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Thermal conductivity (k) of polymers is usually limited to low values of ~0.5 Wm−1K−1 in comparison to metals (>20 Wm−1K−1). The goal of this work is to enhance thermal conductivity (k) of polyethylene–graphene nanocomposites through simultaneous alignment of polyethylene (PE) lamellae and graphene nanoplatelets (GnP). Alignment is achieved through the application of strain. Measured values are compared with predictions from effective medium theory. A twin conical screw micro compounder is used to prepare polyethylene–graphene nanoplatelet (PE-GnP) composites. Enhancement in k value is studied for two different compositions with GnP content of 9 wt% and 13 wt% and for applied strains ranging from 0% to 300%. Aligned PE-GnP composites with 13 wt% GnP displays ~1000% enhancement in k at an applied strain of 300%, relative to k of pristine unstrained polymer. Laser Scanning Confocal Microscopy (LSCM) is used to quantitatively characterize the alignment of GnP flakes in strained composites; this measured orientation is used as an input for effective medium predictions. These results have important implications for thermal management applications. 

Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However, for scientists wishing to publish obtained images and image-analysis results, there are currently no unified guidelines for best practices. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here, we present community-developed checklists for preparing light microscopy images and describing image analyses for publications. These checklists offer authors, readers and publishers key recommendations for image formatting and annotation, color selection, data availability and reporting image-analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby to heighten the quality and explanatory power of microscopy data.