Metall. Res. Technol.
Volume 117, Number 4, 2020
|Number of page(s)||5|
|Published online||04 June 2020|
Analysis of Fe and Mn impurities in Chinese sponge titanium enterprise using an input-output model
School of Materials and Metallurgy, West Campus, Guizhou University,
550025, PR China
* e-mail: email@example.com
Accepted: 7 May 2020
The impurity content is an important index reflecting the quality of sponge titanium, especially Fe and Mn impurities. However, at present, only qualitative research has been conducted on the input of impurities, and no quantitative research has been conducted on the input and output of impurities. Therefore, based on the input-output model, this study analyzes the input and output of typical impurities in the magnesiothermic reduction-vacuum distillation process, product sorting process, and magnesium processing process, respectively. Quantitative characterization of the input and output of impurities in sponge titanium production. The results show that the Fe impurity is mainly input by the equipment, and the Mn impurity is mainly input from the raw materials. Determined the chemical reactions of impurities Fe and Mn during reduction, impurities of Fe and Mn exist in the product as the form of simple substance after the reaction.
Key words: sponge titanium / input-output / typical impurities / quantitative characterization
© EDP Sciences, 2020
The contemporary aerospace, high purity electronics, and other fields have put forward higher quality requirements for sponge titanium products, and the quality of sponge titanium output by Kroll process directly affects its application scale in these fields . The impurities content is an important index for measuring the quality of sponge titanium, especially iron and manganese impurities .
In order to reduce the content of impurities in sponge titanium, scholars have sought ways to improve the quality of sponge titanium from different views. Chervonyj et al  studied the possible chemical reactions of impurities in the reduction process from the perspective of thermodynamics. Based on thermodynamics, they analyzed the possible effects of the interaction of alloy elements (Mo, W, Nb, Ta, Zr) and the interaction of Fe, Cr, Mn, and Ni with the TiCl4 and O. Li et al  started from the distillation process, in order to remove chloride to the greatest extent and optimize the process parameters in the distillation process, the chlorine content in sponge titanium is controlled between 0.02 to 0.06 wt.% under the final optimized process parameters. Sheng et al  studied that the inflow process of Fe, Ni, and Cr impurities by the Miedema and Troop models, suggested that the key factors affect the content of these impurities. However, no scholars have yet analyzed the Mn impurity. Other studies only qualitatively analyzed the possible input of impurities, and the input of impurities was only theoretical speculations. There is no sufficient production data to support the input of impurities, and the specific input and output of impurities have not been analyzed. The lack of data leads to insufficient knowledge of the input of impurities, which leads to a lack of theory regarding to the removal of impurities, and there is no clear direction on the measures to remove impurities.
This paper takes the input and output of impurities as the starting point, studies all flows of Fe and Mn impurities input and output. These results provide ideas for controlling the input of impurities. Furthermore, it provides data support for the study of impurities behavior during the production of sponge titanium.
The reduction process is a complex physicochemical process. Almost all Fe and Mn impurities are input during the reduction process and then stored in the product. Therefore, this paper only discusses the flow of impurities Fe and Mn in the reduction and distillation process, sorting process, and magnesium processing process.
The sponge titanium production process includes many related processes with different characteristics. Hence, the material flow of each production process should be studied, respectively. A material flow model of a single production process is illustrated in Figure 1.
Where refers to the raw materials containing j element input in process i, k refers to different kinds of raw materials; Bj refers to the amount of j element input by the equipment; means x kinds of products containing j element are output in process i and will enter the next process as raw materials after being output; means that y kinds of products containing j element are output after i process and will not be used as raw materials for the next process. (1) (2) (3) where is the amount of j element in the raw materials input in process i; is the percentage content of j in the corresponding raw materials; is the amount of j element in the product output in process i and used as the raw material for the next process; is the percentage content of j in the corresponding product; is the amount of j element in the product output in process i; is the percentage content of j in the corresponding product.
The formula for establishing the input-output relationship  of materials in a single process is shown as follows: (4)
Through experiments, typical production data and corresponding physical parameters during the study period are shown in Table 1.
According to the input and output model and combined with the actual production data during the research period, the input and output amount of Fe and Mn impurities element in each process of sponge titanium production are calculated based on the output per ton of high-quality titanium.
The amount and parameters of the corresponding materials during the study.
The amount of Fe input from raw materials is 1.57 × 10−1 kg. The total amount of Fe element output after the reduction and distillation process is 572.47 × 10−3 kg. It can be obtained that the amount of Fe element output is much larger than the amount of Fe element input. According to the principle of input-output balance, it can be seen that the amount of Fe impurity output increased due to the input of Fe impurity in the equipment.
The amount of Fe impurity input by the equipment is calculated to be 415.47 × 10−3 kg, which accounts for 72.57% in the total input of Fe impurity. The main reason for the input of this part of impurities is that the Fe in the equipment dissolved into Mg at high temperature. At the same time, there are a small amount Fe compounds in the equipment could occur corresponding chemical reaction in the reactor, the reaction is shown as follows: (5)
It can be seen from the equation (5) that the Gibbs free energy function of the reaction is less than 0 at a temperature range of 973–1273 K. Therefore, the chemical reaction equation can occur from the perspective of thermodynamics.
The total amount of Fe element output after the magnesium electrolytic process is 13.24 × 10−2 kg. However, the amount of Fe element input in the refining of magnesium process is 0.15 kg. The reason for this phenomenon is that after the magnesium electrolysis is completed, the crude magnesium is transferred to the next process using a Fe vacuum lifter. During this process, the Fe dissolved into liquid magnesium at high temperature, resulting in an increase of Fe impurity content.
The relationship between the solubility of Fe in liquid magnesium and temperature is shown in Table 2. It can be seen that between 973–1273 K, the solubility of Fe in magnesium gradually increases along with increasing temperature. Therefore, it can be considered that during the process of transferring, all the added Fe impurities originate from the dissolution of iron in the Vacuum carry bag.
Based on the above analysis, as the Fe impurity mainly inputs by the equipment, they are finally stored in the product with the form of Fe simple substance. It can be seen that the percentage of dissolution of Fe in Mg is 0.021%, and the percentage of dissolution in MgCl2 is 0.0060%. Therefore, the amount of Fe impurity dissolved in Mg is higher than that dissolved in MgCl2, so the amount of liquid magnesium directly affects the content of impurities in the product. From this perspective, we put forward the following suggestions: under the condition of ensuring the complete reduction reaction, the excess coefficient of Mg is reduced as much as possible.
Input-output details of Fe impurity in the production process.
Relationship between the solubility of Fe in liquid magnesium and temperature.
The 12.25 × 10−2 kg Mn input was contributed by TiCl4 (6.94%), circulating magnesium (42.45%), and outsourced magnesium (50.61%). The total amount of Mn element output after the reduction distillation process is 1963.85 × 10−4 kg. It can be obtained that in the process of reducing distillation, the amount of Mn element output is larger than the amount of Mn element input. According to the principle of input-output balance, it can be explained that the amount of Mn impurity output increased due to the input of Mn impurity in the equipment. The amount of Mn impurity input by raw materials accounts for 62.38% in the total input of Mn impurity.
The main reason for the production of Mn impurity in the product is that the circulating magnesium contains a small amount of Mn impurity. During the initial stage of the reaction, the sponge titanium was dropped to the bottom of the reactor, due to its own adsorption, a certain amount of Mn impurity was adsorbed from liquid magnesium.
The amount of Mn impurity input by the equipment is calculated to be 738.85 × 10−4 kg, which accounts for 37.62% in the total input of Mn impurity. The main reason for the input of this part of impurities is that the Mn in the equipment dissolved into Mg at high temperature. At the same time, there are a small amount Mn compounds in the equipment could occur corresponding chemical reaction in the reactor, the reaction is shown as follows: (6)
It can be seen from the equation (6) that the Gibbs free energy function of the reaction is less than 0 at a temperature range of 973–1273 K, so the chemical reaction equation can occur from the perspective of thermodynamics.
After the magnesium refining process is completed, the amount of Mn element was taken away by circulating magnesium (96.30%), impurity removal (3.33%), and flue gas (0.47%). However, the Mn impurity was not specifically removed in the magnesium refining process, hence, the circulating magnesium still contains more Mn impurity.
It can be seen that the percentage of dissolution of Mn in Mg is 0.010%, and the percentage of dissolution in MgCl2 is 0.0026%. Same as Fe, reducing the excess Mg coefficient as much as possible will reduce the amount of Mn impurity. It can be found that Mn impurity is mainly input from circulating magnesium, and there is almost no removal of Mn impurity during magnesium refining. From the perspective of reducing the content of Mn impurity in circulating magnesium, the removal of Mn impurity in the magnesium refining process can effectively control the content of Mn impurity in the product.
Input-output details of Mn impurity in the production process.
The amount of Fe impurity input by the equipment and raw materials account for 72.57% and 27.43% of the total amount of Fe impurity input, respectively. During the transportation of the crude magnesium, the Fe in the equipment dissolved into liquid magnesium, leading to the increase of Fe impurity content in crude magnesium. The amount of Mn impurity input by the equipment and raw materials account for 62.38% and 37.62% of the total amount of Mn impurity input, respectively. Reducing the excess coefficient of Mg as much as possible can effectively reduce the content of impurities Fe and Mn in the product.
This work was supported by the National Natural Science Foundation of China [grant number 51874108]. It was also partly supported by the talent introduction project of Guizhou University [grant number GDRJHZ2019-14], and the projects of the Science & Technology Department of Guizhou Province [grant numbers QKHJC2019-1406 and QKHPTRC2018-5781(04)]. The authors are grateful to Mr. Qiang Liang and Mr. Lvguo Zhang of Zunyi Titanium Co., Ltd. for their valuable discussions. And all co-authors thank the reviewers for the valuable comments and suggestions.
- W. Wang, F. Wu, Q. Yu, H. Jin, Experimental investigation of titanium tetrachloride in pool boiling heat transfer, Int. J. Heat Mass Transf. 122, 1308 (2018)
- C.R.V.S. Nagesh, C.S. Ramachandran, R.B. Subramanyam, Methods of titanium sponge production, Trans. Indian Inst. Met. 61, 341 (2008)
- W. Wang, F. Wu, Q. Yu, H. Jin, Interfacial liquid-vapor phase change and entropy generation in pool boiling experiment for titanium tetrachloride, J. Therm. Anal. Calor. 133, 1571 (2018)
- W. Wang, F. Wu, H. Jin, Enhancement and performance evaluation for heat transfer of air cooling zone for reduction system of sponge titanium, Heat Mass Transfer. 53, 465 (2017)
- C. Cui, B. Hu, L. Zhao, S. Liu, Titanium alloy production technology, market prospects and industry development, Mater. Des. 32, 1684 (2011)
- C.Z. Yu, M.I. Jones, Investigation of chloride impurities in hydrogenated-dehydrogenated Kroll processed titanium powders, Powder Metall. 56, 304 (2013)
- I.F. Chervonyj, D.O. Listopad, Thermodynamic laws of impurities in the titanium sponge inflow during its production, Acta Mech. Slovaca. 13, 40 (2009)
- L. Li, D. Liu, H. Wan, K. Li, J. Deng, W. Jiang, Removal of chloride impurities from titanium sponge by vacuum distillation, Vaccum 152, 166 (2018)
- Z. Sheng, K. Li, L. Li, X. Cheng, Inflow process of Fe, Ni, and Cr impurities in Ti sponge during kroll process, Metall. Res. Technol. 117, 101 (2020)
- M. Li, J. Zhou, C. Tong, W. Zhang, H. Li, Mathematical model of whole-process calculation for bottom-blowing copper smelting, Metall. Res. Technol. 115, 107 (2018)
- A. Katta, M. Davis, A. Kumar, Development of disaggregated energy use and greenhouse gas emission footprints in Canada’s iron, gold, and potash mining sectors, Resour. Conserv. Recycl. 152 (2020)
Cite this article as: Wei Li, Fuzhong Wu, Huixin Jin, Shuie Li, Analysis of Fe and Mn impurities in Chinese sponge titanium enterprise using an input-output model, Metall. Res. Technol. 117, 401 (2020)
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.