Mengya Liu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Mengya Liu has a total of 14 co-authors. Here are the top co-authors by number of shared publications:
- Jinyu Qiu
Nankai University
4 shared publications - Qili Zhao
Nankai University
4 shared publications - Ruimin Li
Nankai University
4 shared publications - Xin Zhao
Nankai University
4 shared publications - Shaojie Fu
Tianjin Key Laboratory of Intelligent Robotic (tjKLlR), Institute of Robotics and Automatic Information System (IRAIS), Nankai University, Tianjin, China
3 shared publications - Biting Ma
Nankai University
2 shared publications
Latest Publications
- 28 April 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE/ASME Transactions on Mechatronics
- Vol. PP (10834435) , 1-12
Robotic Fast Cell Positioning Based on a Narrow-Necked Micropipette in Cell Transportation
In this article, a narrow-necked micropipette (NNM) was designed, fabricated, and utilized for robotic fast cell positioning in cell transportation. First, key geometrical parameters of NNM were determined through the aspiration model and computational microfluidics model. Then, a heating-and-rotation method was developed to fabricate a narrow neck structure inside the micropipette based on a heating model. Further, the dynamic models of the cell before and after being held by the narrow neck were conducted. Based on that, a sliding mode motion controller and a deformation controller were designed for fast positioning of the cell at the narrow neck position and reducing the cell deformation, respectively. Robotic transportation results of 15 sheep oocytes demonstrate that our system can position the cell with a 100% success rate at doubled throughput in comparison to the traditional methods. The average positioning error and cell deformation degree are significantly reduced to 1.89 pixels and 2.59%, respectively. In addition, experiments on HeLa cells showed an average position time of 2.1 s with 100% success rate. Besides, limited harm to the cell survival rate is found through culturing experiments. With the above advantages, our robotic system is expected to improve cell transportation efficiency in the future.
- 28 April 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE/ASME Transactions on Mechatronics
- Vol. PP (10834435) , 1-12
Robotic Fast Cell Positioning Based on a Narrow-Necked Micropipette in Cell Transportation
In this article, a narrow-necked micropipette (NNM) was designed, fabricated, and utilized for robotic fast cell positioning in cell transportation. First, key geometrical parameters of NNM were determined through the aspiration model and computational microfluidics model. Then, a heating-and-rotation method was developed to fabricate a narrow neck structure inside the micropipette based on a heating model. Further, the dynamic models of the cell before and after being held by the narrow neck were conducted. Based on that, a sliding mode motion controller and a deformation controller were designed for fast positioning of the cell at the narrow neck position and reducing the cell deformation, respectively. Robotic transportation results of 15 sheep oocytes demonstrate that our system can position the cell with a 100% success rate at doubled throughput in comparison to the traditional methods. The average positioning error and cell deformation degree are significantly reduced to 1.89 pixels and 2.59%, respectively. In addition, experiments on HeLa cells showed an average position time of 2.1 s with 100% success rate. Besides, limited harm to the cell survival rate is found through culturing experiments. With the above advantages, our robotic system is expected to improve cell transportation efficiency in the future.
- Open Access
Precise Control of Micropipette Flow Rate for Fluorescence Imaging in In Vivo Micromanipulation
Precise regulation of micropipette outlet flow is critical for fluorescence imaging in vivo micromanipulations. In such procedures, a micropipette with a micro-sized opening is driven by gas pressure to deliver internal solution into the in vivo environment. The outlet flow rate needs to be precisely regulated to ensure a uniform and stable fluorescence distribution. However, conventional manual pressure injection methods face inherent limitations, including insufficient precision and poor reproducibility. Existing commercial microinjection systems lack a quantitative relationship between pressure and flow rate. And existing calibration methods in the field of microfluidics suffer from a limited flow-rate measurement resolution, constraining the establishment of a precise pressure–flow quantitative relationship. To address these challenges, we developed a closed-loop pressure regulation system with 1 Pa-level control resolution and established a quantitative calibration of the pressure–flow relationship using a droplet-based method. The calibration revealed a linear relationship with a mean pressure–flow gain of 4.846 (R2 > 0.99). Validation results demonstrated that the system achieved the target outlet flow rate with a flow control error less than 10 fL/s. Finally, the application results in brain-slice environment confirmed its capability to maintain stable fluorescence imaging, with fluorescence intensity fluctuations around 1.3%. These results demonstrated that the proposed approach provides stable, precise, and reproducible flow regulation under physiologically relevant conditions, thereby offering a valuable tool for in vivo micromanipulation and detection.Open AccessPrecise Control of Micropipette Flow Rate for Fluorescence Imaging in In Vivo Micromanipulation
Precise regulation of micropipette outlet flow is critical for fluorescence imaging in vivo micromanipulations. In such procedures, a micropipette with a micro-sized opening is driven by gas pressure to deliver internal solution into the in vivo environment. The outlet flow rate needs to be precisely regulated to ensure a uniform and stable fluorescence distribution. However, conventional manual pressure injection methods face inherent limitations, including insufficient precision and poor reproducibility. Existing commercial microinjection systems lack a quantitative relationship between pressure and flow rate. And existing calibration methods in the field of microfluidics suffer from a limited flow-rate measurement resolution, constraining the establishment of a precise pressure–flow quantitative relationship. To address these challenges, we developed a closed-loop pressure regulation system with 1 Pa-level control resolution and established a quantitative calibration of the pressure–flow relationship using a droplet-based method. The calibration revealed a linear relationship with a mean pressure–flow gain of 4.846 (R2 > 0.99). Validation results demonstrated that the system achieved the target outlet flow rate with a flow control error less than 10 fL/s. Finally, the application results in brain-slice environment confirmed its capability to maintain stable fluorescence imaging, with fluorescence intensity fluctuations around 1.3%. These results demonstrated that the proposed approach provides stable, precise, and reproducible flow regulation under physiologically relevant conditions, thereby offering a valuable tool for in vivo micromanipulation and detection. - 2 April 2025
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Instrumentation and Measurement
- Vol. 74 (00189456) , 1-8
Robotic Improved Micropipette Aspiration Method for Accurate Measurement of Cellular Mechanical Properties
For the first time, an improved robotic micropipette aspiration (MA) method considering the effects of the intra-cellular pressure, friction between cell and micropipette, and the micropipette opening size was proposed for improving the measurement accuracy of the cell elasticity properties in this paper. First, an elastic energy model of the aspirated cell was established to analyze the effects of intracellular pressure on MA results. Then a force analysis of MA process was conducted to evaluate the influences of the friction force between the cell surface and micropipette opening as well as the inner diameter of the micropipette opening to MA results. Based on the above work, an improved robotic MA process was developed for reducing the cell elasticity measurement errors through automated release of intracellular pressure, micropipette opening polishing and inner diameter control of the micropipette. The effectiveness of the above work was validated by both finite elemental model (FEM) and MA experiments. The MA results on porcine oocytes demonstrate that our proposed MA method can rectify the 20.11%, 35.08% and 6.80% measure errors of cell Young’s modulus caused by the above three factors, respectively. Our research may provide a more objective evaluation of cell mechanical properties in the related research.
- 2 April 2025
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Instrumentation and Measurement
- Vol. 74 (00189456) , 1-8
Robotic Improved Micropipette Aspiration Method for Accurate Measurement of Cellular Mechanical Properties
For the first time, an improved robotic micropipette aspiration (MA) method considering the effects of the intra-cellular pressure, friction between cell and micropipette, and the micropipette opening size was proposed for improving the measurement accuracy of the cell elasticity properties in this paper. First, an elastic energy model of the aspirated cell was established to analyze the effects of intracellular pressure on MA results. Then a force analysis of MA process was conducted to evaluate the influences of the friction force between the cell surface and micropipette opening as well as the inner diameter of the micropipette opening to MA results. Based on the above work, an improved robotic MA process was developed for reducing the cell elasticity measurement errors through automated release of intracellular pressure, micropipette opening polishing and inner diameter control of the micropipette. The effectiveness of the above work was validated by both finite elemental model (FEM) and MA experiments. The MA results on porcine oocytes demonstrate that our proposed MA method can rectify the 20.11%, 35.08% and 6.80% measure errors of cell Young’s modulus caused by the above three factors, respectively. Our research may provide a more objective evaluation of cell mechanical properties in the related research.