journal article·2022-11-23

A Novel Ionic Conductive Polyurethane Based on Deep Eutectic Solvent Continuing Traditional Merits

Haoge Cheng, Kaiyue Yang, Yuze Zhang, Shenglong Liao, Menghao Du, Jiaqi Li, Ning Ma, Mianqi Xue, Xinyue Zhang, Yapei Wang

ACS Applied Materials & Interfaces· Volume 14· Issue 46
Publisher page

Abstract

Artificial intelligence (AI) has become increasingly popular along with the development of the bionic neural system. Ionic conductors play an important role in the AI system due to the ability of bionic sensing and signal transporting. Traditional low-polarity elastomers possess outstanding mechanical strength and stability, such as polyurethane, which is difficult to be directly endowed with ionic conductivity without impairing its properties. Herein, we have first put forward a new approach to synthesize a liquid-free ionic conductive polyurethane (CPU) through one-step copolymerization between a green deep eutectic solvent (DES) and a prepolymer of polyurethane. The as-prepared CPU can retain the native properties of the traditional polyurethane (PU) such as the homogeneous phase, ease of molding, high transparency (about 93.3%), and excellent mechanical properties. By introducing the DES as the covalent cross-linking agent and ionic conductor at the same time, the CPU also has fine ionic conductivity (3.78 × 10–5 S cm–1), environmental resistance like anti-freezing (−20 °C), and solvent resistance. Based on the excellent conductivity and mechanical strength, the flexible CPU can be applied as a sensing element in pressure sensors. The CPU-based sensor has presented long-term stability, high sensitivity, and wide-ranging response (0.17–3.28 MPa) to the applied pressure, which will be suitable for the industrial demands for practical applications.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Dielectric materials and actuators · Advanced Memory and Neural Computing

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Qingdao Innovation and Development Center, Harbin Engineering University, Qingdao 266000, China

Department of Chemistry, Renmin University of China, Beijing 100872, China

Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, China

Funding

Central University Basic Research Fund of China · Natural Science Foundation of Heilongjiang Province · National Natural Science Foundation of China

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