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Jianwei Guo

affiliation not provided to SSRN

SCHOLARLY PAPERS

4

DOWNLOADS

103

TOTAL CITATIONS

0

Scholarly Papers (4)

1.

Selective Removal of Aluminum Ion from Rare Earth Leaching Solution by Using Hydrotalcite as Solid Base

Number of pages: 24 Posted: 21 Mar 2024
affiliation not provided to SSRN, affiliation not provided to SSRN, Chongqing University, affiliation not provided to SSRN, affiliation not provided to SSRN and Chinese Academy of Sciences (CAS)
Downloads 33 (1,277,121)

Abstract:

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Rare earth, Aluminum ion impurities, Hydrotalcite, Selective removal, Solid base

2.

Application of Graphite Composite Slow Cooling Mold to Optimize the Composition and Microstructure of Ti-Si Alloy During Esr for Recycle Ti-Bearing Slag

Number of pages: 35 Posted: 12 Sep 2022
affiliation not provided to SSRN, North Minzu University, affiliation not provided to SSRN, Shenyang University of Technology, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, Jiangsu University of Science and Technology, North Minzu University and Chinese Academy of Sciences (CAS)
Downloads 27 (1,359,097)

Abstract:

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Ti-Si alloy, TBBFS, Electroslag remelting, Graphite composite slow cooling mold, Carbide reinforcement.

3.

Unveiling the Dual Tunability of Dimension and Pore Structure in Max-Derived Carbon Via Molten Salt Electrolysis

Number of pages: 33 Posted: 06 Oct 2023
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, Shenyang University of Technology, Shenyang University of Technology, affiliation not provided to SSRN, Shenyang University of Technology, affiliation not provided to SSRN, affiliation not provided to SSRN, Westlake University and Chinese Academy of Sciences (CAS)
Downloads 22 (1,424,331)

Abstract:

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MAX-derived carbon, tunable nanostructures, molten salt electrolysis, gas delamination, Li-ion Batteries

4.

Bridging the gap between empirical and rational design: machine learning framework for lithium ion-sieve performance prediction

Number of pages: 31 Posted: 12 Dec 2025
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, Chinese Academy of Sciences (CAS) and affiliation not provided to SSRN
Downloads 21 (1,436,435)

Abstract:

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Lithium ion-sieve、 Machine learning、 Adsorption prediction, 、Stacking ensemble、 SHAP analysis