Electrically Guided DNA Immobilization and Multiplexed DNA Detection with Nanoporous Gold Electrodes.

Molecular diagnostics have significantly advanced the early detection of diseases, where the electrochemical sensing of biomarkers (e.g., DNA, RNA, proteins) using multiple electrode arrays (MEAs) has shown considerable promise. Nanostructuring the electrode surface results in higher surface coverage of capture probes and more favorable orientation, as well as transport phenomena unique to nanoscale, ultimately leading to enhanced sensor performance. The central goal of this study is to investigate the influence of electrode nanostructure on electrically-guided immobilization of DNA probes for nucleic acid detection in a multiplexed format. To that end, we used nanoporous gold (np-Au) electrodes that reduced the limit of detection (LOD) for DNA targets by two orders of magnitude compared to their planar counterparts, where the LOD was further improved by an additional order of magnitude after reducing the electrode diameter. The reduced electrode diameter also made it possible to create a np-Au MEA encapsulated in a microfluidic channel. The electro-grafting reduced the necessary incubation time to immobilize DNA probes into the porous electrodes down to 10 min (25-fold reduction compared to passive immobilization) and allowed for grafting a different DNA probe sequence onto each electrode in the array. The resulting platform was successfully used for the multiplexed detection of three different biomarker genes relevant to breast cancer diagnosis

Local damage in a 5-harness satin weave composite under static tension, part II: meso-FE modelling

International audienceThis study forms the second part of a paper on the local damage analysis in a thermo-plastic 5-harness satin weave composite under uni-axial static tensile load. The experimental observations of Part I are confronted with the meso-FE simulations. Part II describes the following steps regarding the unit cell meso-FE modeling starting from: 1) Construction of the unit cell geometrical model; 2) Estimation of the homogenized elastic constants of the unit cell using different boundary conditions; 3) Evaluation of the local stress and damage behavior of the unit cell using meso-FE simulations. The aim of the numerical analysis is to investigate the dependency of local ply stress and damage profiles on the adjacent layers of the laminate

Progressive fatigue damage modeling of textile composite on meso-scale with FE-method

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Macro-mechanical and microscopic study of the fatigue damage behaviour of a carbon fabric/PPS thermoplastic composite

This manuscript elaborates on the tension-tension fatigue behaviour of a carbon fabric reinforced polyphenylene sulphide. The damage behaviour will be investigated by (i) conducting fatigue experiments, in order to determine the macroscopic behaviour such as permanent deformation and stiffness degradation and (ii) a microscopic investigation using both optical and scanning electron (SEM) microscopy. It may be concluded that for the [(0°,90°)]4s stacking sequence the material does not show significant stiffness reduction and that only limited permanent deformation is present. Furthermore, the material shows very brittle failure behaviour. For the [(+45°,-45°)]4s stacking sequence, however, a different behaviour manifests itself. Stiffness reduction does occur and there is a significant permanent deformation, in combination with a high rise in temperature, above the softening temperature of the matrix

FE-modeling of damage of twill carbon/epoxy composite on meso-scale, materials characterization and experimental verification

Aim of this work is to evaluate the damage in twill carbon/epoxy composites on meso-scale level (fabric unit cell level). Averaged stiffness, Poisson ratios of pre- and post damage phase are calculated based on numerical homogenization technique with periodic boundary conditions (PBCs). The static strengths and initiation of the damage are calculated and validated by experiments. The anisotropic stiffness degradation model is implemented into Abaqus (R) UMAT. The algorithm of quasi-static damage is further used to model the cycles of the fatigue loading, together with the experimental S-N curves of unidirectional composite (UD), utilized as input data for the impregnated yarns. The output of the model is S-N curve of textile composites

A new meso-scale modelling of static and fatigue damage in woven composite materials with finite element method

Aim of this work is to evaluate the fatigue damage in textile composites on meso-scale level. Pre-damage properties, damage thresholds and damage propagation of unit cell (UC) are calculated and validated by experiments. Quasi-static damage algorithm is further used to model the cycles of the fatigue loading. Model output is the computed SN curve of textile composites

A progressive damage model of textile composites on meso-scale using finite element method: static damage analysis

A meso-scale finite element model for static damage in textile composites was established. The impregnated yarn is taken as homogeneous and transverse isotropic material, whose mechanical properties are calculated using Chamis' equations. The damage modes are determined by using the Tsai-Wu criterion and additional criteria. The Murakami damage tensor is used to calculate the post-damage stiffness matrix. The model has been validated using plain weave and twill weave carbon-epoxy composites. The initiation of inter-fiber matrix cracks and fiber rupture were analyzed using this meso-FE model

Damage analysis and fracture toughness evaluation in a thin woven composite laminate under static tension using infrared thermography

This work deals with the issue of damage growth in thin woven composite laminates subjected to tensile loading. The conducted tensile tests were monitored on-line with an infrared camera, and tested specimens were analysed using Scanning Electron Microscopy (SEM). Combined with SEM micrographs, observation of heat source fields enabled us to assess the damage sequence. Transverse weft cracking was confirmed to be the main damage mode and fiber breakage was the final damage leading to failure. For cracks which induce little variation of specimen stiffness, the classic “Compliance method” could not be used to compute energy release rate. Hence, we present here a new procedure based on the estimation of heat source fields to calculate the energy release rate associated with transverse weft cracking. The results are then compared to those computed with a simple 3D inverse model of the heat diffusion problem and those presented in the literature

In-situ local strain measurement in textile composites with embedded optical fibre sensors

To understand the local strains inside a textile composite, numerical simulations are typically done on the scale of one repetitive unit cell of the weaving pattern. Periodic boundary conditions are applied to the edges of the unit cell and different load cases can then be applied to the unit cell of the textile composite. Most often, the periodic boundary conditions are applied on all faces of the unit cell, which implies the assumption that the material is repeating itself over an infinite distance in all three orthogonal directions. This assumption is more or less valid for the textile composite material in the midplane of thick laminates, where it is constrained by neighbouring material in all three directions. It is very difficult to validate such simulations, because local strain measurements inside a textile composite have rarely been done, and the interpretation is not straightforward. This paper shows the successful use of embedded optical fibre sensors to measure the local strains inside a satin weave carbon/PPS composite (typically used in aerospace applications). The length of the Bragg grating inside the optical fibre sensor has been chosen such that it is longer than the length of one unit cell of the satin weave architecture (7.4 mm). The read-outs of the optical fibre sensor give the minimum and maximum local strains that occur along the length of the Bragg grating

Data Mining Ancient Script Image Data Using Convolutional Neural Networks

The recent surge in ancient scripts has resulted in huge image libraries of ancient texts. Data mining of the collected images enables the study of the evolution of these ancient scripts. In particular, the origin of the Indus Valley script is highly debated. We use convolutional neural networks to test which Phoenician alphabet letters and Brahmi symbols are closest to the Indus Valley script symbols. Surprisingly, our analysis shows that overall the Phoenician alphabet is much closer than the Brahmi script to the Indus Valley script symbols