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Nowadays, immersion cooling-based battery thermal management systems have demonstrated their effectiveness in controlling the temperature of lithium-ion batteries. While previous scientific research has primarily concentrated on traditional dielectric fluids such as mineral oil, the current research investigates the effectiveness of the dielectric fluid FC-40. A three-dimensional Computational Fluid Dynamics model of an eight-cell 18650 battery system was constructed using ANSYS Fluent 19.2 to examine the effect of cooling fluids (air, mineral oil, and FC-40), velocity of flow (0.01 m/s to 0.15 m/s), discharge rate (1C to 5C), and inlet/outlet size (2.5 mm to 3.5 mm) on thermal efficiency as well as pressure drop. The findings indicate that employing FC-40 as the dielectric fluid significantly reduces the peak cell temperature, with an absolute decrease of 2.80 °C compared to mineral oil and 15.10 °C compared to air. Furthermore, FC-40 achieves the highest uniformity with minimal hotspot. On the other hand, as the fluid velocity increases, the maximum temperature of the battery drops, reaching a minimum of 26 °C at a velocity of 0.15 m/s. Otherwise, at lower flow velocities, the pressure drop remains minimal, thereby reducing the pumping power consumption. Additionally, increasing the inlet and outlet diameter of the fluid directly improves cooling uniformity. Consequently, the temperature dropped by up to 4.3%. Finally, the findings demonstrate that elevated discharge rates contribute to increased heat dissipation but adversely affect the efficiency of the thermal management system. This study provides critical knowledge for the enhancement of battery thermal management systems based on immersion cooling using FC-40 as a dielectric. Full article

(This article belongs to the Special Issue Thermal Safety of Lithium Ion Batteries—2nd Edition)

15 pages, 1363 KB

Open AccessArticle

Decoupling Water Consumption from Economic Growth in Inner Mongolia, China

by Danjun Wang, Yunqi Zhou and Fengwei Wang

Water 2025, 17(21), 3073; https://doi.org/10.3390/w17213073 (registering DOI) - 27 Oct 2025

Abstract

Using economic and water consumption data from Inner Mongolia and its 12 cities (2004–2023), this study employs the Tapio decoupling model to investigate the relationship between water consumption and economic growth. The results show a general shift from weak to strong decoupling across the region, with extreme events such as the 2020–2021 pandemic period (decoupling index, DI = 10.31) causing clear disruptions. Regional disparities followed a triple pattern: industrial areas (e.g., Ordos, Baotou) achieved strong decoupling via innovation; agricultural regions (e.g., Tongliao, Bayannur) remained in weak negative decoupling modes due to rigid water demand; and ecologically vulnerable areas (e.g., Alxa League, Xilin Gol) saw high volatility and unsustainable policy effects. Our interpretation of the three patterns highlights the need for region-specific governance. The driving mechanisms mainly include uneven adoption of water-saving technology (e.g., low drip irrigation rates in agriculture), virtual water trade shifting pressures across regions, and climate extremes worsening imbalances. Based on these findings, we recommend differentiated subsidies, regional compensation mechanisms, and adaptive policies to support sustainable water–economy coordination in arid regions. Full article

(This article belongs to the Special Issue Water: Economic, Social and Environmental Analysis)

27 pages, 5014 KB

Open AccessArticle

Axial Compressive Behavior of Square Double-Skin Hybrid Concrete Bar Columns with Small-Diameter Concrete-Infilled GFRP Tubes

by Jingran He, Yi Liu, Qinling Hong, Runran Li, Ruofan Gao, Bing Fu, Luchuan Ding and Xiaodi Dai

Buildings 2025, 15(21), 3888; https://doi.org/10.3390/buildings15213888 (registering DOI) - 27 Oct 2025

Abstract

With the increasing demand for lightweight, high-strength, and ductile structural systems in modern infrastructure, the hybrid composite column has emerged as a promising solution to overcome the limitations of single-material members. This paper proposes an innovative variant of double-skin tubular columns (DSTCs), termed as square double-skin hybrid concrete bar columns (SDHCBCs), composed of one square-shaped outer steel tube, small-diameter concrete-infilled glass FRP tubes (SDCFs), interstitial mortar, and an inner circular steel tube. A series of axial compression tests were conducted on eight SDHCBCs and one reference DSTC to investigate the effects of key parameters, including the thicknesses of the outer steel tube and GFRP tube, the substitution ratio of SDCFs, and their distribution patterns. As a result, significantly enhanced performance is observed in the proposed SDHCBCs, including the following: ultimate axial bearing capacity improved by 79.6%, while the ductility is increased by 328.3%, respectively, compared to the conventional DSTC. A validated finite element model was established to simulate the mechanical behavior of SDHCBCs under axial compression. The model accurately captured the stress distribution and progressive failure modes of each component, offering insights into the complex interaction mechanisms within the hybrid columns. The findings suggest that incorporating SDCFs into hybrid columns is a promising strategy to achieve superior load-carrying performance, with strong potential for application in high-rise and infrastructure engineering. Full article

(This article belongs to the Special Issue Innovations in Composite Material Technologies and Structural Design)

24 pages, 940 KB

Open AccessArticle

Evaluating the Role of Hybrid Renewable Energy Systems in Supporting South Africa’s Energy Transition

by Mxolisi Miller, Xolani Yokwana and Mbuyu Sumbwanyambe

Processes 2025, 13(11), 3455; https://doi.org/10.3390/pr13113455 (registering DOI) - 27 Oct 2025

Abstract

This report evaluates the role of Hybrid Renewable Energy Systems (HRESs) in supporting South Africa’s energy transition amidst persistent power shortages, coal dependency, and growing decarbonisation imperatives. Drawing on national policy frameworks including the Integrated Resource Plan (IRP 2019), the Just Energy Transition (JET) strategy, and Net Zero 2050 targets, this study analyses five major HRES configurations: PV–Battery, PV–Diesel–Battery, PV–Wind–Battery, PV–Hydrogen, and Multi-Source EMS. Through technical modelling, lifecycle cost estimation, and trade-off analysis, the report demonstrates how hybrid systems can decentralise energy supply, improve grid resilience, and align with socio-economic development goals. Geographic application, cost-performance metrics, and policy alignment are assessed to inform region-specific deployment strategies. Despite enabling technologies and proven field performance, the scale-up of HRESs is constrained by financial, regulatory, and institutional barriers. The report concludes with targeted policy recommendations to support inclusive and regionally adaptive HRES investment in South Africa. Full article

(This article belongs to the Special Issue Advanced Technologies of Renewable Energy Sources (RESs))

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17 pages, 1250 KB

Open AccessArticle

Mitigating Dynamic Load-Altering Attacks on Grid Frequency with the Proportional–Integral Control Strategy

by Yunhao Yu, Meiling Dizha and Zhenyong Zhang

Electronics 2025, 14(21), 4203; https://doi.org/10.3390/electronics14214203 (registering DOI) - 27 Oct 2025

Abstract

Grid frequency is a critical factor for the stability of a power system. However, with the penetration of massive dynamic load requirements and information and communication infrastructure, grid frequency is vulnerable to cyberattacks on the load side. In this paper, we model dynamic load-altering attacks (LAAs) on grid frequency and propose a control-based mitigation strategy. First, the dynamic grid-frequency model for frequency-sensitive loads is constructed. Then, the vulnerability of grid frequency to dynamic LAAs is analyzed using eigenvalue sensitivity analysis. To design the mitigation strategy, a stability condition with the first-order dynamic model is derived. Further, a second-order dynamic model is constructed to illustrate the joint impact of dynamic LAAs and the control strategy on eigenvalues, thereby revealing insights into mitigating factors for maintaining grid frequency stability. Finally, we conduct extensive simulations to evaluate the vulnerability of grid frequency under dynamic LAAs and to validate the effectiveness of the mitigation strategy. Full article

24 pages, 4069 KB

Open AccessArticle

High-Precision HRWS SAR Phase Error Estimation with Inaccurate Baseline: A Joint-Pixel-Based Image Subspace Approach

by Jixia Fan, Quan Chen, Jixiang Xiang, Xiaojie Ding, Wenxin Zhao and Guangcai Sun

Remote Sens. 2025, 17(21), 3554; https://doi.org/10.3390/rs17213554 (registering DOI) - 27 Oct 2025

Abstract

HRWS (high resolution and wide swath, HRWS) SAR always suffers channel phase error in the multichannel reconstruction stage and results in a lower imaging quality. The image domain error estimation method can achieve superior performance by utilizing the signal-to-noise ratio (SNR) advantage. Nevertheless, in practice, the inevitable baseline error in HRWS SAR will lead to the inability of multichannel images to be registered in azimuth time and reduction of the channel phase error estimation accuracy. Considering that the joint-pixel model can fully contain the coherent information in such a case, a novel multichannel phase error estimation method is proposed. In this paper, by establishing a multichannel signal model in the image domain, an image domain subspace-based phase error estimation method based on joint-pixel selection and vector construction is derived. The proposed method can weaken the influence of subspace estimation inaccuracy caused by the inaccurate azimuth baseline and avoid the large amount of calculation caused by iterative elimination of baseline error and phase error in traditional algorithms, thus further improving computational efficiency. Simulation experiments and real acquired HRWS SAR data processing validate the estimation accuracy of the proposed method. Full article

(This article belongs to the Special Issue Processing Methods and Techniques of Spaceborne SAR with Ultra-High Resolution)

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31 pages, 1852 KB

Open AccessArticle

QuantumTrust-FedChain: A Blockchain-Aware Quantum-Tuned Federated Learning System for Cyber-Resilient Industrial IoT in 6G

by Saleh Alharbi

Future Internet 2025, 17(11), 493; https://doi.org/10.3390/fi17110493 (registering DOI) - 27 Oct 2025

Abstract

Industrial Internet of Things (IIoT) systems face severe security and trust challenges, particularly under cross-domain data sharing and federated orchestration. We present QuantumTrust-FedChain, a cyber-resilient federated learning framework integrating quantum variational trust modeling, blockchain-backed provenance, and Byzantine-robust aggregation for secure IIoT collaboration in 6G networks. The architecture includes a Quantum Graph Attention Network (Q-GAT) for modeling device trust evolution using encrypted device logs. This consensus-aware federated optimizer penalizes adversarial gradients using stochastic contract enforcement, and a shard-based blockchain for real-time forensic traceability. Using datasets from SWaT and TON IoT, experiments show 98.3% accuracy in anomaly detection, 35% improvement in defense against model poisoning, and full ledger traceability with under 8.5% blockchain overhead. This framework offers a robust and explainable solution for secure AI deployment in safety-critical IIoT environments. Full article

(This article belongs to the Special Issue Security and Privacy in Blockchains and the IoT—3rd Edition)

25 pages, 1508 KB

Open AccessArticle

Phytochemical Profiling and Anti-Obesogenic Potential of Scrophularia Aestivalis Griseb. (Scrophulariaceae)

by Konstantina Priboyska, Monika N. Todorova, Vanya I. Gerasimova, Martina S. Savova, Slaveya Krustanova, Zhanina Petkova, Stoyan Stoyanov, Milena P. Popova, Milen I. Georgiev and Kalina Alipieva

Molecules 2025, 30(21), 4202; https://doi.org/10.3390/molecules30214202 (registering DOI) - 27 Oct 2025

Abstract

Scrophularia aestivalis Griseb. is a Balkan endemic species whose phytochemical composition and medicinal properties have not been previously investigated. The therapeutic potential of Scrophularia species has attracted considerable attention, resulting in extensive studies on their chemical and pharmacological properties, with over 200 secondary metabolites identified to date. The present study aimed to explore the phytochemical composition of Bulgarian-origin S. aestivalis, including isolation and characterization of individual secondary metabolites. From methanol extract of the plant’s aerial parts, aucubin, harpagide, 8-O-acetylharpagide, cis- and trans-harpagoside, 6-O-methyl catalpol, acylated derivatives of catalpol, and linarin were isolated and identified. The anti-obesity activity of the extract and primary fractions was evaluated in a Caenorhabditis elegans model of obesity. Significant lipid-reducing activity was demonstrated in four fractions, indicating promising anti-obesogenic properties. Following chemical profiling and quantitative analysis, the main components of the most active fractions were identified, namely the cis- and trans-harpagoside isomers. Subsequent experiments demonstrated that treatment with harpagoside reduced lipid accumulation and improved mitochondrial function in glucose-supplemented worms, with the data suggesting potential involvement of the SKN-1 signaling pathway. Full article

(This article belongs to the Section Natural Products Chemistry)

17 pages, 643 KB

Open AccessArticle

Voluntary Food Reformulation Initiatives Failed to Reduce the Salt Content of Artisanal Breads in Greece

by Georgios Marakis, Sotiria Kotopoulou, Stavroula Skoulika, Georgios Petropoulos, Zoe Mousia, Emmanuella Magriplis and Antonis Zampelas

Nutrients 2025, 17(21), 3374; https://doi.org/10.3390/nu17213374 (registering DOI) - 27 Oct 2025

Abstract

Background: Reducing salt in bread is considered a straightforward, cost-effective public health intervention and is implemented in several countries, either voluntarily or through legislation. A Memorandum of Understanding (MoU) was signed in Greece in 2016, setting a voluntary maximum salt content of 1.2% in artisanal bread. This study aimed to evaluate the effectiveness of the MoU and assessed the potential impact of reducing salt in bread on overall salt intake, using the MoU target and the relevant WHO global sodium benchmark. Methods: Artisanal bread samples (n = 253) randomly collected from different parts of Greece in 2024 were analyzed for salt content and compared with samples collected in 2012 (n = 220). Salt intake from bread was estimated using data from the Hellenic National Nutrition and Health Survey (HNNHS), and modeling scenarios were conducted. Results: The MoU and related voluntary awareness activities were ineffective as a strategy to reduce salt in bread. The mean salt content in bread in 2024 was 1.41 (0.30)%, representing a 6.8% increase compared to 1.32 (0.31)% in 2012. Only 19.4% of samples in 2024 contained ≤1.2% salt, compared to 31.8% in 2012. Full MoU compliance would enable an additional 3.1% of Greek bread consumers, currently exceeding 5 g in their daily salt intake from foods alone, to reduce their intake to below 5 g. This would rise to 6.2% if the WHO sodium benchmark was implemented. Conclusions: A mandatory salt limit, aligned with the WHO global benchmark, is urgently needed to support national reformulation strategies. This work can contribute to European and international discussions on food reformulation. Full article

(This article belongs to the Special Issue Towards Healthy and Sustainable Diets: Environmental and Nutritional Perspectives)

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26 pages, 6881 KB

Open AccessArticle

State of Health Aware Adaptive Scheduling of Battery Energy Storage System Charging and Discharging in Rural Microgrids Using Long Short-Term Memory and Convolutional Neural Networks

by Chi Nghiep Le, Arangarajan Vinayagam, Phat Thuan Tran, Stefan Stojcevski, Tan Ngoc Dinh, Alex Stojcevski and Jaideep Chandran

Energies 2025, 18(21), 5641; https://doi.org/10.3390/en18215641 (registering DOI) - 27 Oct 2025

Abstract

This study presents a novel LSTM–CNN-based adaptive scheduling framework (LSTM-CNN–AS) designed to improve real-time energy management and extend the lifespan of lithium-ion Battery Energy Storage Systems (BESS) in rural and resource-constrained microgrids. In contrast to conventional methods that prioritize economic optimization, the proposed framework incorporates state of health (SOH) aware control and adaptive closed-loop scheduling to enhance operational reliability and battery longevity. The architecture combines Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN) for accurate SOH estimation, with lightweight Multi-Layer Perceptron (MLP) models supporting real-time scheduling and state of charge (SOC) regulation. Operational safety is maintained by keeping SOC within 20–80% and SOH above 70%. The proposed model training and validation are conducted using two real-world datasets: the Mendeley Lithium-Ion SOH Test Dataset and the DKA Solar System Dataset from Alice Springs, both sampled at 5-minute intervals. Performance is evaluated across three operational scenarios, which are 2C charging with random discharge; random charging with 3C discharge; and fully random profiles, achieving up to 44% reduction in MAE and an R² score of 0.9767. A one-month deployment demonstrates a 30% reduction in charging time and 40% lower operational costs, confirming the framework’s effectiveness and scalability for rural microgrid applications. Full article

20 pages, 6870 KB

Open AccessArticle

Bond Properties Between Bimetallic Steel Bar and Polyoxymethylene Fiber-Reinforced Seawater Sea–Sand Concrete

by Fei Wang, Xuanyi Xue, Neng Wang, Shuai Li, Zhengtao Yang and Yuruo Chang

Polymers 2025, 17(21), 2866; https://doi.org/10.3390/polym17212866 (registering DOI) - 27 Oct 2025

Abstract

With the development of infrastructure construction, seawater sea–sand concrete (SWSSC) is expected to solve the shortage of freshwater and river sand. Polyoxymethylene (POM) fiber, owing to its excellent corrosion resistance, provides a novel approach to enhancing the bond performance of SWSSC. This study systematic study of the bond properties of bimetallic steel bars (BSBs) in POM fiber-reinforced SWSSC and develops a predictive model. Mechanical property tests of SWSSC and pull-out tests of BSB and SWSSC were conducted with various POM fiber contents. The results showed that the optimal volume fraction of POM fibers was 0.6%. At this fraction, the compressive strength and splitting tensile strength of SWSSC were improved by 17.7% and 20.3%, respectively, compared with the group without fibers. All pull-out specimens experienced splitting failure. The bond strength increased monotonically with the increase in relative cover thickness and exhibited a trend of first increasing and then stabilizing with rising POM fiber volume fraction. In addition, a bond stress–slip prediction model between BSBs and POM fiber-reinforced SWSSC was established based on the test results, which can provide theoretical support for the numerical simulation and design of BSB-SWSSC structures. Full article

(This article belongs to the Special Issue Polymers Reinforced Civil Engineering Materials and Components)

18 pages, 9540 KB

Open AccessArticle

Leveraging Explainable Artificial Intelligence for Genotype-to-Phenotype Prediction: A Case Study in Arabidopsis thaliana

by Pierfrancesco Novielli, Nelson Nazzicari, Stefano Pavan, Chiara Delvento, Domenico Diacono, Claudia Zoani, Roberto Bellotti and Sabina Tangaro

Appl. Syst. Innov. 2025, 8(6), 164; https://doi.org/10.3390/asi8060164 (registering DOI) - 27 Oct 2025

Abstract

Predicting phenotypes from genomic data can significantly advance agriculture. Genomic selection, which uses genome-wide DNA markers to identify individuals with high genetic value, enhances the accuracy of breeding programs. While linear models are routinely used for genomic selection (GS), machine learning (ML) models offer complementary potential. In this study, robust ML-based models were developed to predict five phenotypic traits—three related to flowering time and two to leaf number—in Arabidopsis thaliana, a model plant with a fully sequenced genome. Using explainable artificial intelligence (XAI), specifically SHapley Additive exPlanations (SHAP) values, we identified SNPs that contributed most to trait prediction. Many of these SNPs were located in or near genes known to regulate flowering and stem elongation, such as DOG1 and VIN3, supporting the biological plausibility of the model. SHAP also enabled local interpretability at the single-plant level, revealing the genotypic basis of individual predictions. Our results indicate that integrating ML with XAI improves model interpretability and provides predictive performance comparable to traditional methods. This approach confirms known genotype–phenotype relationships and highlights new candidate loci, paving the way for functional validation. The proposed methodology offers promising applications in precision breeding and translation of insights from Arabidopsis to crop species. Full article

20 pages, 878 KB

Open AccessArticle

Functional Properties of Enriched Curd with Collagen and Plant Phytochemicals for Athletes and Physiological Benefits: Evidence Data from Preclinical Trials In Vivo

by Klara Zharykbasova, Aitbek Kakimov, Yerlan Zharykbasov, Zhainagul Kakimova, Raimkhanova Guldana, Kozykenova Zhanna, Beisembayeva Galiya, Zhanat Baigazinov, Tibor Kovács and Amin Shahrokhi

Nutrients 2025, 17(21), 3373; https://doi.org/10.3390/nu17213373 (registering DOI) - 27 Oct 2025

Abstract

Background/Objectives: The aim of this study was to establish the multifactorial physiological effect of a functional curd product enriched with collagen-containing concentrate and phytochemical extracts of various natures, under conditions of in vivo experiment. Methods: Biomarkers, such as antioxidant activity (glutathione peroxidase, glutathione reductase, MDA), immune response (IgA, IgG, IgM, IL-6, TNF-α), and purine metabolism (uric acid, xanthine oxidase, 5′-nucleotidase) were selected for evaluation and their influence change. The model was white outbred rats (n = 45), randomly distributed into three groups: control (basic product), experimental group 1 (supplements of collagen-containing concentrate and extract of the composition of sea buckthorn and rosehips), and experimental group 2 (supplements of collagen-containing concentrate and extract of the composition of yarrow and sage). Results: In both experimental groups, a reliable increase in the enzymatic activity of the antioxidant system, a decrease in lipid peroxidation and the level of proinflammatory cytokines, an increase in immunoglobulins, and activation of 5′-nucleotidase were observed. The most pronounced effects were observed with the introduction of a curd product containing collagen-containing concentrate and sea buckthorn and rosehip extract. Conclusions: The scientific novelty of the study lies in the first comprehensive in vivo evaluation of the combined enrichment of a dairy product with collagen and plant extracts for a set of biomarkers. The data obtained confirm the physiological activity and functional properties of the developed product, which can be considered as a promising means of specialized and sports nutrition with proven biological action. Full article

(This article belongs to the Section Sports Nutrition)

18 pages, 21614 KB

Open AccessArticle

Multi-Omics Analysis of the Potential Mechanisms of Skin Albinism in Edangered Percocypris pingi: Abnormal Ubiquitination and Calcium Signal Inhibition

by Senyue Liu, Xiaoyun Wu, Qiaolin Zou, Jiansheng Lai, Luyun Ni, Yongqiang Deng, Yang Feng, Mingjiang Song, Pengcheng Li, Jun Du, Qiang Li and Ya Liu

Cells 2025, 14(21), 1684; https://doi.org/10.3390/cells14211684 (registering DOI) - 27 Oct 2025

Abstract

Percocypris pingi is an endangered protected fish species in China. Its albino variants exhibit growth retardation and physiological abnormalities. Understanding its albinism mechanism holds significant scientific importance for molecular breeding programs and disease model development. This study integrated transcriptomic and proteomic analyses, combined with histopathological and molecular biological techniques, to systematically compare molecular differences in skin tissues between albino and wild-type P. pingi, with a focus on elucidating the multidimensional regulatory mechanisms underlying skin albinism. Our findings suggest that albinism in P. pingi is synergistically driven by hyperactivation of ubiquitin-mediated proteolysis (which suppressed TYR/TYRP1 enzymatic activity and disrupted the pH homeostasis of melanosomes), and inhibition of calcium signaling (which impeded melanin transport). This discovery provides novel insights into the mechanisms of pigment loss in fish species and offers a valuable reference for molecular breeding of endangered species as well as research on pigmentation-related disorders. Full article

(This article belongs to the Topic Animal Models of Human Disease 3.0)

26 pages, 13572 KB

Open AccessArticle

Effects of Sterilization Processes with Hydrogen Peroxide and Ethylene Oxide on Commercial 3D-Printed PLA, PLA-FC, and PETG by Fused Deposition Modeling

by Jorge Mauricio Fuentes, Homero Cadena, Abel Remache, Omar Flor-Unda, Santiago Sarria, Jonathan Delgado, Pablo Bonilla and Santiago Ferrándiz

Polymers 2025, 17(21), 2864; https://doi.org/10.3390/polym17212864 (registering DOI) - 27 Oct 2025

Abstract

Polymers such as PLA, PLA reinforced with carbon fiber (PLA + CF), and PETG are widely employed in utensils, structural components, and biomedical device housings where load-bearing capability and chemical resistance are desirable. This is particularly relevant for reusable applications in which sterilization with hydrogen peroxide (HP) or ethylene oxide (EO) is often required. In this study, the impact of HP and EO sterilization processes on the mechanical, thermal, and structural properties of PLA, PLA + CF, and PETG was evaluated. The mechanical properties assessed included elongation at break, elastic modulus, and tensile strength after sterilization. The thermal properties examined comprised thermal stability and the coefficient of thermal expansion (CTE). Additionally, Fourier Transform Infrared Spectroscopy (FTIR) was performed to detect potential alterations in functional groups. For PLA, sterilization with HP and EO resulted in a 22% increase in ultimate tensile strength (UTS) and a 21% increase in elastic modulus, accompanied by a noticeable reduction in ductility and the appearance of more brittle fracture surfaces. PLA + CF exhibited greater stability under both sterilization methods due to the reinforcing effect of carbon fibers. In the case of PETG, tensile strength and stiffness remained stable; however, HP sterilization led to a remarkable increase in elongation at break (294%), whereas EO sterilization reduced it. Regarding thermal properties, glass transition temperature (Tg) showed variations: PLA presented either an increase or decrease in Tg depending on the sterilization treatment, PLA + CF displayed a Tg reduction after EO sterilization, while PETG exhibited a moderate Tg increase under HP sterilization. CTE decreased at lower temperatures but increased after EO treatment. FTIR analysis revealed only minor chemical modifications induced by sterilization. Overall, HP and EO sterilization can be safely applied to additively manufactured medical components based on these polymers, provided that the structures are not subjected to high mechanical loads and do not require strict dimensional tolerances. Full article

(This article belongs to the Section Polymer Processing and Engineering)

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