Search NASA⌕ Search

DOE OSTI · 2538598

Defects vibrations engineering for enhancing interfacial thermal transport in polymer composites

Zhou, Yijie [Univ. of Massachusetts, Amherst, MA (United States)] (ORCID:0009000750801593)·Ciarla, Robert [Univ. of Massachusetts, Amherst, MA (United States)] (ORCID:0009000491287998)·Boonkird, Artittaya [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)]·Raza, Saqlain [North Carolina State University, Raleigh, NC (United States)]·Nguyen, Thanh [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)] (ORCID:0000000336772160)·Zhou, Jiawei [Stanford Univ., CA (United States)]·Osti, Naresh C. [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000202132299)·Mamontov, Eugene [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000256842675)·Jiang, Zhang [Argonne National Laboratory (ANL), Argonne, IL (United States). Advanced Photon Source (APS)] (ORCID:0000000335038909)·Zuo, Xiaobing [Argonne National Laboratory (ANL), Argonne, IL (United States). Advanced Photon Source (APS)] (ORCID:0000000201344804)·Ranasinghe, Jeewan [Rice Univ., Houston, TX (United States)] (ORCID:0000000277445644)·Hu, Weiguo [Univ. of Massachusetts, Amherst, MA (United States)] (ORCID:0000000278681657)·Scott, Brendan [Univ. of Massachusetts, Amherst, MA (United States)] (ORCID:0009000128057864)·Chen, Jihua [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Sciences (CNMS)] (ORCID:0000000168795936)·Hensley, Dale K. [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Sciences (CNMS)] (ORCID:0000000187637765)·Huang, Shengxi [Rice Univ., Houston, TX (United States)] (ORCID:0000000236189074)·Liu, Jun [North Carolina State University, Raleigh, NC (United States)] (ORCID:0000000273355860)·Li, Mingda [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)] (ORCID:0000000270556368)·Xu, Yanfei [Univ. of Massachusetts, Amherst, MA (United States)] (ORCID:0000000348092832)

Abstract

To push upper boundaries of thermal conductivity in polymer composites, understanding of thermal transport mechanisms is crucial. Despite extensive simulations, systematic experimental investigation on thermal transport in polymer composites is limited. To better understand thermal transport processes, we design polymer composites with perfect fillers (graphite) and defective fillers (graphite oxide), using polyvinyl alcohol (PVA) as a matrix model. Measured thermal conductivities of ~1.38 ± 0.22 W m -1 K -1 in PVA/defective filler composites is higher than those of ~0.86 ± 0.21 W m -1 K -1 in PVA/perfect filler composites, while measured thermal conductivities in defective fillers are lower than those of perfect fillers. We identify how thermal transport occurs across heterogeneous interfaces. Thermal transport measurements, neutron scattering, quantum mechanical modeling, and molecular dynamics simulations reveal that vibrational coupling between PVA and defective fillers at PVA/filler interfaces enhances thermal conductivity, suggesting that defects in polymer composites improve thermal transport by promoting this vibrational coupling.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Zhou, Yijie [Univ. of Massachusetts, Amherst, MA (United States)] (ORCID:0009000750801593), Ciarla, Robert [Univ. of Massachusetts, Amherst, MA (United States)] (ORCID:0009000491287998), Boonkird, Artittaya [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)], Raza, Saqlain [North Carolina State University, Raleigh, NC (United States)], Nguyen, Thanh [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)] (ORCID:0000000336772160), Zhou, Jiawei [Stanford Univ., CA (United States)], Osti, Naresh C. [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000202132299), Mamontov, Eugene [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000256842675), Jiang, Zhang [Argonne National Laboratory (ANL), Argonne, IL (United States). Advanced Photon Source (APS)] (ORCID:0000000335038909), Zuo, Xiaobing [Argonne National Laboratory (ANL), Argonne, IL (United States). Advanced Photon Source (APS)] (ORCID:0000000201344804), Ranasinghe, Jeewan [Rice Univ., Houston, TX (United States)] (ORCID:0000000277445644), Hu, Weiguo [Univ. of Massachusetts, Amherst, MA (United States)] (ORCID:0000000278681657), Scott, Brendan [Univ. of Massachusetts, Amherst, MA (United States)] (ORCID:0009000128057864), Chen, Jihua [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Sciences (CNMS)] (ORCID:0000000168795936), Hensley, Dale K. [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Sciences (CNMS)] (ORCID:0000000187637765), Huang, Shengxi [Rice Univ., Houston, TX (United States)] (ORCID:0000000236189074), Liu, Jun [North Carolina State University, Raleigh, NC (United States)] (ORCID:0000000273355860), Li, Mingda [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)] (ORCID:0000000270556368), Xu, Yanfei [Univ. of Massachusetts, Amherst, MA (United States)] (ORCID:0000000348092832). 2025-01-22. Defects vibrations engineering for enhancing interfacial thermal transport in polymer composites. https://doi.org/10.1126/sciadv.adp6516

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

Large language models for transportation research: Methodologies, state of the art, and future opportunities

The rapid rise of large language models (LLMs) is transforming transportation research, with significant advancements emerging between 2023 and 2025, a period marked by the inception and swift growth of adopting and adapting LLMs for various transportation applications. Despite these significant advancements, however, a systematic review and synthesis of the existing literature remains lacking. This paper aims to fill this gap by providing a comprehensive review of the methodologies and applications of LLMs in transportation. We explore key applications, including autonomous driving, travel behavior prediction, and general transportation-related queries, alongside LLM methodologies such as zero- or few-shot learning, prompt engineering, and fine-tuning. From the review, critical research gaps are identified. From the methodological perspective, many of the research limitations can be addressed by integrating LLMs with existing tools and refining LLM architectures. From the application perspective, research opportunities for LLMs to address various transportation challenges are also explored. By synthesizing these findings, this review not only presents the state-of-the-art LLM adoption and adaptation in transportation, but also proposes future research directions as well as insights and recommendations for policymakers and practitioners, paving the way for greater LLM-driven research innovations in transportation in the future.

42 ENGINEERING↗