Predicting the Properties of High-Performance Epoxy Resin by Machine Learning Using Molecular Dynamics Simulations
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Predicting the Properties of High-Performance Epoxy Resin by Machine Learning Using Molecular Dynamics Simulations
Authors
Keywords
-
Journal
Nanomaterials
Volume 12, Issue 14, Pages 2353
Publisher
MDPI AG
Online
2022-07-11
DOI
10.3390/nano12142353
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Artificial Neural Network Potential for Encapsulated Platinum Clusters in MOF-808
- (2022) Yangyang Yu et al. Journal of Physical Chemistry C
- Prediction of Lap Shear Strength and Impact Peel Strength of Epoxy Adhesive by Machine Learning Approach
- (2021) Haisu Kang et al. Nanomaterials
- Development of Mg/Al/Si/O ReaxFF Parameters for Magnesium Aluminosilicate Glass Using an Artificial Neural Network-Assisted Genetic Algorithm
- (2021) Jejoon Yeon et al. Journal of Physical Chemistry C
- Optimized Artificial Neural Network for Evaluation: C4 Alkylation Process Catalyzed by Concentrated Sulfuric Acid
- (2021) Yuntao Tian et al. ACS Omega
- Composition optimization of a high-performance epoxy resin based on molecular dynamics and machine learning
- (2020) Kai Jin et al. MATERIALS & DESIGN
- A Machine Learning Assisted Approach for Textile Formability Assessment and Design Improvement of Composite Components
- (2019) Clemens Zimmerling et al. COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING
- Simulation and design of energy materials accelerated by machine learning
- (2019) Hongshuai Wang et al. Wiley Interdisciplinary Reviews-Computational Molecular Science
- Fast and Accurate Artificial Neural Network Potential Model for MAPbI3 Perovskite Materials
- (2019) Hsin-An Chen et al. ACS Omega
- Prediction and optimization of epoxy adhesive strength from a small dataset through active learning
- (2019) Sirawit Pruksawan et al. SCIENCE AND TECHNOLOGY OF ADVANCED MATERIALS
- Diamine-functional bisphthalonitrile: Synthesis, characterization and its application in curing epoxy resin
- (2019) Caizhao Liu et al. EUROPEAN POLYMER JOURNAL
- Machine learning and the physical sciences
- (2019) Giuseppe Carleo et al. REVIEWS OF MODERN PHYSICS
- A Study on Curing Kinetics of Nano-Phase Modified Epoxy Resin
- (2018) Hailing Ma et al. Scientific Reports
- Rapid energy-efficient manufacturing of polymers and composites via frontal polymerization
- (2018) Ian D. Robertson et al. NATURE
- Structural vibration-based classification and prediction of delamination in smart composite laminates using deep learning neural network
- (2018) Asif Khan et al. COMPOSITES PART B-ENGINEERING
- Gas Lift Optimization Using Artificial Neural Network and Integrated Production Modeling
- (2017) Eissa Mohamed El-M. Shokir et al. ENERGY & FUELS
- A molecular dynamics study on the thermal transport properties and the structure of the solid–liquid interfaces between face centered cubic (FCC) crystal planes of gold in contact with linear alkane liquids
- (2017) Abdul Rafeq bin Saleman et al. INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
- Effects of Solid Fraction on Droplet Wetting and Vapor Condensation: A Molecular Dynamic Simulation Study
- (2017) Shan Gao et al. LANGMUIR
- A Comparison of a Machine Learning Model with EuroSCORE II in Predicting Mortality after Elective Cardiac Surgery: A Decision Curve Analysis
- (2017) Jérôme Allyn et al. PLoS One
- Sensitivity, Prediction Uncertainty, and Detection Limit for Artificial Neural Network Calibrations
- (2016) Franco Allegrini et al. ANALYTICAL CHEMISTRY
- Prediction of remission in obsessive compulsive disorder using a novel machine learning strategy
- (2015) Kathleen D. Askland et al. INTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH
- A Comparison of Barostats for the Mechanical Characterization of Metal–Organic Frameworks
- (2015) S.M.J. Rogge et al. Journal of Chemical Theory and Computation
- Machine learning: Trends, perspectives, and prospects
- (2015) M. I. Jordan et al. SCIENCE
- An artificial neural network ensemble method for fault diagnosis of proton exchange membrane fuel cell system
- (2014) Meng Shao et al. ENERGY
- Curing reaction of epoxy resin composed of mixed base resin and curing agent: Experiments and molecular simulation
- (2013) Tomonaga Okabe et al. POLYMER
- Artificial Neural Network Modeling of Surface Tension for Pure Organic Compounds
- (2011) Aliakbar Roosta et al. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
- Cellulose Whisker/Epoxy Resin Nanocomposites
- (2010) Liming Tang et al. ACS Applied Materials & Interfaces
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now