Search Results (1,453)

The Qingshankou Formation shales in the southeastern uplift of the Songliao Basin provide an ideal archive for constraining the controls of paleoenvironment on organic matter enrichment. Taking the shale succession at the Niaohexiang section of Binxian as the study object, we combined field sampling with TOC measurements, whole-rock X-ray diffraction, and major, trace, and rare earth element analyses. The strata are dominated by black shale and dark gray mudstone, with mineral assemblages composed mainly of clay, felsic, and carbonate minerals; argillaceous shale exceeds 60%. Normal alkanes display a post-peak distribution with C₂₇ as the dominant peak, low Pr/Ph ratios, and gammacerane index values of 0.18–0.26. Regular steranes are generally V-shaped, whereas some samples show high C₂₉ sterane contents and a reversed L-shaped pattern. Major elements are dominated by SiO₂ and Al₂O₃, trace elements such as Sr and Ba are relatively enriched, and rare earth elements show light REE enrichment with a pronounced negative Eu anomaly. These signatures indicate an upper-crustal felsic provenance and a continental island arc tectonic setting. Organic matter contents are low and derived mainly from terrestrial higher plants with minor aquatic input. Paleoenvironmental reconstruction suggests deposition in a freshwater to slightly brackish, semi-arid, anoxic-reducing shallow lacustrine setting with relatively low productivity, whereas dolostone formed under more saline, arid, and more productive conditions. Climatic fluctuations, salinity variations, and alternating redox states jointly controlled organic matter enrichment, and late-stage lacustrine salinization and anoxia associated with dolostone horizons enhanced organic matter preservation. Full article

Beryllium (Be), a critical strategic metal element, is predominantly extracted from beryl, which serves as a key mineral combining significant strategic importance with essential industrial applications. Significant debate remains, however, regarding the mineralogical characteristics and color-causing mechanisms of beryl. In this study, we integrate Electron Probe Microanalysis (EPMA), Fourier transform infrared spectrometer (FTIR), laser Raman spectrometer (LRS), X-ray diffractometer (XRD), and ultraviolet–visible spectrophotometer (UV-VIS) to elucidate the mineralogy and spectral characteristics of pegmatitic beryl from Xinjiang, Northwest China. The results indicate that the beryl mainly presents a yellowish-green color, associated with minerals such as feldspar, quartz, and garnet. The EPMA results confirm the chemical composition of the typical beryl and indicate that the Al content is lower than the theoretical value, reflecting the substitution of Al³⁺. The FTIR shows characteristic vibrations of Si-O tetrahedral groups within the range of 1400~400 cm⁻¹, along with distinct bending and stretching vibration peaks of H₂O molecules observed in the range of 1700~1500 cm⁻¹ and 3500~3800 cm⁻¹, respectively. Combined with spectral analysis, it can be determined that both Type I water and Type II H₂O are present in the samples. Raman spectroscopy reveals that the two distinct peaks of beryl are located at approximately 685 cm⁻¹ (attributed to the stretching vibration of Be-O) and 1067 cm⁻¹ (corresponding to the bending vibration of Si-O), respectively. The XRD analysis shows that the ratio of unit cell parameters c/a of the samples ranges from 0.9950 to 1.0068, and the isomorphous substitution in its structure is mainly manifested as the replacement of octahedral coordination sites by Al³⁺. The UV-VIS shows that Fe³⁺ exhibits a broad absorption band in the range of 200~300 nm, while no obvious absorption peaks are observed in the range of 300~800 nm. The above characteristics indicate that Fe³⁺ has a significant impact on the color of beryl. For green beryl samples, a portion of Fe³⁺ occupies the structural channel sites and interacts with H₂O molecules within the channels, which contributes to the yellowish hue of beryl. Our study highlights crucial data for mineralogical identification, genetic tracing, as well as efficient utilization of beryl resources. Full article

Background/Objectives: MYC-driven tumors exhibit significant glutamine addiction, but the metabolic adaptation mechanisms enabling their survival under glutamine deprivation remain incompletely understood. Malic enzymes catalyze the oxidative decarboxylation of malate to pyruvate while generating NADPH, linking central carbon metabolism to redox homeostasis. This study investigates whether and how ME1 and ME2 mediate cell adaptation to glutamine starvation and explores their functional division in relation to p53 status. Methods: Using MYC-amplified, p53-mutant (G266E) SF188 glioblastoma cells, we performed siRNA-mediated knockdown, overexpression, and rescue experiments. Cell survival was assessed by trypan blue exclusion and Annexin V/PI staining. ROS levels and NADP⁺/NADPH ratios were measured by DCFH-DA fluorescence and enzymatic assays. Metabolite tracing was conducted using [U-¹³C₅] glutamine followed by LC-MS. Key findings were validated in additional cell lines including HCT116, U2OS and MDA-MB-231. Results: ME1 and ME2 promote SF188 cell survival under glutamine deprivation, an effect that depends on their catalytic activity but is independent of TCA cycle anaplerosis. ME1 maintains redox balance by generating NADPH, and antioxidant treatment rescues the survival defect caused by ME1 knockdown. In contrast, ME2 does not contribute to redox regulation but stabilizes mutant p53 (G266E) via proteasome inhibition. Both of these pro-survival functions are attenuated upon MYC knockdown, suggesting a dependency on MYC expression. Across all cell lines tested, ME1 and ME2 also promote survival through redox maintenance, although the isoform responsible for antioxidant function differs. Conclusions: ME1 and ME2 support metabolic adaptation to glutamine starvation through distinct, isoform-specific mechanisms that depend on MYC expression and p53 mutation status. These findings suggest malic enzymes as potential therapeutic targets in MYC-driven, p53-mutant tumors. Full article

The peripheries of rare-metal metallogenic systems frequently host skarn-type or hydrothermal vein-type Pb-Zn deposits, though their genetic connections with parental systems remain debated. The newly identified Gariatong W-Mo polymetallic metallogenic system in the Lhasa Terrane displays well-defined Nb-Ta-Rb, Mo-W, W-Mo, W-Bi, and Pb-Zn-Ag metallogenic zoning, establishing it as an exemplary site for investigating genetic relationships between Pb-Zn and rare-metal mineralization. This investigation targets skarn-type Pb-Zn deposits spatially associated with rare-metal orebodies at Gariatong, utilizing integrated analytical approaches, including in situ LA-ICP-MS trace-element analysis of sulfides, sulfur isotope geochemistry, and LA-ICP-MS elemental mapping of sphalerite, to constrain metal sources, characterize fluid evolution, and establish genetic correlations with the rare-metal system. Key findings include the following: (1) sphalerite shows enrichment in Fe, Mn, Co, and Cd, while pyrite contains elevated As, Pb, Co, Cu, and Mn. Fe, Cd, and Mn primarily occur as solid solutions or nanoparticles, whereas As and Pb exist as micro-inclusions. (2) Sphalerite Zn/Cd ratios (73.6–184) and Co-Ni-As ternary diagrams confirm a magmatic–hydrothermal skarn origin. (3) Mineralization occurred under moderate-temperature, mildly oxidized conditions, as constrained by sphalerite Fe contents and mineral assemblages. Sulfur isotope compositions (δ³⁴S = −1.0‰ to 3.2‰; mean: 1.9‰) indicate a magmatic sulfur source. This study reveals that the Nb-Ta-Rb mineralization, quartz-vein- and greisen-type W-Mo deposits, and skarn-type Pb-Zn orebodies—all genetically associated with highly fractionated granites—constitute an integrated magmatic–hydrothermal system with vertical (depth-related) zoning relative to the granitic intrusion. These results provide critical constraints for understanding rare-metal–Pb-Zn genetic associations and suggest that Pb-Zn mineralization may serve as a key exploration indicator for rare metals in the Lhasa Terrane. Full article

The Huoyanshan Cu-Zn volcanogenic massive sulfide (VMS) deposit, located in the North Qilian Orogenic Belt, China, is of significant economic importance. This study provides new constraints on the ore-forming processes through high-resolution in situ trace element and sulfur isotope analyses of pyrite and sphalerite using LA-(MC)-ICP-MS. Petrographic and geochemical investigations identified three distinct generations of pyrite (Py l to Py III). Early-stage Py I and Py II are characterized by high trace element contents (Au, As, Bi, Cu, Pb), elevated Co/Ni ratios (>1–10), and enriched δ³⁴S values (+4.98‰ to +7.47‰). These signatures indicate precipitation from high-temperature, reduced magmatic–hydrothermal fluids influenced by thermochemical sulfate reduction (TSR). Late-stage Py IIl exhibits markedly lower Co/Ni ratios (<0.1) and lighter δ³⁴S values (+3.72‰ to 3.89‰). This geochemical shift reflects a transition toward a cooler, more oxidized environment driven by the incursion and mixing of ambient seawater as the hydrothermal system waned. Trace element geochemistry of sphalerite reveals an average crystallization temperature of 265.8 °C (derived from the “GGIMFis” geothermometer), consistent with fluid inclusion data and representing a thermal “snapshot” of the waning hydrothermal stage. Systematic discriminant analysis using Ga/In, Ge/In, and Co-Ni-As systematics further confirms a strong magmatic–hydrothermal affiliation. Full article

The Vehicle-to-Grid (V2G) technology is considered one of the best solutions for integrating renewable energy systems; however, most literature reports favorable economic results using synthetic data, without accounting for seasonal or market limitations. The current research presents the results of the MATLAB R2023b (Version 23.2, MathWorks, Natick, MA, USA) simulation of the 100-household energy community in Debrecen, Hungary, with 30 electric vehicles (EVs) using entirely simulation-based Lithium Iron Phosphate (LiFePO4) batteries, a simulation-based 150 kW solar photovoltaic (PV) system, and a simulation-based 200 kW wind power system, using real meteorological data for January 2024. The optimization of charging/discharging for electric vehicles was performed using a multi-objective genetic algorithm (GA) over 30 days at a 15 min time resolution, accounting for stochastic loads and temperature effects on battery degradation, with a sensitivity analysis of key parameters. The results of the optimized solution for the electric vehicle charging/discharging were unexpected: the total energy cost increased by 68.9% ($4337.65 to $7327.54), the peak demand increased by 266.2% (31.9 to 116.9 kW), the degradation cost was $479.63, the load factor was reduced from 0.847 to 0.722, and the SOC constraint was violated for 0.758% of measurements. The V2G is not economically viable under current Hungarian pricing and Central Europe winter conditions. Results are robust for varying parameters using sensitivity analysis and Pareto front tracing. The break-even point is achieved when ratios of peak-to-off-peak prices are above 3.5:1. Seasonal policies and market reforms are critical for V2G viability. Importantly, the influence of inherent design deficiencies in the optimization model on the reported results cannot be ruled out. Full article

Anaerobic digestion (AD) plays an important role in the circular bioeconomy by converting organic waste into renewable methane and nutrient-rich fertilizer. However, consistent, high-quality biomethane production is hindered by four main factors: hydrolysis limitations, fluctuating feedstock quality, microbial instability, and the high cost/energy demand of purification. This review explores three key areas that improve biomethane production: (i) process intensification (pretreatments and advanced reactors), (ii) microbial regulation through additives, and (iii) biogas upgrading for pipeline use. Anaerobic digestion can be greatly improved by combining thermal or hybrid pretreatments, staged digestion, high-solids technology, and electrochemical systems. These methods speed up hydrolysis and help the system handle higher amounts of organic material more effectively. However, actual performance benefits depend on specific substrate characteristics, heat integration, and control complexity. Optimizing the C:N ratio, buffering capacity, and trace-element supplementation, while simultaneously diluting toxic inhibitors, makes co-digestion an effective and adaptable approach to enhancing anaerobic digestion processes. Additives like carbon, iron nanoparticles, enzymes, and buffers can optimize digestion, but their performance is highly dependent on dosage and substrate. Additionally, they lack validation in long-term, industrial-scale applications. Conventional physicochemical techniques continue to be standard for generating high-quality biomethane, but biological methanation and microalgal systems are playing a growing role in integrating Power-to-Gas technology and using CO₂ efficiently. Critical research needs to focus on four areas: (1) standardized reporting metrics, (2) AI-enabled monitoring and control, (3) coupled techno-economic and life-cycle analysis (TEA-LCA), and (4) long-term pilot or full-scale validation. Overall, comprehensive optimization of the entire flow is more effective than improving isolated parts. Full article

This study implemented and validated View Factor (VF) and Ray Tracing (RT) simulation models against four-season field-measured data to evaluate the accuracy of energy yield prediction in bifacial PV systems under three installation configurations: (1) Single-row tilted, (2) Multi-row tilted, and (3) Vertical East–West facing. Front-side and rear-side irradiance and electrical energy yield were evaluated using nRMSE and nMBE metrics, and the relationship between irradiance component ratios (direct, diffuse, reflected) derived from RT results and error trends was analyzed. For front-side irradiance prediction, VF and RT methods showed similar performance in Single-row tilted and Multi-row tilted systems (nRMSE difference within 1 percentage point), while the RT method generally showed lower error than the VF method for rear-side irradiance prediction across the evaluated systems. Notably, in the Multi-row tilted system with high structural complexity, RT achieved nRMSE of 13.3%, which was 14.4 percentage points lower than VF (27.7%). Critically, the performance difference between the two methods was maximized under diffuse-dominant conditions. During shaded periods of the Vertical East–West facing system (diffuse ratio 76–81%), VF method’s nRMSE increased to 14.1–33.5%, while RT method maintained a stable level of 8.8–14.3%. This difference is likely related to differences in diffuse-radiation treatment between the two approaches, including the anisotropic sky representation used in the RT workflow and simplified assumptions in the VF-based rear-side model. In the temporal resolution analysis, the 1 h interval showed the lowest nRMSE for cumulative energy prediction, while the 5 min interval more accurately reproduced peak timing and rapid power fluctuations. This study suggests that the RT method can improve rear-side irradiance prediction accuracy, particularly under conditions of increased structural complexity and higher diffuse radiation ratios. It also indicates that simulation temporal resolution should be selected according to research objectives, such as long-term energy yield estimation or short-term power fluctuation analysis. Full article

Submarine volcanic-hosted iron oxide deposits are critical archives for reconstructing the interplay between hydrothermal activities and marine redox conditions, yet the genesis of these deposits remains controversial. Here, we present a comprehensive geochronological and geochemical study on the Shikebutai iron deposit in the Western Tianshan, northwestern China, to constrain the mineralization age, the source of iron, and deposit genesis. The stratiform-to-lenticular orebodies are hosted within the Late Carboniferous marine volcanic–sedimentary sequence of the Yishijilike Formation. The iron ores consist primarily of hematite and quartz, with minor siderite and barite, exhibiting massive to locally banded textures. SHRIMP zircon U-Pb dating of the overlying andesite yields an age of 315.8 ± 1.5 Ma, consistent with the Sm–Nd isochron age of the iron ore samples (319 ± 26 Ma), precisely constraining the mineralization age to the Late Carboniferous (ca. 315–320 Ma). The geochemical compositions of the iron ore samples indicate negligible syn-depositional detrital contamination, as evidenced by low Al₂O₃ (<1.00 wt%) and TiO₂ (<0.20 wt%) contents. Low abundances of trace elements, including Sr (0.33–31.18 ppm), Hf (0.05–1.77 ppm) and Rb (1.49–39.02 ppm), further support the minimal detrital influence. Geochemical signatures, such as pronounced positive Eu anomalies (Eu/Eu = 1.62–7.12, mean 4.14), LREE enrichment ((La/Yb) _(PAAS) = 0.58–4.78), and near-chondritic Y/Ho ratios (mean 28.5), suggest a significant high-temperature (>250 °C) hydrothermal contribution. Moreover, the ε_Nd(t) values of iron ore samples (+1.99 to +2.93) are comparable to those of coeval andesites (+2.75 to +3.44) but exceed those of associated metasiltstones (+0.41 to +0.95), suggesting that ore-forming materials were derived from hydrothermal fluids leaching juvenile crust. The Shikebutai iron deposit exhibits geochemical and mineralogical similarities to modern Red Sea and East Pacific Rise metalliferous sediments, establishing the deposit as a product of active vent-proximal hydrothermal systems rather than marine chemical sediments such as banded iron formations. Full article

Neoproterozoic iron formations (NIFs), deposited during Cryogenian glaciation events, are critical for understanding early Earth oxidation events and the evolution of glacial–interglacial environments. Apatite, a common accessory mineral in iron formations, holds significant implications for sedimentary environments and diagenetic processes, but these aspects remain underexplored. This study focuses on the Hengyang NIF in the Nanhua Basin, South China. Using whole-rock geochemistry and major and trace element analysis of apatite, we investigate the environmental significance of apatite and associated diagenetic processes. Our results show that the Hengyang NIF are formed through the mixing of low-temperature hydrothermal fluids, seawater, and terrigenous detrital materials, with hydrothermal contributions increasing progressively from the bottom to the top of the iron formation layers. Whole-rock geochemical proxies indicate that the depositional water column evolved from relatively oxidizing to weakly oxidizing conditions. The study further demonstrates that the rare earth element patterns in apatite, characterized by middle rare earth element enrichment, are primarily controlled by porewater chemistry during diagenesis. In contrast, Ce anomalies and the V/Cr and V/(V + Ni) ratios in apatite, which are strongly influenced by fluid–rock interactions and magnetite recrystallization, no longer reliably reflect the primary depositional environment. The Th/U ratio in apatite, due to its geochemical stability, aligns with whole-rock trends and serves as a more reliable redox proxy. Based on these findings, we propose a three-stage depositional-diagenetic model: the early and late stages are characterized by high-energy, rapid sedimentation with minimal diagenetic modification, while the middle stage is dominated by low-energy, stagnant conditions with slow sedimentation rates, leading to prolonged diagenesis and significant decoupling of mineral geochemical signatures. This study emphasizes the need to distinguish between sedimentary and diagenetic signals when using mineral geochemical proxies to reconstruct paleoenvironments and provides new insights into the genesis of Neoproterozoic iron formations. Full article

Coral reef ecosystems are declining rapidly due to climate change, disease, and anthropogenic stressors, driving the expansion of land-based coral propagation for reef restoration. A major bottleneck in these efforts is the manual measurement of coral recruit tissue area from microscopy images, which requires 2–7 min per image and limits scalability. We present a hierarchical deep learning pipeline that automates this measurement by integrating YOLO-based detection with Segment Anything Model (SAM) segmentation. YOLO localizes recruits and classifies them by developmental stage; stage-specific fine-tuned SAM models then segment live tissue using bounding box and background point prompts to suppress segmentation leakage and improve boundary precision. Surface area is computed directly from the segmented masks using pixel size extracted from image metadata. The pipeline reduces processing time to approximately 3–5 s per image—a 24–140× speedup over manual tracing. Evaluated on 3668 microscopy images from two national coral research facilities, the system achieves a mean IoU exceeding 95% and an auto-acceptance rate (AAR) of 71.51%, where predicted-to-ground-truth area ratios fall within a ±5% tolerance of expert annotation, substantially reducing manual workload while maintaining measurement reliability across species, developmental stages, and imaging conditions. This workflow addresses a critical bottleneck in restoration research and demonstrates the broader applicability of AI-based image analysis in marine ecology. Full article

During the interpretation of Borehole Radar (BHR) B-scan profiles, the accurate determination of the azimuth of geological targets in three-dimensional space is a critical issue for achieving precise anomaly localization and spatial structure inversion. However, existing directional BHR anomaly localization methods exhibit limited intelligence, insufficient adaptability to multi-site data, and weak generalization capability, rendering them inadequate for engineering applications under complex geological conditions. To address these challenges, a robust deep learning model, termed BSS-Pose-BHR, is developed based on YOLOv11n-pose for keypoint detection in directional BHR profiles. The model incorporates three key optimizations: Bi-Level Routing Attention (BRA) replaces Multi-Head Self-Attention (MHSA) in the backbone to improve computational efficiency; Conv_SAMWS enhances keypoint-related feature weighting in the backbone and neck; and Spatial and Channel Reconstruction Convolution (SCConv) is integrated into the detection head to reduce redundancy and strengthen local feature extraction, thereby improving suitability for keypoint detection tasks. In addition, a three-dimensional electromagnetic model of limestone containing a certain density of clay particles is established to construct a simulation dataset. On the simulated test set, compared with current mainstream deep learning approaches and conventional directional borehole radar anomaly localization algorithms, BSS-Pose-BHR achieves superior performance, with an mAP50(B) of 0.9686, an mAP50–95(B) of 0.7712, an mAP50(P) of 0.9951, and an mAP50–95(P) of 0.9952. Ablation experiments demonstrate that each proposed module contributes significantly to performance improvement. Compared with the baseline, BSS-Pose-BHR improves mAP50(B) by 5.39% and mAP50(P) by 0.86%, while increasing model weight by only 1.05 MB, thereby achieving a reasonable trade-off between detection accuracy and complexity. Furthermore, indoor physical model experiments validate the effectiveness of the method on measured data. Robustness experiments under different Peak Signal-to-Noise Ratio (PSNR) conditions and varying missing-trace rates indicate that BSS-Pose-BHR maintains high detection accuracy under moderate noise and data loss, demonstrating strong engineering applicability and practical value. Full article

The timing of uranium mineralization in the Xiangshan ore field has long been controversial. Although various geochronometers have been applied by previous researchers, including pyrite Rb-Sr, mica Ar-Ar, and fluorite Sm-Nd, the results remain inconsistent and inconclusive. In recent years, the discovery of abundant Pb-Zn veins in the deeper parts of the Xiangshan ore field has further complicated the interpretation of its metallogenic history. In this study, abundant vein-type hydrothermal apatites closely associated with U-Pb-Zn polymetallic mineralization were identified in both uranium and Pb-Zn ore veins. Combined major-element Electron Probe Microprobe Analysis (EPMA), Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry (LA-ICP-MS) U-Pb dating, and trace-element analysis were conducted on these apatite grains. The results suggest a mineralization age of 130.9 ± 1.1 Ma for the Shannan uranium deposit, which is consistent with the previously reported apatite U-Pb age of 131.3 ± 7.2 Ma from the Zoujiashan uranium deposit and coincides with the main pulse of volcanic-intrusive activity in the Xiangshan ore field (133–137 Ma). The deep Niutoushan Pb-Zn deposit suggests a younger mineralization age of 124.5 ± 1.3 Ma, which is consistent with a thermal event age of 125.6 Ma determined by zircon fission-track dating and the zircon LA-ICP-MS U-Pb age of late-stage granite porphyry (125.4 ± 1.0 Ma). These ages may constrain the timing of U-Pb-Zn polymetallic mineralization in the Xiangshan ore field. Both magmatic and hydrothermal apatites are classified as fluorapatite and exhibit similar chondrite-normalized rare earth element (REE) patterns. Compared with magmatic apatites, hydrothermal apatites are characterized by elevated Th, U, Ca, and Sr contents, depletion in light rare earth elements (LREEs), Mn, and Na, and distinctly lower Th/U ratios. On major-element variation diagrams, magmatic and hydrothermal apatites define coherent trends but display clear compositional differences related to their formation stages. Apatites from uranium ore veins show strongly negative Eu anomalies and weakly positive Ce anomalies, similar to magmatic apatites. In contrast, apatites from Pb-Zn ore veins display positive Eu anomalies and weakly negative Ce anomalies, with lower Mn and Ga contents and higher SO₃ contents relative to both magmatic apatites and hydrothermal apatites from uranium ore veins. These features indicate that the ore-forming fluids during Pb-Zn mineralization were characterized by significantly higher oxygen fugacity than those during uranium mineralization and magmatism. Combined with published Sr isotopic data for the Xiangshan ore field, we propose that both uranium and Pb-Zn mineralization were genetically linked to the prolonged magmatic evolution of the deep volcanic-intrusive complex. The subsequent incursion of meteoric water modified the physicochemical conditions of the ore-forming system, particularly during the formation of the Pb-Zn mineralization. Full article

In polar environments, icing on ship deck surfaces severely compromises navigation safety. Conventional electric trace heating systems operate in continuous heating mode, resulting in high energy consumption. This study proposes an intelligent periodic heating control method that integrates physics-informed neural networks (PINNs) and deep reinforcement learning (DRL) for energy-efficient anti-icing of circular pipe components on polar vessels. Using a polar coupled environment simulation platform, experiments were conducted on electric heating anti-icing for circular pipe components. Temperature data under various heating modes were collected, and a physically constrained PINN temperature prediction model was constructed, achieving high prediction accuracy with limited samples (test set R² = 0.9091; 5-fold cross-validation R² = 0.8877 ± 0.0312). The DRL agent trained in this virtual environment autonomously optimized the heating strategy, yielding optimal cycle parameters: heating ratio D = 0.722 and cycle duration τ = 88 s. While maintaining surface temperatures above 0 °C against a −10 °C ambient baseline, this strategy achieved a unit energy consumption of 0.27 kJ/°C, representing a 63% reduction compared to conventional continuous heating. This study provides a data-physics fusion control approach for polar vessel anti-icing systems, demonstrating strong potential for engineering applications. Full article

Three-dimensional printed polymers produced using Fused Deposition Modelling (FDM) exhibit directional microstructures resulting from filament paths, layer interfaces, and cellular infill, leading to mechanical and tribological responses distinct from those of homogeneous bulk materials. This study presents a comparative tribomechanical evaluation of polypropylene (PP) bulk inserts and 3D-printed polyethylene terephthalate glycol (PETG) inserts with a 30% hexagonal infill, relevant for robotic gripping applications. Progressive scratch tests were performed under loads from 5 to 100 N (150 N for PP), and profilometry was applied to quantify groove morphology, ridge formation, and displaced-volume ratios. An elasto-plastic conical indentation model was used to derive indentation pressures and elastic–plastic transition radii from groove geometry. The PETG inserts exhibited heterogeneous groove depth, intermittent ridge tearing, and friction fluctuations associated with the internal infill structure, consistent with previous findings on anisotropy and architecture-dependent behaviour in additively manufactured polymers. In contrast, bulk PP demonstrated smoother friction profiles and more stable plastic flow under increasing loads. Two functional indices—specific frictional work and ridge-to-trace volumetric ratio—are introduced to support material selection for robotic gripping systems. The results show that local contact mechanics in 3D-printed inserts are governed by print-induced structural features and can be effectively evaluated through a scratch-based elasto-plastic analysis. The methods and results presented in this work support the rational selection and design of polymer inserts for robotic gripper fingertips. The proposed scratch-based elasto-plastic evaluation framework enables manufacturers and automation engineers to compare 3D-printed and conventional materials based on friction stability, wear response, and deformation resistance. This approach can be directly applied to optimise gripping performance in industrial handling, packaging, and collaborative robotics. Full article