Thermal Transport in SrSnO ₃ Revealed by First-principles Theory, Raman Thermometry and Machine Learning

Santosh  Kumar Sahu; Sandip Kumar Padhi; Rasmi  Ranjan Mohapatra; Prahallad Padhan

doi:10.1039/d6ta02865a

January 1, 2026Journal of Materials Chemistry A

Thermal Transport in SrSnO ₃ Revealed by First-principles Theory, Raman Thermometry and Machine Learning

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Key Points

This research aims to investigate the thermal transport properties of SrSnO3 using advanced methodologies.
Utilized Raman thermometry and laser flash analysis (LFA) for thermal conductivity measurements.
Employed first-principles calculations based on density functional theory (DFT).
Leveraged machine learning techniques to analyze the data and improve predictions.
Demonstrated significant variations in thermal conductivity across different conditions.
Identified correlations between experimental data and DFT calculations.
Machine learning analysis improved prediction accuracy for thermal transport properties.

Implication

Investigates thermal transport in SrSnO3, highlighting novel measurement techniques.

Abstract

The thermal conductivity (κ) of SrSnO 3 is systematically investigated using a comprehensive approach integrating Raman thermometry, laser flash analysis (LFA), first-principles calculations based on density functional theory (DFT) combined with...

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Cite This Study

Sahu et al. (2026) studied this question.

synapsesocial.com/papers/6a1fc6f7dee9eb8c0dce7c7c https://doi.org/10.1039/d6ta02865a

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Thermal Transport in SrSnO ₃ Revealed by First-principles Theory, Raman Thermometry and Machine Learning

Key Points

Implication

Abstract

Discussion

Cite This Study

Thermal Transport in SrSnO ₃ Revealed by First-principles Theory, Raman Thermometry and Machine Learning

Key Points

Implication

Abstract

Discussion

Cite This Study

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