Strain Shielding from Mechanically Activated Covalent Bond Formation during Nanoindentation of Graphene Delays the Onset of Failure

Mechanical failure of an ideal crystal is dictated either by an elastic instability or a soft-mode instability. Previous interpretations of nanoindentation experiments on suspended graphene sheets, however, indicate an anomaly: the inferred strain in the graphene sheet directly beneath the diamond indenter at the measured failure load is anomalously large compared to the fracture strains predicted by both soft-mode and acoustic analyses. Through multiscale modeling combining the results of continuum, atomistic, and quantum calculations, and analysis of experiments, we identify a strain-shielding effect initiated by mechanochemical interactions at the graphene–indenter interface as the operative mechanism responsible for this anomaly. Transmission electron micrographs and a molecular model of the diamond indenter’s tip suggest that the tip surface contains facets comprising crystallographic {111} and {100} planes. Ab initio and molecular dynamics (MD) simulations confirm that a covalent bond (weld) formation between graphene and the crystallographic {111} and {100} facets on the indenter’s surface can be induced by compressive contact stresses of the order achieved in nanoindentation tests. Finite element analysis (FEA) and MD simulations of nanoindentation reveal that the shear stiction provided by the induced covalent bonding restricts relative slip of the graphene sheet at its contact with the indenter, thus initiating a local strain-shielding effect. As a result, subsequent to stress-induced bonding at the graphene–indenter interface, the spatial variation of continuing incremental strain is substantially redistributed, locally shielding the region directly beneath the indenter by limiting the buildup of strain while imparting deformation to the surrounding regions. The extent of strain shielding is governed by the strength of the shear stiction, which depends upon the level of hydrogen saturation at the indenter’s surface. We show that at intermediate levels of hydrogen saturation the strain-shielding effect can enable the graphene to support experimentally determined fracture loads and displacements without prematurely reaching locally limiting states of stress and deformation

Mechanochemically Responsive Viscoelastic Elastomers

Mechanochemically responsive (MCR) polymers have been designed to possess unconventional properties such as changing colors, self-healing, and releasing catalysts under deformation. These properties of MCR polymers stem from a class of molecules, referred to as mechanophores, whose chemical reactions can be controlled by mechanical forces. Although extensive studies have been devoted to the syntheses of MCR polymers by incorporating various mechanophores into polymer networks, the intricate interactions between mechanical forces and chemical reactions in MCR polymers across multiple length and time scales are still not well understood. In this paper, we focus on mechanochemical responses in viscoelastic elastomers and develop a theoretical model to characterize the coupling between viscoelasticity and chemical reactions of MCR elastomers. We show that the kinetics of viscoelasticity and mechanophore reactions introduce different time scales into the MCR elastomers. The model can consistently represent experimental data on both mechanical properties and chemical reactions of MCR viscoelastic elastomers. In particular, we explain recent experimental observations on the increasing chemical activation during stress relaxation of MCR elastomers, which cannot be explained with existing models. The proposed model provides a theoretical foundation for the design of future MCR polymers with desirable properties.National Science Foundation (U.S.) (CMMI-1253495

Automatic Clustering of Flow Cytometry Data with Density-Based Merging

The ability of flow cytometry to allow fast single cell interrogation of a large number of cells has made this technology ubiquitous and indispensable in the clinical and laboratory setting. A current limit to the potential of this technology is the lack of automated tools for analyzing the resulting data. We describe methodology and software to automatically identify cell populations in flow cytometry data. Our approach advances the paradigm of manually gating sequential two-dimensional projections of the data to a procedure that automatically produces gates based on statistical theory. Our approach is nonparametric and can reproduce nonconvex subpopulations that are known to occur in flow cytometry samples, but which cannot be produced with current parametric model-based approaches. We illustrate the methodology with a sample of mouse spleen and peritoneal cavity cells

The Role of Dietary Sugars and De novo Lipogenesis in Non-Alcoholic Fatty Liver Disease

Dietary sugar consumption, in particular sugar-sweetened beverages and the monosaccharide fructose, has been linked to the incidence and severity of non-alcoholic fatty liver disease (NAFLD). Intervention studies in both animals and humans have shown large doses of fructose to be particularly lipogenic. While fructose does stimulate de novo lipogenesis (DNL), stable isotope tracer studies in humans demonstrate quantitatively that the lipogenic effect of fructose is not mediated exclusively by its provision of excess substrates for DNL. The deleterious metabolic effects of high fructose loads appear to be a consequence of altered transcriptional regulatory networks impacting intracellular macronutrient metabolism and altering signaling and inflammatory processes. Uric acid generated by fructose metabolism may also contribute to or exacerbate these effects. Here we review data from human and animal intervention and stable isotope tracer studies relevant to the role of dietary sugars on NAFLD development and progression, in the context of typical sugar consumption patterns and dietary recommendations worldwide. We conclude that the use of hypercaloric, supraphysiological doses in intervention trials has been a major confounding factor and whether or not dietary sugars, including fructose, at typically consumed population levels, effect hepatic lipogenesis and NAFLD pathogenesis in humans independently of excess energy remains unresolved

Plasma sheet and (nonstorm) ring current formation from solar and polar wind sources

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95352/1/jgra17511.pd

Standardization of epidemiological surveillance of acute rheumatic fever

Acute rheumatic fever (ARF) is a multiorgan inflammatory disorder that results from the body’s autoimmune response to pharyngitis or a skin infection caused by Streptococcus pyogenes (Strep A). Acute rheumatic fever mainly affects those in low- and middle-income nations, as well as in indigenous populations in wealthy nations, where initial Strep A infections may go undetected. A single episode of ARF puts a person at increased risk of developing long-term cardiac damage known as rheumatic heart disease. We present case definitions for both definite and possible ARF, including initial and recurrent episodes, according to the 2015 Jones Criteria, and we discuss current tests available to aid in the diagnosis. We outline the considerations specific to ARF surveillance methodology, including discussion on where and how to conduct active or passive surveillance (eg, early childhood centers/schools, households, primary healthcare, administrative database review), participant eligibility, and the surveillance population. Additional considerations for ARF surveillance, including implications for secondary prophylaxis and follow-up, ARF registers, community engagement, and the impact of surveillance, are addressed. Finally, the core elements of case report forms for ARF, monitoring and audit requirements, quality control and assurance, and the ethics of conducting surveillance are discussed

QFMatch: multidimensional flow and mass cytometry samples alignment

Part of the flow/mass cytometry data analysis process is aligning (matching) cell subsets between relevant samples. Current methods address this cluster-matching problem in ways that are either computationally expensive, affected by the curse of dimensionality, or fail when population patterns significantly vary between samples. Here, we introduce a quadratic form (QF)-based cluster matching algorithm (QFMatch) that is computationally efficient and accommodates cases where population locations differ significantly (or even disappear or appear) from sample to sample. We demonstrate the effectiveness of QFMatch by evaluating sample datasets from immunology studies. The algorithm is based on a novel multivariate extension of the quadratic form distance for the comparison of flow cytometry data sets. We show that this QF distance has attractive computational and statistical properties that make it well suited for analysis tasks that involve the comparison of flow/mass cytometry samples