Index Catalog // MDR

Start Over

Filtering by: Author Lambard, Guillaume Computational methods machine learning Instrument manufacturer Zeiss Keyword Machine learning Publisher National Institute for Materials Science Resource type Dataset

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.

Limit your search

Type of work

Keyword

Language

Publisher

Resource type

Visibility

Rights Statement Sim

Computational methods

Data origin

Properties addressed

Synthesis and processing

Characterization methods

Material/Specimen

Author

Operator

Instrument manufacturer

Instrument model number

Search Constraints

Search Results

Limit your search