First-principles prediction of high-performance thermoelectric nitrides

IF 3.1 3区 材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY
Xinxin Yan , Xuan Zheng , Wei Cao , Haohuan Li
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Abstract

Nitride thermoelectric materials have garnered significant research interest due to their abundant availability, low cost, and low toxicity. However, compared to traditional thermoelectric materials, the range of nitride-based options remains limited. In this study, we performed a systematic screening of potential nitride thermoelectric materials using first-principles calculations. The screening identified several promising candidates, including Ca3BiN, Sr3BiN, Sr3SbN, and LiZnN, all of which exhibit low lattice thermal conductivity (below 1 W/mK at 300 K). Subsequent evaluation of their thermoelectric properties revealed that Ca3BiN, Sr3BiN, and Sr3SbN show strong n-type and p-type performance, while LiZnN demonstrates enhanced p-type performance, attributed to its wider band gap, but poor n-type performance. Expanding the scope to A3BN (A = Mg, Ca, Sr; B = P, As, Sb, Bi) structures, we found that Mg-based compositions exhibited the best thermoelectric properties, following consistent trends across the examined structures. These results provide a theoretical basis for the development of high-performance nitride thermoelectric materials.

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来源期刊
Computational Materials Science
Computational Materials Science 工程技术-材料科学:综合
CiteScore
6.50
自引率
6.10%
发文量
665
审稿时长
26 days
期刊介绍: The goal of Computational Materials Science is to report on results that provide new or unique insights into, or significantly expand our understanding of, the properties of materials or phenomena associated with their design, synthesis, processing, characterization, and utilization. To be relevant to the journal, the results should be applied or applicable to specific material systems that are discussed within the submission.
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