Search Results (357)

In carbon sequestration in saline aquifers, many factors affect multiphase fluid migration and reservoir pressure change. This study developed a high-resolution three-dimensional numerical model to investigate large-scale CO₂ geological storage in the Ordovician carbonate aquifer of the Tarim Basin, China. This study focuses on the quantitative prediction of CO₂ plume migration, multiphase flow interactions between supercritical CO₂ and brine, and formation pressure evolution under coupled injection operations. Injection strategies were compared by constant rate (CR) and variable rate (VR) injection, and two caprock morphology-type selection by placing wells into monocline traps (wells 1/3/5) and anticline traps (wells 2/4) with varying limb dip angles and closure depths. The results demonstrate that both injection speed and caprock morphology strongly control CO₂ trapping evolution and storage security. At the end of the 500-year simulation, the dissolved-CO₂ migration distance followed the order CR > VR, indicating that, under the studied conditions, VR injection most effectively limited the lateral spread of dissolved CO₂ and thereby enhanced dissolved-CO₂ immobilization. In addition, CR and VR injection schedules have a subtle impact on long-term pressure change; Across all cases, formation pressure remained below the caprock breakthrough pressure. CR injection promotes the fastest CO₂ dissolution and pressure dissipation but yields the weakest long-term immobilization, whereas VR injection trades early dissolution rate for more effective plume containment. This result indicates that injection-strategy selection should be matched to dominant site controlled near-term pressure management versus long-term containment and to the trapping behavior imposed by caprock morphology. This study provides a mechanistically grounded optimization framework linking injection-speed control and caprock morphology to the coupled evolution of pressure-buildup safety and long-term CO₂ immobilization, supporting CCUS decision-making in the Tarim Basin. Full article

In the process of oil and gas drilling, the blowout preventer (BOP) serves as the last line of defense before wellhead loss of control, and its sealing reliability is of critical importance. However, under the erosion of high-pressure sand-containing fluids, the sealing components of the BOP are prone to failure, resulting in long-slit-type leakage ports, which seriously threaten well control safety. In response to the current lack of theoretical guidance for emergency plugging process parameters, this paper adopts the coupled computational fluid dynamics and discrete element method (CFD-DEM) to establish a numerical model for the plugging of long-slit-type gaps with particles under blowout conditions. The migration and bridging plugging behaviors of three typical shaped particles, namely spherical, cylindrical, and square, under different sizes, concentrations, and pump injection rates are systematically studied. The results indicate that particle transport within the wellbore can be divided into an initial transport stage dominated by jet diffusion and a plugging-structure formation stage dominated by bridging and particle accumulation. When the particle size exceeds the slit width, cylindrical particles exhibit comparatively better plugging performance under the conditions considered in this study. For a long-slit leakage channel with a width of 5 mm, the combination of cylindrical particles with an equivalent diameter of 6 mm, a particle volume concentration of 20%, and a pumping rate of 2.4 m³/min demonstrated relatively favorable overall plugging performance. The particle concentration mainly affects the bridging time, and the bridging time tends to stabilize when the concentration reaches 20%. The higher the pump injection rate, the earlier the particles reach the gap opening, but it has little impact on the final plugging effect. This study provides a scientific basis for the optimization of emergency plugging process parameters after BOP sealing failure, filling the gap in the research on the plugging mechanism of equipment leakage under blowout conditions. Full article

This work examines the machining responses of dry turning in ultrasonic-assisted stir-squeeze cast A356 hybrid nanocomposites reinforced with zirconia (ZrO₂) and graphene oxide (GO). Accordingly, flank wear (VBc) ranged from 0.061 to 0.238 mm, influenced by abrasion, adhesion, built-up edge (BUE) formation, and diffusion mechanisms. Cutting speed had the most significant effect on flank wear (65.65%), followed by depth of cut (18.2%) and feed rate (11.13%), supported by a well-fitted regression model (R² = 0.987; p < 0.05). Surface roughness (Ra) ranged from 1.733 to 7.012 μm, with cutting speed, feed rate, and depth of cut contributing 70.42%, 15.43%, and 9.56%, respectively. The cutting temperature was limited to 127 °C, primarily influenced by cutting speed (60.68%), whereas cutting power varied between 0.353 and 0.644 kW, mainly governed by cutting speed (68.71%) and depth of cut (25.92%). The chip morphology showed a segmented sawtooth pattern due to cyclic fracture initiation during material removal. Multi-criteria optimization using complex proportional assessment (COPRAS) identified v = 90 m/min, f = 0.06 mm/rev, and d = 0.1 mm as the optimal parameters, yielding a tool life of 22.6 min and a machining cost of INR 58.69 per item. This research is further focused on the implementation of different cooling lubrication techniques utilizing environmentally friendly cutting fluids, including Minimum-Quantity Lubrication and nano-MQL, among other types of environments. Full article

In gas-condensate reservoirs, the phase behavior of reservoir fluids is inherently dynamic during pressure depletion. When the rate of external pressure decline exceeds the intrinsic relaxation rate governing phase equilibrium, the system deviates from thermodynamic equilibrium and exhibits pronounced non-equilibrium effects. These transient behaviors significantly influence fluid properties; meanwhile, conventional equilibrium models neglect phase transition lag, resulting in inaccurate phase behavior and biased production predictions. In this study, a non-equilibrium dynamic phase transition model is developed to quantitatively couple the pressure depletion rate with the relaxation kinetics of the system. This model, established based on controlled non-equilibrium phase transition experiments performed on the condensate-gas fluid investigated in this work, provides an analytical framework for describing the temporal evolution of phase behavior under dynamic conditions. Model validation through integrated experimental measurements and numerical simulations shows good agreement between calculated and measured results for the studied condensate-gas system, with average relative errors below 5%. Results reveal that accelerated pressure depletion strengthens non-equilibrium effects. At a rate of 15 MPa/h, the relative volume and retrograde condensate saturation decrease by 9.09% and 5.38%, respectively, while condensate recovery improves by 13.85%. Moreover, the characteristic relaxation time toward equilibrium exhibits a strong dependence on the depletion rate, increasing as the depletion rate rises. This work provides an experimentally constrained analytical framework for describing rate-dependent non-equilibrium phase behavior during pressure depletion and for interpreting its impact on condensate recovery in the specific condensate-gas system studied. Although the governing framework may be transferable to other rate-sensitive hydrocarbon systems after fluid-specific recalibration, the parameterized analytical model and validation presented in this study are limited to the investigated condensate-gas fluid, and its applicability to other hydrocarbon fluid types remains to be evaluated in future studies. Full article

This study analyzes and explores the influence of multiple physical mechanisms—namely the influences of heat and mass transfer, thermal radiation, and magnetic field effects on the peristaltic transport of a Rabinowitsch-type non-Newtonian fluid within an inclined channel. To accurately represent the intricate behavior of the fluid under these coupled physical phenomena, a nonlinear model was formulated that integrates thermal, magnetic, and radiative forces into its framework. The given coupled differential equations are transformed into ordinary differential equations (ODEs). Using assumptions of long-wavelength and low-Reynolds-number approximations, the governing equations were significantly simplified. The resulting set of equations was solved analytically using Mathematica, subject to appropriate boundary conditions for velocity, temperature, and concentration. Graphs for velocity, temperature and concentration are illustrated. Thermal radiation was incorporated into the energy equation via the Rosseland approximation, thereby enabling a more accurate characterization of heat transport within the system. Moreover, the rate of heat and mass transfer for different variables was also examined. These findings are essential for the progression of advanced fluid transport systems in biomedical engineering, chemical processing, and energy generation, improving the design and management of non-Newtonian fluid dynamics. Full article

To elucidate the solute sources, migration and enrichment mechanisms of water bodies in the endorheic lake region of the Qiangtang Plateau on the Tibetan Plateau and clarify the hydrogeochemical cycling patterns in alpine arid environments, this study focuses on two core scientific objectives: quantitative identification of the multi-source contributions of aquatic solutes, and revelation of the key processes governing the enrichment of strategic elements including lithium (Li) and boron (B). To achieve these goals, we conducted systematic hydrogeological field investigations and collected 28 multi-type water samples, covering springs, rivers, thermal springs, freshwater lakes, salt lake brines, atmospheric precipitation, and glacial meltwater. The physicochemical properties, major ions, and trace elements of all samples were comprehensively analyzed. On this basis, the hydrogeochemical characteristics, evolutionary processes, and solute origins of regional waters were systematically explored. Combined with PHREEQC numerical simulation, principal component analysis (PCA), and Pearson correlation analysis, the dominant controlling factors of water geochemistry were quantified, and a conceptual hydrogeochemical evolution model was established. The results reveal a clear hydrogeochemical evolutionary gradient across the study area: water bodies evolve from low-salinity HCO₃-Ca recharge end-members and transitional HCO₃·SO₄-Ca(Mg) type water to highly mineralized Cl-Na (SO₄·Cl-Na) salt lake brines, accompanied by synchronous enrichment of Li, B, arsenic (As), and other characteristic elements. Solute accumulation in regional waters is governed by the ternary coupling effects of evaporative concentration, rock weathering and leaching, and deep geothermal fluid input, while cation exchange and mineral dissolution–precipitation reactions further modulate ionic composition and ratios. Elements including As, Li, B, and chloride (Cl⁻) exhibit conservative migration behaviors in non-hydrothermal waters, whereas thermal springs possess unique geochemical signatures driven by deep fluid recharge. PCA results indicate that evaporative concentration serves as the primary controlling factor with a contribution rate of 55.39%; rock weathering provides the basic solute load (17.09%); and the coupled processes of deep fluid mixing and carbonate precipitation regulate elemental fractionation (14.21%). These findings systematically clarify the hydrogeochemical evolution laws and multi-source coupling mechanisms of inland lake waters in the Qiangtang Plateau. Furthermore, this study establishes a conceptual framework of “multi-source recharge–water–rock interaction–evaporative concentration”, advances the understanding of alpine hydrological cycling under climate change, and provides a solid scientific foundation for hydrological cycle research and green exploration of strategic mineral resources in endorheic salt lake regions. Full article

Tool wear in CNC milling increases friction and torque demand at the tool-workpiece interface, which is reflected in spindle motor current. This study develops a non-intrusive tool wear condition classification method using spindle motor current monitoring during practical CNC milling of commercial medium-carbon steel workpieces (JIS S50C/AISI SAE 1050-equivalent; as-received and non-heat-treated; nominal laboratory hardness approximately 4.3 HRC). Experiments were performed on a Tongtai MDV-508 vertical machining center at fixed cutting conditions (3000 rpm spindle speed, 2 mm axial depth of cut, 5 mm cutting width, and 300 mm/min feed rate) using eight TiAlN-coated fine-grain WC–Co solid carbide end mills (10 mm diameter, four flutes; nominal Co binder approximately 10 wt%). An oil-based HS Highstart/HS-SSHS-BH10 cutting fluid was applied through the machine external coolant nozzle in flood mode at an estimated nominal flow rate of approximately 3 L/min and near-room coolant temperature (25 ± 2 °C), and was used as supplied without dilution. A clamp-type AC current sensor was installed on one phase line supplying the spindle motor, and current was acquired using an NI-9221 module at 20 kHz. Cutting intervals were isolated by envelope-based segmentation, concatenated, and divided into 1 s windows (0.5 s overlap) for feature extraction. Three feature sets were evaluated: time-domain statistics, frequency-domain statistics, and an FFT→PCA hybrid representation. Tool states (New, Mid-life, Old) were labeled using post-process surface roughness Ra thresholds supported by microscope observation. The PCA transformation was fitted only on training data and then applied to the held-out test data. A logistic regression classifier achieved 97.44% test accuracy (152/156 windows; 95% Wilson CI: 93.59–99.00%) with the PCA-hybrid features, outperforming time-domain (89.74%) and frequency-domain (94.87%) models. The results support spindle current monitoring as a low-cost approach for quality-aligned tool condition monitoring, while the external validity remains limited to the tested machine, material, tool, coolant, and cutting-parameter combination. Full article

Z- and U-type parallel pipe network configurations are widely used in engineering applications such as solar collectors, fuel cells, microchannels, spargers, and irrigation systems. Although the Z configuration is more commonly employed, the U configuration may provide advantages under specific operating conditions. This study presents a comparative analysis of the two configurations in terms of flowdistribution uniformity and pressure drop. A three-dimensional computational fluid dynamics (CFD) model was developed to simulate realistic solar collector conditions, including both fluid and solid domains together with detailed inlet and outlet junctions. The system consists of manifolds and headers with a diameter of 20 mm and a length of 1150 mm, connected to ten parallel tubes of 7 mm diameter and 1780 mm length. The analysis was conducted over a wide range of inlet Reynolds numbers (Re_D = 100–5000) to represent diverse practical operating conditions. The CFD model was validated against experimental data from the literature and showed good agreement. Flowdistribution uniformity was evaluated using two quantitative indicators. The results show that flow maldistribution increases with Reynolds number in both configurations; however, the U configuration exhibits significantly improved flow uniformity at higher Reynolds numbers. In addition, both configurations exhibited comparable pressure drop characteristics over the investigated operating range. The findings suggest that the U configuration is better suited to high-flow-rate applications that require improved hydraulic and thermal uniformity, while the Z configuration remains effective at lower Reynolds numbers. Full article

The present Part I of the comprehensive study is dedicated to establishing the fundamental mathematical and experimental apparatus required for the multi-criteria optimization of the geometric parameters of an innovative three-rotor hydraulic pump with bilateral lantern meshing, subjected to the actual volumetric flow rate $Q$ and the volumetric efficiency ${\eta }_v$. A complex approach integrating similarity theory, dimensional analysis, and mathematical modeling is employed to define and refine the two objective functions subject to optimization. Based on the area of geometric existence of the gearing and additionally imposed geometric and operational constraints, the exact domain for seeking the optima of $Q$ and ${\eta }_v$ is defined. Based on the statistical processing of experimental data, empirical dependencies of the objective functions are derived, accounting for the influence of the pump’s geometric parameters, the operational conditions and the physical properties of the fluid. The criterion equation of the volumetric efficiency, approximated using all experimental data, was obtained with a very high coefficient of determination $R^2=0.9898$. The rest of the study, related to parameter optimization, is contained in Part II. In it, through numerical investigation and analytical proof, the universal optimal parametric values of the dimensionless geometric coefficients (the relative lantern radius $r_{c,opt}^{*}$ and the shortening coefficient ${\lambda }_{opt}$) are identified to achieve maximum flow rate and volumetric efficiency. Furthermore, in Part II, a multi-criteria Pareto optimization (MINLP) is conducted to resolve the engineering conflict regarding the number of teeth $z$, and a direct simple algebraic dependency $z=f\left(p,n\right)$. The generalized results from both parts provide a methodological toolkit and recommendations for the optimal selection of the geometric parameters in the design of pumps of this type with respect to the actual flow rate and volumetric efficiency, in accordance with the operating conditions and regimes. Full article

Background: This study aimed to evaluate the association between comorbidity and hospital admission, hospital length of stay (LOS), and in-hospital mortality among adult trauma patients across the injury severity spectrum in South Korea, and to assess whether these associations vary according to injury severity. Methods: We conducted a retrospective cohort study using the national Community-Based Severe Trauma Survey (2019–2023). Adult patients (≥18 years) with trauma were included after excluding records with missing key exposure or outcome variables. Comorbidity was defined using the ICD-10–based Elixhauser comorbidity framework. In addition to a binary classification (any vs. none), comorbidity burden was categorized into 0, 1, 2, and ≥3 conditions to evaluate dose–response relationships. The primary outcomes were hospital admission, LOS, and in-hospital mortality. Multivariable logistic regression models were used for admission and mortality, and regression models were applied for LOS, adjusting for demographic characteristics, injury mechanism, physiologic status, and system-level factors. Effect modification by injury severity was assessed using interaction terms and ISS-stratified analyses. Results: Among 49,259 patients, 32,999 (67.0%) had at least one comorbidity. Patients with comorbidities were older, had higher injury severity, and showed higher admission rates, longer LOS, and higher in-hospital mortality compared with those without comorbidities. After adjustment, comorbidity remained independently associated with increased odds of admission, prolonged LOS, and in-hospital mortality. A dose–response relationship was observed, with increasing comorbidity burden associated with progressively worse outcomes (p for trend < 0.001). In addition, substantial heterogeneity was identified across individual comorbidities, with conditions such as metastatic cancer, liver disease, coagulopathy, renal disease, and fluid and electrolyte disorders showing stronger associations with adverse outcomes. The magnitude of these associations varied across ISS strata, indicating injury severity-dependent effects. Conclusions: In this nationwide cohort, comorbidity burden and type were important determinants of acute-care utilization and in-hospital mortality among trauma patients. Incorporating comorbidity information into early risk stratification may improve prognostic accuracy and support more efficient resource allocation and clinical decision-making across the trauma care continuum. Full article

Cerebrospinal fluid (CSF) oligoclonal band (OCB) analysis remains central to the diagnostic evaluation of neuroinflammatory diseases of the central nervous system (CNS), as it reflects intrathecal immunoglobulin synthesis. However, its reliance on lumbar puncture limits its applicability for screening and repeated longitudinal assessment. Serum metabolomics offers a minimally invasive strategy to explore peripheral biochemical correlates of central immune activity. Building on previous binary OCB comparisons, the present study extends serum metabolomic analysis to encompass all five classical OCB patterns, thereby capturing a broader immunological spectrum. A total of 92 adults undergoing diagnostic evaluation for suspected CNS inflammatory disorders were retrospectively stratified according to OCB type (Types 1–5). Serum samples were analysed using targeted ¹H-NMR spectroscopy on a Bruker Avance Neo 600 MHz platform and processed using Bruker’s IVDr pipeline. Group-wise differences were assessed using non-parametric statistical testing with false discovery rate (FDR) correction, complemented by effect size estimation, exploratory multivariate analyses, and Receiver Operating Characteristic (ROC) modelling. Distributional characteristics were further examined using boxplots and violin plots. Across analytical approaches, several metabolites—most prominently leucine, 2-oxoglutaric acid, histidine, threonine, and glycerol—exhibited nominal variation and moderate effect sizes across OCB patterns. Rather than discrete metabolic separation, these metabolites demonstrated graded shifts in central tendency accompanied by substantial overlap between groups. Unsupervised principal component analysis did not reveal robust clustering, while supervised multivariate models highlighted amino acid- and tricarboxylic acid cycle-related metabolites as contributors to partial differentiation. Post hoc power analysis indicated limited sensitivity to detect small-to-moderate effects under multiple-testing correction, supporting an exploratory interpretation of the findings. Taken together, this first targeted serum ¹H-NMR metabolomic evaluation spanning all classical OCB patterns suggests that peripheral metabolic profiles may reflect graded immunometabolic variation associated with intrathecal immune activity. While not intended for diagnostic classification, these findings provide a spectrum-based framework for integrating serum metabolomics with OCB phenotyping and identify candidate metabolites for future prospectively powered and clinically characterised studies. Full article

It is well known that gas sensor responses are affected by the presence of humidity in the analyzed gas. This is particularly true when dealing with biological fluid samples, whose high moisture content interferes with the adsorption of the trace volatile organic compounds (VOCs) on the sensors’ active layer. To address this challenge, this study focuses on designing and testing a novel sampling system for the dehumidification of biological fluid headspace to be characterized by an electronic nose (e-Nose). Such a system, based on the use of disposable polymeric sampling bags purged with dry air, exploits the polymers’ permeability to water vapor to reduce sample humidity. Tested materials included Nalophan^TM (20 μm), high-density polyethylene (HDPE, 8, 9, 10 and 11 μm), low-density polyethylene (LDPE, 12 and 50 μm), and biodegradable polyester (Bio-PS, 15 μm). First, dehumidification performance was characterized as a function of dry air flow rate and film type. A purge of 1 L/min accelerated the sample humidity removal compared to passive storage of bags from >2 h to <1 h (from 80% to 20% RH). Second, a mass-balance model was applied to dedicated experiments to decouple water losses due to diffusion and adsorption, showing that diffusion through the polymer wall dominates, while adsorption occurs in the early stages of conditioning. Third, because these materials are not selectively permeable to water, potential loss of water-soluble VOCs during dehumidification was investigated. Pooled urine headspace samples—both raw and spiked with a metabolite mix of VOCs—were dried using each material and analyzed using a photo-ionization detector (PID) and an e-Nose. Results were compared against a Nafion^TM dryer. Comparison was based on the e-Nose’s ability to discriminate between pooled vs. spiked samples and reveal real-life metabolomic changes. Nalophan^TM bags and Nafion^TM dryer provided the highest VOC fingerprint to support discrimination by the e-Nose, while Bio-PS provided the fastest sample dehumidification. The proposed bag-based system offers a cost-effective, disposable, and contamination-free solution to humidity interference in e-Noses. Full article

In response to the technical bottleneck of the Venlo greenhouse’s inability to achieve year-round production due to the high temperature and humidity in the summer in South China, this study took an existing Venlo-type greenhouse in Guangzhou as the research object and constructed a three-dimensional computational fluid dynamics (CFD) model of the greenhouse by comprehensively considering key factors such as solar radiation, thermal radiation, and crop canopy resistance. After on-site experiments, it was verified that, except for the top area of the greenhouse, the temperature deviation between the model simulation values and the measured values was less than 2 °C, and the error rate was less than 5%, confirming the model’s accurate representation of the temperature field distribution within the greenhouse. Based on the characteristics of the temperature and humidity fields revealed by the CFD simulation (canopy temperature gradient K = 0.144 °C/m, maximum temperature difference between upper and lower layers 20 °C), an optimized scheme of “wet curtain fan + salt bath dehumidification equipment” for local cooling and dehumidification of the crop canopy was proposed, and a non-uniform air duct layout was designed according to the temperature gradient characteristics. Field experiments showed that after optimization, the daytime temperature of the crop canopy was mostly controlled within 30 °C, the relative humidity was stably maintained below 80%, and the maximum temperature difference along the length of the greenhouse was reduced from 7 °C to 2 °C, effectively solving the problem of poor cooling and dehumidification effects of the traditional system. This scheme enabled the stable operation and year-round production of Venlo-type greenhouses in South China during the summer, providing technical support and engineering reference for greenhouse environmental control in high-humidity areas. Full article

Proppant transport in complex fracture networks strongly influences the effectiveness of volumetric hydraulic fracturing in deep shale reservoirs; however, experimental investigations remain limited by the scale and structural complexity of existing laboratory models. In this study, large-scale physical experiments were conducted using a self-designed fracture system consisting of a main fracture and multi-level tertiary branch fractures to investigate proppant transport and placement behavior under different operational conditions. Twelve experimental cases were performed by varying injection rate, fracturing fluid viscosity, proppant concentration, proppant type, and particle-size pumping sequence. The results show that increasing the injection rate and fluid viscosity improves the proppant transport capacity and promotes proppant migration into tertiary branch fractures, increasing the proppant distribution ratio by 6.58%, while the placement proportion in the main fracture decreases by 15.92%. Increasing the proppant concentration enhances proppant placement in all fracture levels, with the placement ratio of quartz sand increasing by 10–15%, but excessive concentration causes accumulation and bridging near the fracture entrance. Under identical conditions, ceramic proppant exhibits better overall placement performance than quartz sand, with a 22.81% higher placement ratio in the main fracture. In addition, the pumping sequence significantly affects proppant distribution; the large–small–large particle-size sequence achieves the highest placement ratio of 74.52%. These results provide quantitative experimental evidence for optimizing proppant injection strategies and fracturing parameters in deep shale reservoirs. Full article

Deep brines represent important sources of strategic resources such as lithium and potassium, characterized by low exploration costs and high utilization rates. The Triassic strata in the Sichuan Basin contain abundant lithium- and potassium-rich brines, and understanding their origin is essential for exploring similar deposits. This study integrated field sampling and published data to systematically analyze the brines through hydrochemical testing, statistical methods, and water–rock reaction experiments, providing a comprehensive genetic interpretation based on hydrochemical features, element correlations, and characteristic coefficients. The results indicated that the brines are of the Cl–Na type, and both the sodium–chloride and chloride–bromide coefficients are consistent with a marine origin. Evapo-concentration was identified as the main controlling factor for ion enrichment, with subordinate influence from atmospheric precipitation. The common source of Ca²⁺ and Mg²⁺ likely includes the widespread marine carbonate rocks and/or the alteration of Ca–Mg-bearing silicate minerals (e.g., in green bean rocks or detrital layers) during brine–rock interaction. The desulfation coefficient indicated that lithium enrichment depends on a closed reducing environment, while potassium enrichment shows minimal correlation with brine confinement. Leaching experiments confirmed that green bean rocks serve as a key effective source rock for lithium and potassium, with elemental leaching efficiency positively correlated with fluid salinity. Based on these findings, a “dual-recharge” genetic model is proposed: paleo-marine brines undergoing deep circulation and meteoric water infiltrating along tectonic fractures collectively leached lithium and potassium from the green bean rocks, providing abundant lithium and potassium to the deep brines. This study refines the metallogenic mechanism of lithium- and potassium-rich brines in the Triassic Sichuan Basin and provides guidance for regional brine mineral exploration. Full article