Transfer learning enhanced water-enabled electricity generation in highly oriented graphene oxide nanochannels.

ABSTRACT: Harvesting energy from spontaneous water flow within artificial nanochannels is a promising route to meet sustainable power requirements of the fast-growing human society. However, large-scale nanochannel integration and the multi-parameter coupling restrictive influence on electric generation are still big challenges for macroscale applications. In this regard, long-range (1 to 20 cm) ordered graphene oxide assembled framework with integrated 2D nanochannels have been fabricated by a rotational freeze-casting method. The structure can promote spontaneous absorption and directional transmission of water inside the channels to generate considerable electric energy. A transfer learning strategy is implemented to address the complicated multi-parameters coupling problem under limited experime

SUBMITTER: Yang C 

PROVIDER: S-EPMC9649687 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature