Molecular dynamics study of thermal conductivities of cubic diamond,lonsdaleite,and nanotwinned diamond via machine-learned potential

Diamond is a wide-bandgap semiconductor with a variety of crystal configurations,and has the potential applications in the field of high-frequency,radiation-hardened,and high-power devices.There are several important polytypes of diamonds,such as cubic diamond,lonsdaleite,and nanotwinned diamond(NTD).The thermal conductivities of semiconductors in high-power devices at different temperatures should be calculated.However,there has been no reports about thermal conductivities of cubic diamond and its polytypes both efficiently and accurately based on molecular dynamics(MD).Here,using interatomic potential of neural networks can provide obvious advantages.For example,comparing with the use of density functional theory(DFT),the calculation time is reduced,while maintaining high accuracy in predicting the thermal conductivities of the above-mentioned three diamond polytypes.Based on the neuroevolution potential(NEP),the thermal conductivities of cubic diamond,lonsdaleite,and NTD at 300 K are respectively 2507.3 W·m^(-1)·K^(-1),1557.2 W·m^(-1)·K^(-1),and 985.6 W·m^(-1)·K^(-1),which are higher than the calculation results based on Tersoff-1989 potential(1508 W·m^(-1)·K^(-1),1178 W·m^(-1)·K^(-1),and 794 W·m^(-1)·K^(-1),respectively).The thermal conductivities of cubic diamond and lonsdaleite,obtained by using the NEP,are closer to the experimental data or DFT data than those from Tersoff-potential.The molecular dynamics simulations are performed by using NEP to calculate the phonon dispersions,in order to explain the possible reasons for discrepancies among the cubic diamond,lonsdaleite,and NTD.In this work,we propose a scheme to predict the thermal conductivity of cubic diamond,lonsdaleite,and NTD precisely and efficiently,and explain the differences in thermal conductivity among cubic diamond,lonsdaleite,and NTD.

Mechanism of cancer-induced fatigue

Cancer related fatigue(CRF)is one of the most common and painful reactions in cancer patients.Due to the negative effects of cancer itself and long-term treatment,patients often feel continuous burnout,fatigue and powerlessness in both mental and physical aspects.Fatigue related to cancer and cancer treatment will affect the physical and mental health of cancer patients for a long time and continuously,and it is hard to be relieved through rest.Nowadays,most of the researches focus on the clinical manifestations of patients with cancer,such as pain,nausea and vomiting,weight loss and so on.The fatigue feeling of cancer patients is often one of the most easily overlooked pain symptoms in the treatment process.The influence of CRF on cancer patients may be one of the reasons for reducing the survival time of cancer patients.This paper aims to summarize and explore the pathogenesis of cancer-related fatigue,in order to analyze the related factors of cancer-related fatigue from multi-dimensional and multi-angle,and provide reference for its comprehensive treatment in clinic.