The effect of constitutive parameters and microstructure on the kinematic and constitutive responses within grains in a crystal plasticity finite element (CPFE) simulation of a polycrystalline titanium alloy are compared with experimental results. The simulation of a Ti-5Al-2.5Sn sample deformed in uniaxial tension at room temperature used a phenomenological power-law based CPFE model, which includes four families of slip systems commonly observed in structural metals with hexagonal lattice structure. The experimentally characterized microstructure patch was approximated by a quasi-3D columnar grain structure and by a more realistic 3D representation. The quasi-3D microstructure was generated by extending the EBSD characterized surface microstructure in the depth direction, while the 3D microstructure was built based on subsurface orientation information acquired using differential-aperture X-ray microscopy (DAXM). The effect of grain morphology and constitutive parameters on simulation results are compared in terms of stress-strain responses and lattice reorientation.
Diospyros mafiensis F. White is a medicinal shrub or small tree (6 m tall) widely distributed in the Zanzibar-Inhambane regional mosaic and traditionally used to treat leprosy, diarrhoea, and skin fungal infections in Tanzania and Mozambique. Our objective was to determine the anti-aflatoxigenic properties of compounds from D. mafiensis root bark against vegetative growth, sporulation and aflatoxin production by Aspergillus flavus and Aspergillus parasiticus. Bioassay-guided extraction, fractionation, and isolation of bioactive compounds using A. parasiticus B62 were employed. The bioactive compounds were elucidated using 1H and 13CNMR and LC-MS. Growth inhibition was determined by measuring the colony diameter of A. flavus AF3357 and A. parasiticus SU-1 ATCC56775. Inhibitory effects on sporulation were estimated using a haemocytometer. Total aflatoxin was quantified by direct competitive enzyme-linked immunosorbent assay (ELISA). Bioactive compounds diosquinone (DQ) and 3-hydroxydiosquinone (3HDQ) were identified. DQ weakly inhibited A. flavus and A. parasiticus vegetative growth (MIC50 > 100 µg/ml) and 3HDQ strongly inhibited A. flavus (MIC50 = 14.9 µg/ml) and A. parasiticus (MIC50 = 39.1 µg/ml). DQ strongly reduced total aflatoxin production by A. flavus from 157 to 36 ng/plate, and by A. parasiticus from 1,145 ng/plate to 45 ng/plate at 100 µg/ml. 3HDQ reduced total aflatoxin production by A. parasiticus from 1,145 to 32 ng/plate; stimulated production by A. flavus from 157 to 872 ng/plate at 12.5 µg/ml but reduced to 45 ng/plate at 100 µg/ml. In summary, DQ and 3HDQ could be used as natural antifungal compounds to prevent mould growth and aflatoxin accumulation in food and feed.
Highly sensitive and conformal sensors are essential for the implementation of human−machine interfaces, health monitoring, and rehabilitation prostheses. The proper adjustment of conductive pathways in the sensing materials is essential for their sensitive transduction of mechanical stimuli into electrical signals. However, the rational, precise, and wide-range control of electrical networks within traditional conductive composites is difficult due to the randomly distributed fillers. Herein, we adopt an indirect 3D-printing method to fabricate pressure sensors with various microchannels for liquid metal (LM) to form consistent and tunable conductive pathways. LM is highly conductive, fluidic, and incompressible at ambient conditions, which guarantees the reliable regulation and function of our pressure sensor. Additive manufacturing provides a facile way to construct complicated microchannels with different lengths, different orientations, crosssectional sizes, depth-width ratios, and shapes, which can effectively modulate the sensitivity and the sensing range. Under the optimized structural configurations, our sensor achieves a high sensitivity of 1.139 kPa −1 , a detection range of 0−68 kPa (loading process), and stability of over 5000 cycles, whose sensing performance is better than most microchannel-filled LM sensors. It can achieve high-accuracy monitoring of pulse, speaking and gestures, and exhibit a full recognition of objects under the assistance of machine learning. This work can provide new ideas on the design of conductive pathways in flexible electronics and expand the application of recyclable LM in human−machine interfaces.
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