Computational Prediction of Superlubric Layered Heterojunctions.
ACS Appl Mater Interfaces
; 13(28): 33600-33608, 2021 Jul 21.
Article
in En
| MEDLINE
| ID: mdl-34213300
ABSTRACT
Structural superlubricity has attracted increasing interest in modern tribology. However, experimental identification of superlubric interfaces among the vast number of heterojunctions is a trial-and-error and time-consuming approach. In this work, based on the requirements on the in-plane stiffnesses of layered materials and the interfacial interactions at the sliding incommensurate interfaces of heterojunctions for structural superlubricity, we propose criteria for predicting structural superlubricity between heterojunctions. Based on these criteria, we identify 61 heterojunctions with potential superlubricity features from 208 candidates by screening the data of first-principles calculations. This work provides a universal route for accelerating the discovery of new superlubric heterojunctions.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Type of study:
Prognostic_studies
/
Risk_factors_studies
Language:
En
Journal:
ACS Appl Mater Interfaces
Journal subject:
BIOTECNOLOGIA
/
ENGENHARIA BIOMEDICA
Year:
2021
Document type:
Article
Affiliation country: