Color-Shifting Iontronic Skin for On-Site, Nonpixelated Pressure Mapping Visualization.

Mimicking the function of human skin is highly desired for electronic skins (e-skins) to perceive the tactile stimuli by both their intensity and spatial location. The common strategy using pixelated pressure sensor arrays and display panels greatly increases the device complexity and compromises the portability of e-skins. Herein, we tackled this challenge by developing a user-interactive iontronic skin that simultaneously achieves electrical pressure sensing and on-site, nonpixelated pressure mapping visualization.

Welded Carbon Nanotube-Graphene Hybrids with Tunable Strain Sensing Behavior for Wide-Range Bio-Signal Monitoring.

Carbon nanotubes (CNTs) and graphene have commonly been applied as the sensitive layer of strain sensors. However, the buckling deformation of CNTs and the crack generation of graphene usually leads to an unsatisfactory strain sensing performance. In this work, we developed a universal strategy to prepare welded CNT-graphene hybrids with tunable compositions and a tunable bonding strength between components by the in situ reduction of CNT-graphene oxide (GO) hybrid by thermal annealing.

In Situ Synthesis of Rare-Earth Hybridized Functional Core-Shell Architectures from Microporous Salt Templates and Capacitance-Adsorption Correlation Mechanisms.

Biochar Porous Carbon (BPC) has become a research hotspot in the fields of energy storage, conversion, catalysis, adsorption, and separation engineering. However, the key problem of pore structure liable to collapse has not yet been addressed effectively. Here, an innovative salt ionic coordination modulation technique is reported to synthesize a new core-shell structure of BPC (Dual-doped porous carbonaceous materials, RHPC3@LaYO) by the asymmetric load of the f orbital ion, which prevents pore structural collapse.

Protein Complexes Detection Based on Semi-Supervised Network Embedding Model.

A protein complex is a group of associated polypeptide chains which plays essential roles in the biological process. Given a graph representing protein-protein interactions (PPI) network, it is critical but non-trivial to detect protein complexes, the subsets of proteins that are tightly coupled, from it. Network embedding is a technique to learn low-dimensional representations of vertices in networks.