Internal Structural Features Research Articles

Constructing High-Performance and Versatile Liquid-Solid Triboelectric Nanogenerator with Inflatable Columnar Units

Abstract The use of water resources for energy generation has become increasingly prevalent, encompassing the conversion of kinetic energy from streams, tides, and waves into renewable electrical power. Water energy sources offer numerous benefits, including widespread availability, stability, and the absence of carbon dioxide and other greenhouse gas emissions, making them a clean and environmentally friendly form of energy. In this work, we develop a droplet-based liquid-solid triboelectric nanogenerator (LS-TENG) using sophisticatedly designed inflatable columnar structures with inner and outer dual-electrode. This device can be utilized to harvest both the internal droplet-rolling mechanical energy and the external droplet-falling mechanical energy, capable of assembling into various structures for versatile applications. The design incorporates a combined structure of both internal and external TENG to optimize output performance via multiple energy harvesting strategies. The internal structure features a dual-electrode columnar-shaped LS-TENG, designed to harvest fluid kinetic energy from water droplet flowing. By leveraging the back-and-forth motion of a small amount of water within the air column, mechanical energy can be collected, achieving a maximum mass power density of 9.02 W/Kg and an energy conversion efficiency of 10.358%. The external component is a droplet-based LS-TENG, which utilizes a double-layer capacitor switch effect elucidated with an equivalent circuit model. Remarkably, without the need for pre-charging, a single droplet can generate over 140 V of high voltage, achieving a maximum power density of 7.35 W·m² and an energy conversion efficiency of 22.058%. The combined LS-TENG with sophisticated inflatable columnar structure can simultaneously collect multiple types of energy in high efficacy, exhibiting great significance in potential applications such as TENG aeration rings, inflatable lifejacket, wind energy harvesting, gas-column TENG tents, and green houses.

Metal nitrides as electrocatalysts in green ammonia synthesis

Green ammonia is assumed to be an important part of the European hydrogen economy and one of the most important substrates of chemical industry. The future development of its manufacturing processes can be related to the electrocatalytic studies yielding in the development of the catalytic materials that would effectively break the nitrogen-nitrogen bond to successfully drive the N2RR—a process of molecular nitrogen electroreduction to ammonia. Molecular nitrogen is characterized with strong triple bond energies (942 kJ/mol) which leading into large dissociation energy of N2 (9,76 eV) and also large energy barrier of the first step of triple bond dissociation 410 kJ/mol (4,25 eV). Those large energies makes reduction to ammonia an extremely difficult task. Metal nitrides of d and f block became in interest due to their activity in ammonia production from molecular nitrogen and hydrogen. Practically all the transition elements occurs in one of the four types of crystalline structures: regular, regular face cantered, hexagonal and hexagonal close packed. The reactions of these metals with nitrogen (or ammonia) typically yields in nitride compounds of an identical type of crystalline structure as the initial metal. Dealing with single metal systems, their ternary counterparts and metal–metal nitride heterostructures, the presented review shows that nitrides are promising groups of electrocatalytic materials. Being property-prone to their internal structural features such as non-stoichiometry and correlated concentration of nitrogen vacancies, metal nitrides are a good candidate for joined investigations spanned between electrochemistry, inorganic chemistry and material engineering.

Probing the inner structure and dynamics of pH-sensitive block copolymer nanoparticles with nitroxide radicals using scattering and EPR techniques

This research emphasizes the crucial role of electron paramagnetic resonance (EPR) spectroscopy in nanoparticle analysis, showcasing its distinctive ability to probe molecular-level details. We demonstrate the synthesis and self-assembly of a new class of pH-responsive amphiphilic diblock copolymers, specifically poly[N-(2-hydroxypropyl)-methacrylamide]-block-poly[2-(diisopropylamino)ethyl methacrylate] (PHPMA-b-PDPA), incorporating 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO) radicals covalently bound to the hydrophilic PHPMA segment. The copolymer synthesis involved a three-step process, combining reversible addition − fragmentation chain transfer (RAFT) polymerization with carbodiimide (DCC) chemistry. TEMPO radical-containing nanoparticles (RNPs) were created using microfluidic (MF) nanoprecipitation, a technique essential for generating uniform nanoparticles with predictable biodistribution and cellular uptake. Adjusting MF protocol parameters allowed fine-tuning of RNP sizes. EPR spectroscopy confirmed the formation of core–shell RNPs, with features aligning closely with those obtained from scattering techniques like dynamic light scattering (DLS), static light scattering (SLS), small-angle X-ray scattering (SAXS), and cryo-transmission electron microscopy (cryo-TEM). EPR spectroscopy emerges as a potent tool for molecular-level analysis of colloidal polymer systems. This study highlights the EPR-spin label method’s efficacy in probing the internal structural features and dynamics of core–shell nanoparticles, especially their response to pH-triggered disassembly. The findings open new avenues for the use of pH-responsive TEMPO-labeled diblock copolymers in controlled drug delivery applications.

A method for the determination of local packing factor distribution of a packed pebble bed by the improved line-based averaging method

The packing factor is an important parameter for describing the internal structural features in pebble beds, which have a significant influence on the heat and mass transfer behavior and the thermo-mechanical properties of the pebble bed. A comprehensive understanding of the packing structure is essential for the design and optimization of the pebble bed and can promote the application of the pebble bed. In this work, an improved line-based averaging method was proposed to calculate the local packing factor or local porosity distribution and validated by comparing the results with those obtained from experimental and numerical studies of cylindrical packed pebble bed. Furthermore, the local packing factor distributions in the angular-radial plane of the cylindrical pebble bed were revealed for the first time. In addition, the line-based averaging method has been applied to reveal the local packing factor distributions in the annular pebble beds, U-shaped pebble beds and hexagonal pebble beds. The main feature of this method is the ability to calculate and plot contour maps of local packing factor or porosity distributions for columnar pebble beds of arbitrary shapes, especially the local packing factor distributions in the cross-sectional plane and the angular-radial plane.

Statistical Exploration of the Salar de Atacama’s: Brine Measurements of the Basin Wells

Abstract In this study, we conduct a statistical analysis using the 4-plot, visibility graph, and horizontal visibility graph methods on brine extraction data from the Salar de Atacama basin in Chile. The 4-plot reveals real trends in the data that could lead model proposals. Conversely, complex networks analysis yields no significant findings, suggesting that the data lacks internal structural features and appears random. This randomness underscores the decision-making processes and highlights areas for potential optimization.

Optimization and thermal characterization of a new liquid-cooled plate with branching channels of fractal geometry

In order to improve the heat transfer effect of the liquid-cooled plate with the traditional straight channel, 24 new liquid-cooled structures were obtained based on the fractal concept by adding 6 geometrically structured branch channels to the traditional straight channel and adding different forms of secondary channels between the branch channels and between the branch channels and the main channel. On the basis of establishing a numerical simulation model and verifying the accuracy of the model, the thermal characteristics of 24 liquid-cooled structures were analysed by computational fluid dynamics (CFD) simulation, and the initial relative optimal liquid-cooled channel structure was obtained by taking the comprehensive thermal performance as the evaluation index. Then, the initial relative optimal channel structure parameters were optimised in steps using NSGA-II and grey relational analysis algorithms. In order to further improve the heat transfer effect of the liquid-cooled plate, the relative optimal model after stepwise optimization was arced. The final results showed a decrease in the average temperature by 0.57 °C (1.6 %), an increase in the heat transfer coefficient by 356 W m−2 k−1 (21.3 %), and a decrease in the pressure drop by 34.55 Pa (50.2 %), as compared with the initial model. This study will provide some reference for the optimisation of the internal structural features of the channel and the improvement of the thermal performance of the liquid-cooled plate.

Deciphering of karst geomorphology and sinkhole (doline) structures using multiple geophysical and geological methods (Trabzon, NE Türkiye)

To date, in Türkiye only a limited number and volume of combined geophysical and geological studies about karst have been performed. In this study, karstification and geomorphological features were examined with geophysical and geological methods together and initial results were obtained for Türkiye. Although the geology of the limestone forming the Şahinkaya Member, which contains Çayırbağı, Çalköy, and Çal Cave, near the Düzköy district of Trabzon/Türkiye province was studied by many researchers to date, there is no geophysical study to determine the internal structural features, groundwater, dolines, and karstic voids. The aim of this study was to identify karst formations and their structural extensions in Şahinkaya Member with geophysical methods. Therefore, three different study locations with a total surface area of approximately 3.2 km2 were examined with electrical resistivity tomography, self-potential, seismic refraction tomography, multichannel analysis of surface waves, and ground penetrating radar. These geophysical applications in limestone helped to identify karst cavities, water-saturated zones and dolines. Finally, the order of priority and efficiency of the five applied geophysical methods was compared, and the stages of the applications were outlined. In addition, the origin of karstification in the area investigated in this study was supported by petrographic, petrophysical and rock mechanic data.

Optical coherence tomography for multicellular tumor spheroid category recognition and drug screening classification via multi-spatial-superficial-parameter and machine learning.

Optical coherence tomography (OCT) is an ideal imaging technique for noninvasive and longitudinal monitoring of multicellular tumor spheroids (MCTS). However, the internal structure features within MCTS from OCT images are still not fully utilized. In this study, we developed cross-statistical, cross-screening, and composite-hyperparameter feature processing methods in conjunction with 12 machine learning models to assess changes within the MCTS internal structure. Our results indicated that the effective features combined with supervised learning models successfully classify OVCAR-8 MCTS culturing with 5,000 and 50,000 cell numbers, MCTS with pancreatic tumor cells (Panc02-H7) culturing with the ratio of 0%, 33%, 50%, and 67% of fibroblasts, and OVCAR-4 MCTS treated by 2-methoxyestradiol, AZD1208, and R-ketorolac with concentrations of 1, 10, and 25 µM. This approach holds promise for obtaining multi-dimensional physiological and functional evaluations for using OCT and MCTS in anticancer studies.

Effect of compaction degree on the topological characteristics of force chain network (FCN) in aggregate blend

Aggregates are the main carrier to resist external loads for asphalt pavement, and the characteristics of force chain network (FCN) in aggregate blend are closely related to the skeleton performance of asphalt mixture. This study analyzed the effect of compaction degree of aggregate blend on the topological characteristics of FCN using discrete element (DEM) and complex network theory. Six types of aggregate blends with different gradations were generated and compacted using DEM software EDEM. The compaction degree was evenly divided into 7 parts from the loose to the compacted states. FCN topology graph (FCNTG) of aggregate blend at each compaction degree was built according to the contact information between aggregates and the definition of complex network. The features of each FCNTG were quantified using the indicators characterizing complex network (including degree, vertex strength, clustering coefficient, and path length). The effect of compaction degree on the characteristics of FCN was analyzed. The results showed that complex network theory is a feasible method for investigating aggregate blend FCN. Each topological feature indicator in complex network method can be used to analyze the internal structural features of aggregate blend. With increasing compaction degree, the average degree and the average vertex strength of aggregate blend FCN and different size particles increase gradually, the clustering performance of particles becomes better gradually, and the average path length of FCN decreases gradually. There is a good linear relationship between the compaction degree and each topology indicator except the vertex strength. The compaction can reduce the dispersion degree of the contact forces between particles in aggregate blend and make it more uniform. It can also shorten the path length between two particles, which is important to improve the efficiency of transferring the external load.

Skin dark spot mapping and evaluation of brightening product efficacy using Line-field Confocal Optical Coherence Tomography (LC-OCT).

Facial dark spots remain a significant challenge for the cosmetic industry, in terms of providing effective treatment. Using Line-field Confocal Optical Coherence Tomography (LC-OCT), we investigated the internal structural features of photo-aging spot areas and evaluated the efficacy of a skin-brightening cosmetic product. Twenty-six Asian female volunteers, aged between 29 and 65 years, applied a cosmetic product on their entire face twice a day for 2 months. LC-OCT was used to evaluate the dermal-epidermal junction (DEJ) undulation and the volume density of melanin in the epidermis at D0 and D56. Skin brightening and redness were also assessed by photography (SkinCam). Using LC-OCT technology, various microscopic dark spot morphologies, spanning from minimally deformed DEJ to complex DEJ patterns, were identified. Dark spots characterized by slight deformities in the DEJ were predominantly observed in the youngest age group, while older volunteers displayed a wavier pattern. Furthermore, a total of 44 spots were monitored to evaluate the brightening product efficacy. A statistically significant reduction in melanin volumetric density of 7.3% in the spots and 12.3% in their surrounding area was observed after 56 days of product application. In line with these results, an analysis of color parameters using SkinCam reveals a significant increase in brightening and decrease in redness in both pigmented spots and the surrounding skin following application. LC-OCT proves to be a valuable tool for in-depth dark spots characterization and assessment of skin brightening products, enabling various applications in the field of dermatological sciences.

Optoelectronic Properties of Cold Plasma-Deposited, Oxidized Sn-C Thin Films.

We report on investigating the structural and electronic properties of semiconducting and insulating layers produced in a process resembling percolation in a unique cold plasma fabrication method (plasma-enhanced chemical vapor deposition-PECVD). Amorphous carbon-tin films (Sn-C) produced from tetramethyl tin (TMT) with an acoustic-frequency glow discharge in a three-electrode reactor were investigated. The layers, after air exposure, oxidized to SnO2/Sn-C. Depending on the coupling capacitance applied to the plasma reactor, the films could be obtained in the form of an amorphous semiconductor or an amorphous insulator. We assume that the semiconductor consists of an internal network of channels auto-organized during deposition. The insulator does not demonstrate any internal structure features. An investigation on conductive filaments creating low-dimensional (LD) nanojunctions in the semiconductor and the location of energetic levels in the insulator was performed. The main parameters of the electronic band structure of the insulating film, such as the transport gap EG (5.2 eV), optical gap Eopt (3.1 eV), electron affinity Χ (2.1 eV), and ionization potential J (7.3 eV), were determined. We have demonstrated a simple approach for developing a catalyst candidate consisting of amorphous semiconductor-insulator nanojunctions for (photo)catalytic hydrogen evolution or CO2 reduction.

Rapid Determination of Meteorolite Composition Based on X-ray Phase Contrast Imaging-Assisted Raman Spectroscopy

Returning extraterrestrial samples to Earth has become essential for future deep space exploration. Achieving a comprehensive evaluation of the physical and chemical properties of samples with minimal damage is key to analyzing extraterrestrial samples in the future, as well as to the future sampling and returning of heterogeneous solid samples. This article aims to reconstruct the three-dimensional internal structure of high-contrast objects, select sections of interest through internal structure and detail features, and then analyze the physical and chemical properties of the samples based on laser spectroscopy technology. This paper proposes a strategy based on Raman mapping and X-ray phase-contrast imaging technology to reconstruct the three-dimensional internal structure of a heterogeneous solid sample and detect the substance composition of the region of interest. This study takes meteorite samples as an example and uses X-ray phase-contrast imaging technology to distinguish and reconstruct the spatial distribution of different components in the meteorite, providing a three-dimensional visualization reference with a high spatial resolution for the spatial positioning of the region of interest. Raman spectroscopy, in combination with LIBS, was used to further identify the meteorite as pallasite and to achieve the spectral image fusion of high spatial and high spectral resolutions. The experimental results show that the unknown meteorite’s three-dimensional structure and its components’ spatial distribution can be evaluated based on Raman mapping combined with X-ray phase-contrast imaging technology. This article provides a highly valuable analytical strategy by which to analyze samples returned from deep space exploration.

Green synthesis of a mesoporous hyper-cross-linked polyamide/polyamine 3D network through Michael addition for the treatment of heavy metals and organic dyes contaminated wastewater

Environmental pollution is the greatest challenge of the modern age due to unprecedented industrialization and urbanization that has led to the contamination of water resources with a wide range of pollutants. The release of untreated industrial and municipal wastewater to water bodies further intensifies the problem. The presence of heavy metals and organic contaminants in water poses significant threats to humans, aquatic life, and the environment. Adsorption is one of the famous water treatment technologies due to its simplicity, low cost, efficiency, and minimal secondary pollution. The selection or synthesis of an effective adsorbent is key to the success of the adsorptive removal of pollutants. In this work, we synthesized an adsorbent consisting of a mesoporous hyper-cross-linked polyamide/polyamine 3D network through a single-step Michael addition reaction. The adsorbent was characterized by FTIR, PXRD, TGA, SEM, and TEM to investigate its functional moieties, material nature, thermal, morphological, and internal structural features, respectively. Due to its mesoporous structure, presence of functional groups, and 3D hyper-cross-linked network, it efficiently removed heavy metals (Cd, Cr, and Pb) from aqueous media. The effect of various parameters such as sample pH, adsorbent dosage, contact time, and adsorbate concentrations was thoroughly investigated. The experimental data were analyzed by a variety of isotherm models wherein Langmuir was found to be the best fit for explaining the adsorption of all the metals. The adsorption kinetics was best explained by the pseudo-second-order model. The maximum adsorption capacities for Cd, Cr, and Pb were 60.98 mg g−1, 119 mg g−1, and 9.302 mg g−1, respectively. The synthesized adsorbent was also tested for removal of organic dyes, and it showed selective and fast removal of Eriochrome Black T. Polymeric resins can be promising materials for adsorptive remediation of pollutants in aqueous media.

ZnO–TiO2 Nanoparticles Coated by the Dioxomolybdenum (VI) bis-Schiff Base Complex for Catalytic Oxidation of Sulfides

The oxygenation processes for the organic compounds have great applications in fine organic fabrications. To speed up progress in the industrialization of such oxidation systems, a monometallic dioxomolybdenum (VI) bis-Schiff base complex (MoO2L2) was synthesized through coordination of easily accessible 4-hydroxyiminophenol ligand (HL) with cis-MoO22+ ion in an octahedral geometry. The structural conformation of MoO2L2 and its coordinated ligand (HL) was determined using modern spectrophotometric tools. A heterogeneous catalyst (MoO2L2@ZnO–TiO2) was successfully prepared by immobilization of MoO2L2 on the surface of ZnO–TiO2 nanostructured particles through the deprotonation of 4-OH group in its coordinated ligand. Various analytical techniques were used to examine the surface morphology and internal structure features of ZnO–TiO2 and MoO2L2@ZnO–TiO2 nanocomposites. To study the catalytic efficiency of MoO2L2 and MoO2L2@ZnO–TiO2-based catalysts, they were employed in the oxygenation process of Ph2S (diphenyl sulfide) and MePhS (methylphenyl sulfide) using the most environmentally friendly oxidant (an aqueous H2O2) under an aerobic environment. A high degree of selectivity was observed for the productivity of diphenyl sulfoxide (Ph2SO) and methylphenyl sulfoxide (MePhSO), with some contamination of overoxidation side products (Ph2SO2 and MePhSO2). The catalytic oxidative ability was not observably superior for the heterogeneous coated catalyst by ZnO–TiO2 over its homogeneous one (MoO2L2) due to the less redox activity of ZnO and TiO2 nanoparticles in the catalytic cycles for the oxygen-transfer mechanism. Both catalysts were successfully recycled, in which the homogeneous catalyst sustained its high catalytic potential for up to three cycles, while the heterogeneous catalyst was able to be reused up to six times.

A Machine-learning Approach to Assessing the Presence of Substructure in Quasar-host Galaxies Using the Hyper Suprime-cam Subaru Strategic Program

The conditions under which galactic nuclear regions become active are largely unknown, although it has been hypothesized that secular processes related to galaxy morphology could play a significant role. We investigate this question using optical i-band images of 3096 SDSS quasars and galaxies at 0.3 < z < 0.6 from the Hyper Suprime-Cam Subaru Strategic Program, which possesses a unique combination of area, depth, and resolution, allowing the use of residual images, after removal of the quasar and smooth galaxy model, to investigate internal structural features. We employ a variational auto-encoder, which is a generative model that acts as a form of dimensionality reduction. We analyze the lower-dimensional latent space in search of features that correlate with nuclear activity. We find that the latent space does separate images based on the presence of nuclear activity, which appears to be associated with more pronounced components (i.e., arcs, rings, and bars) as compared to a matched control sample of inactive galaxies. These results suggest the importance of secular processes and possibly mergers (by their remnant features) in activating or sustaining black hole growth. Our study highlights the breadth of information available in ground-based imaging taken under optimal seeing conditions and having an accurate characterization of the point-spread function (PSF), thus demonstrating future science to come from the Rubin Observatory.

An Analysis of the Categories and Structures of Expertise for Students’ Cognitive States

Knowledge networks play an important role in the process of knowledge acquisition and sharing by students. An analysis of their complex structural features is required for the connectivity between students and knowledge. Existing research lacks insight into the internal structural features of knowledge networks constructed from expertise. There is also a lack of effective methods for constructing personalised knowledge networks for students' cognitive states. This paper analyses the categories and structures of expertise for students' cognitive states, and presents in detail a grey prediction algorithm to identify students' cognitive states. Then, the paper presents a typological description of the knowledge nodes in the expertise network for students' cognitive states, and analyses the knowledge network structure from the perspectives of paths and statistical properties. After that, the paper gives a method for analysing the knowledge flow of the expertise network. The experimental results validate the effectiveness of the proposed method.

Assessment of the formation and volume of tax expenditures in the federal budget

This article analyzes approaches to the formation of tax expenditures in the federal budget, their volumes, and their interconnectedness with state programs and national development goals. The concept of tax expenditures is based on the premise that tax benefits and preferences should have a greater effect than direct methods of budget financing, such as subsidies. Tax expenditures in the federal budget are primarily focused on stimulating the oil and gas industry, with a significant amount associated with VAT and income tax. The risks of tax incentives, caused by both foreign policy factors and internal structural features of the economy, are considered. Conclusions are drawn that the risks of federal budget revenue losses are increasing. Simultaneously, the list of expenses eligible for investment tax deductions is expanding, although they can be considered productive tax expenditures since the effect of self-sufficiency in recovering lost budget revenues is expected. The primary direction for improving tax expenditures is proposed to involve enhancing the realism of assessments, increasing transparency, and ensuring the targeted nature of tax expenditures by reflecting them in government programs.

A Review of Cyclodextrin Encapsulation and Intelligent Response for the Release of Curcumin.

To overcome the low water solubility and low bioavailability of curcumin (CUR), multiple delivery strategies have been proposed. Among these, cyclodextrin-based carriers have been widely used for the encapsulation and delivery of CUR. Cyclodextrins (CDs), as natural oligosaccharides, have been well known for their biodegradability, biocompatibility, non-toxicity, and internal hydrophobic and external hydrophilic structural features. This paper summarizes the recently reported CD-based carriers for encapsulating CUR. Particularly, the polymerization properties of CD self-assembly to enhance the encapsulation of CUR are discussed. In addition, the current progress on stimuli-responsive CD carriers for controlled release of CUR is described, which laid an important foundation for the development of CUR-based precision therapy in clinical practice. In conclusion, this review may provide ideas for the future development of a CD-based encapsulant for CUR.

Size effects in the uniaxial compressive properties of 3D printed models of rocks: an experimental investigation

Transparent physical models of real rocks fabricated using three-dimensional (3D) printing technology are used in photoelastic experiments to quantify the evolution of the internal stress and deformation fields of rocks. Therefore, they are rendered as an emerging powerful technique to quantitatively reveal the intrinsic mechanisms of rock failure. The mechanical behavior of natural rocks exhibits a significant size effect; however, limited research has been conducted on whether transparent physical models observe similar size effects. In this study, to make the transparent printed models accurately demonstrate the mechanical behavior of natural rocks and reveal the internal mechanism of the size effect in rock mechanical behavior, the size effect in 3D printed models of fractured and porous rocks under uniaxial compressive loading was investigated. Transparent cylindrical models with different sizes that contained different fractured and porous structures were printed using the fracture and porous characteristics extracted from natural coal and sandstone. The variation in uniaxial compressive strength and elastic modulus of fractured and porous models for increasing model sizes were obtained through uniaxial compression experiments. Finally, the influence of internal discontinuous structural features, such as fractures and pores, on the size effect pertaining to the mechanical behavior of the model was analyzed and elaborated by comparing it with the mechanical properties of the continuous homogeneous model without fractures and pores. The findings provided support and reference to analyze the size effect of rock mechanical behavior and the effect of the internal discontinuous structure using 3D printed transparent models.

Partial Least Squares-Discriminant Analysis of the Major and Trace Elements and their Evolutionary Characteristics from the Jinchuan Ni-Cu-(PGE) Sulfide Deposit, NW China

The world-renowned Jinchuan Cu-Ni-(PGE) sulfide deposit consists of four mainly independent intrusive units from west to east, namely Segments III, I, II-W, and II-E, and the main sulfide types are the disseminated, net-textured, massive, and Cu-rich ores. Due to the similar geochemical characteristics of each segment, there is no convenient method to distinguish them and explain their respective variations. Meanwhile, considering that the division of different types of ores is confusing and their formation is still controversial, direct classification using elemental discrimination maps can facilitate subsequent mining and research. In this paper, we report the new major and trace elements data from the Jinchuan deposit and collect the published data to construct a database of 10 major elements for 434 samples and 33 trace elements for 370 samples, respectively, and analyze the data based on multivariate statistical analysis for the first time. Robust estimation of compositional data (robCompositions) was applied to investigate censored geochemical data, and the input censored data were transformed using the centered log-ratios (clr) to overcome the closure effect on compositional data. Exploratory data analysis (EDA) was used to characterize the spatial distribution and internal structural features of the data. The transformed data were classified by partial least squares-discriminant analysis (PLS-DA) to identify different compositional features for each segment and ore type. The receiver operator characteristic (ROC) curve was used to verify the model results, which showed that the PLS-DA model we constructed was reliable. The main discriminant elements were obtained by PLS-DA of the major and trace elements, and based on these elements, we propose the plot of SiO2 + Al2O3 vs. CaO + Na2O + K2O and Cs + Ce vs. Th + U to discriminate the different segments of the Jinchuan deposit, and the Al2O3 + CaO vs. Fe2O3T + Na2O and Co + Cu vs. Rb + Th + U to discriminate the different ore types. In addition, we predict that there are still considerable metal reserves at the bottom of Segment I.