Search Results (220)

Accurately predicting the remaining useful life (RUL) of lithium-ion batteries is critical for ensuring the safe operation of equipment, optimizing industrial cost management, and promoting the sustainable development of the renewable energy sector. Although various deep learning-based approaches for RUL prediction have been proposed, their performance is highly dependent on the availability of large training datasets. As a result, these methods generally achieve satisfactory accuracy only when sufficient training samples are available. To address this limitation, this study proposes a novel hybrid strategy that combines a parameter-optimized signal decomposition algorithm with an enhanced neural network architecture, aiming to improve RUL prediction reliability under small-sample conditions. Specifically, we develop a lithium-ion battery capacity prediction method that integrates the Triangle Topology Aggregation Optimizer (TTAO), Variational Mode Decomposition (VMD), and a Bidirectional Long Short-Term Memory (BiLSTM) network. First, the TTAO algorithm is used to optimize the number of modes and the quadratic penalty factor in VMD, enabling the decomposition of battery capacity data into multiple intrinsic mode functions (IMFs) while minimizing the impact of phenomena such as capacity regeneration. Key features highly correlated with battery life are then extracted as inputs for prediction. Subsequently, a BiLSTM network is employed to capture subtle variations in the capacity degradation process and to predict capacity based on the decomposed sequences. The prediction results are effectively integrated, and comprehensive experiments are conducted on the NASA and CALCE lithium-ion battery aging datasets. The results show that the proposed TTAO-VMD-BiLSTM model exhibits a small number of parameters, low memory consumption, high prediction accuracy, and fast convergence. The root mean square error (RMSE) does not exceed 0.8%, and the maximum mean absolute error (MAE) is less than 0.5%. Full article

The Tuzla area, located in the Ayvacık district of Çanakkale (Biga Peninsula, northwestern Türkiye), hosts a Oligocene-Miocene volcanic system comprising andesitic, dacitic, rhyolitic lavas, trachyandesite, pyroclastics, and ignimbrites, and the Kestanbol Pluton. Petrographic and X-ray diffraction (XRD) analyses indicate that the altered volcanic units are dominated by porphyritic dacitic/rhyodacitic and trachyandesitic rocks, with silicification, iron oxide formation, and opacification. XRD results reveal smectite, smectite–illite/mica, illite–mica, kaolinite, cristobalite–opal, K-feldspar, plagioclase, dolomite, hematite, and quartz as the principal mineral phases. Geochemical data, including rare earth elements (REEs), suggest that fractional crystallization of primary mineral phases played a major role in controlling magmatic evolution. Chondrite-normalized REE patterns display enrichment in light REEs relative to heavy REEs, indicating derivation from a common magma source. K₂O–Na₂O and (Na₂O + K₂O)–FeOᵗ–MgO (AFM) diagrams show high-K calc-alkaline, calc-alkaline, and tholeiitic affinities, with most rhyodacite/dacite and all trachyandesite samples plotting in the tholeiitic field. Tectonic discrimination diagrams indicate formation in both volcanic arc and intraplate tectonic settings. Moderate enrichments in Ba and Sr reflect magmatic evolution and source characteristics, whereas the highest concentrations are attributed to post-magmatic fluid–rock interaction. Overall, the Tuzla volcanic rocks originated from a collision-related enriched lithospheric mantle source and subsequently evolved through fractional crystallization and assimilation processes, accompanied by crustal contamination and variable hydrothermal overprint. Full article

Accurately estimating the state of health (SOH) of lithium-ion batteries is vital for guaranteeing battery safety and prolonging their operational lifespan. However, current data-driven approaches often suffer from limited utilization of health indicators, weak noise suppression, and inefficient feature fusion across multiple branches. To overcome these limitations, this paper proposes DFFNet, a Dual-Branch Feature Fusion Network with Improved Dynamic Elastic Weight Consolidation (IDEWC) for battery SOH estimation. The proposed DFFNet captures both local degradation behaviors and global aging trends through two parallel branches, while a gated attention mechanism adaptively integrates multi-scale features. Moreover, IDEWC dynamically updates the Fisher Information Matrix to retain previously learned knowledge and adapt to new data, thereby mitigating catastrophic forgetting. Experimental validation on the NASA and CALCE datasets shows that DFFNet outperforms baseline methods in accuracy, demonstrating its robustness and generalizability for precise battery SOH estimation. Full article

Grokhovskyite, CuCrS₂, was observed in small sulfide inclusions (up to 50–80 µm) in Ni-rich iron (kamacite) of the Uakit iron meteorite (IIAB) in the Republic of Buryatia, Russia. The grain sizes of this mineral are usually less than 5 μm, and the biggest detected crystals are 10 × 5 μm in size. It is commonly associated with daubréelite, troilite, schreibersite, and, sometimes, with carlsbergite and uakitite. Within inclusions, the mineral forms elongated splintered crystals, or, rarely, needle-shaped grains in daubréelite. The grokhovskyite-containing associations in the Uakit meteorite seem to form due to high-temperature (>1000 °C) separation of Fe-Cr sulfide liquid, which is locally enriched in Cu, from Fe-Ni metal melt. Physical and optical properties of grokhovskyite are quite similar to those of synthetic CuCrS₂: yellow–brown and non-transparent phase with metallic luster; Mohs hardness ≈ 4; gray to light gray color with yellow tint in reflected light; weak to medium bireflectance, anisotropy, and pleochroism; density (calc.) = 4.559 g/cm³. Grokhovskyite is structurally related to the Cr-containing disulfide minerals with general formula Me⁺CrS₂ (where Me⁺ = Na, Cu, Ag), including caswellsilverite, NaCrS₂; schöllhornite, Na_0.3CrS₂·H₂O; and cronusite, Ca_0.2CrS₂·2H₂O. Structural data were obtained for one grokhovskyite crystal using the EBSD technique. Fitting of the EBSD patterns for a synthetic α-CuCrS₂ model (trigonal R3m; a = 3.4794(8) Å; c = 18.702(4) Å; V = 196.08(10) ų; Z = 3) resulted in the parameter MAD = 0.57–1.16° (good fit). Analytical data for grokhovskyite (n = 36, in wt.%) are as follows: Cu—32.97; Cr—27.65; Fe—3.69; Ni—0.16; S—35.71; Na, Zn, V, Mn, and Co—below detection limit (<0.005 wt.%). The empirical formula is (Cu_0.930Cr_0.952Fe_0.118Ni_0.005)_2.005S_1.995; however, different concentrations of Fe are indicated in two individual grains of grokhovskyite (0.09–0.17 apfu). Such variations may be explained by Fe incorporation in the grokhovskyite structure according to the scheme ^IVCu⁺ + ^VICr³⁺ → ^IVFe²⁺ + ^VIFe²⁺. The three main bands (near 110, 250, and 310 cm⁻¹), which are common of synthetic CuCrS₂, were observed in the Raman spectra of grokhovskyite. Full article

This study aimed to investigate the growth behavior of key precipitates in 9–12 wt.% Cr ferritic/martensitic heat-resistant steel as a function of tempering duration. Tempering was carried out at 670 °C for durations between 1 h and 300 h. The precipitates identified were M₂₃C₆, Laves phase, Nb-rich MX, and V-rich MX, each exhibiting distinct growth behavior with increasing tempering time. Transmission electron microscopy (TEM) was used to quantitatively analyze their growth behavior. The results revealed that M₂₃C₆, Laves phase, and V-rich MX underwent progressive coarsening with time, whereas Nb-rich MX showed negligible growth even after prolonged tempering. Based on the quantified data, a precipitate-growth model was implemented in MatCalc, and the key parameters were derived and validated against experimental data. The modeling results showed excellent agreement with experimental observations, confirming that the proposed model can reliably predict the microstructural evolution of ferritic/martensitic heat-resistant steel under long-term high-temperature exposure relevant to USC applications. Full article

Magma oxidation state and water content are pivotal factors governing porphyry copper mineralization. The Xiongcun deposit, the only super-large porphyry copper deposit (PCD) formed in an oceanic subduction environment in the Gangdese belt, has been the primary focus of prior research, with limited systematic comparisons conducted among Xiongcun, weakly mineralized, and barren igneous rocks across the Jurassic Arc. Furthermore, the interaction between ore-controlling factors and deep-seated magmatic processes remains poorly understood. This study examines Xiongcun volcanic rocks, as well as weakly mineralized and barren volcanic rocks from the Jurassic Arc, with Dazi and Jiamagou samples from the eastern segment of Jurassia Arc (ESJA) and Xiongcun, Chucun, and Qinze samples from the western segment of Jurassia Arc (WSJA). All samples (168.0–184.8 Ma) are predominantly calc-alkaline, which is typical of arc magmas. Zircon Hf isotopic data reveal pronounced E-W variations but minimal N-S differences, dividing the arc into the WSJA and ESJA subzones. The WSJA volcanic rocks exhibit uniform Hf isotopic signatures (ε_Hf(t) = 11.2–16.3) and young crustal model ages (186–500 Ma), whereas the ESJA mantle source region is heterogeneous, reflecting greater retention of ancient crustal material. Compared to the ESJA, new data from WSJA samples display higher zircon Ce⁴⁺/Ce³⁺ ratios (454 vs. 145), lower T(Zr-Ti) values (716 °C vs. 779 °C), and elevated whole-rock Ba/La ratios. These differences suggest that mineralization contrasts between the two segments arise from varying fluid metasomatism in their source regions, leading to divergent magma oxygen fugacity and water content—critical controls on porphyry Cu formation. The WSJA magmas exhibit higher values in both parameters, while the ESJA lacks significant mineralization potential. Full article

The dedifferentiation of smooth muscle cells (SMCs) is the main cause of atherosclerosis and vascular calcification. This study integrated the gene expression data of multiple microarrays to identify relevant marker molecules. A total of 72 Gene Expression Omnibus (GEO) samples (GSM) were collected from 10 gene expression data series (GSE) and divided into five groups: non-SMC, SMC, atherosclerotic SMC (SMC-ath), calcified SMC (SMC-calc), and treated SMC (SMC-t). The SMC-t group included synthetic SMCs that had undergone treatment to inhibit proliferation, migration, or inflammation. The gene expression data were merged, normalized, and batch effects were removed before differential gene expression (DGE) analysis was performed via linear models for microarray data (limma) and statistical analysis of metagenomic profiles (STAMPs). The genes with expressions that significantly differed were subsequently subjected to protein-protein interaction (PPI) and functional prediction analyses. In addition, the random forest method was used for classification. Twelve proteins that may be marker molecules for SMC differentiation and dedifferentiation were identified, namely, Proprotein convertase subtilisin/kexin type 1 (PCSK1), Transforming growth factor beta-induced (TGFBI), Complement C1s (C1S), Phosphomannomutase 1 (PMM1), Claudin 7 (CLDN7), Calcium binding and coiled-coil domain 2 (CALCOCO2), SAC3 domain-containing protein 1 (SAC3D1), Natriuretic peptide B (NPPB), Monoamine oxidase A (MAOA), Regulator of the Cell Cycle (RGCC), Alpha-crystallin B Chain (CRYAB), and Alcohol dehydrogenase 1B (ADH1B). Finally, their possible roles in SMCs are discussed. This study highlights the feasibility of bioinformatics analysis for studying SMC dedifferentiation. Full article

This study documents the first A1-type granite identified on the southern margin of the central Lhasa terrane: a two-mica syenogranite pluton in the Meibaqieqin region. Because A-type granite provides sensitive records of crustal melting and lithospheric extension, this pluton offers important insights into magmatic processes and tectonic evolution along the southern margin of the Lhasa terrane. We analyzed two sample suites collected from different sites within the same pluton using zircon U–Pb geochronology and Hf isotopes, whole-rock geochemistry and Nd isotope. Zircon U–Pb weighted mean ages were 130.5 ± 0.7 Ma and 130.0 ± 0.7 Ma, placing emplacement in the Early Cretaceous. Zircon ε_Hf(t) values ranged from −11.29 to −9.00 and −11.04 to −7.27, with two-stage Hf model ages (T_DM2) of 1.76–1.90 Ga and 1.65–1.89 Ga. Whole-rock ε_Nd(t) values clustered between −11.77 and −11.36, yielding two-stage Nd model ages (T_NdDM2) of 1.85–1.88 Ga. Geochemically, the pluton is high-K calc-alkaline. These isotopic signatures indicate derivation predominantly from ancient crustal sources with a little mantle material. Chondrite-normalized REE patterns are overall right-inclined and display a V-shaped profile. Together with trace-element characteristics, these features support classification as A1-type granite. Regional comprehensive data suggest that pluton emplacement was controlled mainly by lithospheric extension related to northward subduction of the Neo-Tethyan oceanic plate, with a lesser contribution from southward subduction along the Bangongco–Nujiang suture. The source characteristics and geodynamic context differ markedly from A2-type granites on the northern margin of the central Lhasa terrane, which reflect distinct magmatic sources and tectonic regimes. Full article

The Southern Great Xing’an Range (SGXR), an important W–Sn polymetallic metallogenic belt in northern China, hosts multiphase magmatism and has witnessed recent discoveries of multiple tungsten–tin polymetallic deposits. The W–Sn mineralization in this area is intimately associated with Early Cretaceous highly fractionated granites. The Chamuhan deposit, a small-sized W–Mo polymetallic deposit in SGXR, is genetically linked to a concealed fine-grained porphyritic alkali feldspar granite intrusion. In this study, we present the LA-ICP-MS zircon U-Pb ages, whole-rock geochemical, and electron probe microanalysis (EPMA) mineral chemistry to constrain the petrogenesis and metallogenic implications of this granite. Zircon U–Pb dating yields a crystallization age of 141.3 ± 1.2 Ma, consistent with molybdenite Re–Os ages. The granite is characterized by elevated SiO₂ (76.9–79.1 wt%) and total alkalis (7.3–8.5 wt%), and exhibits peraluminous high-K calc-alkaline affinity (A/CNK = 1.37–1.57). Geochemical signatures reveal enrichment in large ion lithophile elements (LILEs, e.g., Rb, Th, U) coupled with depletion in high-field strength elements (HFSEs, e.g., Ba, Sr, P, Eu, Ti, Nb, Ta), and are accompanied by right-sloping REE patterns with LREE enrichment and HREE depletion. EPMA data indicate that the mica in the intrusion is primarily zinnwaldite and Li-rich phengite, whereas the plagioclase occurs as albite. The feldspar thermobarometry yields crystallization temperatures of 689–778 °C and 313 MPa–454 MPa, while the melt H₂O content and oxygen fugacity are 8.61–11.1 wt% and −22.58–−14.48, respectively. These geochemical signatures indicate that the granites are highly fractionated I-type granites with extensive fractional crystallization of various minerals like plagioclase, K-feldspar, and apatite, etc. From the Late Jurassic to the Early Cretaceous, the subduction and rollback of the Paleo-Pacific Ocean plate resulted in extensional tectonic environments in eastern China. Asthenospheric upwelling and lower crustal melting generated parental magmas, wherein progressive fractional crystallization during ascent concentrated ore-forming elements and volatiles within residual melts. This process played a key role in the formation of the Chamuhan deposit, exemplifying the metallogenic potential of highly evolved granitic systems in the SGXR. Full article

The aim of this study is to evaluate the mechanical properties and long-term stability of 3D-printable resins for permanent fixed dental prostheses (FDPs), focusing on whether material performance is influenced by 3D-printer type or by differences in resin formulations. Specimens (N = 621) were printed. CAD/CAM blocks (BRILLIANT Crios) served as control. Flexural strength (FS) with elastic modulus (E_calc), Weibull modulus (m), Martens’ hardness (HM), indentation modulus (EIT), elastic modulus (E_RFDA), shear modulus (G_RFDA), and Poisson’s Ratio (ν) were measured initially, after water storage (24 h, 37 °C), and after thermocycling (5–55 °C, 10,000×). SEM analysis assessed microstructure. Data were analyzed using Kolmogorov–Smirnov, ANOVA with Scheffe post hoc, Kruskal–Wallis with Mann–Whitney U, and Weibull statistics with maximum likelihood (α = 0.05). A ceramic crown printed with Midas showed higher FS, HM, and EIT values after thermocycling than with Pro55s, and higher E_calc scores across all aging regimes. A Varseo Smile Crown Plus printed with VarseoXS and AsigaMax showed a higher FS value than TrixPrint2, while AsigaMax achieved the highest initial E_calc and E_RFDA values, and VarseoXS did so after thermocycling. HM, EIT, and G_RFDA were higher for TrixPrint2 and AsigaMax printed specimens, while ν varied by system and aging. 3Delta Crown, printed with AsigaMax, showed the highest FS, E_calc, HM, EIT, and m values after aging. VarseoSmile triniQ and Bridgetec showed the highest E_RFDA and G_RFDA values depending on aging, and Varseo Smile Crown Plus exhibited higher ν initially and post-aging. Printer system and resin formulation significantly influence the mechanical and aging behaviors of 3D-printed FDP materials, underscoring the importance of informed material and printer selection to ensure long-term clinical success. Full article

The Jiapigou mining district, a world-famous gold-producing district with a capacity that greatly exceeds 180 t Au, has a mining history longer than 200 years. The large amount of Jurassic Au mineralization in this district significantly differs from that in other districts of the North China Craton (130–115 Ma). However, the deep-seated dynamic processes and mechanisms that triggered the unique Jurassic mineralization in the Jiapigou district are poorly understood. Here, we present new data on the geology, petrography, and zircon U–Pb and Lu–Hf isotopes of the typical Huangnihe pluton in the Jiapigou district to address the above issues. The results revealed the following: (1) The Huangnihe pluton comprises mainly fine-grained granite and porphyritic granite, which were emplaced at 187 ± 2 Ma (n = 13) and 166 ± 2 Ma (n = 15), respectively. (2) The Hf isotope data indicate that the two episodes of granites exhibit distinct origins: the former (εHf(t) = −1.4 to +5.3; T_DM2 = 1784–1181 Ma) originated from juvenile lower crust, whereas the latter (εHf(t) = −14.9 to −9.7; T_DM2 = 2987–2518 Ma) was derived from Archean crust. (3) On the basis of published geochemical data, the estimated crustal thicknesses of the Jiapigou district ca. 187 Ma, ca. 175 Ma, and ca. 166 Ma ranged from 45 to 52 km, 43 km, and 58 to 63 km, respectively. Combined with regional observations, the results of this study further reveal the following: (1) The Jurassic magmatism in the Jiapigou district can be subdivided into three episodes: 187–186 Ma, ca. 175 Ma, and 166–165 Ma. (2) The crust in the Jiapigou district gradually thickened during the Jurassic and underwent partial melting during multiple episodes of Paleo-Pacific Plate subduction, thereby generating arc-like calc-alkaline (ca. 187 Ma), adakite-like (ca. 175 Ma), and adakite magmas (ca. 166 Ma) that were emplaced to form corresponding granitoids. Moreover, syn-ore magma mixing between the ca. 175 Ma adakite-like felsic magma and mantle-derived mafic magmas was considered a crucial process in magma evolution. This process in turn promoted the enrichment of ore-forming elements within the magma system, which significantly contributed to the formation of the large Au mineralization in the Jiapigou district. Full article

Accurately estimating the remaining useful life (RUL) of lithium-ion batteries in energy storage systems is critical for ensuring both the safety and reliability of the power grid. To address the complex nonlinear degradation behavior associated with battery aging, this study proposes a novel RUL prediction framework that integrates ensemble empirical mode decomposition (EEMD) with an ensemble learning algorithm. The approach first applies EEMD to decompose aging data into a residual component and several intrinsic mode functions (IMFs). The residual component is then modeled using a long short-term memory (LSTM) network, while the Kolmogorov–Arnold network (KAN) focuses on learning from the IMF components. These individual predictions are subsequently combined to reconstruct the overall capacity degradation trajectory. Experimental validation on real lithium-ion battery aging datasets demonstrates that the proposed method provides highly accurate RUL predictions, exhibits strong robustness, and effectively captures nonlinear characteristics under varying operating conditions. Specifically, the method achieves R² above 0.96 with absolute RUL errors within 2–3 cycles on NASA datasets, and maintains R² values above 0.91 with errors within 7–15 cycles on CALCE datasets. Furthermore, the optimal KAN hyperparameters for different IMF components are identified, offering valuable insights for multi-scale modeling and future model optimization. Full article

The Galale Cu–Au deposit lies on the northern margin of the western Gangdese metallogenic belt, near the western edge of the Gangdese arc within the Bangong–Nujiang suture zone. Unlike the well-studied Miocene Cu belt in southern Gangdese, this region remains insufficiently investigated, particularly in terms of geochemical characterization, leading to an ambiguous metallogenic model and a debated tectonic setting—specifically, the unresolved issue of subduction polarity across the Bangong–Nujiang suture. This tectonic ambiguity has important implications for understanding magma sources, metal transport pathways, and, consequently, for guiding mineral exploration strategies in the area. To address this, we conducted zircon U–Pb dating on the ore-related quartz diorite and granodiorite, yielding crystallization ages of 84.05 ± 0.34 Ma and 77.20 ± 0.69 Ma, respectively. Integrated with previous data, these results constrain mineralization to 83–89 Ma, which includes both skarn-type Cu–polymetallic and porphyry-type Cu mineralization. Regional comparisons support a tectonic model involving slab rollback and southward subduction of the Bangong–Nujiang oceanic lithosphere. Geochemical analyses of quartz diorite, granodiorite, and monzonitic granite show high-K calc-alkaline, peraluminous I-type affinities, with enrichment in LREEs and LILEs, and depletion in HREEs and HFSEs. Notably, the monzonitic granite is marked by high SiO₂, Sr/Y, and Rb/Sr ratios, low Zr/Hf, strong LREE enrichment, weak Eu anomalies, and pronounced Nb–Ta depletion, indicating high oxygen fugacity and favorable conditions for Mo mineralization. The deposit formed through tectono-magmatic processes related to the closure of the Bangong–Nujiang Neo-Tethys Ocean. Subduction and subsequent lithospheric delamination induced partial melting of mantle and crustal sources, generating quartz diorite and granodiorite intrusions. Magmatic fluids interacted with carbonate wall rocks to form skarn assemblages, concentrating ore metals along structures. The mineralization formed within the contact zones between intrusions and surrounding country rocks. Late-stage granite porphyry intrusions (~77 Ma), inferred from major, trace, and rare earth element compositions to have the highest Mo potential, may represent an extension of earlier skarn mineralization in the area (83–89 Ma). This study presents the first comprehensive geochemical dataset for the Galale deposit, refines its metallogenic model, and identifies key geochemical indicators (e.g., Sr, Y, Nb, Rb, Zr, Hf) for Mo exploration. Full article

With the intensification of extreme climate change, hurricanes are becoming increasingly frequent, and coastal regions are often impacted by hurricane-induced storm surges. While GNSS-IR (Global Navigation Satellite System–Interferometric Reflectometry) has been widely used for sea level monitoring, its application in extreme weather events such as storm surges remains limited. This study focuses on GNSS-IR-based storm surge monitoring and investigates six hurricane events using data from two GNSS stations (CALC and FLCK) located in the Gulf of Mexico. The monitoring accuracy and effectiveness are systematically evaluated. Results indicate that GNSS-IR achieves a sea level accuracy of approximately 7 cm under non-storm surge conditions. Compared with the FLCK station, the CALC station has a wider field of water reflection and higher precision observation results. This further confirms that an open environment is a prerequisite for ensuring the accuracy of GNSS-IR measurements. However, accuracy degrades significantly during storm surges, reaching only a decimeter-level precision. Multi-GNSS observations notably improve temporal resolution, with valid observation periods covering 83% to 97% of the total time, compared with only 40% to 60% for single-system observations. Moreover, dynamic sea level variations are closely correlated with hurricane trajectories, which affects GNSS-IR measurement accuracy to some extent. The GPS L2 band is particularly sensitive, likely due to the complex surface-reflected condition caused by hurricanes. Despite reduced accuracy during storm surges, GNSS-IR remains capable of capturing dynamic sea level changes effectively, demonstrating its potential as a valuable supplement to the existing observation networks for extreme weather monitoring. Full article

Widespread Triassic granitic magmatism is archived in the East Kunlun Orogen Belt (EKOB) of Northern Qinghai–Tibet Plateau. Mafic magmatic enclaves (MMEs), commonly hosted in these plutons, are generally interpreted as products of magma mixing; however, the specific magmatic processes remain poorly understood. In this study, we present new data on the complex zoning patterns, in situ U–Pb ages, trace element compositions, and Nd isotopic characteristics of titanite grains from the MMEs and host granodiorite of Laningzaohuo Zhongyou pluton. Whole-rock geochemical data indicate that the pluton is composed of volcanic arc-related, calc-alkaline, metaluminous I-type granodiorite. Titanite in the MMEs and the granodiorite yield similar U–Pb ages of ~244 Ma but display distinct textural and compositional features. Titanite from the granodiorite is typically euhedral, characterized by magmatic core and mantle with deuteric rim, and exhibits sector and fir-tree zoning in the core. In contrast, titanite from the MMEs is generally anhedral, also showing magmatic core and mantle as well as deuteric rims, but exhibits oscillatory zoning and incomplete sector and fir-tree zoning in the core. Titanite cores in the MMEs have ε_Nd(t) ranging from −2.5 to −3.4, comparable to those of the coeval gabbro and MMEs elsewhere in the EKOB. These cores also show higher LREE/HREE ratios compared to titanite cores in the granodiorite, suggesting crystallization from mixed magmas with greater contributions from enriched lithospheric mantle sources. Titanite mantles in the MMEs yield ε_Nd(t) of −4.0 to −4.8, slightly lower than the cores in the MMEs but higher than those of titanite cores and mantles in the granodiorite (−4.6 to −5.5). The mantle can be interpreted as crystallized from mixed magmas with less mafic components. Titanite rims in the MMEs have ε_Nd(t) of −5.0 to −5.7, identical to those in the granodiorite, and have REE concentrations and Th/U and Nb/Ta ratios consistent with the titanite rims in the granodiorite, clearly indicative of crystallization from evolved, hydrated, granodioritic magmas. Plagioclase in the MMEs exhibits disequilibrium textures such as sieve texture and reverse zoning, with An_36–66, contrasting with the more uniform An contents (An_35–37) in the granodiorite. This suggests that plagioclase in the MMEs crystallized in an environment influenced by both mafic and felsic magmas. Amphibole thermobarometry indicates that amphibole in the MMEs crystallized at ~788 °C and ~295 MPa, slightly higher than the crystallization conditions in the granodiorite (~778 °C and ~259 MPa). We thus propose that the chemical and textural differences between titanite in the MMEs and granodiorite suggest that the MMEs formed within a mushy hybrid layer generated by injection of upwelling basaltic magma into a pre-existing granitic magma chamber. Titanite cores and mantles in the MMEs likely crystallized from variably mixed magmas. They subsequently underwent resorption and disequilibrium growth within the hybrid layer, and were eventually overgrown by rims formed from evolved interstitial granitic melts within the mushy enclaves. These findings demonstrate that the complex zoning and geochemical titanite in the MMEs provide valuable insights into magma mixing processes. Full article