Polypyrrole and Carbon Nanotube-Based Textile Thermoelectric Fabrics for the Development of 2D and 3D Energy-Harvesting Devices

Flexible wearable textile thermoelectric generators (TEGs) are developed from polypyrrole (PPy) coated cotton fabric as p-type and multiwall carbon nanotube (MWCNT) coated cotton fabric as n-type materials. An in situ chemical polymerization method is used to coat cotton fabrics with PPy in an aqueous medium, using ferric chloride as the oxidant. The MWCNT coating on cotton fabric is applied by using the brushing–coating–drying process. Thermocouples are developed using PPy-coated textiles as p-type conductors and MWCNT-coated fabrics as n-type conductors. Two different TEG designs, i.e., 2D (I-design) and 3D (Pie-design), are developed and evaluated for their electrical and thermoelectric properties, including output current versus output voltage, output current versus output power, power factor, figure of merit, and Seebeck coefficient. The electrical conductivities of 2D and 3D TEGs were measured as 56.422 and 12.833 S/m, respectively. Their maximum Seebeck coefficients are found to be 100.773 and 94.958 μV/K, respectively. Their highest power factors are achieved to be 572.99 × 10–3 μW m–1 K–2 and 115.72 × 10–3 μW m–1 K–2, respectively, and the highest figures of merit at an absolute temperature of 300 K are achieved to be 37.430 × 10–4 and 6.358 × 10–4, respectively.

Authors

Institutions

Publication Details

Journal
ACS Applied Energy Materials
Published
2026-03-28
DOI
https://doi.org/10.1021/acsaem.6c00410
Primary Topic
Advanced Thermoelectric Materials and Devices
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Polypyrrole and Carbon Nanotube-Based Textile Thermoelectric Fabrics for the Development of 2D and 3D Energy-Harvesting Devices

Prashant Vishnoi, Subhankar Maity, Vivek Jangra
ACS Applied Energy Materials
Advanced Thermoelectric Materials and Devices
article

Polypyrrole and Carbon Nanotube-Based Textile Thermoelectric Fabrics for the Development of 2D and 3D Energy-Harvesting Devices

Prashant Vishnoi, Subhankar Maity, Vivek Jangra
article en

Abstract

Flexible wearable textile thermoelectric generators (TEGs) are developed from polypyrrole (PPy) coated cotton fabric as p-type and multiwall carbon nanotube (MWCNT) coated cotton fabric as n-type materials. An in situ chemical polymerization method is used to coat cotton fabrics with PPy in an aqueous medium, using ferric chloride as the oxidant. The MWCNT coating on cotton fabric is applied by using the brushing–coating–drying process. Thermocouples are developed using PPy-coated textiles as p-type conductors and MWCNT-coated fabrics as n-type conductors. Two different TEG designs, i.e., 2D (I-design) and 3D (Pie-design), are developed and evaluated for their electrical and thermoelectric properties, including output current versus output voltage, output current versus output power, power factor, figure of merit, and Seebeck coefficient. The electrical conductivities of 2D and 3D TEGs were measured as 56.422 and 12.833 S/m, respectively. Their maximum Seebeck coefficients are found to be 100.773 and 94.958 μV/K, respectively. Their highest power factors are achieved to be 572.99 × 10–3 μW m–1 K–2 and 115.72 × 10–3 μW m–1 K–2, respectively, and the highest figures of merit at an absolute temperature of 300 K are achieved to be 37.430 × 10–4 and 6.358 × 10–4, respectively.

ACS Applied Energy Materials
Textile Research Institute (US)
Affordable and clean energy
Openalex Percentile: Top 6%
Advanced Thermoelectric Materials and Devices
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.