Forecasting soybean oil extraction using cyclopentyl methyl ether through soft computing models with a density functional theory study

Gasparetto, Henrique; Fuhr, Ana Carolina Ferreira Piazzi; Salau, Nina Paula Gonçalves

doi:10.1016/j.jiec.2023.03.046

Journal of Industrial and Engineering Chemistry

2023

DOI: 10.1016/j.jiec.2023.03.046

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Forecasting soybean oil extraction using cyclopentyl methyl ether through soft computing models with a density functional theory study

Henrique Gasparetto

Ana Carolina Ferreira Piazzi Fuhr

Nina Paula Gonçalves Salau

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Cited by 9 publications

References 74 publications

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Efficient Chemical Prelithiation with Modificatory Li⁺ Solvation Structure Enabling Spatially Homogeneous SEI toward High Performance SiO_x Anode^†

Wang,

Wu,

Niu

et al. 2024

Chin. J. Chem.

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Comprehensive SummaryChemical prelithiation is widely proven to be an effective strategy to address the low initial coulombic efficiency (ICE) of promising SiOx anode. Though the reagent composition has been widely explored, the Li+ solvation structure, which practically plays the cornerstone role in the prelithiation ability, rate, uniformility, has rarely been explored. A novel environmentally‐friendly reagent with weak solvent cyclopentyl methyl ether (CPME) is proposed that enables both improved ICE and spatial homogeneous solid electrolyte interphase (SEI). And the prelithiation behavior and mechanism were explored focused on the Li+ solvation structure. Both theoretical investigation and spectroscopic results suggest that weak solvent feature of CPME reduces the solvent coordination number and decreases the Li+ desolvation energy. The optimized Li+ solvation structure enables high‐efficiency prelithiation that ensures the horizontal homogenization and mechanical properties of SEI. Moreover, the accompanied CPME molecules preferentially occupy positions in initial SEI, reducing the likelihood of LiPF6 decomposition and promoting longitudinal homogenization of SEI. Consequently, the efficient and homogenous prelithiation enables impressive ICE of 109.52% and improved cycling performance with 80.77% retained after 300 cycles via just 5 min soaking. Furthermore, the full cells with LiNi0.83Co0.12Mn0.05O2 (NCM831205) cathode display an enhancement in the energy density of 179.74% and up to 648.35 Wh·kg–1.

show abstract

Efficient Chemical Prelithiation with Modificatory Li⁺ Solvation Structure Enabling Spatially Homogeneous SEI toward High Performance SiO_x Anode^†

Wang,

Wu,

Niu

et al. 2024

Chin. J. Chem.

View full text Add to dashboard Cite

show abstract

Development of hybrid ANFIS-GAN-XGBOOST models for accurate prediction of material removal rates from PCB-polluted concrete surfaces using laser technology for sustainable energy generation

Pang,

Li,

Al_Tamimi

et al. 2023

Advances in Engineering Software

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Innovative composite machine learning approach for biodiesel production in public vehicles

Yang,

Gao,

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Forecasting soybean oil extraction using cyclopentyl methyl ether through soft computing models with a density functional theory study

Cited by 9 publications

References 74 publications

Efficient Chemical Prelithiation with Modificatory Li⁺ Solvation Structure Enabling Spatially Homogeneous SEI toward High Performance SiO_x Anode^†

Efficient Chemical Prelithiation with Modificatory Li⁺ Solvation Structure Enabling Spatially Homogeneous SEI toward High Performance SiO_x Anode^†

Development of hybrid ANFIS-GAN-XGBOOST models for accurate prediction of material removal rates from PCB-polluted concrete surfaces using laser technology for sustainable energy generation

Innovative composite machine learning approach for biodiesel production in public vehicles

Contact Info

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Forecasting soybean oil extraction using cyclopentyl methyl ether through soft computing models with a density functional theory study

Cited by 9 publications

References 74 publications

Efficient Chemical Prelithiation with Modificatory Li+ Solvation Structure Enabling Spatially Homogeneous SEI toward High Performance SiOx Anode†

Efficient Chemical Prelithiation with Modificatory Li+ Solvation Structure Enabling Spatially Homogeneous SEI toward High Performance SiOx Anode†

Development of hybrid ANFIS-GAN-XGBOOST models for accurate prediction of material removal rates from PCB-polluted concrete surfaces using laser technology for sustainable energy generation

Innovative composite machine learning approach for biodiesel production in public vehicles

Contact Info

Product

Resources

About

Efficient Chemical Prelithiation with Modificatory Li⁺ Solvation Structure Enabling Spatially Homogeneous SEI toward High Performance SiO_x Anode^†

Efficient Chemical Prelithiation with Modificatory Li⁺ Solvation Structure Enabling Spatially Homogeneous SEI toward High Performance SiO_x Anode^†