Literature DB >> 27569053

Ab Initio-Based Bond Order Potential to Investigate Low Thermal Conductivity of Stanene Nanostructures.

Mathew J Cherukara, Badri Narayanan, Alper Kinaci, Kiran Sasikumar, Stephen K Gray1, Maria K Y Chan1, Subramanian K R S Sankaranarayanan1.   

Abstract

We introduce a bond order potential (BOP) for stanene based on an ab initio derived training data set. The potential is optimized to accurately describe the energetics, as well as thermal and mechanical properties of a free-standing sheet, and used to study diverse nanostructures of stanene, including tubes and ribbons. As a representative case study, using the potential, we perform molecular dynamics simulations to study stanene's structure and temperature-dependent thermal conductivity. We find that the structure of stanene is highly rippled, far in excess of other 2-D materials (e.g., graphene), owing to its low in-plane stiffness (stanene: ∼ 25 N/m; graphene: ∼ 480 N/m). The extent of stanene's rippling also shows stronger temperature dependence compared to that in graphene. Furthermore, we find that stanene based nanostructures have significantly lower thermal conductivity compared to graphene based structures owing to their softness (i.e., low phonon group velocities) and high anharmonic response. Our newly developed BOP will facilitate the exploration of stanene based low dimensional heterostructures for thermoelectric and thermal management applications.

Entities:  

Year:  2016        PMID: 27569053     DOI: 10.1021/acs.jpclett.6b01562

Source DB:  PubMed          Journal:  J Phys Chem Lett        ISSN: 1948-7185            Impact factor:   6.475


  5 in total

1.  Machine Learning Force Field Parameters from Ab Initio Data.

Authors:  Ying Li; Hui Li; Frank C Pickard; Badri Narayanan; Fatih G Sen; Maria K Y Chan; Subramanian K R S Sankaranarayanan; Bernard R Brooks; Benoît Roux
Journal:  J Chem Theory Comput       Date:  2017-09-01       Impact factor: 6.006

2.  Thermal transport characterization of carbon and silicon doped stanene nanoribbon: an equilibrium molecular dynamics study.

Authors:  Ishtiaque Ahmed Navid; Samia Subrina
Journal:  RSC Adv       Date:  2018-09-12       Impact factor: 4.036

3.  Stability of Strained Stanene Compared to That of Graphene.

Authors:  Igor V Kosarev; Sergey V Dmitriev; Alexander S Semenov; Elena A Korznikova
Journal:  Materials (Basel)       Date:  2022-08-26       Impact factor: 3.748

4.  Three-dimensional X-ray diffraction imaging of dislocations in polycrystalline metals under tensile loading.

Authors:  Mathew J Cherukara; Reeju Pokharel; Timothy S O'Leary; J Kevin Baldwin; Evan Maxey; Wonsuk Cha; Jorg Maser; Ross J Harder; Saryu J Fensin; Richard L Sandberg
Journal:  Nat Commun       Date:  2018-09-17       Impact factor: 14.919

5.  Bandgap prediction of two-dimensional materials using machine learning.

Authors:  Yu Zhang; Wenjing Xu; Guangjie Liu; Zhiyong Zhang; Jinlong Zhu; Meng Li
Journal:  PLoS One       Date:  2021-08-13       Impact factor: 3.240

  5 in total

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