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Filtering by: Computational methods machine learning Type of work Dataset Keyword Coercivity Keyword Machine learning Publisher National Institute for Materials Science Rights Statement Sim MIT License

Process parameters and magnetic properties (coercivity, remanence, squareness, maximum energy product) of data-driven fabrication of Nd-Fe-B anisotropic magnets by direct hot extrusion.

Description/Abstract:

We implemented an active learning pipeline assisted by machine learning and Bayesian optimization (ALMLBO) for predicting magnetic proper...

Keyword:

Active learning, Machine learning, Bayesian Optimization, Nd-Fe-B magnet, Hot extrusion, Process, Coercivity, Remanence, Squareness, and Maximum energy product

Material/Specimen:

Anisotropic permanent magnets fabricated by hot extrusion using a commercial Nd14Fe76Co3.4B6Ga0.6 (at%) powder (MQU-F™)

Resource Type:

Dataset

Data origin:

experiments

Author:

Lambard, Guillaume, Sasaki, Taisuke, Sodeyama, Keitaro, Ohkubo, Tadakatsu, and Hono, Kazuhiro

Operator:

PRYTULIAK, Anastasiia and TOYOOKA, Yoshiya

Date Uploaded:

11/05/2021

Date Modified:

11/10/2021

Process parameters and magnetic properties (coercivity, remanence, squareness, maximum energy product) of data-driven fabrication of Nd-Fe-B anisotropic magnets by direct hot extrusion.

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