Alignment of edge dislocations – the reason lying behind composition inhomogeneity induced low thermal conductivity

Compositional inhomogeneity in a material can result in low thermal conductivity, benefiting applications such as thermoelectric energy conversion, energy gas storage, and thermal barrier coating. However, current understanding remains limited to effective thermal conductivity models, which largely overlook detailed structural features of the material. Here, taking Bi<sub>0.4</sub>Sb<sub>1.6</sub>Te<sub>3</sub> compound as a proof-of-concept material, we reveal that the true reason for low thermal conductivity determined by compositional inhomogeneity originates from randomly aligned edge dislocations. The random alignment of edge dislocations is consistent with the alignment of composition distribution. This is because these edge dislocations are primarily gathered at composition gradient domains between domains with different compositions, having preferential orientation along the composition gradient direction. This work offers a structural perspective on the mechanism underlying reduced thermal conductivity due to compositional inhomogeneity, providing valuable insights for designing materials with tailored thermal properties.

Authors

Institutions

Publication Details

Journal
Nature Communications
Published
2025-11-05
DOI
https://doi.org/10.1038/s41467-025-64749-5
Citations
9
Primary Topic
Thermal properties of materials
Type
article
Field-Weighted Citation Impact
4.66

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Alignment of edge dislocations – the reason lying behind composition inhomogeneity induced low thermal conductivity

Xiao‐Lei Shi, Wei‐Di Liu, James D. Riches, Wanyu Lyu et al.
9 citations
Nature Communications
Thermal properties of materials
4.66
article

Alignment of edge dislocations – the reason lying behind composition inhomogeneity induced low thermal conductivity

Xiao‐Lei Shi, Wei‐Di Liu, James D. Riches, Wanyu Lyu, Liang‐Cao Yin, Dmitri Golberg, Zhi‐Gang Chen, Qingfeng Liu, Siqi Liu, Meng Li, Han Gao, Yicheng Yue, Ning Wang
article en
9 citations

Abstract

Compositional inhomogeneity in a material can result in low thermal conductivity, benefiting applications such as thermoelectric energy conversion, energy gas storage, and thermal barrier coating. However, current understanding remains limited to effective thermal conductivity models, which largely overlook detailed structural features of the material. Here, taking Bi<sub>0.4</sub>Sb<sub>1.6</sub>Te<sub>3</sub> compound as a proof-of-concept material, we reveal that the true reason for low thermal conductivity determined by compositional inhomogeneity originates from randomly aligned edge dislocations. The random alignment of edge dislocations is consistent with the alignment of composition distribution. This is because these edge dislocations are primarily gathered at composition gradient domains between domains with different compositions, having preferential orientation along the composition gradient direction. This work offers a structural perspective on the mechanism underlying reduced thermal conductivity due to compositional inhomogeneity, providing valuable insights for designing materials with tailored thermal properties.

Nature CommunicationsVol. 16(1)
Nanjing Tech University (CN), Qingdao University of Science and Technology (CN), Queensland University of Technology (AU), National Institute for Materials Science (JP), Zhengzhou University (CN)
National Computational Infrastructure, Australian Government
Openalex Percentile: Top 4%
Thermal properties of materials
4.66
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.