Property Prediction Model Built for Copper Alloys

Property Prediction Model Built for Copper Alloys | News

Mitsubishi Materials Corporation and the National Institute for Materials Science have developed a new property prediction model for copper ...

A property-oriented design strategy for high performance copper ...

The first BP NN (C2P) model is trained to predict properties of UTS and EC from compositions of copper alloys on a condition of keeping the ...

Revealing the structure-property relationships of copper alloys with ...

Our FAGC method has shown remarkable results, significantly improving the accuracy of predicting the electronic conductivity and hardness of Cu-Cr-Zr alloys, ...

Predictive Modeling and Analysis of Cu–Be Alloys - MDPI

Cu–Be alloys are renowned for their exceptional mechanical and electrical properties, making them highly sought after for various industrial applications.

Introducing explainable artificial intelligence to property prediction in ...

Historical data for as-built Ti-6Al-4 V alloy manufactured via selective laser melting (SLM) was mined to generate a comprehensive dataset. Robust Gaussian ...

A property-oriented design strategy for high performance copper ...

There exists a good consistency between the predicted and measured values for three alloys from literatures and two newly made alloys with designed compositions ...

An improved composition design method for high-performance ...

In this paper, a total of 407 copper alloy data were collected. In the multi-objective prediction problem, the many-to-many prediction using ...

(PDF) Predictive Modeling and Analysis of Cu–Be Alloys: Insights ...

This study presents a comprehensive approach to predicting the compositions of various types of Cu–Be alloys, integrating a Random Forest ...

Accelerated composition-process-properties design of precipitation ...

The material design strategy for the multi-performance optimization of Cu-Ni-Si alloy through Bayesian optimization was proposed. This work ...

Machine-learning-assisted prediction of the mechanical properties ...

Specifically, its predictions exhibited the highest correlation coefficient and lowest error among the predictions of the six models. The SMOreg ...

(PDF) An improved composition design method for high ...

The overall coefficient of determination reached 0.87, the prediction effect was better than the original MLDS model and with stronger stability ...

An improved composition design method for high-performance ...

In order to predict the tensile strength and electrical con- ductivity of copper alloys according to the alloy composition, a composition to property model was ...

Intelligent Design of High Strength and High Conductivity Copper ...

Thus, these newly generated datasets were coupled with suitable ML model for property-to-composition prediction. Several of the predicted alloy compositions ...

An Effective Framework for Predicting Performance of Solid-Solution ...

Utilized extensively in a myriad of industries, solid-solution copper alloys are prized for their superior electrical conductivity and mechanical properties ...

Using AI to predict new materials with desired properties

This trains the model to understand relationships between alloys' mechanical properties and the different elements they are made of, as well as the type of heat ...

Deep image learning of quantitative structure-property relationships ...

The paper introduces a deep learning framework for predicting quantitative structure-property relationships of copper alloys. The core ...

Machine learning-guided design and development of metallic ...

More specifically, the C2P (i.e., composition → property) model predicts the properties of alloys from their compositions, while the P2C (i.e., property → ...

A Knowledge Transfer Framework for General Alloy Materials ... - NCBI

The prediction of alloy material properties is also one of the topics promoted by computational science. Combined with model-based theoretical ...

Comprehensive elemental screening of solid-solution copper alloys

The other model (using the first model as a feature with elemental features) has a high prediction performance for the testing set. Combining the predicted ...

Predicting the optimum compositions of high-performance Cu–Zn ...

In other words, they can represent the prediction ability of MLFFANN models for Cu–Zn alloys with random composition at the same process. Table ...