This paper reports results from detrital zircon U–Pb geochronology, Hf isotopic geochemistry, sandstone modal analysis, and palaeocurrent analysis of the early Mesozoic strata within the Ningwu basin, China, with the aims of constraining the depositional ages and sedimentary provenances and shedding new light on the Mesozoic tectonic evolution of the northcentral North China Craton (NCC). The zircons from early Mesozoic sandstones are characterized by three major populations: Phanerozoic (late Palaeozoic and early Mesozoic), late Palaeoproterozoic (with a peak at approximately 1.8 Ga), and Neoarchaean (with a peak at approximately 2.5 Ga). Notably, three Phanerozoic zircons in the Early Triassic Liujiagou Formation were found to have positive ε_Hf(t) values and characteristics typical of zircons from the Central Asian Orogenic Belt (CAOB). Therefore, the CAOB began to represent the provenance of sediment in the sedimentary basins in the northern NCC no later than the Early Triassic (261 Ma), implying that the final amalgamation of the NCC and CAOB occurred before the Early Triassic. The U–Pb geochronologic and Hf isotopic results show that the Lower Middle Triassic sediments were mainly sourced from the Yinshan–Yanshan Orogenic Belt (YYOB), and that a sudden change in provenances occurred, shifting from a mixed YYOB and CAOB source in the Middle Jurassic to a primarily YYOB source in the Late Jurassic. The results of the sandstone modal analysis suggest that the majority of the samples from the Lower Middle Jurassic rocks were derived from either Continental Block or Recycled Orogen sources, whereas all the samples from the Upper Jurassic rocks were derived from Mixed sources. The change in source might be ascribed to the southward subduction and closure of the Okhotsk Ocean and the resulting intense uplift of the YYOB during the Late Jurassic. This uplift likely represents the start of the Yanshan Orogeny.

The low-grade bauxite in southern Shanxi Province, China is enriched in multiple critical metal elements, including Li, Ga, V, Se, and rare earth elements (REEs), which have reached the standard of comprehensive utilization as independent deposits or associated resources. Even more importantly, identifying the modes of occurrence of these critical elements is essential for designing technologies to extract critical metals from bauxite ores. This study used a combination of direct (X-ray diffraction, scanning electron microscopy–energy dispersive X-ray spectroscopy, and micro-X-ray fluorescence spectrometer), and indirect (size sieving method, float-sink experiment, and correlation analysis) methods to effectively reveal the distribution of critical elements in the different identified mineral phases. The results regarding the low-grade bauxite are as follows: Li was mainly hosted in cookeite as an independent mineral; Ga was mainly associated with diaspore; anatase is the main carrier mineral for V; REEs were present in the low-grade bauxite in multiples modes of occurrence, the most common of which were goyazite, and to a lesser extent, florencite; Se primarily occurs in sulfides. This study contributes to the development and utilization of these essential metal resources in bauxite by providing a useful reference.

In order to ascertain the kaolinite crystallinity of Carboniferous Permian coal-measure kaolinite rocks, seven groups of fresh samples were collected from below the ground in the Xiaoyu mine, Datong coalfield. Microscopy, X-ray diffraction (XRD), differential thermal analysis (DTA), infrared (IR) spectroscopy and X-ray fluorescence (XRF) spectrometry methods were applied to the samples. The petrographic analysis results show that the kaolinite rocks are characterized as compact, phaneritic, clastic, sand-bearing, sandy and silty types; the kaolinite content in the Shanxi formation and upper Taiyuan formations was more than 95%, while it was 60–90% in the middle and lower Taiyuan formations. Based on the Hinckley index and the features of XRD, DTA and IR of kaolinites, crystallinity was classified as having three grades: ordered, slightly disordered and disordered. The kaolinites’ SiO₂/Al₂O₃ molar ratio was about 1.9–5.7, with a chemical index of alteration (CIA) of about 95.4–99.5. This research suggests that the kaolinite crystallinity correlates positively to its clay mineral content, purity and particle size, which are also related to the SiO₂/Al₂O₃ molar ratio and CIA. The original sedimentary environment and weathering have a direct influence on kaolinite crystallinity, and the existence of organic matter is conducive to the stable existence of kaolinite. The study results have significance for the extraction and utilization of coal-measure kaolinite and the development of kaolinite crystallography and mineralogy.

Through the stability evaluation of a slope, a landslide geological disaster can be identified, and the safety and risk control of a project can be ensured. This work proposes an improved sparrow search algorithm to optimize the slope safety factor prediction model (ISSA–BP) of a BP neural network, through an improvement in two aspects: introducing dynamic weight factors and reverse learning strategies to realize adaptive searches. The optimal value improves a defect in the traditional model, preventing it from easily falling into the local minimum. First, combined with 352 sets of actual slope data, three machine learning models were used to predict the safety factor of the slope. Then, the accuracy index was used for evaluation. Compared with other models, the MAPE, RMSE, and R² of the ISSA-BP model were 1.64%, 0.0296, and 0.99, respectively, and the error was reduced by 78% compared with the BP neural network, showing better accuracy. Finally, the three models were applied to the slope stability analysis of Tianbao Port in Wenshan Prefecture. The research shows that the predicted value of the ISSA–BP model was the closest to the actual safety factor, which verified the experimental results. The improved ISSA–BP model can effectively predict the safety factor of slopes under different conditions, and it provides a new technology for slope disaster warning and control.