Structural design of electrospun nanofibers for electrochemical energy storage and conversion

Wang, Ning; Wang, Bin; Wang, Wanli; Yang, Hao; Wan, Yi; Zhang, Yunlong; Guan, Lu; Yao, Yazhen; Teng, Xiaoling; Meng, Chao; Hu, Han; Wu, Mingbo

doi:10.1016/j.jallcom.2022.167920

Cited by 23 publications

(6 citation statements)

References 176 publications

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“…Contrasted and the conventional business permeable polyethylene (PE) separator, the PAN@PVDF‐HFP microfiber complex films displayed higher porosity, prevalent warm steadiness, better electrolyte wettability and higher ionic conductivity. Consequently, batteries gathered with the PAN@PVDF‐HFP microfiber complex layer show better cycling strength and better rate execution contrasted than those and the PE separator [44].…”

Section: Fabrication Strategies From Electrospinningmentioning

confidence: 97%

Electrospun nanofibers synthesis enhancing the activity of energy storage devices/electrochemical and biosensor applications

Noor,

Saleem,

Furqan Mughal

et al. 2024

Electroanalysis

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Section: Fabrication Strategies From Electrospinningmentioning

confidence: 97%

Electrospun nanofibers synthesis enhancing the activity of energy storage devices/electrochemical and biosensor applications

Noor,

Saleem,

Furqan Mughal

et al. 2024

Electroanalysis

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“…Zhou et al [100] reported on polyaniline and graphene nanocomposite nanofibers developed through electrospinning technique. The electrospun nanofibers have been used for supercapacitor electrodes [101] . The potential polyaniline/graphene electrode had higher specific capacitance (250 Fg −1 ) than that of unfilled polyaniline (175 Fg −1 ) electrode.…”

Section: Applications Of Nanocomposite Nanofibers and Membranes Prepa...mentioning

confidence: 99%

State-of-the-art of electrospun nanocomposite nanofibers and membranes with carbon nanoparticles—Prevailing progressions

Kausar,

Ahmad

2024

Charact. Appl. Nanomater.

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This state-of-the-art overview emphasizes electrospinning technique and resulting electrospun nanofibers and nanofibrous membranes. Consequently, the electrospinning method as well as the formation and features of the electrospun nanofiber/membrane nanomaterials have been described. Properties of the electrospun nanofibers have found to be enhanced several folds through the incorporation of carbon nanoparticles in the nanofibers. Important properties and utilizations of carbon nanocomposite electrospun nanofibers were seemed to be affected by nanoparticle amount and dispersal. Importantly, diameter, microstructure, and physical features (thermal, mechanical, conductive, etc.) of the nanofibers and resulting membranes can be affected by the nanofiller behavior. The high performance electrospun nanofibers have been used to form efficient nanocomposite nanofibrous membranes. Sequentially, the electrospun nanocomposite nanofibrous membranes have been applied in technical membrane applications.

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“…Electrode materials decide the theoretical limit of energy density, while electrolytes as the "blood" of a battery largely determine the practical working states. [88][89][90] ML has accelerated the discovery and optimization of the constituents for electrolyte and electrode materials by learning continuously. The electrolyte can be divided into solid-state electrolytes (SSEs) and liquid ones.…”

Section: Constituent Optimizationmentioning

confidence: 99%

“…The electrolyte and electrode materials are extremely two critical components in a battery. Electrode materials decide the theoretical limit of energy density, while electrolytes as the “blood” of a battery largely determine the practical working states 88–90 . ML has accelerated the discovery and optimization of the constituents for electrolyte and electrode materials by learning continuously.…”

Section: Applying Machine Learning In Electrochemical Energy Storage ...mentioning

confidence: 99%

Reshaping the material research paradigm of electrochemical energy storage and conversion by machine learning

Yang

Zhang

et al. 2023

EcoMat

Self Cite

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For a "Carbon Neutrality" society, electrochemical energy storage and conversion (EESC) devices are urgently needed to facilitate the smooth utilization of renewable and sustainable energy where the electrode materials and catalysts play a decisive role. However, the efficiency of the current trial-and-error research paradigm largely lags behind the imminent demands of EESC requiring increasingly improved performance. The emerged machine learning (ML), a subfield of artificial intelligence, is capable of evaluating and analyzing big data for hidden rules. In this regard, the relationships between the structure and performance of the key materials can be more efficiently revealed, which fundamentally revolutionizes the material research manner of the current EESC devices. In this review, the typical ML algorithms utilized in EESC development are first introduced. Then, focused attention has been paid to multiple aspects of applying ML to reshape the materials research for EESC. In addition to highlighting the emerging prospect, the challenges which are still hindering the further development of this emerging field are also discussed.

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Structural design of electrospun nanofibers for electrochemical energy storage and conversion

Cited by 23 publications

References 176 publications

Electrospun nanofibers synthesis enhancing the activity of energy storage devices/electrochemical and biosensor applications

Electrospun nanofibers synthesis enhancing the activity of energy storage devices/electrochemical and biosensor applications

State-of-the-art of electrospun nanocomposite nanofibers and membranes with carbon nanoparticles—Prevailing progressions

Reshaping the material research paradigm of electrochemical energy storage and conversion by machine learning

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