Cold, Rapid, and Scalable Stamping of Aramid‐Networked Viscoelastic h‐BN Doughs for Complex Thermal Architectures

Extensive efforts have been made to fabricate complex 3D thermal management materials from hexagonal boron nitride (h-BN) using 3D printing and templating. However, these techniques are often energy-intensive, time-consuming, and inherently limited in scalability, owing to prolonged processing times and low throughput. Herein, we report a cold, rapid, and scalable stamping approach for constructing intricate, large-area h-BN-based thermal architectures. This strategy relies on forming highly viscoelastic h-BN doughs achieved through developing a para-aramid (p-aramid) fiber network and densification via a bimodal alumina mixture. The p-aramid network maximizes viscoelasticity with a minimal binder content (5.1 wt.%), enabling the doughs to exhibit pronounced plasticity during stamping while maintaining solid-like behavior after relaxation. Consequently, the doughs conform precisely to complex stamp geometries within 2 s under ambient conditions, preserving their high structural integrity. Scalability is demonstrated by stamping various 3D geometries exceeding 10 cm, including cubes, cylinders, annular sectors, and honeycombs. Furthermore, the fiber-reinforced structures exhibit enhanced thermal conductivity (TC) and fatigue resistance under extreme temperatures (- 50°C and 200°C). Notably, the resulting architectures substantially improve the TC of the polymer composites when used as internal frameworks. This low-energy stamping strategy represents a paradigm shift in the processing of advanced thermal materials.

Authors

Institutions

Publication Details

Journal
Advanced Materials
Published
2026-02-05
DOI
https://doi.org/10.1002/adma.202512454
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

Cold, Rapid, and Scalable Stamping of Aramid‐Networked Viscoelastic h‐BN Doughs for Complex Thermal Architectures

Wonjin Na, Minji Kim, Hyeseo Choi, Youngho Eom et al.
Advanced Materials
Thermal properties of materials
article

Cold, Rapid, and Scalable Stamping of Aramid‐Networked Viscoelastic h‐BN Doughs for Complex Thermal Architectures

Wonjin Na, Minji Kim, Hyeseo Choi, Youngho Eom, Hyun Ju Oh
article en

Abstract

Extensive efforts have been made to fabricate complex 3D thermal management materials from hexagonal boron nitride (h-BN) using 3D printing and templating. However, these techniques are often energy-intensive, time-consuming, and inherently limited in scalability, owing to prolonged processing times and low throughput. Herein, we report a cold, rapid, and scalable stamping approach for constructing intricate, large-area h-BN-based thermal architectures. This strategy relies on forming highly viscoelastic h-BN doughs achieved through developing a para-aramid (p-aramid) fiber network and densification via a bimodal alumina mixture. The p-aramid network maximizes viscoelasticity with a minimal binder content (5.1 wt.%), enabling the doughs to exhibit pronounced plasticity during stamping while maintaining solid-like behavior after relaxation. Consequently, the doughs conform precisely to complex stamp geometries within 2 s under ambient conditions, preserving their high structural integrity. Scalability is demonstrated by stamping various 3D geometries exceeding 10 cm, including cubes, cylinders, annular sectors, and honeycombs. Furthermore, the fiber-reinforced structures exhibit enhanced thermal conductivity (TC) and fatigue resistance under extreme temperatures (- 50°C and 200°C). Notably, the resulting architectures substantially improve the TC of the polymer composites when used as internal frameworks. This low-energy stamping strategy represents a paradigm shift in the processing of advanced thermal materials.

Advanced MaterialsVol. 38(14)
Korea Food Research Institute (KR), Hanyang University (KR), Jeonbuk National University (KR), Korea Institute of Industrial Technology (KR)
Affordable and clean energy
Openalex Percentile: Top 66%
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.