Quantitative Characterization of Local Thermal Properties in Thermoelectric Ceramics Using "Jumping-Mode" Scanning Thermal Microscopy

resumo

Thermoelectric conversion may take a significant share in future energy technologies. Oxide-based thermoelectric composite ceramics attract attention for promising routes for control of electrical and thermal conductivity for enhanced thermoelectric performance. However, the variability of the composite properties responsible for the thermoelectric performance, despite nominally identical preparation routes, is significant, and this cannot be explained without detailed studies of thermal transport at the local scale. Scanning thermal microscopy (SThM) is a scanning probe microscopy method providing access to local thermal properties of materials down to length scales below 100 nm. To date, realistic quantitative SThM is shown mostly for topographically very smooth materials. Here, methods for SThM imaging of bulk ceramic samples with relatively rough surfaces are demonstrated. "Jumping mode" SThM (JM-SThM), which serves to preserve the probe integrity while imaging rough surfaces, is developed and applied. Experiments with real thermoelectric ceramics show that the JM-SThM can be used for meaningful quantitative imaging. Quantitative imaging is performed with the help of calibrated finite-elements model of the SThM probe. The modeling reveals non-negligible effects associated with the distributed nature of the resistive SThM probes used; corrections need to be made depending on probe-sample contact thermal resistance and probe current frequency.

palavras-chave

TRANSPORT-PROPERTIES; CONDUCTIVITY

categoria

Chemistry; Science & Technology - Other Topics; Materials Science

autores

Alikin, D; Zakharchuk, K; Xie, WJ; Romanyuk, K; Pereira, MJ; Arias-Serrano, BI; Weidenkaff, A; Kholkin, A; Kovalevsky, AV; Tselev, A

nossos autores

agradecimentos

The authors acknowledge Sergei Nesterov and Vasiliy Komkov (Techno-NT, Netherlands) for the help with SPM tuning and Claudio Duran Alarcon (University of Aveiro) for the help with Python programming. This work was supported by project POCI-01-0145-FEDER-032117 financed by the COMPETE 2020 Program and National Funds through the FCT/MEC and when applicable co-financed by FEDER under the PT2020 Partnership Agreement and project CICECO-Aveiro Institute of Materials, UIDB/50011/2020, UIDP/50011/2020 and LA/P/0006/2020, financed by national funds through the FCT/MCTES (PIDDAC). K.R. acknowledges support funded by national funds (OE) through FCT - Fundacao para a Ciencia e a Tecnologia, I.P., in the scope of the framework contract foreseen in the numbers 4, 5, and 6 of the articles 23, of the Decree-Law 57/2016, of August 29, changed by Law 57/2017, of July 19. A.T. acknowledges individual support by the 2021.03599.CEECIND through national funds provided by FCT - Fundacao para a Ciencia e a Tecnologia. W.X. and A.W. acknowledge the support by DAAD through DAAD Foerderprogramme (Project-ID: 57610929).

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