Effect of Nitric Oxide Treatment on Storage Quality of Glorious Oranges

AbstractEffect of nitric oxide (NO) treatment on storage quality and disease resistance of Glorious oranges was investigated in the experiment. The results showed that NO treatment could effectively reduce disease incidence inoculated with Collletotichum goeosporioides Penz and inhibit the increase of lesion diameter of Glorious oranges during storage. Compared with the control, NO treatment kept higher level of titritable acidity (TA), soluble protein, ascorbic acid (ASA) and reducing sugar, and lower level of weight lose rate and soluble solid concentration (SSC), retarding ripening of fruits

An E-shape broadband piezoelectric energy harvester induced by magnets

We describe in this work a broadband magnetic E-shape piezoelectric energy harvester with wide frequency bandwidth. We develop first a nonlinear electromechanical model of the harvester based on the Hamilton variation principle that simulates the effect of the nonlinear magnetic restoring force at different spacing distances. The model is used to identify the distances existing between two different magnets that enable the system to perform with a specific nonlinearity. The performance of the E-shape piezoelectric energy harvester is also investigated through experiments, with E-shape energy harvesters at different spacing distances tested under several base acceleration excitations. We observe that the frequency domain output voltage of the system shows a general excellent controllable performance, with a widening of the frequency bandwidth. The half-power bandwidth of the linear energy harvester for a distance of 25 mm is 0.8 Hz only, which can be expanded to 2.67 Hz for the larger distance of 11 mm between magnets. The energy harvester presented in this work shows promising performances for broad-spectrum vibration excitations compared to conventional cantilever piezoelectric energy harvester systems with a tip mass. </jats:p

Automatic Identification of Individual Nanoplastics by Raman Spectroscopy Based on Machine Learning

The increasing prevalence of nanoplastics in the environment underscores the need for effective detection and monitoring techniques. Current methods mainly focus on microplastics, while accurate identification of nanoplastics is challenging due to their small size and complex composition. In this work, we combined highly reflective substrates and machine learning to accurately identify nanoplastics using Raman spectroscopy. Our approach established Raman spectroscopy data sets of nanoplastics, incorporated peak extraction and retention data processing, and constructed a random forest model that achieved an average accuracy of 98.8% in identifying nanoplastics. We validated our method with tap water spiked samples, achieving over 97% identification accuracy, and demonstrated the applicability of our algorithm to real-world environmental samples through experiments on rainwater, detecting nanoscale polystyrene (PS) and polyvinyl chloride (PVC). Despite the challenges of processing low-quality nanoplastic Raman spectra and complex environmental samples, our study demonstrated the potential of using random forests to identify and distinguish nanoplastics from other environmental particles. Our results suggest that the combination of Raman spectroscopy and machine learning holds promise for developing effective nanoplastic particle detection and monitoring strategies.</p

Large datasets of water vapor sorption, mass diffusion immersed in water, hygroscopic expansion and mechanical properties of flax fibre/shape memory epoxy hygromorph composites

This data article presents four experimental sets of results related to flax fibre composites with epoxy shape memory polymer matrix: water vapor absorption, mass diffusion immersed in water, hygroscopic expansion, mechanical properties. The water vapor absorption tests are described in raw data related to four types of laminates with weights measured at different relative humidity (0%, 9%, 33%, 44%,75%, 85% and 100%). The mass diffusion experiments are related to weights of immersed samples over time. The unidirectional composite hygroscopic expansion is also measured along the fibre longitude and transverse directions. The mechanical properties of flax composite at various temperatures (20°C, 40°C, 60°C, 80°C and 100°C) and humidity environments (50% and immersed) are also described. Load-displacement diagrams of the hygromorph composites are converted into stress-strain diagrams via a compliance calibration, from which the tensile moduli are extracted. The data presented in this article can provide a benchmark for the development of new models, or for the determination of other properties via post processing. The detailed interpretation of the data can be found in [1]. The data is available in the Mendeley Data repository at [2]

Biobased and Programmable Electroadhesive Metasurfaces

[Image: see text] Electroadhesion has shown the potential to deliver versatile handling devices because of its simplicity of actuation and rapid response. Current electroadhesion systems have, however, significant difficulties in adapting to external objects with complex shapes. Here, a novel concept of metasurface is proposed by combining the use of natural fibers (flax) and shape memory epoxy polymers in a hygromorphic and thermally actuated composite (HyTemC). The biobased material composite can be used to manipulate adhesive surfaces with high precision and controlled environmental actuation. The HyTemC concept is preprogrammed to store controllable moisture and autonomous desorption when exposed to the operational environment, and can reach predesigned bending curvatures up to 31.9 m(–1) for concave and 29.6 m(–1) for convex shapes. The actuated adhesive surface shapes are generated via the architected metasurface structure, incorporating an electroadhesive component integrated with the programmable biobased materials. This biobased metasurface stimulated by the external environment provides a large taxonomy of shapes—from flat, circular, single/double concave, and wavy, to piecewise, polynomial, trigonometric, and airfoil configurations. The objects handled by the biobased metasurface can be fragile because of the high conformal matching between contacting surfaces and the absence of compressive adhesion. These natural fiber-based and environmentally friendly electroadhesive metasurfaces can significantly improve the design of programmable object handling technologies, and also provide a sustainable route to lower the carbon and emission footprint of smart structures and robotics