5 papers
Higher-Order-Phonon Scattering Governs Targeted Control of Heat Conduction in Bulk Boron Arsenide
Tianhao Li, Yangjun Qin, Dongkai Pan +3
Conventional approaches for modulating thermal conductivity usually rely on structural modifications and therefore cannot achieve reversible in situ regulation. Targeted phonon exc…
Machine learning potential for predicting thermal conductivity of θ-phase and amorphous Tantalum Nitride
Zhicheng Zong, Yangjun Qin, Jiahong Zhan +2
Tantalum nitride (TaN) has attracted considerable attention due to its unique electronic and thermal properties, high thermal conductivity, and applications in electronic component…
Unveiling the thermal transport mechanism in compressed plastic crystals assisted by deep potential
Yangjun Qin, Zhicheng Zong, Junwei Che +3
The unique properties of plastic crystals highlight their potential for use in solid-state refrigeration. However, their practical applications are limited by thermal hysteresis du…
Deep potential for interaction between hydrated Cs+ and graphene
Yangjun Qin, Liuhua Mu, Xiao Wan +3
The influence of hydrated cation-Ï interaction forces on the adsorption and filtration capabilities of graphene-based membrane materials is significant. However, the lack of inter…
The effect of dataset size and the process of big data mining for investigating solar-thermal desalination by using machine learning
Guilong Peng, Senshan Sun, Zhenwei Xu +6
Machine learning's application in solar-thermal desalination is limited by data shortage and inconsistent analysis. This study develops an optimized dataset collection and analysis…