Transfer and updating of near infrared (NIR) spectroscopy model of fruit internal quality has become the focus of the industrial application. Internet of Things (IoT) and deep learning (DL) were proposed to perform soluble solids content (SSC) model transfer of apple by NIR. A model transfer platform including low-power handheld internal quality terminal and interacting cloud data system had been constructed. An autoencoder (AE) neural network model was developed for the spectral correction and model transfer. The average time for transmitting detection results to the detection terminal was 1.5 to 2.0 s, with a 100% effective transmission rate. After 5000 iterations of training, the correlation coefficient of different detection terminals improved by 55%, and the root mean square error was reduced by 94%. Selected samples from the second batch of apples detected by the No. 1 detection terminal were added to the original neural network for training. After adding 30 samples, the correlation coefficient increased by 13% and the root mean square error decreased by 90%. The results demonstrated that the AE neural network for spectral correction was effective in eliminating differences between devices and significantly reducing the impact of different detection terminals on the accuracy of NIR detection of SSC in apples. Therefore, the NIR detection model transfer technique could be practically exploited for fruit quality control assessment using different detection terminals. 

Detection model transfer of apple soluble solids content based on NIR spectroscopy and deep learning

Construction of polyphosphazene-coated halloysite nanotube composite with in-situ released PO43- for efficient and rapid removal of uranium from wastewater

Chrysanthemum, a traditional Chinese medicine, possesses diverse pharmacological effects with a myriad of origins and varieties. Due to the difficulty of acquiring and modeling all Chrysanthemum varieties comprehensively, it becomes imperative to establish models based on the available samples in order to swiftly identify newly emerging Chrysanthemum categories from a limited dataset. In this study, hyperspectral imaging combined with deep learning was exploited for the classification of fourteen Chrysanthemum categories by origin and variety. Leveraging the convolutional neural network, the few-shot class-incremental learning (class-IL) method was applied to the detection of few-shot Chrysanthemum categories. By employing a Replay training strategy, the challenges associated with severely sample-limited and unbalanced classes can be effectively addressed. When incrementally expanding from four to fourteen categories, with each new category consisting of only 30 samples, the achieved accuracy on the test dataset reached 80.13 %. This remarkable performance exhibited a narrow margin of 15.75 % compared to conventional supervised learning, which utilized an incremental training sample size nearly 100 times larger. This approach consistently outperforms conventional supervised learning methods, thereby showcasing its remarkable scalability. It facilitates the practical implementation of few-shot learning and deep learning models, providing a substantiated framework to tackle real-world scenarios in various domains using hyperspectral imaging and related techniques. 

Identification of chrysanthemum using hyperspectral imaging based on few-shot class incremental learning

Sulfonephthaleins represent one of the most common and widely employed reactive dyes in analytical chemistry, thanks to their stability, low-cost, well-visible colors, reactivity and possibilities of chemical modification. Despite being first proposed in 1916, nowadays, these molecules play a fundamental role in biological and medical applications, environmental analyses, food quality monitoring and other fields, with a particular focus on low-cost and disposable devices or methods for practical applications. Since up to our knowledge, no reviews or book chapters focused explicitly on sulfonephthaleins have ever been published, in this review, we will briefly describe sulfonephthaleins history, their acid-base properties will be discussed, and the most recent applications in different fields will be presented, focusing on the last ten years literature (2014–2023). Finally, safety and environmental issues will be briefly discussed, despite being quite controversial. 

The colorful world of sulfonephthaleins: Current applications in analytical chemistry for “old but gold” molecules

Polyurethane elastomer has become a current focal point in the field of damping materials due to superior comprehensive properties. However, its effective damping temperature range is limited, and existing methods often lead to a reduction in mechanical performance. Moreover, polyurethane exhibits poor water resistance and flame resistance, constraining its applications. In this study, we introduce a small amount of dangling chain and aromatic dynamic disulfide bond into polyurethane to achieve a balance between damping and mechanical performance. Notably, the fluorinated dangling chain improves water resistance of the material synchronously and effectively. Additionally, ammonium polyphosphate modified by melamine and diethyl bis(2-hydroxyethyl)aminomethylphosphonate are introduced into polyurethane to improve flame resistance. The prepared polyurethane elastomer exhibits excellent comprehensive performance, featuring an effective damping (tanδ≥0.3) temperature range of 153.2 °C (−53.2 °C ∼ 100 °C), V-0 level flame resistance and excellent water resistance. Meanwhile, the heat stability of the polyurethane elastomer has been significantly enhanced, while maintaining a certain level of mechanical performance (9.72 ± 0.25 MPa, 602.4 ± 30.1%). These improvements extend the service life of polyurethane and expand its range of potential applications. 

A multi-functional polyurethane elastomer with high damping, water resistance and flame retardancy

Near infrared spectroscopy quantification based on Bi-LSTM and transfer learning for new scenarios.

A series of aromatic polyesters were prepared by the reaction of bisphenol-A and bis(hydroxyphenyl)butane with diacyl chloride monomers by phase transfer interfacial polycondensation in order to improve the processability of the bisphenol A-based polyarylate. The microstructure, molecular weight, crystallinity, solubility, thermal properties, mechanical properties, and optical properties of the prepared copolyesters were investigated. Inherent viscosities of the copolyesters are in the range of 0.14–0.53 dl g−1, and their average molecular weights are 7362–44,413 g mol−1, respectively. The feed compositions and copolymer compositions were nearly identical. The results show that with the increase in the content of side ethyl units, the copolyester gradually transforms into an amorphous structure, which is also verified by the improvement in dissolution properties. When the copolyester backbone was introduced into the side ethyl units, the thermal decomposition temperature was less affected and varied in the range of about 10°C, while the value of glass transition temperature reduced from 196.5°C to 165.1°C. The mechanical properties of the polymers are similar to those of the industrial commodity U-100. In addition, the copolyester films have good optical properties, and the transmittance reached the maximum value of 98.41% when the content of bis(hydroxyphenyl)-butane was 10%. 

Synthesis of aromatic polyesters derived from bisphenol‐A and bis(hydroxyphenyl)butane with diacyl chloride monomers

Waterborne polyurethane (WPU) is an environmentally friendly product that can replace organic solvents with water. Still, its linear molecular chain structure and the presence of hydrophilic groups greatly affect water resistance and mechanical properties, limiting its wide application in the field of coatings. Herein, a series of fluorosilicone modified waterborne polyurethanes (FSiWPUs) were prepared by introducing tridecafluoro-nonanol (TFN) and (3-aminopropyl) triethoxysilane (APTES) into the ends of molecular chains of WPUs. These chains were constituted by different soft segments, including polybutylene adipate glycol, polycarbonate diol, or polytetramethylene ether glycol. Then fluorine element in TFN migrates and aggregates onto the surface during FSiWPU film-forming to reduce the surface energy. Meanwhile, the hydrolytic condensation of APTES forms a Si–O–Si micro-crosslinking structure. As a result, the two capping agents enable the modified FSiWPU to have better hydrophobicity, water resistance, and mechanical properties. The research results show that when the TFN:APTES molar ratio of capping agents introduced is 8:2, the static water contact angles of FSiWPUs with different soft sections reach 161.4°–165.3° and the maximum water absorption rate reduce to 8.9%–13.78%. Due to the simultaneous improvement of hydrophobic, water resistance, and mechanical properties, the modified FSiWPUs become the most promising candidates for superhydrophobic coatings. 

Synergistic modification of short‐chain fluoro‐alcohol and siloxane end‐capping agents endowing an enhanced superhydrophobic waterborne polyurethane coating

A novel bisphenol A‐free polyarylates synthesis strategy: 4,4′‐sulfobisphenol/2,2‐bis(4‐hydroxyphenyl)butane co‐polyarylate prepared by interfacial polymerization

A series of novel copolyarylates(co-PARs) containing phenol red units in the backbone were synthesized by interfacial polymerization at 10°C from bisphenol A (BPA), phenol red (PR) and diacid chloride monomers. The obtained copolyarylates (co-PARs) are all amorphous, the inherent viscosity (ηinh) of 0.22–0.62 dl g−1, and the number- and weight-average molecular weight are 10,200–46,200 and 38,600–203,600, respectively. Adding a small number of PR units to the molecular chains improved the processing fluidity of polyarylates, and the glass transition temperatures (Tg) decreased from 202.8 to 166.7°C. In addition, the co-PARs have excellent thermal stability with the maximum thermal decomposition temperature of 532.4–545.2°C. The co-PARs show the best mechanical properties (57.6 MPa) when the PR content is 15 mol%. The transmittances of the co-PARs at 400 and 450 nm are 79.2%–97.9% and 87.0%–99.8%, respectively, and the cut-off wavelength is between 320 and 328 nm. The designed and synthesized copolyarylates can be considered as a promising and easy-to-process high-performance engineering plastic. 

Synthesis and properties of copolyarylates containing phenol red units

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