HYHaocheng Yin

Haocheng Yin

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Haocheng Yin has a total of 37 co-authors. Here are the top co-authors by number of shared publications:

  • Jingkai Guo

    School of Microelectronics, Key Laboratory of Wide Band-Gap Semiconductor Materials and Devices, Xidian University, Xi'an 710071, China

    2 shared publications
  • Lejia Sun

    School of Microelectronics, Key Laboratory of Wide Band-Gap Semiconductor Materials and Devices, Xidian University, Xi'an 710071, China

    2 shared publications
  • Yuming Zhang

    School of Microelectronics, Key Laboratory of Wide Band Gap Semiconductor Materials and Devices, Xidian University, Xi'an 710071, China

    2 shared publications
  • Zeyu Zhang

    School of Microelectronics, Key Laboratory of Wide Band Gap Semiconductor Materials and Devices, Xidian University, Xi'an 710071, China

    2 shared publications
  • Baosen Tan

    Air Force Medical Center, Air Force Medical University

    1 shared publication
  • Chao Tan

    Institute for Micromanufacturing, Louisiana Tech University, Ruston, LA 71272, USA

    1 shared publication

Latest Publications

  • Open Access

    Development and validation of an AI-driven blood glucose prediction system for pilots based on continuous glucose monitoring

    by Dalong Guo, Guangyun Wang, Dexin Kong, Zhen Tian, Baosen Tan, Yufei Qin, Zhaoting Yang, Yubin Zhou, Haocheng Yin, Yimeng Zhang

    During flight, pilots are exposed to unique environmental factors such as low air pressure, acceleration, and psychological stress, which can lead to altered glucose metabolism that poses a threat to flight safety. Traditional fingerstick blood glucose monitoring has drawbacks such as the need for intermittent readings, time-consuming procedures, and passive monitoring. Conventional continuous glucose monitoring (CGM) can only display historical and real-time glucose data and lacks predictive capabilities. In the present study, an artificial intelligence (AI)-driven blood glucose prediction system for pilots based on CGM and a multimodal transformer was developed with the aim of achieving proactive early warning of blood glucose risks among pilots. Sixty healthy male volunteers aged 25–50 years were recruited. Subjects completed 180 simulated flight experiments, during which multimodal data such as CGM glucose level, heart rate, blood oxygen saturation, and physical activity levels, were simultaneously collected to establish a scenario-specific dataset in aviation. A multimodal transformer model was developed to predict future blood glucose levels at 15, 30, and 60 min, and its performance was compared with baseline models such as linear extrapolation, long short-term memory (LSTM), and gated recurrent unit (GRU).The results showed that the mean absolute percentage error (MAPE) of the model for the prediction of blood glucose at 30 min was 7.2%, and the root mean square error (RMSE) was 9.4 mg/dL, which indicated a significantly superior prediction performance compared with the baseline models. For hypoglycemia event prediction, sensitivity was 92.5%, specificity was 89.7%, and the area under the receiver operating characteristic (ROC) curve was 0.94. A Clarke error grid analysis revealed that 98.7% of the predicted points fell within the clinically accurate region, which could potentially provide pilots with approximately 32 min of lead time for intervention. This system proved capable of accurately predicting blood glucose fluctuations during flight. Therefore, it may aid in shifting the metabolic health management of pilots from passive monitoring to proactive prevention, and serve as a novel tool for assuring aviation medical safety.

  • AI-optimized pulsed electric field for low-carbon urban water disinfection

    by Haocheng Yin, Lejia Sun, Wenjing Xue, Ziyan Chen, Zeyu Zhang, Liuya Peng, Hejia Sun, Weijia Sun, Xiaowu Gong, Yuming Zhang

  • Open Access

    Construction of Highly Active Interfaces on Screen-Printed Carbon Electrodes via Controllable Electrochemical Exfoliation for High-Performance Flexible Enzyme-Free Glucose Sensing

    by Wenjing Xue, Ziyan Chen, Xiao Peng, Haocheng Yin, Yimeng Zhang, Yuming Zhang

    Enzyme-free flexible glucose sensors hold great promise in the field of wearable health monitoring. However, their performance is limited by the balance between the catalytic interface activity and stability. This paper reports a strategy for interface gradient roughening of screen-printed carbon electrodes (SPCE) via controllable electrochemical exfoliation (EE). It systematically reveals the inherent relationships among the degree of EE treatment, electrode morphology, surface chemistry, and electrochemical performance. On this basis, the deposition of gold nanoparticles (AuNPs) with high density and uniform distribution is achieved, and a high-performance flexible enzyme-free glucose sensor is constructed. The study finds that EE treatment can significantly increase the true surface area of the electrode and introduce abundant oxygen-containing functional groups, thus effectively reducing the charge transfer resistance. Nevertheless, excessive exfoliation leads to the degradation of the conductive network, indicating the existence of a critical “performance window”. The EE-SPCE optimized with 150 cycles has both a high active area and good electrical conductivity, providing an ideal deposition substrate for AuNPs, increasing their distribution density by approximately 158% and reducing the average particle size to 125 nm. The fabricated AuNPs/EE-SPCE sensor exhibits excellent performance in glucose detection: it has a high sensitivity of 550.766 μA·mM−1·cm−2 in the range of 0.1–3 mM, a detection limit of 0.0998 mM, a wide linear range, excellent selectivity, long-term stability, and good mechanical flexibility. This research not only develops an efficient and scalable method for constructing flexible sensing interfaces but also clarifies the trade-off relationship among “roughening–conductivity–catalytic performance” at the mechanistic level, providing an important theoretical basis and a general strategy for rationally designing high-performance flexible electrochemical devices.


  • Open Access

    A SiC Photo-Conductive Switch-Based Pulse Generator with Nanoseconds and High Voltage for Liver Cancer Cells Ablation Therapy

    by Haocheng Yin, Zeyu Zhang, Yapeng Liu, Yutian Wang, Hui Guo, Yuming Zhang

    Electroporation ablation, as an innovative cancer treatment, not only preserves the structure and function of affected organs but also significantly reduces surgical risks, offers patients a safer and more effective therapeutic option, and demonstrates immense potential in the field of oncology. This paper presents the innovative design of a high-voltage nanosecond pulse generator triggered by a silicon carbide (SiC) photoconductive switch. The generator is capable of stably outputting adjustable voltages ranging from 10 kV to 15 kV, with pulse widths precisely controlled between 10 and 15 nanoseconds, and an operating frequency adjustable from 1 Hz to 10 Hz. This device enables instant activation and deactivation of the pulse generator during ablation, enhancing the efficiency of strong electric field applications and preventing overtreatment due to delayed shutdown. This paper introduces the structure and basic principles of this novel SiC photoconductive switch-triggered pulse device and reports on the impact of device-related pulse parameters on the ablation effect of hepatocellular carcinoma cells through cell experiments. Under optimal ablation parameters, the CCK8 results show that the number of viable cells is only 0.7% of that in the untreated control group after 12 h of subculture following ablation. These findings hold significant importance for expanding the application areas of SiC devices.


  • Open Access

    Electrochemical Redox Cycling Behavior of Gold Nanoring Electrodes Microfabricated on a Silicon Micropillar

    by Haocheng Yin, Chao Tan, Shabnam Siddiqui, Prabhu U. Arumugam

    We report the microfabrication and characterization of concentric gold nanoring electrodes (Au NREs), which were fabricated by patterning two gold nanoelectrodes on the same silicon (Si) micropillar tip. Au NREs of 165 ± 10 nm in width were micropatterned on a 6.5 ± 0.2 µm diameter 80 ± 0.5 µm height Si micropillar with an intervening ~ 100 nm thick hafnium oxide insulating layer between the two nanoelectrodes. Excellent cylindricality of the micropillar with vertical sidewalls as well as a completely intact layer of a concentric Au NRE including the entire micropillar perimeter has been achieved as observed via scanning electron microscopy and energy dispersive spectroscopy data. The electrochemical behavior of the Au NREs was characterized by steady-state cyclic voltammetry and electrochemical impedance spectroscopy. The applicability of Au NREs to electrochemical sensing was demonstrated by redox cycling with the ferro/ferricyanide redox couple. The redox cycling amplified the currents by 1.63-fold with a collection efficiency of > 90% on a single collection cycle. The proposed micro-nanofabrication approach with further optimization studies shows great promise for the creation and expansion of concentric 3D NRE arrays with controllable width and nanometer spacing for electroanalytical research and applications such as single-cell analysis and advanced biological and neurochemical sensing.