Author Page for Zhongyang Dai

Light-Responsive Friction Control and Superlubricity on Tio2 Surfaces with Layered Ionic Liquids: Reversible Changes and High-Pressure Performance

Number of pages: 34 Posted: 11 Jun 2025

Qilong Zhou, Zhongyang Dai, Tao Jin, Zehui Liu, Aatto Laaksonen, Jiahua Zhu, Xiaohua Lu and Liwen Mu

Nanjing Tech University, affiliation not provided to SSRN, Nanjing Tech University, Nanjing Tech University, Stockholm University, Nanjing Tech University, Nanjing Tech University and Nanjing Tech University

Downloads 20 (1,459,862)

Abstract:

2.

High-precision prediction of nanoscale friction in ionic liquid films at solid interfaces by region-adaptive hybrid learning

Number of pages: 35 Posted: 04 Apr 2026

Fangfang Wang, Ziyi Wang, Zhongyang Dai, Aatto Laaksonen, Francesca Mocci, Enrico Gnecco and Rong An

Nanjing University of Science and Technology, Nanjing University of Science and Technology, affiliation not provided to SSRN, Stockholm University, affiliation not provided to SSRN, affiliation not provided to SSRN and Nanjing University of Science and Technology

Downloads 8 (1,561,096)

Abstract:

3.

Region-Adaptive Hybrid Learning Framework Enables High-Precision Prediction of Nanoscale Friction in Interfacial Ionic Liquids

Number of pages: 34 Posted: 29 May 2026

Fangfang Wang, Ziyi Wang, Zhongyang Dai, Aatto Laaksonen, Francesca Mocci, Enrico Gnecco and Rong An

Nanjing University of Science and Technology, Nanjing University of Science and Technology, affiliation not provided to SSRN, Stockholm University, affiliation not provided to SSRN, affiliation not provided to SSRN and Nanjing University of Science and Technology

Downloads 6 (1,579,934)

Zhongyang Dai

affiliation not provided to SSRN

3

34

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Scholarly Papers (3)

Light-Responsive Friction Control and Superlubricity on Tio2 Surfaces with Layered Ionic Liquids: Reversible Changes and High-Pressure Performance

Abstract:

High-precision prediction of nanoscale friction in ionic liquid films at solid interfaces by region-adaptive hybrid learning

Abstract:

Region-Adaptive Hybrid Learning Framework Enables High-Precision Prediction of Nanoscale Friction in Interfacial Ionic Liquids​

Abstract:

Region-Adaptive Hybrid Learning Framework Enables High-Precision Prediction of Nanoscale Friction in Interfacial Ionic Liquids