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Accurate weld defect detection is critical for ensuring structural safety and evaluating welding quality in industrial applications. Manual inspection methods have inherent limitations, including inefficiency and inadequate sensitivity to subtle defects. Existing detection models, primarily designed for natural images, struggle to adapt to the characteristic challenges of weld X-ray images, such as high noise, low contrast, and inter-defect similarity, particularly leading to missed detections and false positives for small defects. To address these challenges, a multi-dimensional feature fusion model (MADet), which is a multi-branch deep fusion network for weld defect detection, was proposed. The framework incorporates two key innovations: (1) A multi-scale feature fusion network integrated with lightweight attention residual modules to enhance the perception of fine-grained defect features by leveraging low-level texture information. (2) An anchor-based feature-selective detection head was used to improve the discrimination and localization accuracy for five typical defect categories. Extensive experiments on both public and proprietary weld defect datasets demonstrated that MADet achieved significant improvements over the state-of-the-art YOLO variants. Specifically, it surpassed the suboptimal model by 7.41% in mAP@0.5, indicating strong industrial applicability. Full article

(This article belongs to the Section Manufacturing Processes and Systems)

11 pages, 1174 KiB

Open AccessArticle

385 nm AlGaN Near-Ultraviolet Micro Light-Emitting Diode Arrays with WPE 30.18% Realized Using an AlN-Inserted Hole Spreading Enhancement Superlattice Electron Blocking Layer

by Qi Nan, Shuhan Zhang, Jiahao Yao, Yun Zhang, Hui Ding, Qian Fan, Xianfeng Ni and Xing Gu

Coatings 2025, 15(8), 910; https://doi.org/10.3390/coatings15080910 (registering DOI) - 3 Aug 2025

Abstract

In this work, we demonstrate high-efficiency 385 nm AlGaN-based near-ultraviolet micro light emitting diode (NUV-Micro LED) arrays. The epi structure is prepared using a novel AlN-inserted superlattice electrical blocking layer which enhances hole spreading in the p-type region significantly. The NUV-Micro LED arrays in this work comprise 228 chips in parallel with wavelengths at 385 nm, and each single chip size is 15 × 30 μm². Compared with conventional bulk AlGaN-based EBL structures, the NUV-Micro LED arrays that implemented the new hole spreading enhanced superlattice electrical blocking layer (HSESL-EBL) structure proposed in this work had a remarkable increase in light output power (LOP) at current density, increasing the range down from 0.02 A/cm² to as high as 97 A/cm². The array’s light output power is increased up to 1540% at the lowest current density 0.02 A/cm², and up to 58% at the highest current density 97 A/cm², measured under room temperature (RT); consequently, the WPE is increased from 13.4% to a maximum of 30.18%. This AlN-inserted HESEL-EBL design significantly enhances both the lateral expansion efficiency and the hole injection efficiency into the multi quantum well (MQW) in the arrays, improving the concentration distribution of the holes in MQW while maintaining good suppression of electron leakage. The array’s efficiency droop has also been greatly reduced. Full article

(This article belongs to the Section Surface Engineering for Energy Harvesting, Conversion, and Storage)

48 pages, 16562 KiB

Open AccessArticle

Dense Matching with Low Computational Complexity for Disparity Estimation in the Radargrammetric Approach of SAR Intensity Images

by Hamid Jannati, Mohammad Javad Valadan Zoej, Ebrahim Ghaderpour and Paolo Mazzanti

Remote Sens. 2025, 17(15), 2693; https://doi.org/10.3390/rs17152693 (registering DOI) - 3 Aug 2025

Abstract

Synthetic Aperture Radar (SAR) images and optical imagery have high potential for extracting digital elevation models (DEMs). The two main approaches for deriving elevation models from SAR data are interferometry (InSAR) and radargrammetry. Adapted from photogrammetric principles, radargrammetry relies on disparity model estimation as its core component. Matching strategies in radargrammetry typically follow local, global, or semi-global methodologies. Local methods, while having higher accuracy, especially in low-texture SAR images, require larger kernel sizes, leading to quadratic computational complexity. Conversely, global and semi-global models produce more consistent and higher-quality disparity maps but are computationally more intensive than local methods with small kernels and require more memory (RAM). In this study, inspired by the advantages of local matching algorithms, a computationally efficient and novel model is proposed for extracting corresponding pixels in SAR-intensity stereo images. To enhance accuracy, the proposed two-stage algorithm operates without an image pyramid structure. Notably, unlike traditional local and global models, the computational complexity of the proposed approach remains stable as the input size or kernel dimensions increase while memory consumption stays low. Compared to a pyramid-based local normalized cross-correlation (NCC) algorithm and adaptive semi-global matching (SGM) models, the proposed method maintains good accuracy comparable to adaptive SGM while reducing processing time by up to 50% relative to pyramid SGM and achieving a 35-fold speedup over the local NCC algorithm with an optimal kernel size. Validated on a Sentinel-1 stereo pair with a 10 m ground-pixel size, the proposed algorithm yields a DEM with an average accuracy of 34.1 m. Full article

(This article belongs to the Special Issue Advancing Synthetic Aperture Radar: Imaging, Processing, and Applications in Remote Sensing)

14 pages, 4475 KiB

Open AccessArticle

DFT Investigation into Adsorption–Desorption Properties of Mg/Ni-Doped Calcium-Based Materials

by Wei Shi, Renwei Li, Xin Bao, Haifeng Yang and Dehao Kong

Crystals 2025, 15(8), 711; https://doi.org/10.3390/cryst15080711 (registering DOI) - 3 Aug 2025

Abstract

Although concentrated solar power (CSP) coupled with calcium looping (CaL) offers a promising avenue for efficient thermal chemical energy storage, calcium-based sorbents suffer from accelerated structural degradation and decreased CO₂ capture capacity during multiple cycles. This study used Density Functional Theory (DFT) calculations to investigate the mechanism by which Mg and Ni doping improves the adsorption/desorption performance of CaO. The DFT results indicate that Mg and Ni doping can effectively reduce the formation energy of oxygen vacancies on the CaO surface. Mg–Ni co-doping exhibits a significant synergistic effect, with the formation energy of oxygen vacancies reduced to 5.072 eV. Meanwhile, the O²⁻ diffusion energy barrier in the co-doped system was reduced to 2.692 eV, significantly improving the ion transport efficiency. In terms of CO₂ adsorption, Mg and Ni co-doping enhances the interaction between surface O atoms and CO₂, increasing the adsorption energy to −1.703 eV and forming a more stable CO₃²⁻ structure. For the desorption process, Mg and Ni co-doping restructured the CaCO₃ surface structure, reducing the CO₂ desorption energy barrier to 3.922 eV and significantly promoting carbonate decomposition. This work reveals, at the molecular level, how Mg and Ni doping optimizes adsorption–desorption in calcium-based materials, providing theoretical guidance for designing high-performance sorbents. Full article

(This article belongs to the Special Issue Performance and Processing of Metal Materials)

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21 pages, 2228 KiB

Open AccessArticle

Multi-Objective Optimization of Abrasive Cutting Process Conditions to Increase Economic Efficiency

by Irina Aleksandrova

Technologies 2025, 13(8), 337; https://doi.org/10.3390/technologies13080337 (registering DOI) - 3 Aug 2025

Abstract

Existing studies on the abrasive cutting process have primarily focused on the influence of cutting conditions on key parameters such as temperature, cut-off wheel wear, and machined surface quality. However, the choice of working conditions is often made based on the experience of qualified personnel or using data from reference sources. The literature also provides optimal values for the cutting mode elements, but these are only valid for specific methods and cutting conditions. This article proposes a new multi-objective optimization approach for determining the conditions for the implementation of the abrasive cutting process that leads to Pareto-optimal solutions for improving economic efficiency, evaluated by production rate and manufacturing net cost parameters. To demonstrate this approach, the elastic abrasive cutting process of structural steels C45 and 42Cr4 has been selected. Theoretical–experimental models for production rate and manufacturing net cost have been developed, reflecting the complex influence of the conditions of the elastic abrasive cutting process (compression force of the cut-off wheel on the workpiece and rotational frequency of the workpiece). Multi-objective compromise optimization based on a genetic algorithm has been conducted by applying two methods—the determination of a compromise optimal area for the conditions of the elastic abrasive cutting process and the generalized utility function method. Optimal conditions for the implementation of the elastic abrasive cutting process have been determined, ensuring the best combination of high production rate and low manufacturing net cost. Full article

(This article belongs to the Section Innovations in Materials Science and Materials Processing)

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17 pages, 4783 KiB

Open AccessArticle

Empirical Investigation of the Structural Response of Super-Span Soil–Steel Arches During Backfilling

by Bartłomiej Kunecki

Materials 2025, 18(15), 3650; https://doi.org/10.3390/ma18153650 (registering DOI) - 3 Aug 2025

Abstract

This paper presents field investigations of a corrugated steel soil–steel arch structure with a span of 25.7 m and a rise of 9.0 m—currently the largest single-span structure of its kind in Europe. The structure, serving as a wildlife crossing along the DK16 expressway in northeastern Poland, was constructed using deep corrugated steel plates (500 mm× 237 mm) made from S315MC steel, without additional reinforcements such as stiffening ribs or geosynthetics. The study focused on monitoring the structural behavior during the critical backfilling phase. Displacements and strains were recorded using 34 electro-resistant strain gauges and a geodetic laser system at successive backfill levels, with particular attention to the loading stage at the crown. The measured results were compared with predictions based on the Swedish Design Method (SDM). The SDM equations did not accurately predict internal forces during backfilling. At the crown level, bending moments and axial forces were overestimated by approximately 69% and 152%, respectively. At the final backfill level, the SDM underestimated bending moments by 55% and overestimated axial forces by 90%. These findings highlight limitations of current design standards and emphasize the need for revised analytical models and long-term monitoring of large-span soil–steel structures. Full article

(This article belongs to the Section Construction and Building Materials)

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32 pages, 1747 KiB

Open AccessArticle

Can Regional Infrastructure Predict Its Economic Resilience? Limited Evidence from Spatial Modelling

by Mantas Rimidis and Mindaugas Butkus

Sustainability 2025, 17(15), 7046; https://doi.org/10.3390/su17157046 (registering DOI) - 3 Aug 2025

Abstract

This study examines whether regional infrastructure can predict economic resilience in European regions, focusing on resistance, recovery, and reorientation during the COVID-19 crisis. While infrastructure is widely recognized as a key factor influencing regional resilience, its explicit role has been underexplored in the European context. Using a comprehensive literature review and spatial econometric models applied to NUTS-2 level data from 2017 to 2024, we investigate the direct and spatial spillover effects of various infrastructure types—transportation, healthcare, tourism, education, and digital access—on regional resilience outcomes. We apply OLS and four spatial models (SEM, SLX, SDEM, SDM) under 29 spatial weighting matrices to account for spatial autocorrelation. Results show that motorway density, early school leaving, and healthcare infrastructure in neighbouring regions significantly affect resistance. For recovery, railway density and GDP per capita emerge as key predictors, with notable spatial spillovers. Reorientation is shaped by population structure, railway density, and tourism infrastructure, with both positive and negative spatial dynamics observed. The findings underscore the importance of infrastructure not only in isolation but also within regional systems, revealing complex interdependencies. We conclude that policymakers must consider spatial externalities and coordinate infrastructure investments to enhance regional economic resilience across interconnected Europe. Full article

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14 pages, 4870 KiB

Open AccessArticle

Phase Transformation Principle and Magnetite Grain Growth Law in the Magnetization Sintering Process of Oolitic Hematite Ore

by Hanquan Zhang, Xunrui Liu, Lei Xie, Tiejun Chen, Fan Yang and Bona Deng

Materials 2025, 18(15), 3649; https://doi.org/10.3390/ma18153649 (registering DOI) - 3 Aug 2025

Abstract

Oolitic hematite ore represents a significant iron resource, but its utilization is challenging due to the complex multi-layered circular structure of hematite ore, which makes it difficult to be reduced. This study systematically investigated the phase transformation principle and magnetite grain growth law during the magnetization sintering of oolitic hematite ore, aiming to establish optimal conditions for efficient hematite ore to magnetite conversion. The results demonstrated that both elevated temperature and prolonged reduction duration significantly enhanced the reduction efficiency of hematite (Fe₂O₃) to magnetite. The optimal sintering conditions were determined to be 700 °C for 45 min, under which the magnetite content and Fe/O atomic ratio in the roasted products peaked at approximately 68% and 0.8%, respectively. However, temperatures exceeding 800 °C proved detrimental to magnetite formation, as further reduction to Fe_XO phases occurred. Notably, appropriate temperature elevation promoted substantial magnetite grain growth. When the sintering temperature increased from 600 °C to 700 °C, both the absolute and relative thickness of the magnetite layer exhibited remarkable enhancement, expanding from 9.52 μm to 76.76 μm and from 5.99% to 50.33%, respectively. Furthermore, comparative analysis revealed that a high sintering temperature for a short time was more effective for magnetite particle growth than a low temperature for a long time in the magnetization process of oolitic hematite ore. Full article

(This article belongs to the Section Construction and Building Materials)

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18 pages, 3801 KiB

Open AccessArticle

Characteristics and Transcriptome Analysis of Anther Abortion in Male Sterile Celery (Apium graveolens L.)

by Yao Gong, Zhenyue Yang, Huan Li, Kexiao Lu, Chenyang Wang, Aisheng Xiong, Yangxia Zheng, Guofei Tan and Mengyao Li

Horticulturae 2025, 11(8), 901; https://doi.org/10.3390/horticulturae11080901 (registering DOI) - 3 Aug 2025

Abstract

To elucidate the molecular mechanisms underlying anther abortion in celery male sterile lines, this study investigates the morphological differences of floral organs and differential gene expression patterns between two lines at the flowering stage. Using the male sterile line of celery ‘QCBU-001’ and the fertile line ‘Jinnan Shiqin’ as materials, anther structure was analyzed by paraffin sections, and related genes were detected using transcriptome sequencing and qRT-PCR. The results indicated that the anther locules were severely shrunken at maturity in the sterile lines. The callose deficiency led to abnormal development of microspores, preventing the formation of mature pollen grains and ultimately leading to complete anther abortion. The transcriptome results revealed that 3246 genes were differentially expressed in sterile and fertile lines, which were significantly enriched in pathways such as starch and sucrose metabolism and phenylpropanoid biosynthesis. Additionally, differential expression patterns of transcription factor families (MYB, bHLH, AP2, GRAS, and others) suggested their potential involvement in regulating anther abortion. Notably, the expression level of callose synthase gene AgGSL2 was significantly downregulated in sterile anthers, which might be an important cause of callose deficiency and pollen sterility. This study not only provides a theoretical basis for elucidating the molecular mechanism underlying male sterility in celery but also lays a foundation for the utilization and improvement of male sterile lines in vegetable hybrid breeding. Full article

(This article belongs to the Special Issue Circadian Rhythm Regulation of Growth and Development in Horticultural Plants)

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25 pages, 2846 KiB

Open AccessReview

Silicon-Based Polymer-Derived Ceramics as Anode Materials in Lithium-Ion Batteries

by Liang Zhang, Han Fei, Chenghuan Wang, Hao Ma, Xuan Li, Pengjie Gao, Qingbo Wen, Shasha Tao and Xiang Xiong

Materials 2025, 18(15), 3648; https://doi.org/10.3390/ma18153648 (registering DOI) - 3 Aug 2025

Abstract

In most commercial lithium-ion batteries, graphite remains the primary anode material. However, its theoretical specific capacity is only 372 mAh∙g⁻¹, which falls short of meeting the demands of high-performance electronic devices. Silicon anodes, despite boasting an ultra-high theoretical specific capacity of 4200 mAh∙g⁻¹, suffer from significant volume expansion (>300%) during cycling, leading to severe capacity fade and limiting their commercial viability. Currently, silicon-based polymer-derived ceramics have emerged as a highly promising next-generation anode material for lithium-ion batteries, thanks to their unique nano-cluster structure, tunable composition, and low volume expansion characteristics. The maximum capacity of the ceramics can exceed 1000 mAh∙g⁻¹, and their unique synthesis routes enable customization to align with diverse electrochemical application requirements. In this paper, we present the progress of silicon oxycarbide (SiOC), silicon carbonitride (SiCN), silicon boron carbonitride (SiBCN) and silicon oxycarbonitride (SiOCN) in the field of LIBs, including their synthesis, structural characteristics and electrochemical properties, etc. The mechanisms of lithium-ion storage in the Si-based anode materials are summarized as well, including the key role of free carbon in these materials. Full article

(This article belongs to the Special Issue Electrochemical Materials and Devices for Energy Conversion and Storage—2nd Edition)

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23 pages, 311 KiB

Open AccessArticle

Sustainable Tourism in Protected Areas: Comparative Governance and Lessons from Tara and Triglav National Parks

by Stefana Matović, Suzana Lović Obradović and Tamara Gajić

Sustainability 2025, 17(15), 7048; https://doi.org/10.3390/su17157048 (registering DOI) - 3 Aug 2025

Abstract

This paper investigates how governance frameworks shape sustainable tourism outcomes in protected areas by comparing Tara National Park (Serbia) and Triglav National Park (Slovenia). Both parks, established in 1981 and classified under IUCN Category II, exhibit rich biodiversity and mountainous terrain but differ markedly in governance structures, institutional integration, and local community engagement. Using a qualitative, indicator-based methodology, this research evaluates ecological, economic, and social dimensions of sustainability. The findings reveal that Triglav NP demonstrates higher levels of participatory governance, tourism integration, and educational outreach, while Tara NP maintains stricter ecological protection with less inclusive management. Triglav’s zoning model, community council, and economic alignment with regional development policies contribute to stronger sustainability outcomes. Conversely, Tara NP’s centralized governance and infrastructural gaps constrain its potential despite its significant conservation value. This study highlights the importance of adaptive, inclusive governance in achieving the Sustainable Development Goals (SDGs) within protected areas. It concludes that hybrid approaches, combining legal rigor with participatory flexibility, can foster resilience and sustainability in ecologically sensitive regions. Full article

(This article belongs to the Special Issue Achieving Sustainability in Destination Marketing and Tourism Management)

22 pages, 4267 KiB

Open AccessArticle

MCA-GAN: A Multi-Scale Contextual Attention GAN for Satellite Remote-Sensing Image Dehazing

by Sufen Zhang, Yongcheng Zhang, Zhaofeng Yu, Shaohua Yang, Huifeng Kang and Jingman Xu

Electronics 2025, 14(15), 3099; https://doi.org/10.3390/electronics14153099 (registering DOI) - 3 Aug 2025

Abstract

With the growing demand for ecological monitoring and geological exploration, high‑quality satellite remote‑sensing imagery has become indispensable for accurate information extraction and automated analysis. However, haze reduces image contrast and sharpness, significantly impairing quality. Existing dehazing methods, primarily designed for natural images, struggle with remote-sensing images due to their complex imaging conditions and scale diversity. Given this, we propose a novel Multi-Scale Contextual Attention Generative Adversarial Network (MCA-GAN), specifically designed for satellite image dehazing. Our method integrates multi‑scale feature extraction with global contextual guidance to enhance the network’s comprehension of complex remote‑sensing scenes and its sensitivity to fine details. MCA‑GAN incorporates two self-designed key modules: (1) a Multi‑Scale Feature Aggregation Block, which employs multi‑directional global pooling and multi‑scale convolutional branches to bolster the model’s ability to capture land‑cover details across varying spatial scales; (2) a Dynamic Contextual Attention Block, which uses a gated mechanism to fuse three‑dimensional attention weights with contextual cues, thereby preserving global structural and chromatic consistency while retaining intricate local textures. Extensive qualitative and quantitative experiments on public benchmarks demonstrate that MCA‑GAN outperforms other existing methods in both visual fidelity and objective metrics, offering a robust and practical solution for remote‑sensing image dehazing. Full article

21 pages, 3463 KiB

Open AccessArticle

Soil Sealing, Land Take, and Demographics: A Case Study of Estonia, Latvia, and Lithuania

by Kärt Metsoja, Kätlin Põdra, Armands Auziņš and Evelin Jürgenson

Land 2025, 14(8), 1586; https://doi.org/10.3390/land14081586 (registering DOI) - 3 Aug 2025

Abstract

Soil sealing and land take are increasingly recognised as critical environmental and land use planning challenges across Europe. Although these issues have received limited attention in Baltic policymaking and the academic literature to date, available data indicate ongoing land consumption despite population decline. This study aims to analyse soil sealing patterns in Estonia, Latvia, and Lithuania between 2018 and 2021 using CLC+ Backbone data, linking them to demographic shifts and local planning frameworks. Results reveal that soil sealing increased in nearly all municipalities across the Baltic states, regardless of population trends. The analysis highlights that shrinking municipalities, constrained by limited resources and declining populations, are structurally disadvantaged in terms of land use efficiency, particularly when measured by sealed area per capita. Moreover, this study discusses emerging policy tensions, including the narrowing conceptual gap between land take and soil sealing in the proposed EU Soil Monitoring and Resilience Directive, as well as the risk of overlooking broader land artificialisation. The findings underscore the need for context-sensitive, multi-scalar approaches to land use monitoring and governance, particularly in sparsely populated and demographically imbalanced regions, such as the Baltic states. Full article

(This article belongs to the Special Issue Efficient Land Use and Sustainable Development in European Countries)

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25 pages, 34115 KiB

Open AccessArticle

New Belgrade’s Thermal Mosaic: Investigating Climate Performance in Urban Heritage Blocks Beyond Coverage Ratios

by Saja Kosanović, Đurica Marković and Marija Stamenković

Atmosphere 2025, 16(8), 935; https://doi.org/10.3390/atmos16080935 (registering DOI) - 3 Aug 2025

Abstract

This study investigated the nuanced influence of urban morphology on the thermal performance of nine mass housing blocks (21–26, 28–30) in New Belgrade’s Central Zone. These blocks, showcasing diverse structures, provided a robust basis for evaluating the design parameters. ENVI-met simulations were used to assess two scenarios: an “asphalt-only” environment, isolating the urban structure’s impact, and a “real-world” scenario, including green infrastructure (GI). Overall, the findings emphasize that while GI offers mitigation, the inherent urban built structure fundamentally determines thermal outcomes. An urban block’s thermal performance, it turns out, is a complex interplay between morphological factors and local climate. Crucially, simple metrics like Green Area Percentage (GAP) and Building Coverage Ratio (BCR) proved unreliable predictors of thermal performance. This highlights the critical need for urban planning regulations to evolve beyond basic surface indicators and embrace sophisticated, context-sensitive design principles for effective heat mitigation. Optimal performance arises from morphologies that actively manage heat accumulation and facilitate its dissipation, a characteristic exemplified by Block 22’s integrated design. However, even the best-performing Block 22 remains warmer compared to denser central areas, suggesting that urban densification can be a strategy for heat mitigation. Given New Belgrade’s blocks are protected heritage, targeted GI reinforcements remain the only viable approach for improving the outdoor thermal comfort. Full article

(This article belongs to the Special Issue The Potential of the Built Environment in Climate-Related Challenges (2nd Edition))

26 pages, 614 KiB

Open AccessArticle

Primary School Teachers’ Needs for AI-Supported STEM Education

by Cizem Bas and Askin Kiraz

Sustainability 2025, 17(15), 7044; https://doi.org/10.3390/su17157044 (registering DOI) - 3 Aug 2025

Abstract

In the globalizing world, raising individuals equipped with 21st-century skills is very important for the economic development of countries. Educational practices that support 21st-century skills are also gaining importance. In this context, STEM education, an interdisciplinary educational practice that develops 21st-century skills, emerges. STEM education aims to contribute to sustainable development by training individuals equipped with 21st-century skills and competencies. In a globalizing world, countries must set sustainable development goals to gain a foothold in the global market. In today’s world, where artificial intelligence also shows itself in every area of human life, it is possible to discuss the importance of artificial intelligence-supported STEM education. This study aims to reveal the educational needs of primary school teachers regarding artificial intelligence-supported STEM education. The study was conducted according to the phenomenological design, and the data were collected using a semi-structured interview form and literature review techniques. The thematic analysis method was used in the analysis of the data. According to the research results obtained from the findings of the study, teachers need training on 21st-century skills, interdisciplinary thinking, technology integration into courses, and artificial intelligence practices in courses to develop their knowledge and skills in the context of artificial intelligence-supported STEM education. Full article

(This article belongs to the Special Issue STEM Education and Education for Sustainable Development: From Theory to Practice)

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