People

SUN Lanxiang
SUN Lanxiang / Research Fellow

Email:sunlanxiang@sia.cn
Research Areas:

Industrial big data analysis and artificial intelligence algorithms,Spectral analysis and sensing technology,Online analytical detection technology and instrument development


Honor and Awards

[1] 2025, First Prize of Liaoning Provincial Science and Technology Award for Technological Invention

[2] 2024, Leading Talent under the "Xingliao Talent Plan"

[3] 2024, Outstanding Young Scientific and Technological Talent of Shenyang in the U40 Category

[4] 2023, Young Scholar of Regional Development of the Chinese Academy of Sciences

[5] 2020, Candidate for the "Hundred-Thousand-Million Talent Project" at the hundred-level in Liaoning Province

[6] 2019, the 12th Liaoning Provincial Youth Science and Technology Award

[7] 2018, Young Top-notch Talent under the "Xingliao Talent Plan"

[8] 2018, Outstanding Member of the Youth Innovation Promotion Association of the Chinese Academy of Sciences

[9] 2016, Liaoning Provincial Natural Science Academic Achievement Award


Publications

[1] Zhang P, Yu T, Sun LX*, Yu HB, Qi LF, Zheng LM. Information fusion of slurry concentration,  particle size and LIBS data for iron grade analysis in mineral processing industry[J]. Minerals Engineering, 2025, 234:1-12.

[2] Lu GH, Sun LX*, Cong ZB, Zhang P, Li Y, Wang JC. Development and sea trial validation of a deep-sea element sensor based on laser-induced breakdown spectroscopy[J]. JOURNAL OF ANALYTICAL ATOMIC SPECTROMETRY, 2025:1-10.

[3] Lu GH, Sun LX*, Cong ZB, Chen T. Study on laser-induced breakdown spectroscopy in high-pressure helium gas environment for deep ocean applications[J]. Talanta, 2024, 270:1-9.

[4] Zhang Q, Sun LX*, Chen T, Qi LF, Zeng P. On-line Measurement of Iron Grade in Iron Ore Slurry by LIBS Technique Combined with Gaussian Process Regression[J]. IEEE Transactions on Instrumentation and Measurement, 2024, 73:1-8.

[5] Chen T, Sun LX*, Yu HB, Qi LF, Zhang P, Dong HY. Application of S-transform-based nonlinear processing for accurate LIBS quantitative analysis of iron ore slurry[J]. Analyst, 2024, 149(17):4407-4417.

[6] Zhou Y, Sun LX*, Li Y, Xin Y, Dong W, Wang JC. Combination of the internal standard and dominant factor PLS for improving long-term stability of LIBS measurements[J]. JOURNAL OF ANALYTICAL ATOMIC SPECTROMETRY, 2024, 39(7):1778–1788.

[7] Zhang P, Sun LX*, Qi LF, Yu HB. On-line quantitative analysis of major elements in phosphate slurry using LIBS assisted by plasma information from orthogonal directions imaging[J]. Measurement: Journal of the International Measurement Confederation, 2024, 234:1-11.

[8] Chen T, Sun LX*, Yu HB, Zeng P, Qi LF. Online Fe grade monitoring of iron ore slurry by Morse wavelet transform and lightweight convolutional neural network based on LIBS[J]. Spectrochimica Acta - Part B Atomic Spectroscopy, 2023, 210:1-12.

[9] Chen T, Sun LX*, Yu HB, Wang W, Qi LF, Zeng P. Deep learning with laser-induced breakdown spectroscopy (LIBS) for the classification of rocks based on elemental imaging[J]. Applied Geochemistry, 2022, 136:1-10.

[10] Wang WJ, Sun LX*, Lu Y, Qi LF, Wang W, Qiao HC. Laser induced breakdown spectroscopy online monitoring of laser cleaning quality on carbon fiber reinforced plastic[J]. Optics and Laser Technology, 2022, 145:1-10.