Among kinds of flexible tactile sensors, piezoelectric tactile sensor has the advantage of fast response for dynamic force detection. However, it suffers from low sensitivity at high-frequency dynamic stimuli. Here, inspired by finger structure—rigid skeleton embedded in muscle, we report a piezoelectric tactile sensor using a rigid-soft hybrid force-transmission-layer in combination with a soft bottom substrate, which not only greatly enhances the force transmission, but also triggers a significantly magnified effect in d₃₁ working mode of the piezoelectric sensory layer, instead of conventional d₃₃ mode. Experiments show that this sensor exhibits a super-high sensitivity of 346.5 pC N⁻¹ (@ 30 Hz), wide bandwidth of 5–600 Hz and a linear force detection range of 0.009–4.3 N, which is ~17 times the theoretical sensitivity of d₃₃ mode. Furthermore, the sensor is able to detect multiple force directions with high reliability, and shows great potential in robotic dynamic tactile sensing.

Flexible pressure sensors are indispensable components in various applications such as intelligent robots and wearable devices, whereas developing flexible pressure sensors with both high sensitivity and wide linear range remains a great challenge. Here, we present an elegant strategy to address this challenge by taking advantage of a pyramidal carbon foam array as the sensing layer and an elastomer spacer as the stiffness regulator, realizing an unprecedentedly high sensitivity of 24.6 kPa⁻¹ and an ultra-wide linear range of 1.4 MPa together. Such a wide range of linearity is attributed to the synergy between the nonlinear piezoresistivity of the sensing layer and the nonlinear elasticity of the stiffness regulator. The great application potential of our sensor in robotic manipulation, healthcare monitoring, and human-machine interface is demonstrated. Our design strategy can be extended to the other types of flexible sensors calling for both high sensitivity and wide-range linearity, facilitating the development of high-performance flexible pressure sensors for intelligent robotics and wearable devices.

In a forest of a hundred thousand trees, no two leaves are alike. Similarly, no two cells in a genetically identical group are the same. This heterogeneity at the single-cell level has been recognized to be vital for the correct interpretation of diagnostic and therapeutic results of diseases, but has been masked for a long time by studying average responses from a population. To comprehensively understand cell heterogeneity, diverse manipulation and comprehensive analysis of cells at the single-cell level are demanded. However, using traditional biological tools, such as petri-dishes and well-plates, is technically challengeable for manipulating and analyzing single-cells with small size and low concentration of target biomolecules. With the development of microfluidics, which is a technology of manipulating and controlling fluids in the range of micro- to pico-liters in networks of channels with dimensions from tens to hundreds of microns, single-cell study has been blooming for almost two decades. Comparing to conventional petri-dish or well-plate experiments, microfluidic single-cell analysis offers advantages of higher throughput, smaller sample volume, automatic sample processing, and lower contamination risk, etc., which made microfluidics an ideal technology for conducting statically meaningful single-cell research. In this review, we will summarize the advances of microfluidics for single-cell manipulation and analysis from the aspects of methods and applications. First, various methods, such as hydrodynamic and electrical approaches, for microfluidic single-cell manipulation will be summarized. Second, single-cell analysis ranging from cellular to genetic level by using microfluidic technology is summarized. Last, we will also discuss the advantages and disadvantages of various microfluidic methods for single-cell manipulation, and then outlook the trend of microfluidic single-cell analysis.

We report a two-bubble based micro-swimmer that can be propelled and steered entirely using one ultrasound transducer.

Single cell surgery such as manipulation or removal of subcellular components or/and organelles from single cells is increasingly used for the study of diseases and their causes in precision medicine. This paper presents a robotic surgery system to achieve automated organelle biopsy of single cells with dimensions of less than 20 μm in diameter. The complexity of spatial detection of the organelle position is reduced by patterning the cells using a microfluidic chip device. A sliding mode nonlinear controller is developed to enable extraction of organelles, such as the mitochondria and the nucleus, from single cells with high precision. An image processing algorithm is also developed to automatically detect the position of the desired organelle. The effectiveness of the proposed robotic surgery system is demonstrated experimentally with automated extraction of mitochondria and nucleus from human acute promyelocytic leukemia cells and human fibroblast cells. Extraction is followed by biological tests to indicate the functionality of biopsied mitochondria as well as the cell viability after removal of mitochondria. The results presented here have revealed that the proposed approach of automated organelle biopsy on single small cells is feasible.

A contact acoustic tweezer uses a single ultrasound transducer to move droplets on superhydrophobic surfaces with great simplicity, versatility, and controllability.