Search2023 Vol. 30, No. 11
Display Method:
2023, vol. 30, no. 11, pp.
2055-2075.
https://doi.org/10.1007/s12613-023-2646-1
Abstract:
With the development of automation and informatization in the steelmaking industry, the human brain gradually fails to cope with an increasing amount of data generated during the steelmaking process. Machine learning technology provides a new method other than production experience and metallurgical principles in dealing with large amounts of data. The application of machine learning in the steelmaking process has become a research hotspot in recent years. This paper provides an overview of the applications of machine learning in the steelmaking process modeling involving hot metal pretreatment, primary steelmaking, secondary refining, and some other aspects. The three most frequently used machine learning algorithms in steelmaking process modeling are the artificial neural network, support vector machine, and case-based reasoning, demonstrating proportions of 56%, 14%, and 10%, respectively. Collected data in the steelmaking plants are frequently faulty. Thus, data processing, especially data cleaning, is crucially important to the performance of machine learning models. The detection of variable importance can be used to optimize the process parameters and guide production. Machine learning is used in hot metal pretreatment modeling mainly for endpoint S content prediction. The predictions of the endpoints of element compositions and the process parameters are widely investigated in primary steelmaking. Machine learning is used in secondary refining modeling mainly for ladle furnaces, Ruhrstahl–Heraeus, vacuum degassing, argon oxygen decarburization, and vacuum oxygen decarburization processes. Further development of machine learning in the steelmaking process modeling can be realized through additional efforts in the construction of the data platform, the industrial transformation of the research achievements to the practical steelmaking process, and the improvement of the universality of the machine learning models.
With the development of automation and informatization in the steelmaking industry, the human brain gradually fails to cope with an increasing amount of data generated during the steelmaking process. Machine learning technology provides a new method other than production experience and metallurgical principles in dealing with large amounts of data. The application of machine learning in the steelmaking process has become a research hotspot in recent years. This paper provides an overview of the applications of machine learning in the steelmaking process modeling involving hot metal pretreatment, primary steelmaking, secondary refining, and some other aspects. The three most frequently used machine learning algorithms in steelmaking process modeling are the artificial neural network, support vector machine, and case-based reasoning, demonstrating proportions of 56%, 14%, and 10%, respectively. Collected data in the steelmaking plants are frequently faulty. Thus, data processing, especially data cleaning, is crucially important to the performance of machine learning models. The detection of variable importance can be used to optimize the process parameters and guide production. Machine learning is used in hot metal pretreatment modeling mainly for endpoint S content prediction. The predictions of the endpoints of element compositions and the process parameters are widely investigated in primary steelmaking. Machine learning is used in secondary refining modeling mainly for ladle furnaces, Ruhrstahl–Heraeus, vacuum degassing, argon oxygen decarburization, and vacuum oxygen decarburization processes. Further development of machine learning in the steelmaking process modeling can be realized through additional efforts in the construction of the data platform, the industrial transformation of the research achievements to the practical steelmaking process, and the improvement of the universality of the machine learning models.
2023, vol. 30, no. 11, pp.
2076-2094.
https://doi.org/10.1007/s12613-023-2637-2
Abstract:
Electric arc furnace dust (EAFD) is a hazardous waste but can also be a potential secondary resource for valuable metals, such as Zn and Fe. Given the increased awareness of carbon emission reduction, energy conservation, and environmental protection, hydrometallurgical technologies for the detoxification and resource use of EAFD have been developing rapidly. This work summarizes the generation mechanisms, compositions, and characteristics of EAFD and presents a critical review of various hydrometallurgical treatment methods for EAFD, e.g., acid leaching, alkaline leaching, salt leaching, and pretreatment–enhanced leaching methods. Simultaneously, the phase transformation mechanisms of zinc-containing components in acid and alkali solutions and pretreatment processes are expounded. Finally, two novel combined methods, i.e., oxygen pressure sulfuric acid leaching combined with composite catalyst preparation, and synergistic roasting of EAFD and municipal solid waste incineration fly ash combined with alkaline leaching, are proposed, which can provide future development directions to completely recycling EAFD by recovering valuable metals and using zinc residue.
Electric arc furnace dust (EAFD) is a hazardous waste but can also be a potential secondary resource for valuable metals, such as Zn and Fe. Given the increased awareness of carbon emission reduction, energy conservation, and environmental protection, hydrometallurgical technologies for the detoxification and resource use of EAFD have been developing rapidly. This work summarizes the generation mechanisms, compositions, and characteristics of EAFD and presents a critical review of various hydrometallurgical treatment methods for EAFD, e.g., acid leaching, alkaline leaching, salt leaching, and pretreatment–enhanced leaching methods. Simultaneously, the phase transformation mechanisms of zinc-containing components in acid and alkali solutions and pretreatment processes are expounded. Finally, two novel combined methods, i.e., oxygen pressure sulfuric acid leaching combined with composite catalyst preparation, and synergistic roasting of EAFD and municipal solid waste incineration fly ash combined with alkaline leaching, are proposed, which can provide future development directions to completely recycling EAFD by recovering valuable metals and using zinc residue.
2023, vol. 30, no. 11, pp.
2095-2111.
https://doi.org/10.1007/s12613-023-2710-x
Abstract:
Solidification structure is a key aspect for understanding the mechanical performance of metal alloys, wherein composition and casting parameters considerably influence solidification and determine the unique microstructure of the alloys. By following the principle of free energy minimization, the phase-field method eliminates the need for tracking the solid/liquid phase interface and has greatly accelerated the research and development efforts geared toward optimizing metal solidification microstructures. The recent progress in the application of phase-field simulation to investigate the effect of alloy composition and casting process parameters on the solidification structure of metals is summarized in this review. The effects of several typical elements and process parameters, including carbon, boron, silicon, cooling rate, pulling speed, scanning speed, anisotropy, and gravity, on the solidification structure are discussed. The present work also addresses the future prospects of phase-field simulation and aims to facilitate the widespread applications of phase-field approaches in the simulation of microstructures during solidification.
Solidification structure is a key aspect for understanding the mechanical performance of metal alloys, wherein composition and casting parameters considerably influence solidification and determine the unique microstructure of the alloys. By following the principle of free energy minimization, the phase-field method eliminates the need for tracking the solid/liquid phase interface and has greatly accelerated the research and development efforts geared toward optimizing metal solidification microstructures. The recent progress in the application of phase-field simulation to investigate the effect of alloy composition and casting process parameters on the solidification structure of metals is summarized in this review. The effects of several typical elements and process parameters, including carbon, boron, silicon, cooling rate, pulling speed, scanning speed, anisotropy, and gravity, on the solidification structure are discussed. The present work also addresses the future prospects of phase-field simulation and aims to facilitate the widespread applications of phase-field approaches in the simulation of microstructures during solidification.
2023, vol. 30, no. 11, pp.
2112-2133.
https://doi.org/10.1007/s12613-023-2675-9
Abstract:
Metal corrosion causes significant economic losses, safety issues, and environmental pollution. Hence, its prevention is of immense research interest. Carbon dots (CDs) are a new class of zero-dimensional carbon nanomaterials, which have been considered for corrosion protection applications in recent years due to their corrosion inhibition effect, fluorescence, low toxicity, facile chemical modification, and cost-effectiveness. This study provides a comprehensive overview of the synthesis, physical and chemical properties, and anticorrosion mechanisms of functionalized CDs. First, the corrosion inhibition performance of different types of CDs is introduced, followed by discussion on their application in the development of smart protective coatings with self-healing and/or self-reporting properties. The effective barrier formed by CDs in the coatings can inhibit the spread of local damage and achieve self-healing behavior. In addition, diverse functional groups on CDs can interact with Fe3+ and H+ ions generated during the corrosion process; this interaction changes their fluorescence, thereby demonstrating self-reporting behavior. Moreover, challenges and prospects for the development of CD-based corrosion protection systems are also presented.
Metal corrosion causes significant economic losses, safety issues, and environmental pollution. Hence, its prevention is of immense research interest. Carbon dots (CDs) are a new class of zero-dimensional carbon nanomaterials, which have been considered for corrosion protection applications in recent years due to their corrosion inhibition effect, fluorescence, low toxicity, facile chemical modification, and cost-effectiveness. This study provides a comprehensive overview of the synthesis, physical and chemical properties, and anticorrosion mechanisms of functionalized CDs. First, the corrosion inhibition performance of different types of CDs is introduced, followed by discussion on their application in the development of smart protective coatings with self-healing and/or self-reporting properties. The effective barrier formed by CDs in the coatings can inhibit the spread of local damage and achieve self-healing behavior. In addition, diverse functional groups on CDs can interact with Fe3+ and H+ ions generated during the corrosion process; this interaction changes their fluorescence, thereby demonstrating self-reporting behavior. Moreover, challenges and prospects for the development of CD-based corrosion protection systems are also presented.
2023, vol. 30, no. 11, pp.
2134-2146.
https://doi.org/10.1007/s12613-023-2668-8
Abstract:
Tensile and shear fractures are significant mechanisms for rock failure. Understanding the fractures that occur in rock can reveal rock failure mechanisms. Scanning electron microscopy (SEM) has been widely used to analyze tensile and shear fractures of rock on a mesoscopic scale. To quantify tensile and shear fractures, this study proposed an innovative method composed of SEM images and deep learning techniques to identify tensile and shear fractures in red sandstone. First, direct tensile and preset angle shear tests were performed for red sandstone to produce representative tensile and shear fracture surfaces, which were then observed by SEM. Second, these obtained SEM images were applied to develop deep learning models (AlexNet, VGG13, and SqueezeNet). Model evaluation showed that VGG13 was the best model, with a testing accuracy of 0.985. Third, the features of tensile and shear fractures of red sandstone learned by VGG13 were analyzed by the integrated gradient algorithm. VGG13 was then implemented to identify the distribution and proportion of tensile and shear fractures on the failure surfaces of rock fragments caused by uniaxial compression and Brazilian splitting tests. Results demonstrated the model feasibility and suggested that the proposed method can reveal rock failure mechanisms.
Tensile and shear fractures are significant mechanisms for rock failure. Understanding the fractures that occur in rock can reveal rock failure mechanisms. Scanning electron microscopy (SEM) has been widely used to analyze tensile and shear fractures of rock on a mesoscopic scale. To quantify tensile and shear fractures, this study proposed an innovative method composed of SEM images and deep learning techniques to identify tensile and shear fractures in red sandstone. First, direct tensile and preset angle shear tests were performed for red sandstone to produce representative tensile and shear fracture surfaces, which were then observed by SEM. Second, these obtained SEM images were applied to develop deep learning models (AlexNet, VGG13, and SqueezeNet). Model evaluation showed that VGG13 was the best model, with a testing accuracy of 0.985. Third, the features of tensile and shear fractures of red sandstone learned by VGG13 were analyzed by the integrated gradient algorithm. VGG13 was then implemented to identify the distribution and proportion of tensile and shear fractures on the failure surfaces of rock fragments caused by uniaxial compression and Brazilian splitting tests. Results demonstrated the model feasibility and suggested that the proposed method can reveal rock failure mechanisms.
2023, vol. 30, no. 11, pp.
2147-2156.
https://doi.org/10.1007/s12613-023-2650-5
Abstract:
Effectively strengthening the surface sulfidation is essential for recovering hemimorphite by froth flotation. In this work, inductively coupled plasma optical emission spectrometer (ICP-OES) measurements, Visual MINTEQ calculation, X-ray photoelectron spectroscopy (XPS) analysis, time of flight secondary ion mass spectrometry (ToF-SIMS) analysis, and micro-flotation experiments were explored to systematically investigate the effect of ammonium sulfate ((NH4)2SO4) on the formation of zinc sulfide species on hemimorphite surface and its role in sulfidation flotation. The results showed that (NH4)2SO4 exhibited a positive influence on hemimorphite sulfidation flotation. It was ascribed to the number of zinc components in the form of Zn2+ and [Zn(NH3)i]2+ (i = 1–4) increased in the flotation system after hemimorphite treatment with (NH4)2SO4, which was beneficial to its interaction with sulfur species in solution, resulting in a dense and stable zinc sulfide layer generated on the hemimorphite surface. [Zn(NH3)i]2+ participated in the sulfidation reaction of hemimorphite as a transition state. In addition, the sulfidation reaction of hemimorphite was accelerated by (NH4)2SO4. Thus, (NH4)2SO4 presents a vital role in promoting the sulfidation of hemimorphite.
Effectively strengthening the surface sulfidation is essential for recovering hemimorphite by froth flotation. In this work, inductively coupled plasma optical emission spectrometer (ICP-OES) measurements, Visual MINTEQ calculation, X-ray photoelectron spectroscopy (XPS) analysis, time of flight secondary ion mass spectrometry (ToF-SIMS) analysis, and micro-flotation experiments were explored to systematically investigate the effect of ammonium sulfate ((NH4)2SO4) on the formation of zinc sulfide species on hemimorphite surface and its role in sulfidation flotation. The results showed that (NH4)2SO4 exhibited a positive influence on hemimorphite sulfidation flotation. It was ascribed to the number of zinc components in the form of Zn2+ and [Zn(NH3)i]2+ (i = 1–4) increased in the flotation system after hemimorphite treatment with (NH4)2SO4, which was beneficial to its interaction with sulfur species in solution, resulting in a dense and stable zinc sulfide layer generated on the hemimorphite surface. [Zn(NH3)i]2+ participated in the sulfidation reaction of hemimorphite as a transition state. In addition, the sulfidation reaction of hemimorphite was accelerated by (NH4)2SO4. Thus, (NH4)2SO4 presents a vital role in promoting the sulfidation of hemimorphite.
2023, vol. 30, no. 11, pp.
2157-2168.
https://doi.org/10.1007/s12613-023-2654-1
Abstract:
Galena (PbS) and chalcopyrite (CuFeS2) are sulfide minerals that exhibit good floatability characteristics. Thus, efficiently separating them via common flotation is challenging. Herein, a new method of surface sulfuric acid corrosion in conjunction with flotation separation was proposed, and the efficient separation of galena and chalcopyrite was successfully realized. Contact angle test results showed a substantial decrease in surface contact angle and a selective inhibition of surface floatability for corroded galena. Meanwhile, the contact angle and floatability of corroded chalcopyrite remained almost unaffected. Scanning electron microscope results confirmed that sulfuric acid corrosion led to the formation of a dense oxide layer on the galena surface, whereas the chalcopyrite surface remained unaltered. X-ray photoelectron spectroscopy results showed that the chemical state of S2− on the surface of corroded galena was oxidized to\begin{document}$ \;{\mathrm{S}\mathrm{O}}_{4}^{2-} $\end{document}
Galena (PbS) and chalcopyrite (CuFeS2) are sulfide minerals that exhibit good floatability characteristics. Thus, efficiently separating them via common flotation is challenging. Herein, a new method of surface sulfuric acid corrosion in conjunction with flotation separation was proposed, and the efficient separation of galena and chalcopyrite was successfully realized. Contact angle test results showed a substantial decrease in surface contact angle and a selective inhibition of surface floatability for corroded galena. Meanwhile, the contact angle and floatability of corroded chalcopyrite remained almost unaffected. Scanning electron microscope results confirmed that sulfuric acid corrosion led to the formation of a dense oxide layer on the galena surface, whereas the chalcopyrite surface remained unaltered. X-ray photoelectron spectroscopy results showed that the chemical state of S2− on the surface of corroded galena was oxidized to
2023, vol. 30, no. 11, pp.
2169-2181.
https://doi.org/10.1007/s12613-023-2643-4
Abstract:
To realize the comprehensive utilization of ludwigite ore, an integrated and efficient route for the boron and iron separation was proposed in this work, which via soda-ash roasting under CO–CO2–N2 atmosphere followed by grind-leaching, magnetic separation, and CO2 carbonation. The effects of roasting temperature, roasting time, CO/(CO+CO2) composition, and Na2CO3 dosage on the boron and iron separation indices were primarily investigated. Under the optimized conditions of the roasting temperature of 850°C, roasting time of 60 min, soda ash dosage of 20wt%, and CO/(CO+CO2) of 10vol%, 92% of boron was leached during wet grinding, and 88.6% of iron was recovered during the magnetic separation and magnetic concentrate with a total iron content of 61.51wt%. Raman spectra and 11B NMR results indicated that boron exists as\begin{document}${\rm{B}}({\rm OH})_{4}^{-}$\end{document}
To realize the comprehensive utilization of ludwigite ore, an integrated and efficient route for the boron and iron separation was proposed in this work, which via soda-ash roasting under CO–CO2–N2 atmosphere followed by grind-leaching, magnetic separation, and CO2 carbonation. The effects of roasting temperature, roasting time, CO/(CO+CO2) composition, and Na2CO3 dosage on the boron and iron separation indices were primarily investigated. Under the optimized conditions of the roasting temperature of 850°C, roasting time of 60 min, soda ash dosage of 20wt%, and CO/(CO+CO2) of 10vol%, 92% of boron was leached during wet grinding, and 88.6% of iron was recovered during the magnetic separation and magnetic concentrate with a total iron content of 61.51wt%. Raman spectra and 11B NMR results indicated that boron exists as
2023, vol. 30, no. 11, pp.
2182-2190.
https://doi.org/10.1007/s12613-023-2657-y
Abstract:
Steelmaking industry faces urgent demands for both steel slag utilization and CO2 abatement. Ca and Mg of steel slag can be extracted by acid solution and used to prepare sorbents for CO2 capture. In this work, the calcium-based sorbents were prepared from stainless steel slag leachate by co-precipitation, and the initial CO2 chemisorption capacity of the calcium-based sorbent prepared from steel slag with the Ca and Mg molar ratio of 3.64:1 was 0.40 g/g. Moreover, the effect of Ca/Mg molar ratio on the morphology, structure, and CO2 chemisorption capacity of the calcium-based sorbents were investigated. The results show that the optimal Ca/Mg molar ratio of sorbent for CO2 capture was 4.2:1, and the skeleton support effect of MgO in calcium-based sorbents was determined. Meanwhile, the chemisorption kinetics of the sorbents was studied using the Avrami-Erofeev model. There were two processes of CO2 chemisorption, and the activation energy of the first stage (reaction control) was found to be lower than that of the second stage (diffusion control).
Steelmaking industry faces urgent demands for both steel slag utilization and CO2 abatement. Ca and Mg of steel slag can be extracted by acid solution and used to prepare sorbents for CO2 capture. In this work, the calcium-based sorbents were prepared from stainless steel slag leachate by co-precipitation, and the initial CO2 chemisorption capacity of the calcium-based sorbent prepared from steel slag with the Ca and Mg molar ratio of 3.64:1 was 0.40 g/g. Moreover, the effect of Ca/Mg molar ratio on the morphology, structure, and CO2 chemisorption capacity of the calcium-based sorbents were investigated. The results show that the optimal Ca/Mg molar ratio of sorbent for CO2 capture was 4.2:1, and the skeleton support effect of MgO in calcium-based sorbents was determined. Meanwhile, the chemisorption kinetics of the sorbents was studied using the Avrami-Erofeev model. There were two processes of CO2 chemisorption, and the activation energy of the first stage (reaction control) was found to be lower than that of the second stage (diffusion control).
2023, vol. 30, no. 11, pp.
2191-2199.
https://doi.org/10.1007/s12613-023-2660-3
Abstract:
Waste heat recovery from hot steel slag was determined in a granular bed through the combination of numerical simulation and an industrial test method. First, the effective thermal conductivity of the granular bed was calculated. Then, the unsteady-state model was used to simulate the heat recovery under three different flow fields (O-type, S-type, and nonshielding type (Nontype)). Second, the simulation results were validated by in-situ industrial experiments. The two methods confirmed that the heat recovery efficiencies of the flow fields from high to low followed the order of Nontype, S-type, and O-type. Finally, heat recovery was carried out under the Nontype flow field in an industrial test. The heat recovery efficiency increased from ~76% and ~78% to ~81% when the steel slag thickness decreased from 400 and 300 to 200 mm, corresponding to reductions in the steel slag mass from 3.96 and 2.97 to 1.98 t with a blower air volume of 14687 m3/h. Therefore, the research results showed that numerical simulation can not only guide experiments on waste heat recovery but also optimize the flow field. Most importantly, the method proposed in this paper has achieved higher waste heat recovery from hot steel slag in industrial scale.
Waste heat recovery from hot steel slag was determined in a granular bed through the combination of numerical simulation and an industrial test method. First, the effective thermal conductivity of the granular bed was calculated. Then, the unsteady-state model was used to simulate the heat recovery under three different flow fields (O-type, S-type, and nonshielding type (Nontype)). Second, the simulation results were validated by in-situ industrial experiments. The two methods confirmed that the heat recovery efficiencies of the flow fields from high to low followed the order of Nontype, S-type, and O-type. Finally, heat recovery was carried out under the Nontype flow field in an industrial test. The heat recovery efficiency increased from ~76% and ~78% to ~81% when the steel slag thickness decreased from 400 and 300 to 200 mm, corresponding to reductions in the steel slag mass from 3.96 and 2.97 to 1.98 t with a blower air volume of 14687 m3/h. Therefore, the research results showed that numerical simulation can not only guide experiments on waste heat recovery but also optimize the flow field. Most importantly, the method proposed in this paper has achieved higher waste heat recovery from hot steel slag in industrial scale.
2023, vol. 30, no. 11, pp.
2200-2211.
https://doi.org/10.1007/s12613-023-2645-2
Abstract:
Solution and quenching heat treatments are generally carried out in a roller hearth furnace for large-scale thick aluminum alloy plates. However, the asymmetric or uneven spray water flow rate is inevitable under industrial production conditions, which leads to an asymmetric residual stress distribution. The spray quenching treatment was conducted on self-designed spray equipment, and the residual stress along the thickness direction was measured by a layer removal method based on deflections. Under the asymmetric spray quenching condition, the subsurface stress of the high-flow rate surface was lower than that of the low-flow rate surface, and the difference between the two subsurface stresses increased with the increase in the difference in water flow rates. The subsurface stress underneath the surface with a water flow rate of 0.60 m3/h was 15.38 MPa less than that of 0.15 m3/h. The simulated residual stress by finite element (FE) method of the high heat transfer coefficient (HTC) surface was less than that of the low HTC surface, which is consistent with the experimental results. The FE model can be used to analyze the strain and stress evolution and predict the quenched stress magnitude and distribution.
Solution and quenching heat treatments are generally carried out in a roller hearth furnace for large-scale thick aluminum alloy plates. However, the asymmetric or uneven spray water flow rate is inevitable under industrial production conditions, which leads to an asymmetric residual stress distribution. The spray quenching treatment was conducted on self-designed spray equipment, and the residual stress along the thickness direction was measured by a layer removal method based on deflections. Under the asymmetric spray quenching condition, the subsurface stress of the high-flow rate surface was lower than that of the low-flow rate surface, and the difference between the two subsurface stresses increased with the increase in the difference in water flow rates. The subsurface stress underneath the surface with a water flow rate of 0.60 m3/h was 15.38 MPa less than that of 0.15 m3/h. The simulated residual stress by finite element (FE) method of the high heat transfer coefficient (HTC) surface was less than that of the low HTC surface, which is consistent with the experimental results. The FE model can be used to analyze the strain and stress evolution and predict the quenched stress magnitude and distribution.
2023, vol. 30, no. 11, pp.
2212-2223.
https://doi.org/10.1007/s12613-023-2652-3
Abstract:
The tensile properties of 2297-T87 Al–Li alloy thick plates at different thickness position and in different direction were analyzed via tensile testing, optical microscopy (OM), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectrometry (EDS), and transmission electron microscopy (TEM). Results indicated that the ultimate tensile strength (UTS) and yield strength (YS) of the alloy decreased firstly and then increased from the 1/8T position to the 1/2T position, whereas elongation to failure (Ef) decreased gradually such that its value along the rolling direction (RD) was higher than those along the transverse direction (TD) at the same thickness position. From the 1/8T position to the 3/8T position of the alloy, the UTS and YS along the TD were higher than those along the RD. At the 1/2T position of the alloy, the UTS, YS, and Ef along the RD were the highest, whereas those along the normal direction (ND) were the lowest. Microstructural observations further revealed that the anisotropy of tensile properties was related to grain morphology, crystal texture, second-phase particles, and Li atom segregation.
The tensile properties of 2297-T87 Al–Li alloy thick plates at different thickness position and in different direction were analyzed via tensile testing, optical microscopy (OM), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectrometry (EDS), and transmission electron microscopy (TEM). Results indicated that the ultimate tensile strength (UTS) and yield strength (YS) of the alloy decreased firstly and then increased from the 1/8T position to the 1/2T position, whereas elongation to failure (Ef) decreased gradually such that its value along the rolling direction (RD) was higher than those along the transverse direction (TD) at the same thickness position. From the 1/8T position to the 3/8T position of the alloy, the UTS and YS along the TD were higher than those along the RD. At the 1/2T position of the alloy, the UTS, YS, and Ef along the RD were the highest, whereas those along the normal direction (ND) were the lowest. Microstructural observations further revealed that the anisotropy of tensile properties was related to grain morphology, crystal texture, second-phase particles, and Li atom segregation.
2023, vol. 30, no. 11, pp.
2224-2235.
https://doi.org/10.1007/s12613-023-2664-z
Abstract:
The anisotropy of the structure and properties caused by the strong epitaxial growth of grains during laser powder bed fusion (L-PBF) significantly affects the mechanical performance of Inconel 718 alloy components such as turbine disks. The defects (lack-of-fusion, LoF) in components processed via L-PBF are detrimental to the strength of the alloy. The purpose of this study is to investigate the effect of laser scanning parameters on the epitaxial grain growth and LoF formation in order to obtain the parameter space in which the microstructure is refined and LoF defect is suppressed. The temperature field of the molten pool and the epitaxial grain growth are simulated using a multiscale model combining the finite element method with the phase-field method. The LoF model is proposed to predict the formation of LoF defects resulting from insufficient melting during L-PBF. Defect mitigation and grain-structure control during L-PBF can be realized simultaneously in the model. The simulation shows the input laser energy density for the as-deposited structure with fine grains and without LoF defects varied from 55.0–62.5 J·mm–3 when the interlayer rotation angle was 0°–90°. The optimized process parameters (laser power of 280 W, scanning speed of 1160 mm·s–1, and rotation angle of 67°) were computationally screened. In these conditions, the average grain size was 7.0 μm, and the ultimate tensile strength and yield strength at room temperature were (1111 ± 3) MPa and (820 ± 7) MPa, respectively, which is 8.8% and 10.5% higher than those of reported. The results indicating the proposed multiscale computational approach for predicting grain growth and LoF defects could allow simultaneous grain-structure control and defect mitigation during L-PBF.
The anisotropy of the structure and properties caused by the strong epitaxial growth of grains during laser powder bed fusion (L-PBF) significantly affects the mechanical performance of Inconel 718 alloy components such as turbine disks. The defects (lack-of-fusion, LoF) in components processed via L-PBF are detrimental to the strength of the alloy. The purpose of this study is to investigate the effect of laser scanning parameters on the epitaxial grain growth and LoF formation in order to obtain the parameter space in which the microstructure is refined and LoF defect is suppressed. The temperature field of the molten pool and the epitaxial grain growth are simulated using a multiscale model combining the finite element method with the phase-field method. The LoF model is proposed to predict the formation of LoF defects resulting from insufficient melting during L-PBF. Defect mitigation and grain-structure control during L-PBF can be realized simultaneously in the model. The simulation shows the input laser energy density for the as-deposited structure with fine grains and without LoF defects varied from 55.0–62.5 J·mm–3 when the interlayer rotation angle was 0°–90°. The optimized process parameters (laser power of 280 W, scanning speed of 1160 mm·s–1, and rotation angle of 67°) were computationally screened. In these conditions, the average grain size was 7.0 μm, and the ultimate tensile strength and yield strength at room temperature were (1111 ± 3) MPa and (820 ± 7) MPa, respectively, which is 8.8% and 10.5% higher than those of reported. The results indicating the proposed multiscale computational approach for predicting grain growth and LoF defects could allow simultaneous grain-structure control and defect mitigation during L-PBF.
2023, vol. 30, no. 11, pp.
2236-2244.
https://doi.org/10.1007/s12613-023-2638-1
Abstract:
Porous magnesium strontium phosphate (Sr3−xMgx(PO4)2) (x = 2, 2.5, 3) composite scaffolds were successfully prepared by three dimension gel-printing (3DGP) method in this study. The results show that Sr0.5Mg2.5(PO4)2 scaffolds had good compressive strength, and Sr1.0Mg2.0(PO4)2 scaffolds had good degradation rate in vitro. The weight loss rate of Sr1.0Mg2.0(PO4)2 scaffolds soaked in simulated body fluid (SBF) or 6 weeks was 6.96%, and pH value varied between 7.50 and 8.61, which was within the acceptable range of human body. Preliminary biological experiment shows that MC3T3-E1 cells had good adhesion and proliferation on the surface of Sr3−xMgx(PO4)2 scaffolds. Compared with pure Mg3(PO4)2 scaffolds, strontium doped scaffolds had excellent comprehensive properties, which explain that Sr3−xMgx(PO4)2 composite scaffolds can be used for bone tissue engineering.
Porous magnesium strontium phosphate (Sr3−xMgx(PO4)2) (x = 2, 2.5, 3) composite scaffolds were successfully prepared by three dimension gel-printing (3DGP) method in this study. The results show that Sr0.5Mg2.5(PO4)2 scaffolds had good compressive strength, and Sr1.0Mg2.0(PO4)2 scaffolds had good degradation rate in vitro. The weight loss rate of Sr1.0Mg2.0(PO4)2 scaffolds soaked in simulated body fluid (SBF) or 6 weeks was 6.96%, and pH value varied between 7.50 and 8.61, which was within the acceptable range of human body. Preliminary biological experiment shows that MC3T3-E1 cells had good adhesion and proliferation on the surface of Sr3−xMgx(PO4)2 scaffolds. Compared with pure Mg3(PO4)2 scaffolds, strontium doped scaffolds had excellent comprehensive properties, which explain that Sr3−xMgx(PO4)2 composite scaffolds can be used for bone tissue engineering.
2023, vol. 30, no. 11, pp.
2245-2258.
https://doi.org/10.1007/s12613-023-2662-1
Abstract:
The high temperature compression test of Be/2024Al composites with 62wt% Be was conducted at 500–575ºC and strain rate of 0.003–0.1 s–1. The strain-compensated Arrhenius model and modified Johnson–Cook model were introduced to predict the hot deformation behavior of Be/2024Al composites. The result shows that the activation energy of Be/2024Al composites was 363.364 kJ·mol–1. Compared with composites reinforced with traditional ceramics, Be/2024Al composites can be deformed with ultra-high content of reinforcement, attributing to the deformable property of Be particles. The average relative error of the two models shows that modified Johnson–Cook model was more suitable for low temperature condition while strain-compensated Arrhenius model was more suitable for high temperature condition. The processing map was generated and a hot extrusion experiment was conducted according to the map. A comparation of the microstructure of Be/2024Al composites before and after extrusion shows that the Be particle deformed coordinately with the matrix and elongated at the extrusion direction.
The high temperature compression test of Be/2024Al composites with 62wt% Be was conducted at 500–575ºC and strain rate of 0.003–0.1 s–1. The strain-compensated Arrhenius model and modified Johnson–Cook model were introduced to predict the hot deformation behavior of Be/2024Al composites. The result shows that the activation energy of Be/2024Al composites was 363.364 kJ·mol–1. Compared with composites reinforced with traditional ceramics, Be/2024Al composites can be deformed with ultra-high content of reinforcement, attributing to the deformable property of Be particles. The average relative error of the two models shows that modified Johnson–Cook model was more suitable for low temperature condition while strain-compensated Arrhenius model was more suitable for high temperature condition. The processing map was generated and a hot extrusion experiment was conducted according to the map. A comparation of the microstructure of Be/2024Al composites before and after extrusion shows that the Be particle deformed coordinately with the matrix and elongated at the extrusion direction.
2023, vol. 30, no. 11, pp.
2259-2269.
https://doi.org/10.1007/s12613-023-2648-z
Abstract:
Anion exchange membrane (AEM) electrolysis is a promising membrane-based green hydrogen production technology. However, AEM electrolysis still remains in its infancy, and the performance of AEM electrolyzers is far behind that of well-developed alkaline and proton exchange membrane electrolyzers. Therefore, breaking through the technical barriers of AEM electrolyzers is critical. On the basis of the analysis of the electrochemical performance tested in a single cell, electrochemical impedance spectroscopy, and the number of active sites, we evaluated the main technical factors that affect AEM electrolyzers. These factors included catalyst layer manufacturing (e.g., catalyst, carbon black, and anionic ionomer) loadings, membrane electrode assembly, and testing conditions (e.g., the KOH concentration in the electrolyte, electrolyte feeding mode, and operating temperature). The underlying mechanisms of the effects of these factors on AEM electrolyzer performance were also revealed. The irreversible voltage loss in the AEM electrolyzer was concluded to be mainly associated with the kinetics of the electrode reaction and the transport of electrons, ions, and gas-phase products involved in electrolysis. Based on the study results, the performance and stability of AEM electrolyzers were significantly improved.
Anion exchange membrane (AEM) electrolysis is a promising membrane-based green hydrogen production technology. However, AEM electrolysis still remains in its infancy, and the performance of AEM electrolyzers is far behind that of well-developed alkaline and proton exchange membrane electrolyzers. Therefore, breaking through the technical barriers of AEM electrolyzers is critical. On the basis of the analysis of the electrochemical performance tested in a single cell, electrochemical impedance spectroscopy, and the number of active sites, we evaluated the main technical factors that affect AEM electrolyzers. These factors included catalyst layer manufacturing (e.g., catalyst, carbon black, and anionic ionomer) loadings, membrane electrode assembly, and testing conditions (e.g., the KOH concentration in the electrolyte, electrolyte feeding mode, and operating temperature). The underlying mechanisms of the effects of these factors on AEM electrolyzer performance were also revealed. The irreversible voltage loss in the AEM electrolyzer was concluded to be mainly associated with the kinetics of the electrode reaction and the transport of electrons, ions, and gas-phase products involved in electrolysis. Based on the study results, the performance and stability of AEM electrolyzers were significantly improved.
2023, vol. 30, no. 11, pp.
2270-2279.
https://doi.org/10.1007/s12613-023-2669-7
Abstract:
The catalytic effect of FeCoNiCrMo high entropy alloy nanosheets on the hydrogen storage performance of magnesium hydride (MgH2) was investigated for the first time in this paper. Experimental results demonstrated that 9wt% FeCoNiCrMo doped MgH2 started to dehydrogenate at 200°C and discharged up to 5.89wt% hydrogen within 60 min at 325°C. The fully dehydrogenated composite could absorb 3.23wt% hydrogen in 50 min at a temperature as low as 100°C. The calculated de/hydrogenation activation energy values decreased by 44.21%/55.22% compared with MgH2, respectively. Moreover, the composite’s hydrogen capacity dropped only 0.28wt% after 20 cycles, demonstrating remarkable cycling stability. The microstructure analysis verified that the five elements, Fe, Co, Ni, Cr, and Mo, remained stable in the form of high entropy alloy during the cycling process, and synergistically serving as a catalytic union to boost the de/hydrogenation reactions of MgH2. Besides, the FeCoNiCrMo nanosheets had close contact with MgH2, providing numerous non-homogeneous activation sites and diffusion channels for the rapid transfer of hydrogen, thus obtaining a superior catalytic effect.
The catalytic effect of FeCoNiCrMo high entropy alloy nanosheets on the hydrogen storage performance of magnesium hydride (MgH2) was investigated for the first time in this paper. Experimental results demonstrated that 9wt% FeCoNiCrMo doped MgH2 started to dehydrogenate at 200°C and discharged up to 5.89wt% hydrogen within 60 min at 325°C. The fully dehydrogenated composite could absorb 3.23wt% hydrogen in 50 min at a temperature as low as 100°C. The calculated de/hydrogenation activation energy values decreased by 44.21%/55.22% compared with MgH2, respectively. Moreover, the composite’s hydrogen capacity dropped only 0.28wt% after 20 cycles, demonstrating remarkable cycling stability. The microstructure analysis verified that the five elements, Fe, Co, Ni, Cr, and Mo, remained stable in the form of high entropy alloy during the cycling process, and synergistically serving as a catalytic union to boost the de/hydrogenation reactions of MgH2. Besides, the FeCoNiCrMo nanosheets had close contact with MgH2, providing numerous non-homogeneous activation sites and diffusion channels for the rapid transfer of hydrogen, thus obtaining a superior catalytic effect.
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