High-demand biopolymers for the plastics industry’s transformation — a technical, economic and environmental assessment of production processes

How BPA-free alternative fluorene-9-bisphenol affects the freshwater ecosystems: acute toxicity, immunology and biochemical responses of mussels?

This study addresses production capacity limitations in the K-XX plastic injection line (the company’s primary production line) at PT XYZ, where output is measured in part-sets (finished product units). The installed capacity of 2,250 part-sets per day is insufficient to meet the daily demand of 2,650 part-sets, resulting in overtime dependency and a 40.5% increase in operating costs in 2024 compared to the previous year. The objective of this study is to optimize production capacity using a data-driven quantitative approach. The research integrates the DMAIC (Define–Measure–Analyze–Improve–Control) framework with Discrete-Event Simulation modeling using Tecnomatix Plant Simulation. Initial performance evaluation is conducted through Overall Equipment Effectiveness (OEE) measurement and Six Big Losses analysis to identify root causes of capacity constraints. The simulation model is validated using MAE, RMSE, and MAPE indicators. The results indicate an 8.89% increase in production capacity, raising daily output from 2,250 to 2,450 part-sets. OEE improves from 78.0% to 85.3%, exceeding the company target and approaching world-class manufacturing standards. The optimization also reduces annual overtime costs by 43.5%, with a prediction error of 1.69% MAPE. This study contributes by integrating DMAIC and Discrete-Event Simulation as a quantitative decision-support framework for sustainable and cost-efficient production capacity optimization in plastic manufacturing industries.

Curcumin alleviates BPAF-induced ferroptosis in caprine endometrial epithelial cells through inhibition of endoplasmic reticulum stress and autophagy.

ABSTRACT Di(2-ethylhexyl) phthalate (DEHP) is a widely used industrial plasticizer, raising global concerns due to its potential endocrine-disrupting effects and environmental persistence. Human exposure to DEHP primarily occurs through the ingestion of contaminated food and water, inhalation of airborne particles, and dermal contact with products containing DEHP. Understanding the toxicological mechanisms of DEHP is essential for evaluating its health risks and developing effective strategies to mitigate its adverse effects. In this study, we conducted long-term exposure experiments to DEHP using both an animal model and in vitro system to investigate the complex interplay among DNA methylation, hyperactivation of macroautophagy/autophagy, mitochondrial dysfunction, and lipid accumulation induced by DEHP. The results revealed that DEHP exposure induced the degradation of DNMT1 (DNA methyltransferase 1) by enhancing its interaction with the autophagy-related protein SQSTM1 (sequestosome 1). DNMT1 degradation resulted in decreased methylation of the promoter regions of genes associated with autophagosome formation, subsequently increasing their expression. The resulting demethylation excessively activated autophagy, contributing to mitochondrial dysfunction and lipid accumulation in the liver. This study uncovered a previously unrecognized interplay among hyperactivation of autophagy, mitochondrial dysfunction, and lipid accumulation in the context of DEHP exposure. These findings enhanced our understanding of DEHP’s toxicity and underscored concerns about the long-term health effects of environmental pollutants, particularly regarding metabolic diseases. Abbreviation: ATG5:autophagy related 5; ATG16L1: autophagy related 16 like 1; BECN1:beclin 1; COX4/COXIV: cytochrome c oxidase subunit 4; BS-seq:bisulfite sequencing; DCFH-DA: 2′,7′-dichlorodihydrofluoresceindiacetate; DEHP: di(2-ethylhexyl) phthalate; DNMT1: DNAmethyltransferase 1; DNMT3A: DNA methyltransferase 3A; FABP4: fattyacid binding protein 4; FASN: fatty acid synthase; LPL: lipoproteinlipase; MAP1LC3/LC3: microtubule associated protein1 light chain 3; NAFLD: nonalcoholic fatty liver disease; NR1H3:nuclear receptor subfamily 1 group H member 3; PPARG: peroxisomeproliferator activated receptor gamma; RB1CC1: RB1 induciblecoiled-coil 1; SQSTM1: sequestosome 1; SREBF2: sterol regulatoryelement binding transcription factor 2; VDAC1: voltage dependentanion channel 1.

Biomonitoring Equivalents for interpreting mandelic and phenylglyoxylic acid in urine resulting from exposures to styrene and ethylbenzene.

Polyethylene terephthalate (PET) plays a critical role in the global plastics industry due to its outstanding properties. However, the continuously growing demand for PET not only challenges production capacity but also leads to substantial waste accumulation. Herein, we innovatively integrate enzymatic depolymerization with an efficient synthesis process to achieve the sustainable development of PET. Using mono(2-hydroxyethyl) terephthalate (MHET), which is a key intermediate derived from enzymatic depolymerization of PET, as the raw material, a stepwise heating esterification process is developed to synthesize PET under low ethylene glycol (EG) usage. Under the optimal conditions, the molar ratio of MHET to EG is reduced to 1:0.2-0.4, while the esterification and polycondensation times are shortened to approximately 3-3.5h and 1-1.5h, respectively. Moreover, the synthesized PET demonstrates excellent thermal and mechanical properties, which are comparable to those of commercially available PET, along with the melting point of 252.5°C, the initial decomposition temperature of 388.8°C, the maximum decomposition temperature of 424.8°C, tensile strength of 79.2MPa. This approach significantly reduces EG consumption while shortening the total polymerization reaction time for esterification and polycondensation, providing a new direction for the efficient synthesis and recycling of PET.

Background: The transition from fossil-derived polymer additives to renewable alternatives is essential to mitigate environmental persistence and ensure chemical safety within the plastics industry. This review provides a comprehensive overview of recent developments in bio-based functional additives and their integration into circular economy frameworks. Methods: Following PRISMA guidelines, a systematic literature search was conducted using the Scopus database for studies published between 2023 and 2026. Search terms targeted bio-based plasticizers, flame retardants, antioxidants, and compatibilizers. Studies were screened against predefined inclusion criteria, specifically focusing on experimental validation in polymer matrices, while data mining was employed to map emerging research fronts. Results: From an initial 996 records, 54 studies were selected after removing duplicates and ineligible articles. The findings highlight a paradigm shift from passive physical fillers toward active, multifunctional macromolecular agents. Recent literature demonstrates that targeted molecular interventions, such as phosphorylated lignin and biomimetic structures, can resolve trade-offs between ductility and thermal stability at low loadings (<5 wt%). Synthesis routes, performance outcomes, and end-of-life trajectories for each additive class are summarized. Conclusions: Bio-based additives have evolved from simple substitutes into strategic tools for the molecular programming of sustainable polymers. Although challenges regarding scalability and high-temperature processing persist, their integration into circular economy strategies establishes a clear roadmap for next-generation bioplastics.

The environmental degradation of industrial and consumer plastics leads to the widespread presence of plastic micro- and nanoparticles in marine and terrestrial environments. Yet, their impacts on environmental safety and human health remain poorly understood. A key step in assessing these impacts is elucidating the bio-nano interactions that govern particle behavior in biological media. Here, we combine all-atom molecular dynamics with coarse-grained simulations to investigate protein adsorption and corona formation on polypropylene nanoparticles. The coarse-grain potentials are systematically derived from atomistic simulations of individual amino acids interacting with polypropylene fragments and surfaces. Using these potentials, we evaluated protein binding affinities on various polypropylene surfaces. Corona formation and composition are investigated using a kinetic Monte Carlo approach that mimics the competitive adsorption and desorption dynamics of proteins from a model solution. We show that the final corona composition reflects the relative binding energies and the number of favorable binding orientations of the competing proteins. Understanding the driving forces of adsorption and corona formation may help design safer polymeric materials and inform environmental risk assessment.

Epoxides have been widely used in the daily chemical and plastics industries. However, as a mainstream epoxide production approach, the direct oxidation of olefins with O2 often suffers from extensive energy consumption and excessive CO2 emission. Here, we provide an olefin epoxidation strategy via a photodriven Br-mediated pathway, which exhibits a broad range of extension to olefin substrates, including linear alkenes, cyclic olefins, and aromatic olefins. Employing ethylene epoxidation as a model reaction, a high ethylene oxide yield rate of 7.19 mmol g-1 h-1 with a selectivity of 90.3% was achieved over Pd3.91Au0.50/TiO2 under simulated sunlight. After a 5-day (40 h) outdoor experiment, 862.9 mg of ethylene oxide was obtained by natural sunlight irradiation. Mechanism investigations confirmed that the photogenerated holes oxidized Br- into high-activity Br radicals over Pd3.91Au0.50/TiO2 that initiated the reaction. The alloying of Au and Pd modulated the adsorption capacity of Br and C2H4 species on Pd3.91Au0.50/TiO2 to promote 2-bromoethanol intermediate production, which further underwent spontaneous cyclization into ethylene oxide under NaOH supply.

Quality control is essential for ensuring manufacturing processes consistently meet predefined specifications and for minimizing the risks caused by process deviations. The MEWMA control chart is widely used for detecting small shifts in multivariate processes which does not require strict multivariate normality but the performance can be compromised when data contain outliers or high multicollinearity that commonly found in plastic waste processing. This study proposes a robust monitoring approach by integrating PCA to address multicollinearity, Bayesian estimation to improve parameter robustness. The four charts examined in this study are PCA-Bayesian MEWMA (SELF), PCA-Bayesian MEWMA (MSELF), PCA-Bayesian MEWMA (KLF), and PCA-MEWMA using Bootstrap control limit as comparison. These charts are evaluated across 324 simulated scenarios, varying in collinearity levels (0.2, 0.6, 0.95), sample sizes (10, 20, 30), outlier proportions (5%, 10%, 15%), and smoothing parameters (λ = 0.2, 0.5, 0.8). Performance is measured using Average Run Length (ARL), Standard Deviation of Run Length (SDRL), Median Run Length (MRL), and False Alarm Rate (FAR). Results indicate that the PCA-Bayesian MEWMA outperformed PCA-MEWMA using Bootstrap control limit. PCA-Bayesian MEWMA (SELF) excelled under clean data condition, whereas PCA-Bayesian (MSELF) provided stable detection under high correlation, moderate-to-high outlier contamination, and larger smoothing parameters, achieving an average ARL of 3.44, an SDRL of 0.58, an MRL of 3.46, and FAR of 0.03, making it well-suited for monitoring complex industrial plastic waste processes and demonstrating its effectiveness for robust quality monitoring in production.

To design and develop an AI-based plastic surgery recommendation system using 3D photographs and psychological questionnaire surveys, aiming to provide personalized treatment solutions for the plastic surgery industry. Based on artificial intelligence technology, this study utilized patients' 3D photographs and psychological questionnaire results as training samples to construct a personalized AI-based plastic surgery recommendation system. This system comprehensively considers factors, such as patients' anxiety levels, economic status, and psychological expectations. The study selected 5543 cases of plastic surgery outpatients aged 18-55 years, collected their 3D photographs and questionnaire data, and used these for AI system training. The software predicted treatment projects and compared them with doctors' predictions to validate the system's accuracy and patient satisfaction. Third-party doctors evaluated the system's safety, ultimately developing an efficient and accurate plastic surgery recommendation system. The economic downturn in the post-COVID-19 era significantly impacted psychological health and the plastic surgery industry. Factors, such as age, education level, income, and gender, had significant effects on patients' psychological state and treatment willingness. The AI system integrated patients' psychological state, gender, income, and physical characteristics, providing personalized plastic surgery treatment suggestions and achieving a 93.25% patient satisfaction rate. These results indicate that the AI system offers comparable accuracy and safety to physicians while improving satisfaction, meaning that it could enhance clinical decision-making efficiency. The AI-based personalized plastic surgery recommendation system offers an innovative solution for the industry, enhancing the accuracy of treatment suggestions and patient satisfaction, thereby promoting sustainable development. In the post-pandemic era, the plastic surgery industry should focus on patients' physical, psychological, and economic factors to achieve personalized services. Experiment/New Technology. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Role of Bisphenol A and its Analogues on Epigenetics and their Impact on the Developmental Origins of Female and Male Reproductive Disorders.

In the debate on microplastic (MP) pathways into the environment, the plastics industry is often highlighted but rarely examined in detail. This study investigates MP emissions captured during wastewater pretreatment at eleven industrial plants in Germany, focusing on plastic producing and processing facilities that produce MP-sized products (<2000 μm). Raw wastewater and pretreatment effluents were analyzed. The MP removal efficiencies of single mechanical pretreatment systems (sedimentation, flotation, chamber filter press, and sand filtration) were examined. Two analytical methods for determining MP mass and MP numbers (particles (MPP) and fibers (MPF)) were used in parallel and compared. Raw wastewater concentrations varied between 1·10 4 –3·10 9 MPP m −3 and 5–6·10 4 mg MP m −3 . Partial flows of wastewater from granulation and pulverization processes contained 2·10 5 –1·10 7 MPP m −3 and 5·10 2 –2·10 4 mg MP m −3 . Discharged wastewater into the sewage system after pretreatment showed lower concentrations of 2·10 3 –5·10 6 MPP m −3 and 5·10 −2 - 5·10 3 mg MP m −3 . Mechanical pretreatment reduced MP concentrations by one to three log levels. Sand filtration and chamber filter press had the highest mean MP removal efficiencies of 99.5% and 99.9%, respectively. No MPF were found. Only the polymer types used or produced were identified at the investigated sites, predominantly as MPP < 500 μm. The results show that established mechanical treatment technologies for particulate matter are effective for MP removal. Moreover, the analysis indicates that mass analysis may serve as a cost-effective and efficient method for MP self-control in industrial settings. • Wastewaters within the plastic production chain show high MP concentrations. • Wastewater pretreatment is a crucial first barrier to prevent MP from entering the environment. • Existing mechanical treatments remove MP sufficiently up to 99.9%. • High MP loads from shaping processes may justify separate wastewater treatment. • Low-maintenance DSC analysis suffices for effluents from plastic facilities.

Seasonal dynamics, risk prioritization, and management implications for industrial chemicals, pesticides, and PPCPs in the Yangtze River Delta.

Preterm birth attributable to exposure to chemicals used in plastic materials: a global estimate.

Recent years have seen not only by the widespread use of plastics in many industries but also by the growing importance of recycling and the search for alternative methods for plastic waste disposal. The work proposes the integration of plastic refining products into the hydrotreating process of traditional petroleum fractions. The effect of mono- (Y/ZSM-23) and bi-zeolite (Y+ZSM-23) sulfide NiMo catalysts on the hydrotreating process of feedstock comprising chlorine-containing thermolysis oil is studied. It is shown that all synthesized catalysts provide conversion of chlorine-containing compounds above 92%. It is found that zeolite-containing catalysts in the hydrotreating process affect the fractional composition of the obtained products due to cracking and isomerization reactions, contributing to an increase in the yield of light fractions. It is shown that the catalyst based on zeolite Y demonstrates the potential for its application due to its high activity in the conversion of heteroatomic compounds and high-boiling n-alkanes.

ABSTRACT This research investigates the application of near‐infrared (NIR) laser heating technology applied to polyethylene terephthalate (PET) and polypropylene (PP) preforms to mitigate the high energy consumption and low efficiency associated with conventional halogen lamp heating. Compared to traditional methods, NIR laser heating exhibits significant advantages in terms of both spectral selectivity and angular directivity of the radiation. In this study, the laser beam was successfully shaped and homogenized into a uniform spot using a customized optical system based on a segmented freeform mirror. The photothermal transfer process was simulated based on fundamental principles, including the Beer–Lambert law, employing finite element analysis. Experimental results demonstrate that laser heating allows for the control of the outer‐to‐inner surface heating rate ratio of PET sheets at 1.24, which falls within the acceptable range for the stretch blow molding process. Furthermore, a surface morphology engineering strategy, utilizing the light trapping effect induced by surface microstructures, was implemented to enhance the optical absorption properties of both PET and PP materials. This strategy leads to a 26.9% increase in the absorptance of PET preforms and a further 25% improvement in heating efficiency, thereby effectively elevating the photothermal conversion efficiency during the laser heating process. Crucially, the proposed system radicalizes energy efficiency, achieving an energy‐saving ratio of over 75% by reducing power consumption from 20 kW in traditional ovens to below 5 kW. This work demonstrates considerable application potential within the plastic packaging industry for technological upgrading and sustainable development.

Abstract The use of plastics in the automotive industry is increasing due to their versatility, light weight and affordability. To improve their sustainability credentials, incorporation of recycled content is desired, driven by recent European Union mandates for 25% recycled content for automotive plastics. Current methods to quantify recycled content, however, are imprecise and could promote fraud. This paper extends a method to quantify recycled content in packaging plastics using a fluorescent brightener, 4,4′‐bis(2‐benzoxazolyl)stilbene (BBS), to automotive‐grade polymers. BBS aggregates above threshold concentrations to exhibit aggregation‐induced enhanced emission (AIEE). This study investigates whether fluorescence emission, lifetime and colour analyses can be used to quantify recycled content in four automotive plastics with different chemical structures, matrices or fillers. Quantification using BBS AIEE was most successful for semicrystalline polymers with minimal additives (polyamide‐6 and polyamide‐6,6), with high confidence correlations between fluorescence emission and lifetime measurements and recycled content. Detection was suppressed in amorphous polycarbonates and filled polypropylenes, suggesting this quantification technique may be application‐limited. These new insights into quantifying recycled content in automotive plastics point to both opportunities and limitations for fluorescence‐based techniques in assuring a more circular world. © 2026 The Author(s). Polymer International published by John Wiley &amp; Sons Ltd on behalf of Society of Chemical Industry.

Water contamination by synthetic dyes from textile, plastic,paint,and paper industries poses a significant environmental and publichealth challenge. These dyes are chemically stable, toxic, and proneto bioaccumulation, necessitating efficient and sustainable removalstrategies. Here, we present protein nanofiber-based aerogels derivedfrom bovine serum albumin (BSA) as effective biobased adsorbents fordye removal. BSA nanofibers were prepared through a high-temperature,acid-mediated self-assembly process and subsequently cross-linkedand freeze-dried to form porous aerogels. Degree of cross-linkingwas varied to assess impacts on aerogel porosity, mechanical strength,and adsorption efficiency. Optimized aerogel formulations exhibitedhigh removal efficiencies exceeding 99% for both cationic (crystalviolet) and anionic (rose bengal) dyes. Adsorption isotherms werefitted using Langmuir, Freundlich, and Redlich–Peterson models;while all three showed good correlation, the Redlich–Petersonmodel provided the best overall fit, indicating a hybrid adsorptionmechanism. The maximum Langmuir adsorption capacities achieved were344 mg g–1 for crystal violet and 246 mg g–1 for rose bengal. The adsorption kinetics followed a pseudo-second-ordermodel and reached equilibrium within 6 h. Finally, aerogel regenerationwas performed over three cycles, showcasing the potential of aerogelreuse without significant changes in adsorption/desorption performance.Overall, this work demonstrates the potential of BSA nanofiber aerogelsas a renewable, biodegradable, and high-performance platform for waterpurification of organic dyes.