Design, construction, and operation of a 2 T 240 mm conduction-cooled defect-irrelevant winding (RE) Ba2Cu3O7-x magnet.

In order to explore the applicability of superconducting magnets in a magnetic field range of 3 T or less, where superconducting magnets have not been much used so far, a prototype magnet development project has been launched in collaboration with Hanmi Techwin Corporation and Seoul National University. As a result of the project, here we report the design, construction, and operation results of a 2 T 240 mm defect-irrelevant winding (DIW) (RE) Ba2Cu3O7-x (REBCO) magnet. First, design goals were set considering its potential usage in industrial fields, and a 2 T 240 mm-bore multi-width no-insulation high-temperature superconductor magnet was designed accordingly. Based on the design, a total of 15 double pancake (DP) coils were wound, regardless of defects in REBCO tapes, and assembled together. After being installed in a conduction cooling system, the magnet was tested at a temperature of <20 K, and a magnetic field of 2 T at the magnet center was successfully generated with a total of four DP coils containing multiple defects. Based on the experimental results, the additional considerations required for the DIW approach at the magnet level are discussed.

Adaptive Learning Framework in Prediction and Validation of Gibbs Free Energy for Inorganic Crystalline Solids.

Gibbs free energy is a fundamental physical property for understanding the stability and synthesizability of materials under various thermodynamic conditions, but its accessibility and availability are still limited. In this study, we used 9880 phonon databases to construct a machine learning model to predict approximately 40 000 Inorganic Crystalline Solid Database (ICSD) materials, whose free energy information has not been fully explored. To improve the prediction accuracy, a sampling strategy was implemented by including structures with low accuracy metrics, leading to R2 and mean absolute error values of 0.99 and 18.7 kJ/mol, respectively, in the testing set. Uncertainty analysis was followed for unexplored ICSD materials by obtaining the standard deviation in predictions from 10 surrogate models with different samplings in the training set. Based on this, an optimization process was conducted: density functional calculations were performed for 50 structures with high uncertainty and the training database was updated; this loop was repeated 15 times. This demonstrates the reduction and saturation in the uncertainty, confirming that the constructed model can provide a comprehensive map of the Gibbs free energy for inorganic solid materials. This can accelerate the material screening process by providing information on thermodynamic stability.