Abstract Picrites, dominantly composed of highly forsteritic olivine, can serve as important constraints on primary magma composition and eruption dynamic processes in global continental flood basalt (CFB) provinces. Picrites are commonly divided into high-Ti and low-Ti groups based on whole-rock TiO2 content or Ti/Y ratio. Here, we use an artificial neural network (ANN) to classify the individual olivine in picrites from global CFB provinces according to whether their parental magma is high-Ti or low-Ti to better understand the primary origin and magmatic processes. After training the ANN on 1000 olivine major element compositions data points, the network was able to differentiate chemical patterns for high-Ti and low-Ti olivine and classify olivine into correct types with an accuracy of >95%. Moreover, we find that two types of olivine mix in some single samples from Etendeka, Emeishan, and Karoo CFB provinces. Combining the results with chemical markers of source lithology, we suggest that the two types of olivine originate from two different sources and their olivine populations mixed during the ascent. This mixing then makes the spatial and temporal variation of picrites types in some CFB provinces unclear.
Abstract Altered oceanic crust (AOC) is the largest contributor to the subducted sulfur (S) budget and its recycling modulates the redox evolution and S distribution in the mantle. However, the role of AOC in the deep cycling of S remains poorly constrained. Here we probe the primary S isotopes of Cenozoic intraplate basalts in eastern China by investigating sulfide inclusions in magmatic clinopyroxene megacrysts. These basalts were derived from the deep mantle metasomatized by melts derived from recycled AOC but show MORB‐like S isotopes (−0.9–0.9‰), suggesting that AOC‐derived melts transfer negligible sulfate and hardly change the δ 34 S and redox state of the deeper mantle. This contrasts with the generally high δ 34 S values of mantle wedge peridotites and primary arc magmas that reflect the slab addition of sulfate, indicating that S species and isotopes released from the subducted slab and associated f O 2 are not constant and vary with subduction depth.
The nature of source rocks of basaltic magmas plays a fundamental role in understanding the composition, structure and evolution of the solid earth. However, identification of source lithology of basalts remains uncertainty. Using a parameterization of multi-decadal melting experiments on a variety of peridotite and pyroxenite, we show here that a parameter called FC3MS value (FeO/CaO-3*MgO/SiO2, all in wt%) can identify most pyroxenite-derived basalts. The continental oceanic island basalt-like volcanic rocks (MgO>7.5%) (C-OIB) in eastern China and Mongolia are too high in the FC3MS value to be derived from peridotite source. The majority of the C-OIB in phase diagrams are equilibrium with garnet and clinopyroxene, indicating that garnet pyroxenite is the dominant source lithology. Our results demonstrate that many reputed evolved low magnesian C-OIBs in fact represent primary pyroxenite melts, suggesting that many previous geological and petrological interpretations of basalts based on the single peridotite model need to be reconsidered.
Igneous rock textures reflect the cooling history of the parental magma. Combined with chemical data, they can provide physical and chemical information about the evolution of a magma body. The petrographic textures and chemical compositions of 21 coarse- and fine-grained granite samples along an ∼250 m horizontal outcrop of the Shanggusi granite porphyry are presented in this case study. The coarse-grained granite porphyry is an early intrusion, and the fine-grained granite dykes, mostly intruded into the granite porphyry, are later intrusions. The studied samples have nearly homogeneous major element bulk-rock and mineral compositions, but show large variations in their trace element compositions and textural characteristics. The trace element data suggest the influence of hydrous fluids (possibly enriched in CO2, F, and Cl) in the evolution of the plutonic body. Textural analysis of the coarse-grained granite porphyry indicates that the crystal size distribution (CSD) slopes, intercepts and total numbers of groundmass decrease from the center to the margin of the intrusion in contrast to the maximum diameter of the crystals (Lmax) (average length of the four largest quartz crystals for each sample); however, most fine-grained samples and the groundmass of the coarse-grained samples show concave-down CSDs, indicating textural coarsening. Quartz CSDs in the coarse-grained samples are kinked, with a steep-sloped log–linear section representing small crystals (<1 mm) and a shallow-sloped log–linear section representing large crystals (>1 mm). These two crystal populations are interpreted as resulting from a shift in cooling regime. The straight CSDs of two fine-grained samples may be due to a different cooling history. In general, the spatial variation of the CSD patterns can be attributed to various degrees of overgrowth and mechanical compaction. The quartz phenocrysts in several coarse-grained samples exhibit a high degree of alignment, which may be the result of magmatic flow. By integrating the field geology, geochemistry and quantitative textural data from the horizontal profile of the Shanggusi granite porphyry, it is suggested that hydrous fluids at the top of the intrusion not only controlled the fractionation of elements but also affected its cooling history. Fluid migration-controlled undercooling can explain the solidification processes in the Shanggusi intrusion, and may also be prevalent in other fluid-rich shallow intrusions. Quantitative integration of textural and geochemical data for igneous rocks can contribute to our understanding of the relationships between physical and chemical processes in a magma system, and provide relatively comprehensive insights into the petrogenesis of granites.
The nucleation and growth of crystals in igneous rocks usually occur under thermodynamic equilibrium conditions. However, recent studies on igneous textures and mineral compositions have shown that these processes probably occur under thermodynamic disequilibrium conditions. Titanomagnetite with variable crystal sizes can be observed in Hannuoba alkaline basalt, indicating disequilibrium crystallization processes (different cooling rates). The ratio of the maximum particle size to the area abundance of titanomagnetite, as determined by analysis of literature experiments on the texture of minerals, was negatively correlated with the apparent cooling rate. We analyzed the chemical composition and crystal size distribution of titanomagnetite in ten Hannuoba alkaline basalt samples to determine the connection between the apparent cooling rate and the titanomagnetite composition. In Hannuoba samples, the cooling rate was found to affect cationic substitution in the titanomagnetite solid solution, and an increase in the cooling rate led to a decrease in Ti 4+ and an increase in Fe 3+ . The partition coefficient of Ti between titanomagnetite and the melt (D Ti ) is negatively correlated with the apparent cooling rate. These findings are consistent with those in experimental petrology and help us propose a better, more general geospeedometer. The cooling rate also impacted Mg 2+ and Al 3+ , but they were more impacted by the melt composition and crystallinity of the coexisting melt. Therefore, a new geospeedometer was calibrated by considering the titanomagnetite composition, melt composition and the content of the clinopyroxene:CR(℃/min)=-2.255(±0.051)×DTi/(timtFe 2+ ))+0.032(±0.010)×Cpx content+18.739(±0.386)The cooling rates of the Hannuoba basalt samples measured using the new geospeedometer calibrated in this study ranged from 0.7 to 7.0 (±0.5) ℃/min. It cannot predict the cooling rate from titanomagnetite well in intermediate rock, acidic rock or Fe-rich basaltic melts. The new titanomagnetite geospeedometer can better measure the cooling rate of alkaline basalt and may help identify the effects of kinetically controlled crystallization on isotope fractionation, evaluate mineral thermobarometers and better recognize thermal remanence magnetization and ancient magnetic fields.
Abstract The Panzhihua layered intrusions is generated closely related to the Emeishan LIPs. This paper analyzes the spatial distribution of plagioclase and pyroxene. The quantitative texture analysis of 2209 plagioclase shows that the characteristic length of plagioclase is 0.54 to 0.96 mm, the intercept variation range is large, from –0.67 to 0.96, and the slope is –1.85 to –1.04, the Aspect Ratio shows from 1.84 to 2.59 and fractal dimension D is 1.908–1.933. The quantitative texture analysis of 2342 pyroxene shows that the characteristic length of pyroxene is 0.38–0.64 mm, the intercept shows from 0.46 to 2.26, The slope ranges from –2.6 to –1.47, the Aspect Ratio value varies from 1.53 to 1.71, the fractal dimension D is 0.93 to 1.13. All the CSDs results of the Panzhihua intrusions indicate that plagioclase and pyroxene form in an open magma system and undergo four replenishment of magma injection. The plagioclase crystals do not grow as the lathlike shape, and the fractal growth leads to complex crystal surface. The plagioclase undergoes deformation compaction during the crystal process, and then is oriented. The pyroxene crystals grow along an approximately triaxial ratio and undergo texture adjustment and small crystal dissolution reabsorption. When all crystals in magma system grows up to 2 mm, the pyroxene undergoes cumulation in the Panzhihua layered intrusions. The plagioclase crystallization time scale is 171.23–304.41 years, representing that the crystallization is the more uniform in central part of the melt. The nucleation density continuously increases during the crystallization process of the magma system. The time scale to reach the final maximum crystal nucleation density is 15.28–58.98 years.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)
'/%3e%3cuse xlink:href='%23a' transform='translate(288.889 -214.211)'/%3e%3cuse xlink:href='%23a' transform='translate(108 342.749)'/%3e%3cuse xlink:href='%23a' transform='translate(469.189 342.749)'/%3e%3c/svg%3e)