Graphene Aerogels with a Gradient Porous Structure for Stimulus-Responsive Applications
Source abstract
Abstract
Abstract Stimulus-responsive actuators with gradient porous structures have attracted significant attention among researchers due to their promising applications in soft robotics, drug delivery, tissue engineering, and microfluidics. However, previous studies on gradient porous structures have primarily focused on polymers, and the exploration of such architectures in carbon-based nanomaterials remains limited. In this work, gradient porous graphene aerogels (GGAs) were synthesized via a sequential layer-by-layer casting process of foamed graphene oxide (GO) dispersions with different concentrations. It is shown that the average pore size of GGA increases gradually from the bottom (120 μm) to the top (443 μm), with a density as low as 7 mg/cm3. It also exhibits excellent compressive recovery performance, recovering from 90% strain. The mechanism analysis reveals that in the foamed GO solution, air bubbles undergo fusion over time. Elevated temperature accelerated the fusion rate, whereas increasing the GO concentration to improve the number of GO sheets between bubbles reduced the fusion speed. Consequently, by controlling these conditions, a gradient pore structure is ultimately formed. Furthermore, the GGA was used as a scaffold material for the in situ synthesis of the stimulus-responsive polymer poly(N-isopropylacrylamide), resulting in photothermal-responsive hybrid hydrogels. The composite material could bend 120° within 12 s in 60 °C water and exhibited controllable deformation under near-infrared light irradiation (maximum bending angle of 25°, response time of 12 s). This study presents a feasible method for preparing graphene aerogels with gradient pore structure morphology and demonstrates their potential applications in the field of stimulus-responsive materials.
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Research context
OpenAlex topics: Hydrogels: synthesis, properties, applications · Advanced Materials and Mechanics · Advanced Sensor and Energy Harvesting Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
China FAW Group Co., Ltd. , , ,
Qingdao University of Science and Technology , , ,
University of Cambridge , , ,
Funding
China Postdoctoral Science Foundation · Natural Science Foundation of Shandong Province · Youth Innovation Team Project of Shandong Province, China · National Natural Science Foundation of China
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