Mingjie Tang

Ms. Mingjie Tang


Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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28 January 2019 in Sensors
Verified
Journal Article
Open access
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Mingkun ZhangMingkun Zhang
Mingkun Zhang
YZYang Zhongbo
Yang Zhongbo
MTMingjie Tang
Mingjie Tang
DWDeqiang Wang
Deqiang Wang
HWHuabin Wang
Huabin Wang
HCHong-Liang Cui
Hong-Liang Cui
Terahertz signature detection of biological samples in aqueous solution remains a great challenge due to the strong terahertz absorption of water. Here we propose a new preparation process for fabricating a microfluidic chip and use it as an effective sensor to probe the terahertz absorption signatures of microcystin aptamer (a linear single-stranded DNA with 60 nucleotides) dissolved in TE buffer with different concentrations. The microfluidic chip made of silicon includes thousands of 2.4 μm × 2.4 μm square-cross-section channels. One repeatable terahertz absorption signature is detected and recognized around 830 GHz, fitted to a Lorentz oscillator. This signature is theorized to originate from the bending of hydrogen bonds formed between adjacent hydrated DNA bases surrounded by water molecules. Furthermore, the low-lying vibrational modes are also investigated by molecular dynamics simulations which suggest that strong resonant oscillations are highly probable in the 815–830 GHz frequency band.

1 September 2017 in Applied Sciences
Verified
Journal Article
Open access
PDF file
MTMingjie Tang
Mingjie Tang
LXLiangping Xia
Liangping Xia
Dongshan WeiDongshan Wei
Dongshan Wei
SYShihan Yan
Shihan Yan
CDChunlei Du
Chunlei Du
HCHong-Liang Cui
Hong-Liang Cui
An approach to distinguish eight kinds of different human cells by Raman spectroscopy was proposed and demonstrated in this paper. Original spectra of suspension cells in the frequency range of 623~1783 cm−1 were acquired and pre-processed by baseline calibration, and principal component analysis (PCA) was employed to extract the useful spectral information. To develop a robust discrimination model, a linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were attempted comparatively in the work. The results showed that the QDA model is better than the LDA model. The optimal QDA model was generated with 12 principal components. The classification rates are 100% in the calibration and prediction set, respectively. From the experimental results, it is concluded that Raman spectroscopy combined with appropriate discriminant analysis methods has significant potential in human cell detection.