Search Results (314)

This manuscript reviews the green synthesis of silver nanoparticles (AgNPs) and their incorporation into polymeric nanofiber composites. It discusses various synthesis methods, emphasizing eco-friendly biological approaches over chemical and physical ones due to their cost-effectiveness and reduced toxicity. The review emphasizes the enhanced antimicrobial properties of AgNPs and their composites, particularly in electrospun nanofibers, for diverse biomedical, environmental, and industrial applications. It also covers the characterization, properties, and mechanisms of AgNPs, along with the advantages of combining them with polymers such as PVA and PEO, as well as cyclodextrin, to create novel functional nanocomposites. Full article

The advancement of laser-induced graphene (LIG) has significantly enhanced the development of wearable and flexible electronic devices. Due to its exceptional physical, chemical, and electronic properties, LIG has emerged as a highly effective active material for wearable sensors. However, despite the wide range of materials suitable as precursors for LIG, the scarcity of stretchable and biocompatible polymers amenable to laser graphenization has remained a persistent challenge. In this study, laser-induced graphene (LIG) was fabricated directly on biocompatible and flexible cross-linked PDMS/PEG (with M_n (PEG) = 400 g/mol) composites for the first time, enabling their application in wearable sensors. The addition of PEG compensates for the low carbon content in PDMS, enabling efficient laser graphenization. Laser parameters were systematically optimized to achieve high-quality graphene, and a comprehensive characterization with varying PEG content (10–40 wt.%) was conducted using multiple analytical techniques. Tensile tests revealed that incorporating PEG significantly enhanced elongation at break, reaching 237% for PDMS/40 wt.% PEG while reducing Young’s modulus to 0.25 MPa, highlighting the excellent flexibility of the substrate material. Surface analysis using X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), and Raman spectroscopy demonstrated the formation of high-quality few-layer graphene with the fewest defects in PDMS/40 wt.% PEG composites. Nevertheless, the adhesion of electrical contacts to LIG that was directly induced on PDMS/PEG proved to be challenging. To overcome this challenge, we produced devices by means of laser induction on polyimide and transfer to PDMS/PEG. We demonstrate the practical utility of such devices by applying them to monitor limb motion in real time. The sensor showed a stable and repeatable piezoresistive response under multiple bending cycles. These results provide valuable insights into the fabrication of biocompatible LIG-based flexible sensors, paving the way for their broader implementation in medical and sports technologies. Full article

This review aims to advance quartz processing technology by examining the surface properties, flotation behavior, and selective flotation mechanisms of quartz mineral. Characterized by a strong negative charge over a wide pH range and an isoelectric point around pH 2, quartz surfaces allow physical adsorption of cationic collectors, particularly amines, which render the quartz surface hydrophobic and enhance bubble–particle interactions. In contrast, flotation with anionic collectors requires prior surface activation via multivalent metal cations such as Ca²⁺. The pH value of the medium plays a critical role in both collector adsorption and flotation selectivity. Both direct and reverse flotation strategies can be used, depending on whether quartz is targeted as a valuable mineral or a gangue mineral. In direct flotation, depressants like carboxymethyl cellulose and starch are used to depress gangue minerals, while in reverse flotation, quartz is depressed using chemicals such as fluoride ions and cationic polymers. To improve the efficiency and selectivity of quartz flotation, further research is needed on surface chemistry, collector adsorption mechanisms, and the transition from laboratory-scale experiments to industrial applications. Full article

Polyetheretherketone (PEEK) is a semi-crystalline thermoplastic polymer which, due to its very high mechanical properties and high chemical resistance, has found application in the automotive, aerospace, chemical, food and medical (biomedical engineering) industries. Owing to the use of additive technologies, particularly the Fused Filament Fabrication (FFF) method, this material is the most widely used plastic to produce skull reconstruction implants, parts of dental implants and orthopedic implants, including spinal, knee and hip implants. PEEK enables the creation of personalized implants, which not only have greater elasticity compared to implants made of metal alloys but also resemble the physical properties of the cortical layer of human bone in terms of their mechanical properties. Therefore, the aim of this article is to characterize polyether ether ketone as an alternative material used in the manufacturing of implants in orthopedics and dentistry. Full article

Background: Graphene oxide (GO) is widely explored as a functional additive in polymer composites; however, its simple physical dispersion in dental resins often leads to poor interfacial stability and limited long-term performance. Covalent functionalization may overcome these limitations by enabling chemical integration into the polymer matrix. This study presents the synthesis and FT-IR/Raman characterization of GRAPHYMERE^®, a novel graphene oxide-based monomer obtained through exfoliation, amine functionalization with 1,6-hexanediamine, and transamidation with methyl methacrylate. Methods: A novel GO-based monomer, GRAPHYMERE^®, was synthesized through a three-step process involving GO exfoliation, amine functionalization with 1,6-hexanediamine, and transamidation with methyl methacrylate to introduce polymerizable acrylic groups. The resulting product was characterized using FT-IR and Raman spectroscopy. Results: Spectroscopic analyses confirmed the presence of aliphatic chains and amine functionalities on the GO surface. Although some expected signals were overlapped, the data suggest successful surface modification and partial insertion of methacrylamide groups. The process is straightforward, uses low-toxicity reagents, and avoids complex reaction steps. Conclusions: GRAPHYMERE^® represents a chemically modified GO monomer potentially suitable for copolymerization within dental resin matrices. While its structural features support compatibility with radical polymerization systems, further studies are required to assess its mechanical performance and functional properties in dental resin applications. Full article

The design of materials with programmable degradation profiles presents a fundamental challenge in pattern recognition across molecular space, requiring the identification of complex structure–property relationships within an exponentially large chemical domain. This paper introduces a novel physics-informed deep learning framework that integrates multi-scale molecular sensing data with reinforcement learning algorithms to enable intelligent characterization and prediction of polymer degradation dynamics. Our method combines three key innovations: (1) a dual-channel sensing architecture that fuses spectroscopic signatures from Graph Isomorphism Networks with temporal degradation patterns captured by transformer-based models, enabling comprehensive molecular state detection across multiple scales; (2) a physics-constrained policy network that ensures sensor measurements adhere to thermodynamic principles while optimizing the exploration of degradation pathways; and (3) a hierarchical signal processing system that balances multiple sensing modalities through adaptive weighting schemes learned from experimental feedback. The framework employs curriculum-based training that progressively increases molecular complexity, enabling robust detection of degradation markers linking polymer architectures to enzymatic breakdown kinetics. Experimental validation through automated synthesis and in situ characterization of 847 novel polymers demonstrates the framework’s sensing capabilities, achieving a 73.2% synthesis success rate and identifying 42 structures with precisely monitored degradation profiles spanning 6 to 24 months. Learned molecular patterns reveal previously undetected correlations between specific spectroscopic signatures and degradation susceptibility, validated through accelerated aging studies with continuous sensor monitoring. Our results establish that physics-informed constraints significantly improve both the validity (94.7%) and diversity (0.82 Tanimoto distance) of generated molecular structures compared with unconstrained baselines. This work advances the convergence of intelligent sensing technologies and materials science, demonstrating how physics-informed machine learning can enhance real-time monitoring capabilities for next-generation sustainable materials. Full article

Polymers characterize a different and important class of materials through various industries, all with unique functional properties and structural attributes. Conventional models of polymer classification depend greatly on labor-intensive methods liable to human error and subjectivity. Hence, a continually growing requirement for new polymers with greater properties is a deep understanding and exploration of the chemical space. Hence, data-driven methods for polymers are developing and able to deal with unique challenges originating from the outstanding physical and chemical range of polymers at smaller and larger scales. Recently, Deep Learning (DL) models have considerably transformed material science by allowing for the automatic study and classification of composite polymers. In this paper, a novel optimization algorithm with a DL-Based Neural Networks for Data-Driven Polymer Classification (OADLNN-DDPC) model is proposed. The main intention of the OADLNN-DDPC model is to improve the classification model for data-driven polymers using state-of-the-art optimization algorithms. The data normalization stage is initially executed via Z-score normalization to convert input data into a beneficial format. In addition, the proposed OADLNN-DDPC model implements the bald eagle search (BES) model for feature selection to detect and retain the most appropriate features. For the polymer classification process, the bidirectional gated recurrent unit (BiGRU) technique is employed. Lastly, the zebra optimizer algorithm (ZOA) is implemented for the tuning process. Extensive experiments conducted on a polymers dataset with 19,500 records and 2048 features demonstrated that OADLNN-DDPC achieves an accuracy of 98.58%, outperforming existing models, such as LSTM (83.37%), PLS-DA (88.18%), and K-NN (98.36%). The simulation process of the OADLNN-DDPC model is performed under the polymer classification dataset. The experimental analysis specified that the OADLNN-DDPC model demonstrated improvement over another existing model. Full article

Despite its broad application due to its affordability, biodegradability, and natural antimicrobial and antioxidant activities, chitosan (CS) still exhibits limitations in mechanical strength and barrier effectiveness. Owing to its unique chemical characteristics, itaconic acid (IT) presents potential as a compatibilizing agent in polymeric blend formulations. Biodegradable polymers composed of chitosan (CS), itaconic acid (IT), and starch (S) were synthesized using two polymerization methods. The first method involved grafting IT onto CS at varying ratios of IT (4%, 6%, and 8% wt.), using 1% v/v acetic acid/water as the solvent and potassium persulfate as the initiator. In the second approach, starch (S) was blended with the copolymer P(CS-g-IT) at concentrations of 1%, 3%, and 5%, utilizing water as the solvent and glacial acetic acid as a catalyst. The resulting biodegradable films underwent characterization through FTIR, TGA, SEM, and mechanical property analysis. To further explore the effects of combining IT, starch, and carbon black, the blends, referred to as P[(CS-g-IT)-b-S], were also loaded with carbon black. This allowed for the evaluation of the materials’ physicomechanical properties, such as viscosity, tensile strength, elongation, and contact angle. The findings demonstrated that the presence of IT, starch, and carbon black collectively improved the films’ mechanical performance, physical traits, and biodegradability. Among the samples, the blended copolymer with 1% starch exhibited the highest mechanical properties, followed by the grafted copolymer with 8% IT and the blended copolymer mixed with carbon black at 7%. In contrast, the blended copolymer with 5% starch showed the highest hydrophilicity and the shortest degradation time compared to the grafted copolymer with 8% IT and the blended copolymer mixed with 7% carbon black. Full article

The need to find sustainable solutions to conventional plastics has driven research into alternative materials, including bioplastics, which represent a promising option for reducing pollution and enhancing the value of renewable resources. In this study, bioplastics made from polyvinyl alcohol (PVA) and proteins extracted from the larvae of Black Soldier Fly (BSF), an insect capable of converting organic waste into high-value biomass, were produced and characterized. The proteins were obtained by hydrolysis of defatted BSF larvae with superheated water, avoiding harsh chemical reagents. Next, polymer films were fabricated by mixing PVA and hydrolyzed BSF proteins in different proportions and analyzed for morphological, physical-chemical, mechanical and biodegradability characteristics. The results obtained show that as the BSF protein content increases, the films show a reduction in thermal stability and mechanical properties, and also, they exhibit higher biodegradability, correlated with higher wettability, solubility and ability to absorb moisture. This research highlights the value of using organic waste-fed insects as a resource for bioplastic production, offering an alternative to traditional polymers and contributing to the transition to sustainable materials. Full article

Wastewater reinjection is an important measure for balancing the sustainable development of petroleum resources with environmental protection. However, the polymer-containing wastewater generated after polymer injection presents challenges such as reservoir damage and waterflooded zone identification in oilfields. To address this, this study systematically examined the impact of injection water with varying salinities on the flow characteristics and electrical responses of low-permeability reservoirs, based on rock-electrical and multiphase displacement experiments. Additionally, this study analyzed the factors influencing the damage to reservoirs during polymer-containing wastewater reinjection. Mass spectrometry, chemical compatibility tests, and SEM-based micro-characterization techniques were employed to reveal the micro-mechanisms of reservoir damage during the reinjection process, and corresponding protective measures were proposed. The results indicated the following: (1) The salinity of injected water significantly influences the electrical response characteristics of the reservoir. When low-salinity wastewater is injected, the resistivity–saturation curve exhibits a concave shape, whereas high-salinity wastewater results in a linear and monotonically increasing trend. (2) Significant changes were observed in the pore-throat radius distribution before and after displacement experiments. The average frequency of throats within the 0.5–2.5 µm range increased by 1.894%, while that for the 2.5–5.5 µm range decreased by 2.073%. In contrast, changes in the pore radius distribution were relatively minor. Both the experimental and characterization results suggest that pore-throat damage is the primary form of reservoir impairment following wastewater reinjection. (3) To mitigate formation damage during wastewater reinjection, a combined physical–chemical deblocking strategy was proposed. First, multi-stage precision filtration would be employed to remove suspended solids and oil contaminants. Then, a mildly acidic organic-acid-based compound would be used to inhibit the precipitation of metal ions and dissolve the in situ blockage within the core. This integrated approach would effectively alleviate the reservoir damage associated with wastewater reinjection. Full article

Assessing the detailed characteristics of recycled plastics is essential for evaluating their quality and suitability for high-value applications compared to virgin polymers. This review provides a comprehensive overview of advanced analytical techniques used for characterizing the chemical, structural, morphological, and physical properties of recycled polymeric materials. The techniques examined include Fourier Transform Infrared Spectroscopy (FTIR), Micro-Raman spectroscopy, X-ray Fluorescence (XRF), Inductively Coupled Plasma (ICP) techniques, X-ray Powder Diffraction (XRPD), Differential Scanning Calorimetry (DSC), and Scanning Electron Microscopy (SEM). These methods are critically assessed for their effectiveness in detecting polymer degradation, surface and structural alterations, and the presence of contaminants—factors frequently introduced during mechanical recycling processes. For each technique, this review outlines the working principles, sample preparation protocols, and illustrative case studies while discussing their advantages, limitations, and operational challenges. By synthesizing current knowledge and methodological advancements, this review aims to support the development of robust and standardized quality assessment protocols. Enhancing the reliability and precision of recycled plastic characterization will improve their acceptance as high-quality secondary raw materials, thereby facilitating their upcycling and contributing to the broader goals of the circular economy. Full article

Recent studies focus on recovering materials from Waste Electrical and Electronic Equipment (WEEE). Printed Circuit Boards (PCBs) are promising due to their heterogeneous composition, which includes precious metals, ceramics, and polymers. This research analyzes the leaching process of computer PCB waste to recover valuable metals such as copper and gold. The study involved physical-mechanical processing of PCB samples followed by chemical composition characterization. Metal extraction was performed through a three-stage leaching process. The first two stages used 2 M and 3 M sulfuric acid with hydrogen peroxide as leaching agents, achieving about 75% copper extraction. In the third stage, parameters for gold leaching using thiosulfate were evaluated, including concentrations of ammonium hydroxide and copper sulfate, reaction times (1–4 h), and temperatures (30, 40, and 50 ${\phantom{­}}^{\circ }$C). The leaching solution comprising 0.12 M sodium thiosulfate, 0.2 M ammonium hydroxide, and 20 mM copper sulfate yielded maximum gold extractions of 14.76% for fine and 15.73% for coarse fractions at 40 ${\phantom{­}}^{\circ }$C. In conclusion, the proposed method for recovering metals from PCBs can reduce the environmental impact of improper WEEE disposal while promoting a circular economy of secondary raw materials. Full article

Lignin, the most abundant aromatic polymer in nature, plays a critical role in lignocellulosic biomasses by providing structural support. However, its presence complicates the industrial exploitation of these materials for biofuels, paper production and other high-value compounds. Annually, the industrial extraction of lignin reaches an estimated 225 million tons, yet only a fraction is recovered for reuse, with most incinerated as low-value fuel. The growing interest in lignin potential has sparked research into sustainable recovery methods from lignocellulosic agro-industrial wastes. This review examines the chemical, physical and physicochemical processes for isolating lignin, focusing on innovative, sustainable technologies that align with the principles of a circular economy. Key challenges include lignin structural complexity and heterogeneity, which hinder its efficient extraction and application. Nonetheless, its properties such as high thermal stability, biodegradability and abundant carbon content place lignin as a promising material for diverse industrial applications, including chemical synthesis and energy generation. A structured analysis of advancements in lignin extraction, characterization and valorization offers insights into transforming this undervalued by-product into a vital resource, reducing reliance on non-renewable materials while addressing environmental sustainability. Full article

Polyvinylidene fluoride (PVDF) polymer films, renowned for their exceptional piezoelectric, pyroelectric, and ferroelectric properties, offer a versatile platform for the development of cutting-edge micro-scale functional devices, enabling innovative applications ranging from energy harvesting and sensing to medical diagnostics and actuation. This paper presents an in-depth review of the material properties, fabrication methodologies, and characterization of PVDF films. Initially, a comprehensive description of the physical, mechanical, chemical, thermal, electrical, and electromechanical properties is provided. The unique combination of piezoelectric, pyroelectric, and ferroelectric properties, coupled with its excellent chemical resistance and mechanical strength, makes PVDF a highly valuable material for a wide range of applications. Subsequently, the fabrication techniques, phase transitions and their achievement methods, and copolymerization and composites employed to improve and optimize the PVDF properties were elaborated. Enhancing the phase transition in PVDF films, especially promoting the high-performance β-phase, can be achieved through various processing techniques, leading to significantly enhanced piezoelectric and pyroelectric properties, which are essential for diverse applications. This concludes the discussion of PVDF material characterization and its associated techniques for thermal, crystal structure, mechanical, electrical, ferroelectric, piezoelectric, electromechanical, and pyroelectric properties, which provide crucial insights into the material properties of PVDF films, directly impacting their performance in applications. By understanding these aspects, researchers and engineers can gain valuable insights into optimizing PVDF-based devices for various applications, including energy-harvesting, sensing, and biomedical devices, thereby driving advancements in these fields. Full article

The environmental concerns associated with synthetic polymers have intensified the search for sustainable and biodegradable alternatives, particularly for food packaging applications. Natural biopolymers offer promising solutions due to their biodegradability, reduced environmental impact, and reliance on renewable resources. Among these, agri-food waste and by-products have gained significant attention as valuable feedstocks for polymer production, supporting a circular economy approach. This review critically examines the current status of biopolymers derived from plant, animal, and microbial sources, focusing on their physical and chemical properties and their application in food packaging. The findings underscore that the properties of plant- and animal-based biopolymers are heavily influenced by the source material and extraction techniques, with successful examples in biodegradable films, coatings, and composite materials. However, a critical gap remains in the characterization of microbial biopolymers, as research in this area predominantly focuses on optimizing production processes rather than evaluating their material properties. Despite this limitation, microbial biopolymers have demonstrated considerable potential in composite films and fillers. By addressing these gaps and evaluating the key factors that influence the success of biopolymer-based packaging, we contribute to the ongoing efforts to develop sustainable food packaging solutions and reduce the environmental impact of plastic waste. Full article