most citedMachine learning for predicting fatigue properties of additively manufactured materials

3 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cond-mat.mtrl-sci2023

Magnetocaloric effect and its electric-field regulation in CrI/metal heterostructure

Weiwei He, Ziming Tang, Qihua Gong +2

The extraordinary properties of a heterostructure by stacking atom-thick van der Waals (vdW) magnets have been extensively studied. However, the magnetocaloric effect (MCE) of hete…

cond-mat.mtrl-sci20233 cited

Machine learning for predicting fatigue properties of additively manufactured materials

Min Yi, Ming Xue, Peihong Cong +6

Fatigue properties of additively manufactured (AM) materials depend on many factors such as AM processing parameter, microstructure, residual stress, surface roughness, porosities,…

cond-mat.mtrl-sci2023

Monolayer polar metals with large piezoelectricity derived from MoSiN

Yan Yin, Qihua Gong, Min Yi +1

The advancement of two-dimensional polar metals tends to be limited by the incompatibility between electric polarity and metallicity as well as dimension reduction. Here, we report…

cond-mat.mtrl-sci20231 cited

Giant magnetocaloric effect in magnets down to the monolayer limit

Weiwei He, Yan Yin, Qihua Gong +5

Two-dimensional magnets could potentially revolutionize information technology, but their potential application to cooling technology and magnetocaloric effect (MCE) in a material…

cond-mat.mtrl-sci2023

Thermodynamically consistent non-isothermal phase-field modelling of elastocaloric effect: indirect vs direct method

Wei Tang, Qihua Gong, Min Yi +2

Modelling elastocaloric effect (eCE) is crucial for the design of environmentally friendly and energy-efficient eCE based solid-state cooling devices. Here, a thermodynamically con…