In this work, we propose a novel analysis lines and comparative lines of the six alloy elements of the tool steel (W, Cr, V, Si, Mn, Mo) within the bandwidth of 280nm~310nm wavelength for carrying out the simultaneous quantitative analysis for the six alloy elements of the tool steel. Steels have fundamentally different in their qualities depending on the types and amounts of elements added. In reality, special steels are produced for the several purposes. The correct and rapid analysis of the amounts of elements required and impurities involved for the steel produced is important for the quality of the product. The most frequently used additives in the metal industry are the six elements mentioned above. However, the method of simultaneous and rapid analysis of the above-mentioned elements is not completed. Here the key point is to choose an analysis line and a comparative line for each element used in the analysis. Especially, tool steel plays an important role in the machining industry. The ultraviolet sensors have been extensively used for the spectrum analysis in the steel industry in recent years. We propose a method that quickly analyses tool steel material by combining the ultraviolet sensor with a computer. We choose an analysis line and a comparative line for Si, Mn and Al, which are auxiliary impurities, and for W, Cr and V, which are main alloy components, and make a test curve. According to our recent work, this is the first paper that deals with the analysis of the tool steel by combination of ultraviolet sensor and computer.
| Published in | Engineering Physics (Volume 8, Issue 1) |
| DOI | 10.11648/j.ep.20250801.14 |
| Page(s) | 41-45 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2025. Published by Science Publishing Group |
Tool Steel, Ultraviolet Array CCD Sensor, Spectrum Analysis
| [1] | Zaide Zhou, Kaizhong Zhou, and Xiandeng Hou, Arc/Spark Optical EmissionSpectrometry: Principles, Instrumentation, and Recent Applications, Applied Spectroscopy Reviews, 2005, 40: 165–185. |
| [2] | H. Fan, et al., Flexible nanoplasmonic sensor for multiplexed and rapid quantitative food safety analysis with a thousand-times sensitivity improvement, Biosens. Bioelectron. 2024, vol. 248, p. 115974. |
| [3] | B. Zhang, R. Wang, and X. Du, Rapid and highly sensitive detection of sepsis inflammatory factors based on a plasmonic terahertz-metasurface biosensor, IEEE Trans. Plasma Sci. 2024, vol. 52, no. 4, pp. 1522−1530. |
| [4] | Z. Zhang, R. Zhao, M. Cong, and J. Qiu, “Developments of terahertz metasurface biosensors: a literature review, Nanotechnol. Rev. 2024, vol. 13, no. 1. |
| [5] | Greenfield, S., Jones, I. L., and Berry, C. T. High-pressure plasma as spectroscopic emission sources. Analyst, 1964, 89(1064): 713–720. |
| [6] | Wendt, R. H. and Fassel, V. A. Induction-coupled plasma spectrometric excitation source. Analytical Chemistry, 1965, 37(7): 920–922. |
| [7] | Aldalur, E., Suárez, A. & Veiga, F. Metal transfer modes for wire arc additive manufacturing Al-Mg alloys: influence of heat input in microstructure and porosity. J. Mater. Process. Technol. 2021, 297, 117271. |
| [8] | Arnab Sarkar, Vijay Karki et al, Evaluation of the prediction precision capability of partial least squares regression approach for analysis of high alloy steel by laser induced breakdown spectroscopy, Spectrochimica Acta Part B 2015, 108, 8–14. |
| [9] | Qingze Guan, Zi Heng Lim et al, Review of Miniaturized Computational Spectrometers. Sensors 2023, 23, 8768. |
| [10] | J. Ando, A. Nakamura, M. Yamamoto, C. H. Song, K. Murata, and R. Iino, Multicolor high-speed tracking of single biomolecules with silver, gold, and silver-gold alloy nanoparticles, ACS Photonics, 2019, vol. 6, pp. 2870–2883. |
| [11] | Yuriko Sato, Takahisa Shobu, Aki Tominaga et al, In-situ X-ray imaging of the breakup dynamics of current-carrying molten metal jets during arc discharge, Communications Materials, 2024, 5: 147. |
| [12] | Guanwei Zhou, Henrik Saxén, Olli Mattila, Yaowei Yu, A Method for Image-Based Interpretation of the Pulverized Coal Cloud in the Blast Furnace Tuyeres, Processes 2024, 12, 529. |
| [13] | Krzysztof Karpierz, Michał Szot et al, Magnetospectroscopy of shallow donors in two dimensions in the presence of fluctuations of the electrostatic potential, Nanophotonics 2024; 13(10): 1873–1882. |
| [14] | Wenbo Mao, Yihang Li, Xuefeng Jiang, Zhiwen Liu, Lan Yang, A whispering-gallery scanning microprobe for Raman spectroscopy and imaging, Science & Applications, 2023, 12: 247. |
| [15] | C. Sun, Z. chen, Y. Ye, Y. Weng, K. lei et al, Integrated microring spectrometer with in-hardware compressed sensing to break the resolutionbandwidth limit for general continuous spectrum analysis. Laser Photon. 2023 Rev. 17, 2300291. |
| [16] | Restaino, L.; Jadoun, D.; Kowalewski, M. Probing nonadiabatic dynamics with attosecond pulse trains and soft x-ray Raman spectroscopy. Struct. Dyn. 2022, 9, 034101. |
| [17] | W.-S Tsai and Y.-C. Lin, High-throughput optical biosensing arrays detection using white light fourier transform method, in 2014 Conference on Lasers and Electro-Optics (CLEO) – Laser Science to Photonic Applications, San Jose, California, United States, 2014. |
| [18] | Bryan, M. R.; Butt, J. N.; Bucukovski, J.; Miller, B. L. Biosensing with Silicon Nitride Microring Resonators Integrated with an On-Chip Filter Bank Spectrometer. ACS Sens. 2023, 8, 739–747. |
| [19] | Said, M.; Wahba, A.; Khalil, D. Semi-Supervised Deep Learning Framework for Milk Analysis Using NIR Spectrometers. Chemom. Intell. Lab. Syst. 2022, 228, 104619. |
| [20] | P. T. Shen, S. H. Huang, Z. Y. Huang, J. J. Wilson, and G. Shvets, Probing the drug dynamics of chemotherapeutics using metasurface-enhanced infrared reflection spectroscopy of live cells, Cells, vol. 11, no. 10, 2022. |
APA Style
Song, S. C., Choe, I. S., Choe, Y. B. (2025). A Spectral Analysis of Tool Steel by a Low-voltage Spark Source and a Line Array Ultraviolet CCD Sensor. Engineering Physics, 8(1), 41-45. https://doi.org/10.11648/j.ep.20250801.14
ACS Style
Song, S. C.; Choe, I. S.; Choe, Y. B. A Spectral Analysis of Tool Steel by a Low-voltage Spark Source and a Line Array Ultraviolet CCD Sensor. Eng. Phys. 2025, 8(1), 41-45. doi: 10.11648/j.ep.20250801.14
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Download@article{10.11648/j.ep.20250801.14,
author = {Sung Chol Song and Il Su Choe and Yun Bom Choe},
title = {A Spectral Analysis of Tool Steel by a Low-voltage Spark Source and a Line Array Ultraviolet CCD Sensor
},
journal = {Engineering Physics},
volume = {8},
number = {1},
pages = {41-45},
doi = {10.11648/j.ep.20250801.14},
url = {https://doi.org/10.11648/j.ep.20250801.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ep.20250801.14},
abstract = {In this work, we propose a novel analysis lines and comparative lines of the six alloy elements of the tool steel (W, Cr, V, Si, Mn, Mo) within the bandwidth of 280nm~310nm wavelength for carrying out the simultaneous quantitative analysis for the six alloy elements of the tool steel. Steels have fundamentally different in their qualities depending on the types and amounts of elements added. In reality, special steels are produced for the several purposes. The correct and rapid analysis of the amounts of elements required and impurities involved for the steel produced is important for the quality of the product. The most frequently used additives in the metal industry are the six elements mentioned above. However, the method of simultaneous and rapid analysis of the above-mentioned elements is not completed. Here the key point is to choose an analysis line and a comparative line for each element used in the analysis. Especially, tool steel plays an important role in the machining industry. The ultraviolet sensors have been extensively used for the spectrum analysis in the steel industry in recent years. We propose a method that quickly analyses tool steel material by combining the ultraviolet sensor with a computer. We choose an analysis line and a comparative line for Si, Mn and Al, which are auxiliary impurities, and for W, Cr and V, which are main alloy components, and make a test curve. According to our recent work, this is the first paper that deals with the analysis of the tool steel by combination of ultraviolet sensor and computer.
},
year = {2025}
}
TY - JOUR T1 - A Spectral Analysis of Tool Steel by a Low-voltage Spark Source and a Line Array Ultraviolet CCD Sensor AU - Sung Chol Song AU - Il Su Choe AU - Yun Bom Choe Y1 - 2025/05/24 PY - 2025 N1 - https://doi.org/10.11648/j.ep.20250801.14 DO - 10.11648/j.ep.20250801.14 T2 - Engineering Physics JF - Engineering Physics JO - Engineering Physics SP - 41 EP - 45 PB - Science Publishing Group SN - 2640-1029 UR - https://doi.org/10.11648/j.ep.20250801.14 AB - In this work, we propose a novel analysis lines and comparative lines of the six alloy elements of the tool steel (W, Cr, V, Si, Mn, Mo) within the bandwidth of 280nm~310nm wavelength for carrying out the simultaneous quantitative analysis for the six alloy elements of the tool steel. Steels have fundamentally different in their qualities depending on the types and amounts of elements added. In reality, special steels are produced for the several purposes. The correct and rapid analysis of the amounts of elements required and impurities involved for the steel produced is important for the quality of the product. The most frequently used additives in the metal industry are the six elements mentioned above. However, the method of simultaneous and rapid analysis of the above-mentioned elements is not completed. Here the key point is to choose an analysis line and a comparative line for each element used in the analysis. Especially, tool steel plays an important role in the machining industry. The ultraviolet sensors have been extensively used for the spectrum analysis in the steel industry in recent years. We propose a method that quickly analyses tool steel material by combining the ultraviolet sensor with a computer. We choose an analysis line and a comparative line for Si, Mn and Al, which are auxiliary impurities, and for W, Cr and V, which are main alloy components, and make a test curve. According to our recent work, this is the first paper that deals with the analysis of the tool steel by combination of ultraviolet sensor and computer. VL - 8 IS - 1 ER -
Department of Physics, University of Sciences, Pyongyang, Democratic People’s Republic of Korea
