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Purpose The purpose of this study is to develop a additive manufacturing (AM) process for the fabrication of ionic polymer–metal composite (IPMC) devices with complex designs that would be time-consuming to replicate using conventional manual methods. These IPMC devices have considerable potential in electroactive polymers (EAPs) and soft actuators. Design/methodology/approach This paper presents a novel three–dimensional (3D) AM technique to develop IPMCs. Digital light processing (DLP) fabrication of soft EAPs was undertaken using a vat-based AM method, followed by deposition of cost-effective outer silver electrodes. Findings DLP-fabricated devices were compared to conventional Nafion™-117 devices. DLP layer-by-layer fabrication of these devices allowed for good resolution for a range of printed objects. Electrical actuation of the DLP-produced IPMCs showed tip displacements of up to 3 mm, and greater actuation was seen in the presence of lithium rather than magnesium cations. The IMPCs showed good ion exchange capacities, while electrochemical analysis showed the reversible formation and removal of AgCl layers in addition to ion movement. Practical implications The AM of these devices allows for rapid prototyping as well as potential use in the development of multiple degrees of freedom actuators and devices. Originality/value An original resin formulation was developed for DLP 3D printing. This formula is chemically distinct from the conventional Nafion™-117 membranes that can be purchased. Additionally, this method allows for the manufacture of complex objects that would be difficult to machine by hand. These findings are of value to both the fields of polymer chemistry and AM.

Almost all processed food comes packaged in either plastic, glass, metal, or paper and paperboard materials, and many packaging materials are disposed of after a single use (linear economy). Based on the concept of a circular economy, the recycling of food packaging materials has become one of the main targets for industries and regulators around the world. However, recycling presents particular challenges, mainly related to the recycled material composition, which determines its reusability, application, functionality, and chemical safety. In this latter matter, it has been demonstrated that the use of recycled food packaging materials increases the number and possible sources of substances that could be present in the packaging material, which is of concern as substances that can migrate into food and cause health hazards upon consumption. This review compiles information regarding substances detected in non-permanent food packaging materials, focusing mainly on plastics, paper, and paperboards. The compilation of literature studies (110 research articles) on the presence of intentionally added substances (IAS) and non-intentionally added substances (NIAS) in food packaging materials, their migration, toxicity, and dietary exposure has been summarized, evaluated, and discussed. In addition, current sustainable food packaging trends have been mentioned. Finally, approaches to reduce the presence, migration, and potential exposure to substances that have migrated from packaging materials into food have been reviewed.

Consumer perceptions and purchase behaviours are typically determined by phenolic influenced sensory attributes such as astringency, bitterness, and sourness. Marketing strategies would be more effective if machine learning methods assisted winemakers in understanding the chemical parameters that influence panellists' sensory evaluations of Pinot noir wines. Nowadays, feature selection methods such as random forest classifier and neighbourhood component analysis are utilised to select important factors. In the meantime, decision trees are utilised in regression or classification models as opposed to feature selection methods. In this study, decision trees were able to identify the relationships between sensory attributes and important chemical parameters in Pinot noir wines from diverse product extrinsic cues (regions of origin, vintages and price points) and novice panels. Decision trees not only could be utilised to build soft sensors but also work as effective feature selection methods, which could inspire winemakers to make proper Pinot noir wines. With the help of principal component analysis and scatter plots, it was discovered, for instance, that total phenolics, total flavanols, total flavan-3-ols, and total tannins in wines could considerably contribute to astringency, bitterness, and sourness and that total anthocyanin could contribute to clarity regardless of diverse Pinot noir wine or novice panels.

A new perspective is presented to investigate the sensorially relevant gas-phase concentrations of volatile compounds in wine. This is achieved by measuring the partition coefficients and matrix-phase concentrations of volatiles using static headspace-gas chromatography-ion mobility spectrometry (SHS-GC-IMS). Physicochemical properties that can contribute to the partition behaviors of ten volatile esters, such as hydrophobicity and matrix temperature, are also discussed. Partition coefficients are then linked to quantitative measurements to obtain partial pressures, which describes the availability of volatile compounds in the gas phase. The concept of partition coefficients and partial pressure have then been applied to a time series of aroma changes due to oxidation in commercial wines. As a follow-up study, a full factorial design was devised to inspect the impact of three common wine matrix components, namely, copper, polyphenols and ascorbic acid, on the partial pressure changes after 30-day oxidation treatment in either full-alcohol or low-alcohol simulated wine matrices. Interesting interactive effects between antioxidant behaviors and alcohol levels were elucidated, especially around the controversial use of ascorbic acid in winemaking. These results can guide winemakers who wish to minimize oxidative damage to wine aroma during wine storage or bulk transport, where ullage may be present or continual oxygen ingress may be occurring.

The milk and dairy industries are some of the most profitable sectors in many countries. This business requires close control of product quality and continuous testing to ensure the safety of the consumers. The potential risk of contaminants or degradation products and undesirable chemicals necessitates the use of fast, reliable detection tools to make immediate production decisions. This review covers studies on the application of electrochemical methods to milk (i.e., voltammetric and amperometric) to quantify different analytes, as reported over the last 10 to 15 years. The review covers a wide range of analytes, including allergens, antioxidants, organic compounds, nitrogen- and aldehyde containing compounds, biochemicals, heavy metals, hydrogen peroxide, nitrite, and endocrine disruptors. The review also examines pretreatment procedures applied to milk samples and the use of novel sensor materials. Final perspectives are provided on the future of cost-effective and easy-to-use electrochemical sensors and their advantages over conventional methods.

Rheological properties of gelatin-based solutions containing different concentrations of ribose and/or glycerol were assessed before electrospun mats were manufactured and their properties investigated. Characterization included morphology, X-ray diffraction, Fourier transform infrared, solubility, swelling, the release of Maillard reaction (MR) products and their antioxidant activity. Gelatin concentrations >= 16 % w/v favoured the formation of smooth nanofibres in the electrospinning process due to their higher viscosity than for gelatin concentrations