Low-Temperature Sealing Material Database and Optimization Prediction Based on AI and Machine Learning

database[Title] 2025-05-14

Summary:

Optimization of low-temperature sealing materials is of great significance to improving low-temperature performance and durability. This study leverages DeepSeek-v3 (DS) and GPT-generated data and applies machine learning methods, including XGBoost and neural networks, to perform 3D prediction and analysis of key properties of low temperature sealing materials. Data expansion techniques were employed to enhance data quality and improve model prediction accuracy. Additionally, the study evaluates...

Link:

https://pubmed.ncbi.nlm.nih.gov/40363015/?utm_source=Other&utm_medium=rss&utm_campaign=pubmed-2&utm_content=12QQbiNmM99eUQGIX1JjHIKcROC1Vzv4sOS-2S_LNI19uG_Yrk&fc=20220129225649&ff=20250514140921&v=2.18.0.post9+e462414

From feeds:

📚BioDBS Bibliography » database[Title]

Tags:

Authors:

Honghao Jia, Zhongxu Tai, Rui Lyu, Kousuke Ishikawa, Yixiao Sun, Jianting Cao, Dongying Ju

Date tagged:

05/14/2025, 14:09

Date published:

05/14/2025, 06:00