Long-term stability of phase-separated half-Heusler compounds

Literature Information

Publication Date 2015-10-15
DOI 10.1039/C4CP04875J
Impact Factor 3.676
Authors

B. Balke, S. Ouardi, S. Selle, T. Höche, C. Felser, W. Hermes, M. Schwind


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Abstract

Half-Heusler (HH) compounds have shown high figure of merit up to 1.5. Here, we address the long-term stability of n- and p-type HH materials. For this purpose, we investigated HH materials based on the Ti0.3Zr0.35Hf0.35NiSn-system after 500 cycles (1700 h) from 373 to 873 K. Both compounds exhibit a maximum Seebeck coefficient of |α| ≈ 210 μV K−1 and a phase separation into two HH phases. The dendritic microstructure is temperature resistant and upon cycling the changes in the microstructure are so marginal that the low thermal conductivity values (κ < 4 W m−1 K−1) could be maintained. Our results emphasize that phase-separated HH compounds are suitable low cost materials and can lead to enhanced thermoelectric efficiencies beyond the set benchmark for industrial applications.

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Back cover

Cover

DOI: 10.1039/C7AN90037F

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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