A Generalized Automated Framework for Thermal Characterization: From Bulk Materials to Complex Heterostructures

ABSTRACT Precise determination of thermal conductivity in multilayer structures remains a critical challenge for advancing thermoelectric technologies. Conventional techniques often struggle with surface roughness or require complex preparation, hindering the characterization of electrodeposited materials. To address this gap, a fully automated, MATLAB‐based computational framework operationalizing the generalized photoacoustic theory for a robust inverse analysis is presented. The methodology is rigorously benchmarked against Bi 2 Te 3 /3D anodic aluminum oxide (3D‐AAO) reference nanocomposites, reproducing established literature values with high fidelity. Subsequently, the capability of this framework is demonstrated through the characterization of electrodeposited copper selenide (Cu x Se) films. Results reveal a systematic dependence of thermal conductivity on copper stoichiometry, offering insights into anharmonicity‐driven phonon scattering mechanisms. Comprehensive sensitivity analyses confirm that the photoacoustic signal is predominantly dominated by the film's thermal conductivity. Thus, this work delivers an accessible, validated tool for in situ characterization of structurally non‐ideal films, accelerating next‐generation energy material development.

Authors

Institutions

Publication Details

Journal
Small
Published
2026-05-17
DOI
https://doi.org/10.1002/smll.73824
Primary Topic
Thermal properties of materials
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Generalized Automated Framework for Thermal Characterization: From Bulk Materials to Complex Heterostructures

Olga Caballero‐Calero, Miguel Ángel Tenaguillo, Elena Pérez-Picazo, Marisol Martín-González et al.
Small
Thermal properties of materials
article

A Generalized Automated Framework for Thermal Characterization: From Bulk Materials to Complex Heterostructures

Olga Caballero‐Calero, Miguel Ángel Tenaguillo, Elena Pérez-Picazo, Marisol Martín-González, Cristina V. Manzano
article en

Abstract

ABSTRACT Precise determination of thermal conductivity in multilayer structures remains a critical challenge for advancing thermoelectric technologies. Conventional techniques often struggle with surface roughness or require complex preparation, hindering the characterization of electrodeposited materials. To address this gap, a fully automated, MATLAB‐based computational framework operationalizing the generalized photoacoustic theory for a robust inverse analysis is presented. The methodology is rigorously benchmarked against Bi 2 Te 3 /3D anodic aluminum oxide (3D‐AAO) reference nanocomposites, reproducing established literature values with high fidelity. Subsequently, the capability of this framework is demonstrated through the characterization of electrodeposited copper selenide (Cu x Se) films. Results reveal a systematic dependence of thermal conductivity on copper stoichiometry, offering insights into anharmonicity‐driven phonon scattering mechanisms. Comprehensive sensitivity analyses confirm that the photoacoustic signal is predominantly dominated by the film's thermal conductivity. Thus, this work delivers an accessible, validated tool for in situ characterization of structurally non‐ideal films, accelerating next‐generation energy material development.

Small
Institute of Micro and Nanotechnology (ES), Universidad Autónoma de Madrid (ES)
Affordable and clean energy
Openalex Percentile: Top 12%
Thermal properties of materials
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.