Assessing MWCNT-graphene surface energy through in situ SEM peeling

Carbon nanotubes (CNTs) are envisioned as ideal filaments for next-generation nanocomposites due to their high strength-to-weight ratios. However, while individual nanotubes are strong, interfaces between tubes cannot bear significant load due to the weak van der Waals forces that govern their behavior. Premature interfacial failure could thus counteract the inherent strength of carbon nanotubes and, in turn, prevent CNT-based composites from achieving optimal mechanical performance. To increase the load bearing capacity of these interfaces, interlayer crosslinking schemes have been proposed using chemical functionalization. For instance, introduction of hydrogen bonds or additional van der Waals bonds between tubes could improve load transfer between CNTs. While introducing chemical groups on CNT surfaces may enhance intermolecular interactions at these interfaces, a means of quantitatively evaluating changes in interlayer adhesion as a result of to these treatments needs to be defined. In addition, as sizes of CNTs will inherently vary within a composite, it is important that such energy measurements be normalized irrespective of tube dimensions. Here we report an experimental peeling technique that can be used to measure the adhesion energy between multiwalled carbon nanotubes (MWCNTs) and graphene. Peeling tests conducted in situ a scanning electron microscope allow direct visualization of the nanoscale peeling process which, in turn, enables adhesion energy to be estimated through classical fracture analysis. The applicability of this analysis is validated by finite element simulations with boundary conditions derived from experiments. The effective contact width between tubes and graphene is estimated via atomistic simulations, providing a means to normalize interaction energy per unit area. The surface energies of bare MWCNT-graphene interfaces found in this study compare favorably with theoretical and experimental values reported for graphite. This method can serve as a foundation for evaluating the enhancements afforded by chemical functionalization, which is a critical step toward the development of strong, lightweight composites that effectively utilize the full mechanical potential of CNTs

Morphology and Optical Response of Carbon Nanotubes Functionalized by Conjugated Polymers

Noncovalent functionalization of single wall carbon nanotubes (SWNTs) by biological and conjugated polymers promises significant improvements in their properties important for future nanotube-based optoelectronic and photovoltaic devices. Using a combination of molecular mechanics and quantum chemistry methods, we investigate how the deposition of poly-phenylene vinylene (PPV), a conjugated polymer, on the surface of selected SWNTs affects their morphology, as well as their electronic and optical properties. We found that the interaction between PPV and the nanotube is relatively weak (0.1–0.3 eV per repeat unit), and the most stable structures exhibit small coiling angles (≤20°) of PPV chains around the nanotube. PPV functionalization weakly affects optical excitations of the SWNT, resulting in slight red-shifts of the first and second optical bands of the nanotube. In contrast, the absorption spectra of PPV are strongly affected by specific conformational structures of the wrapped polymer. Our analysis identifies and explains a significant blue-shift of the excited energy and much broader line-width of the coiled PPV compared to that of the respective isolated polymer structures. These trends convey that signatures of polymer wrapping around SWNTs can be detected in experimental optical spectra of hybrid composites

Shear and Friction between Carbon Nanotubes in Bundles and Yarns

We perform a detailed density functional theory assessment of the factors that determine shear interactions between carbon nanotubes (CNTs) within bundles and in related CNT and graphene structures including yarns, providing an explanation for the shear force measured in recent experiments (Filleter, T.et al. Nano Lett. 2012, 12, 732). The potential energy barriers separating AB stacked structures are found to be irrelevant to the shear analysis for bundles and yarns due to turbostratic stacking, and as a result, the tube–tube shear strength for pristine CNTs is estimated to be <0.24 MPa, that is, extremely small. Instead, it is pinning due to the presence of defects and functional groups at the tube ends that primarily cause resistance to shear when bundles are fractured in weak vacuum (∼10^–5 Torr). Such defects and groups are estimated to involve 0.55 eV interaction energies on average, which is much larger than single-atom vacancy defects (approximately 0.039 eV). Furthermore, because graphitic materials are stiff they have large coherence lengths, and this means that push–pull effects result in force cancellation for vacancy and other defects that are internal to the CNTs. Another important factor is the softness of cantilever structures relative to the stiff CNTs in the experiments, as this contributes to elastic instability transitions that account for significant dissipation during shear that has been observed. The application of these results to the mechanical behavior of yarns is discussed, providing general guidelines for the manufacture of strong yarns composed of CNTs

Molecularly Tunable Fluorescent Quantum Defects

We describe the chemical creation of molecularly tunable fluorescent quantum defects in semiconducting carbon nanotubes through covalently bonded surface functional groups that are themselves nonemitting. By variation of the surface functional groups, the same carbon nanotube crystal is chemically converted to create more than 30 distinct fluorescent nanostructures with unique near-infrared photoluminescence that is molecularly specific, systematically tunable, and significantly brighter than that of the parent semiconductor. This novel exciton-tailoring chemistry readily occurs in aqueous solution and creates functional defects on the sp² carbon lattice with highly predictable C–C bonding from virtually any iodine-containing hydrocarbon precursor. Our new ability to control nanostructure excitons through a single surface functional group opens up exciting possibilities for postsynthesis chemical engineering of carbon nanomaterials and suggests that the rational design and creation of a large variety of molecularly tunable quantum emittersfor applications ranging from in vivo bioimaging and chemical sensing to room-temperature single-photon sourcescan now be anticipated

Molecular-Level Engineering of Adhesion in Carbon Nanomaterial Interfaces

Weak interfilament van der Waals interactions are potentially a significant roadblock in the development of carbon nanotube- (CNT-) and graphene-based nanocomposites. Chemical functionalization is envisioned as a means of introducing stronger intermolecular interactions at nanoscale interfaces, which in turn could enhance composite strength. This paper reports measurements of the adhesive energy of CNT–graphite interfaces functionalized with various coverages of arylpropionic acid. Peeling experiments conducted in situ in a scanning electron microscope show significantly larger adhesive energies compared to previously obtained measurements for unfunctionalized surfaces (Roenbeck et al. <i>ACS Nano</i> <b>2014</b>, <i>8</i> (1), 124–138). Surprisingly, however, the adhesive energies are significantly higher when both surfaces have intermediate coverages than when one surface is densely functionalized. Atomistic simulations reveal a novel functional group interdiffusion mechanism, which arises for intermediate coverages in the presence of water. This interdiffusion is not observed when one surface is densely functionalized, resulting in energy trends that correlate with those observed in experiments. This unique intermolecular interaction mechanism, revealed through the integrated experimental–computational approach presented here, provides significant insights for use in the development of next-generation nanocomposites

Evaluation of the portability of computable phenotypes with natural language processing in the eMERGE network

Abstract The electronic Medical Records and Genomics (eMERGE) Network assessed the feasibility of deploying portable phenotype rule-based algorithms with natural language processing (NLP) components added to improve performance of existing algorithms using electronic health records (EHRs). Based on scientific merit and predicted difficulty, eMERGE selected six existing phenotypes to enhance with NLP. We assessed performance, portability, and ease of use. We summarized lessons learned by: (1) challenges; (2) best practices to address challenges based on existing evidence and/or eMERGE experience; and (3) opportunities for future research. Adding NLP resulted in improved, or the same, precision and/or recall for all but one algorithm. Portability, phenotyping workflow/process, and technology were major themes. With NLP, development and validation took longer. Besides portability of NLP technology and algorithm replicability, factors to ensure success include privacy protection, technical infrastructure setup, intellectual property agreement, and efficient communication. Workflow improvements can improve communication and reduce implementation time. NLP performance varied mainly due to clinical document heterogeneity; therefore, we suggest using semi-structured notes, comprehensive documentation, and customization options. NLP portability is possible with improved phenotype algorithm performance, but careful planning and architecture of the algorithms is essential to support local customizations