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Abstract This work explores the 2D interfacial energy transport between monolayer WSe2and SiO2while considering the thermal nonequilibrium between optical and acoustic phonons caused by photoexcitation. Recent modeling and experimental work have shown substantial temperature differences between optical and acoustic phonons (ΔTOA) in various nanostructures upon laser irradiation. Generally, characterizations of interfacial thermal resistance (R′′tc) at the nanoscale are difficult and depend on Raman‐probed temperature measurements, which only reveal optical phonon temperature information. Here it is shown that ΔTOAfor supported monolayer WSe2can be as high as 48% of the total temperature rise revealed by optothermal Raman methods—a significant proportion that can introduce sizeable error toR′′tcmeasurements if not properly considered. A frequency energy transport state‐resolved Raman technique (FET‐Raman) along with a 3D finite volume modeling of 2D material laser heating is used to extract the true interfacial thermal resistanceR′′tc(determined by acoustic phonon transport). Additionally, a novel ET‐Raman technique is developed to determine the energy coupling factorGbetween optical and acoustic phonons (on the order of 1015W m−3K−1). This work demonstrates the need for special consideration of thermal nonequilibriums during laser–matter interactions at the nanoscale.
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Unlocking enhanced thermal conductivity in polymer blends through active learning
Abstract Polymers play an integral role in various applications, from everyday use to advanced technologies. In the era of machine learning (ML), polymer informatics has become a vital field for efficiently designing and developing polymeric materials. However, the focus of polymer informatics has predominantly centered on single-component polymers, leaving the vast chemical space of polymer blends relatively unexplored. This study employs a high-throughput molecular dynamics (MD) simulation combined with active learning (AL) to uncover polymer blends with enhanced thermal conductivity (TC) compared to the constituent single-component polymers. Initially, the TC of about 600 amorphous single-component polymers and 200 amorphous polymer blends with varying blending ratios are determined through MD simulations. The optimal representation method for polymer blends is identified, which involves a weighted sum approach that extends existing polymer representation from single-component polymers to polymer blends. An AL framework, combining MD simulation and ML, is employed to explore the TC of approximately 550,000 unlabeled polymer blends. The AL framework proves highly effective in accelerating the discovery of high-performance polymer blends for thermal transport. Additionally, we delve into the relationship between TC, radius of gyration (Rg), and hydrogen bonding, highlighting the roles of inter- and intra-chain interactions in thermal transport in amorphous polymer blends. A significant positive association between TC andRgimprovement and an indirect contribution from H-bond interaction to TC enhancement are revealed through a log-linear model and an odds ratio calculation, emphasizing the impact of increasingRgand H-bond interactions on enhancing polymer blend TC.
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- Award ID(s):
- 2332270
- PAR ID:
- 10500863
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- npj Computational Materials
- Volume:
- 10
- Issue:
- 1
- ISSN:
- 2057-3960
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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