layers by supplying a cyclohexane/carbon tetrafluoride gas mixture to substrates made of polymeric materials (polyethylene terephthalate and polystyrene) has been demonstrated and the main technological modes of deposition process have been established. The absorption spectra of the obtained coatings were studied, the influence of the gas discharge energy contribution on the concentration of fluorocarbon compounds was established, and the band gap was calculated using the Tauc method. The surface relief of the obtained structures was considered using atomic force microscopy and the root-mean-square deviation of the surface roughness was calculated, which reached a maximum of 36 ± 3 nm. Using the Oliver-Pharr method, the nanohardness and Young's modulus of elasticity of the obtained coatings were calculated, which amounted to 0.447 ± 0.025 and 6.10 ± 0.39 GPa, respectively.","PeriodicalId":12966,"journal":{"name":"High Temperature Materials and Processes","volume":"103 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80644058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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