SUMMARYPeakForce TM Quantitative Nanomechanical Mapping (QNM TM ) is a new atomic force microscopy technique for measuring the Young's modulus of materials with high spatial resolution and surface sensitivity, by probing at the nanoscale. In the present work, modulus results from PeakForce™ QNM™ using three different probes are presented for a number of different polymers with a range of Young's moduli that were measured independently by Instrumented (nano) Indentation Testing (IIT). The results from the diamond and silicon AFM probes were consistent and in reasonable agreement with IIT values for the majority of samples. It is concluded that the technique is complimentary to IIT; calibration requirements and potential improvements to the technique are discussed.
Protein haze is an esthetic problem in white wines that can be prevented by removing grape proteins that have 13 survived the winemaking process. The haze-forming proteins are grape pathogenesis-related proteins that are highly stable during 14 winemaking, but some of them precipitate over time and with elevated temperatures. Protein removal is currently achieved by 15 bentonite addition, an inefficient process that can lead to higher costs and quality losses in winemaking. The development of 16 more efficient processes for protein removal and haze prevention requires understanding the mechanisms that are the main 17 drivers of protein instability and the impacts of various wine matrix components on haze formation. This review covers recent 18 developments in wine protein instability and removal and proposes a revised mechanism of protein haze formation. 24 by land area in the world. 1,2 Furthermore, much value is added 25 in the form of winemaking to over half the world's grapes, with 26 the production of 252 million hectoliters of wine in 2012. 2 The 27 contribution of the wine sector to the world economy in 2013 28 reached a value of U.S.$277.5 billion, 3 with a large proportion 29 of the wine exported. Thus, a substantial volume of wine is 30 subject to potentially damaging conditions during trans-31 portation and storage, such as inappropriate temperature or 32 humidity, that can cause deleterious modifications of the 33 organoleptic features of the wine. 4 f1 34Wine clarity, especially that of white wines (Figure 1), is 35 important to most consumers and is also one of the 36 characteristics that is most easily affected by inappropriate 37 shipping and storage conditions. For this reason, securing wine 38 stability prior to bottling is an essential step of the winemaking 39 process and presents a significant challenge for winemakers. A 40 stable white wine is one that is clear and free from precipitates 41 at the time of bottling, through transport and storage, to the 42 time of consumption. Hazy wine and the presence of 43 precipitates are most commonly caused by three factors: 44 microbial instability, tartrate instability, and protein heat 45 instability. 5 Microbial stability is achieved prior to bottling by 46 sulfur dioxide addition and filtration; 6 tartrate stability is 47 achieved by either cold stabilization, ion exchange resins, or 48 emr00 | ACSJCA | JCA10.0.1465/W Unicode | research.3f (R3.6.i7:4236 | 2.0 alpha 39) 2014/12/19 13:33:00 | PROD-JCAVA | rq_4578338 | 4/10/2015 14:19:11 | 11 | JCA-DEFAULT 55 lees through processing using rotary drum vacuum filtration, 56 specialized lees filtration equipment, or centrifugation 57 processes that are considered laborious and that can potentially 58 degrade wine quality. 8−10 Quality degradation and loss of wine 59 through bentonite usage has been estimated to cost the global 60 wine industry around U.S.$1 billion per year. 11 Other issues 61 and costs related to bentonite use include tank downtime for 62 bentonite treatment, ...
Cytochrome P450 (CYP) and UDP-glucuronosyltransferase (UGT), which both exist as enzyme "superfamilies," are together responsible for the metabolism of most hepatically cleared drugs. There is currently intense interest in the development of techniques that permit identification of the CYP and UGT isoform(s) involved in the metabolism of a newly discovered drug, and hence prediction of factors likely to alter elimination in vivo. In addition, the quantitative scaling of kinetic parameters for a metabolic pathway assumes importance for identifying newly discovered drugs with undesirable in vivo pharmacokinetic properties. Although qualitative and quantitative in vitro-in vivo correlation based on data generated using human liver tissue or recombinant enzymes have been applied successfully to many drugs eliminated by CYP, these strategies have proved less definitive for glucuronidated compounds. Computational (in silico) modeling techniques that potentially provide a facile and economic alternative to the in vitro methods are now emerging. This review assesses the utility of in vitro and in silico approaches for the qualitative and quantitative prediction of drug glucuronidation parameters and the challenges facing the development of generalizable models.
The inplane compressive fracture behaviour of a carbon fibre-epoxy laminate containing a single hole is examined. Failure is due to 0° fibre microbuckling surrounded by delamination. The microbuckled zone initiates at the hole boundary. It extends stably under increasing load before becoming unstable at a critical microbuckle length of 2–3 mm. The damage propagation and failure of the orthotropic laminate is analysed by a cohesive zone model, in which damage around the open hole is represented by a line crack loaded on its faces. Good agreement between experimental and predicted notched strength is observed for the chosen material and lay-up.
This paper gives details of the input data and a full description of a set of 13 test cases provided to the participants of the third world-wide failure exercise for use in their theoretical models. World-wide failure exercise is aimed at benchmarking leading methods, capable of predicting initiation and progression matrix cracking and damage and failure in composites. The originators of leading theories were requested to use the exact input data provided here in their blind predictions of the test cases. The input data include all of the elastic constants, ultimate strains and strengths and the nonlinear stress–strain curves for the unidirectional laminae and their constituents. Various types of laminates, chosen for the analysis, are described together with the lay-up, layer thicknesses, stacking sequences and the loading conditions. Detailed instructions, issued to the contributors, are also presented at the end of this paper.
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