Xuling Liu

Dr. Xuling Liu


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

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

Representative Publications

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31 October 2022 in Energies
Verified
Journal Article
Open access
PDF file
XLXuling Liu
Xuling Liu
WZWensi Zuo
Wensi Zuo
HSHuafeng Song
Huafeng Song
TSTingdong Shang
Tingdong Shang
HDHaiwei Dong
Haiwei Dong
Songjing LiSongjing Li
Songjing Li
A compact, rapid, and portable off-chip pneumatic control valve is significant for the miniaturization and integration of external pneumatic systems for microfluidic chips. In this work, an off-chip microvalve with a high-speed electromagnetic switch actuator and a polydimethylsiloxane (PDMS) material valve body has been designed to be easily encapsulated, simulated using MATLAB/Simulink software, and tested in a micromixer. Multi-physical coupling mathematical models are developed based on the elastic deformation force of the valve membrane, the driving force of the valve core, and the fluid force in the microchannel. Two single microvalves are used to form a three-way microvalve, which can control the air pressure in a pneumatic microchannel on the microfluidic chip. The relationship between the flow–duty cycle, the flow–pressure difference of the single electromagnetic microvalve, and the load pressure of the three-way microvalve is simulated and analyzed. Sample mixing performance controlled by the proposed off-chip three-way microvalve was tested to evaluate the pneumatic control capability, and the results show that the undertaking can fully satisfy the needs of a pneumatic microfluidic chip for most applications.

20 November 2022 in Energies
Verified
Journal Article
Open access
PDF file
XLXuling Liu
Xuling Liu
HSHuafeng Song
Huafeng Song
WZWensi Zuo
Wensi Zuo
GYGuoyong Ye
Guoyong Ye
SJShaobo Jin
Shaobo Jin
Songjing LiSongjing Li
Songjing Li
The compact, simple, and fast-reaction pneumatic microactuator is significant for the integration and high efficiency of pneumatic systems. In this work, the structure, working principle, and multiphysical model of an on-chip pneumatic microactuator are presented. The on-chip pneumatic microactuator is mainly composed of two parts: a polydimethylsiloxane (PDMS) thin membrane and an actuated chamber. The air pressure in the actuated chamber drives the thin elastic membrane to deformation. Dynamic response mathematical models of the actuated chamber for charging and exhaust with variable volume are established, and the deformation characteristics of the polydimethylsiloxane (PDMS) actuated membrane, the capacity of the actuated chamber, and the valve opening of the on-off membrane microvalve are simulated and analyzed to explore the response characteristics of the proposed pneumatic microactuator. Samples valving analysis of the on-chip membrane microvalve and mixing performance of the micromixer integrated with the pneumatic microactuator are tested to evaluate the driving capability of the pneumatic microactuator, and the results show that the response performance of the actuated time fully satisfies the needs of a pneumatic microfluidic chip for most applications.

28 September 2025 in Fluids
Verified
Journal Article
Open access
PDF file
XLXuling Liu
Xuling Liu
LBLe Bo
Le Bo
JSJinggan Shao
Jinggan Shao
CPChaofeng Peng
Chaofeng Peng
KZKaiyi Zhang
Kaiyi Zhang
JSJinggan Shao
Jinggan Shao
The unsteady and discontinuous liquid flow in the microchannel affects the efficiency of sample mixing, molecular detection, target acquisition, and biochemical reaction. In this work, an active method of reducing the flow pulsation in the microchannel of a pneumatic microfluidic chip is proposed by using an on-chip membrane microvalve as a valve chamber damping hole or a valve chamber accumulator. The structure, working principle, and multi-physical model of the reducing element of reducing the flow pulsation in a microchannel are presented. When the flow pulsation in the microchannel is sinusoidal, square wave, or pulse, the simulation effect of flow pulsation reduction is given when the membrane valve has different permutations and combinations. The experimental results show that the inlet flow of the reducing element is a square wave pulsation with an amplitude of 0.1 mL/s and a period of 2 s, the outlet flow of the reducing element is assisted by 0.017 and the fluctuation frequency is accompanied by a decrease. The test data and simulation results verify the rationality of the flow reduction element in the membrane valve microchannel, the correctness of the theoretical model, and the practicability of the specific application, which provides a higher precision automatic control technology for the microfluidic chip with high integration and complex reaction function.

2 February 2024
Verified
Book Chapter
Closed access
PDF file
JSJinggan Shao
Jinggan Shao
TSTingdong Shang
Tingdong Shang
GWGenshang Wu
Genshang Wu
WLWei Liu
Wei Liu
LBLe Bo
Le Bo
XLXuling Liu
Xuling Liu

30 April 2025 in Fluids
Verified
Journal Article
Open access
PDF file
XLXuling Liu
Xuling Liu
JSJinggan Shao
Jinggan Shao
CPChaofeng Peng
Chaofeng Peng
JSJinggan Shao
Jinggan Shao
YZYi kai Zhang
Yi kai Zhang
Songjing LiSongjing Li
Songjing Li
In this paper, a double-mode self-calibration tension system is proposed, which adopts the conversion of hydraulic meter tension and the monitoring of standard force sensors. According to the material characteristics of the jack and the viscosity and temperature characteristics of the hydraulic oil, the differential model of heat conduction in the hydraulic cylinder and the mathematical model of oil film friction heat generation are established, and the internal thermodynamic characteristics of the jack are theoretically analyzed, which provides theoretical support for the temperature compensation of the hydraulic oil pressure gauge of the jack. A simulation analysis was conducted on the thermodynamic characteristics of the hydraulic jack, and the distribution patterns of the temperature field, thermal stress field, and thermal strain field inside the hydraulic cylinder during normal operation were determined by measuring the temperature changes in five different parts of the jack at different times (t = 200 s, 2600 s, 5000 s, 7400 s, and 10,000 s). For the issue of heat generation due to oil film friction in the hydraulic jack, a simulation calculation model is developed by integrating Computational Fluid Dynamics (CFD) techniques with dynamic grid and slip grid methods. By simulating and analyzing frictional heating under conditions where the inlet pressures are 0.1 MPa, 0.3 MPa, 0.5 MPa, 0.7 MPa, and 0.9 MPa, respectively, we can obtain the temperature distribution on the jack, determine the frictional resistance, and subsequently conduct a theoretical analysis of the simulation results. Using the high-precision standard force sensor after data processing and the hydraulic oil gauge after temperature compensation, the online self-calibration of the tensioning system is carried out, and the regression equation of the tensioning system under different oil temperatures is obtained. The double-mode self-calibration tensioning system with temperature compensation is used to verify the compensation accuracy of the proposed double-mode self-calibration tensioning system.

19 September 2025 in Actuators
Verified
Journal Article
Open access
PDF file
YZYi kai Zhang
Yi kai Zhang
XLXuling Liu
Xuling Liu
GYGuohua Yang
Guohua Yang
KZKun Zhai
Kun Zhai
GAGaofei An
Gaofei An
CPChaofeng Peng
Chaofeng Peng
Reliable fault diagnosis of rotating machines under extreme conditions—strong speed, load variation, intense noise, and severe class imbalance—remains a critical industrial challenge. We develop an ultra-light yet robust framework to accurately detect weak bearing, and gear faults when less than 5% labels, 10 dB noise, 100:1 imbalance and plus or minus 20% operating-point drift coexist. Methods: The proposed Adaptive Feature Module–Conditional Dynamic GRU Auto-Encoder (AFM-CDGAE) first compresses 512 d spectra into 32/48 d “feature modules” via K-means while retaining 98.4% fault energy. A workload-adaptive multi-scale convolution with spatial attention and CPU-aware λ-scaling suppresses noise and adapts to edge–device load. A GRU-based auto-encoder, enhanced by self-attention, is trained with balanced-subset sampling and minority-F1-weighted voting to counter extreme imbalance. On Paderborn (5-class) and CWRU (7-class) benchmarks, the 0.87 M-parameter model achieves 99.12% and 98.83% Macro-F1, surpassing five recent baselines by 3.1% under normal and 5.4% under the above extreme conditions, with only 1.5 to 1.8% F1 drop versus 6.7% for baselines. AFM-CDGAE delivers state-of-the-art accuracy, minimal footprint and strong robustness, enabling real-time deployment at the edge.