Predicting the mold-glass interface adhesion in thermal molding

• Developed a novel formula for rapid prediction of adhesion forces. • Revealed how glass molding conditions and glass properties influence adhesion. • Pinpointed molding temperature as the key factor governing adhesion. • Discovered the atomic-level mechanisms behind adhesion behavior. Adhesion between a mold and a glass workpiece during demolding remains a significant challenge in precision glass molding, limiting process efficiency and product quality. Although previous studies have examined factors influencing adhesion, they are limited and predominantly qualitative, lacking a reliable framework to predict adhesion force across different mold-glass systems. This study develops a new dimensionless formulation incorporating twelve key variables to quantify the relationship between molding factors and adhesion force. The model is established through molding experiments on d-FK95 glass with three distinct mold materials, complemented by molecular dynamics simulations. The study evaluates contributions from molding parameters, glass Young's modulus, viscosity, and thermodynamic adhesion work, with atomistic interaction energy analyses at varied molding temperatures. DLC molds demonstrate superior anti-adhesion performance compared to WC and AlCrN due to their lower surface energy and amorphous structure. The model identifies molding temperature as the dominant factor, with an exponent of 42.85, followed by demolding temperature and molding force. The accuracy and applicability of the model are validated through a comparison between experimental data and fitted values for two different mold materials. The results show that the proposed model demonstrates high applicability, underscoring the critical role of precise molding parameter control in minimizing adhesion-induced defects.

Authors

Institutions

Publication Details

Journal
International Journal of Mechanical Sciences
Published
2025-04-14
DOI
https://doi.org/10.1016/j.ijmecsci.2025.110265
Citations
8
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
9.94
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predicting the mold-glass interface adhesion in thermal molding

Hanhan Zhao, Asit Kumar Gain, Zhen Li, Liangchi Zhang
8 citations
International Journal of Mechanical Sciences
Manufacturing Process and Optimization
9.94
article

Predicting the mold-glass interface adhesion in thermal molding

Hanhan Zhao, Asit Kumar Gain, Zhen Li, Liangchi Zhang
article en
8 citations

Abstract

• Developed a novel formula for rapid prediction of adhesion forces. • Revealed how glass molding conditions and glass properties influence adhesion. • Pinpointed molding temperature as the key factor governing adhesion. • Discovered the atomic-level mechanisms behind adhesion behavior. Adhesion between a mold and a glass workpiece during demolding remains a significant challenge in precision glass molding, limiting process efficiency and product quality. Although previous studies have examined factors influencing adhesion, they are limited and predominantly qualitative, lacking a reliable framework to predict adhesion force across different mold-glass systems. This study develops a new dimensionless formulation incorporating twelve key variables to quantify the relationship between molding factors and adhesion force. The model is established through molding experiments on d-FK95 glass with three distinct mold materials, complemented by molecular dynamics simulations. The study evaluates contributions from molding parameters, glass Young's modulus, viscosity, and thermodynamic adhesion work, with atomistic interaction energy analyses at varied molding temperatures. DLC molds demonstrate superior anti-adhesion performance compared to WC and AlCrN due to their lower surface energy and amorphous structure. The model identifies molding temperature as the dominant factor, with an exponent of 42.85, followed by demolding temperature and molding force. The accuracy and applicability of the model are validated through a comparison between experimental data and fitted values for two different mold materials. The results show that the proposed model demonstrates high applicability, underscoring the critical role of precise molding parameter control in minimizing adhesion-induced defects.

International Journal of Mechanical SciencesVol. 294
Shenzhen University (CN), Southern University of Science and Technology (CN), Sustainable Innovation (Sweden) (SE)
Affordable and clean energy
Openalex Percentile: Top 2%
Manufacturing Process and Optimization
9.94
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.