Publications

Abstract Polymer-based piezoelectric devices are promising for developing future wearable force sensors, nanogenerators, and implantable electronics etc. The electric signals generated by them are often assumed as solely coming from piezoelectric effect. However, triboelectric signals originated from contact electrification between the piezoelectric devices and the contacted objects can produce non-negligible interfacial electron transfer, which is often combined with the piezoelectric signal to give a triboelectric-piezoelectric hybrid output, leading to an exaggerated measured “piezoelectric” signal. Herein, a simple and effective method is proposed for quantitatively identifying and extracting the piezoelectric charge from the hybrid signal. The triboelectric and piezoelectric parts in the hybrid signal generated by a poly(vinylidene fluoride)-based device are clearly differentiated, and their force and charge characteristics in the time domain are identified. This work presents an effective method to elucidate the true piezoelectric performance in practical measurement, which is crucial for evaluating piezoelectric materials fairly and correctly.

Abstract A tactile sensor should be able to detect both normal and tangential forces, which is mandatory for simulating human hands, but this fundamental function has been overlooked by most of the previous studies. Here, based on a triboelectric nanogenerator (TENG) with single‐electrode mode, the fully elastic and metal‐free tactile sensor that can detect both normal and tangential forces is proposed. With tiny burr arrays on the contact interface to facilitate the elastic deformation, the detected normal pressure by the device can reach to 1.5 MPa with a sensitivity of about 51.43 kPa V −1 , and a large range of tangential forces can be detected ranging from 0.5 to 40 N with rough sensitivity of 0.83 N V −1 (0.5–3 N) and 2.50 N V −1 (3–40 N). Meanwhile, the applied tangential forces from different directions can also be clearly distinguished by the four‐partitioned electrode structure. Moreover, a shield film is coated on the top surface of the device, which can screen the electrostatic interference and enhance the repeatability of the device. The demonstrated concept of this self‐powered tactile sensor has excellent applicability for industrial robotics, human–machine interactions, artificial intelligence, etc.

Abstract Utilizing inner‐crystal piezoelectric polarization charges to control carrier transport across a metal‐semiconductor or semiconductor–semiconductor interface, piezotronic effect has great potential applications in smart micro/nano‐electromechanical system (MEMS/NEMS), human‐machine interfacing, and nanorobotics. However, current research on piezotronics has mainly focused on systems with only one or rather limited interfaces. Here, the statistical piezotronic effect is reported in ZnO bulk composited of nanoplatelets, of which the strain/stress‐induced piezo‐potential at the crystals’ interfaces can effectively gate the electrical transport of ZnO bulk. It is a statistical phenomenon of piezotronic modification of large numbers of interfaces, and the crystal orientation of inner ZnO nanoplatelets strongly influence the transport property of ZnO bulk. With optimum preferred orientation of ZnO nanoplatelets, the bulk exhibits an increased conductivity with decreasing stress at a high pressure range of 200–400 MPa, which has not been observed previously in bulk. A maximum sensitivity of 1.149 µS m −1 MPa −1 and a corresponding gauge factor of 467–589 have been achieved. As a statistical phenomenon of many piezotronic interfaces modulation, the proposed statistical piezotronic effect extends the connotation of piezotronics and promotes its practical applications in intelligent sensing.

We demonstrate an innovative memory device made of a single crystalline ZnO nanowire/microwire that works with a different mechanism from the p-n junction based memristor. A nonsymmetric, Schottky-Ohmic contacted ZnO nano/microwire can serve as a memristor if the channel length is short and the applied frequency is high. The observed phenomena could be explained based on a screening model of the polar charges at the two ends of the wire owing to the crystal structure of ZnO. The polar charges are usually fully screened by free electrons coming from the metal sides. But when the magnitude of the externally applied field exceeds a threshold value, the free electrons that screen the polar surfaces can be pulled away from the interface region, leading to a transient change in the effective height of the local Schottky barrier height owing to the electrical field formed by the polar surfaces of ZnO nanowires, which acts as a resistor with its magnitude depending on the total charges being transported. Such a phenomenon could be used for high density and fast writing/erasing data storage.

Textile-based energy harvesting is realized by integrating fabric triboelelctric nanogenerator and fiber-shaped dye-sensitized solar cell to scavenge the energy of human motion and solar energy, respectively. The hybrid power-textile is demonstrated to be soft, flexible, wearable, and promising for applications in wearable electronics or smart textiles. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Abstract With the advantages of its light weight, low cost, and high efficiency especially at low operation frequency, the triboelectric nanogenerator (TENG) is considered to be a potential solution for self‐powered sensor networks and large‐scale renewable blue energy. However, the conventional TENG converts mechanical energy into electrical energy only via either electrostatic induction or electrostatic breakdown. Here, a novel dual‐mode TENG is presented, which can simultaneously harvest mechanical energy by electrostatic induction and dielectric breakdown in a single device. Based on the complementary working mechanism, it achieves a great improvement in the output performance with the sum of two TENGs via a single mechanism and reveals the effect of dielectric layer thickness on the triboelectrification, electrostatic induction, and air breakdown. This study establishes a new methodology to optimize TENGs and provides a new tool to investigate the triboelectrification, electrostatic induction and dielectric breakdown simultaneously.

<title>Abstract</title> <bold>Background</bold> Gastric cancer (GC) is the fifth most common cancer in the world, with a late diagnosis and poor prognosis. The mitochondrial permeability transition-driven necrosis (MPTDN) is often associated with cancer, while its mechanism in GC is unclear.<bold>Methods</bold> A single-cell RNA sequencing (scRNA-seq) dataset GSE183904, and two mRNA profile datasets TCGA-stomach adenocarcinoma (STAD) and GSE62254 were downloaded from the online databases. After a series of analyses of GSE183904, the differentially expressed genes (DEGs) in different proportions of cells (DCs) were selected between GC and controls for further analysis, namely DC-DEGs. The DEGs between STAD and normal controls (STAD-DEGs) were screened, and then highly correlated modules with MPTDN-related genes (MPTDN-RGs) were obtained by Weighted gene co-expression network analysis (WGCNA). Next, DC-DEGs, STAD-DEGs, and module genes were overlapped as candidate genes. The prognostic genes were selected via the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression model, and the prognostic risk model was constructed and verified. Then, the immune cell infiltrations and Immunotherapy response were conducted. Later, pseudotime analyses were performed to explore key cell evolution trajectories. Furthermore, the clinic specimens were collected to perform qPCR analysis.<bold>Results</bold> Epithelial cells and Tissue stem cells were obtained as DCs, and 1,592 DC-DEGs were identified between GC and normal controls. After the overlapping of 2,238 STAD-DEGs, 1,592 DC-DEGs, and 3,832 module genes, a total of 112 candidate genes were determined. Then, 4 prognostic genes (<italic>GPX3</italic>, <italic>CD36</italic>, <italic>VCAN</italic>, and <italic>SERPINE1</italic>) were identified the risk model was constructed on this basis. Afterward, risk score, age, and N categories were screened as the independent prognostic factors to construct a nomogram model, which could effectively predict the 1-, 3-, and 5-year OS of STAD patients. Subsequently, Endothelial cells and Tissue stem cells differentiated in normal control were less than those of GC. Finally, Moreover, the qPCR revealed that the expression of <italic>GPX3</italic> and <italic>CD36</italic> was reduced in GC tumor tissues.<bold>Conclusion</bold> Overall <italic>GPX3</italic>, <italic>CD36</italic>, <italic>VCAN</italic>, and <italic>SERPINE1</italic> could be potential therapeutic targets to diagnose and treat GC. Tissue stem cells were key cells in GC patients and provided strong support for further understanding of GC.