Chemical Tests Research Articles

Corrosion of Lithium-ion Battery Cylindrical Cell Hardware: Understanding the Mechanisms and Exploring Effective Solutions

We present a detailed examination of Ni corrosion in lithium-ion battery Ni-coated steel cylindrical cell hardware, focusing on LiPF6-based electrolytes contaminated with water. The corrosion potential of the cell hardware is predominantly controlled by the iron component of the cylindrical can which cathodically protects the Ni coating. Despite the presence of cathodic protection, the Ni coating still experiences significant crevice corrosion, as confirmed through chemical aging tests. Mechanistic investigations on pure Ni metal reveal two distinct corrosion pathways depending on the presence or absence of oxygen in the electrolyte. The pathway involving oxygen proves to be more detrimental, as it oxidizes Ni in conjunction with acid, leading to the generation of water and the regeneration of corrosive species. This pathway exhibits corrosion rates two orders of magnitude higher than the alternative pathway. The dissolved Ni species predominantly exist in the +2 oxidation state and forms highly soluble F-rich compounds, comprising a mixture of associated species denoted by the formula Ni(PxOyFz)w. Finally, several suggestions for effectively mitigating Ni corrosion have been proposed, with alloying with chromium being the most effective.

Multiscale Models to Evaluate the Impact of Chemical Compositions and Test Conditions on the Mechanical Properties of Cement Mortar for Tile Adhesive Applications.

This study aims to develop systematic multiscale models to accurately predict the compressive strength of cement mortar for tile adhesive applications, specifically tailored for applications in the construction industry. Drawing on data from 200 cement mortar tests conducted in previous studies, various factors such as cement/water ratios, curing times, cement/sand ratios, and chemical compositions were analyzed through static modeling techniques. The model selection involved utilizing various approaches, including linear regression, pure quadratic, interaction, M5P tree, and artificial neural network models to identify the most influential parameters affecting mortar strength. The analysis considered the water/cement ratio, testing ages, cement/sand ratio, and chemical compositions, such as silicon dioxide, calcium dioxide, iron (III) oxide, aluminum oxide, and the pH value. Evaluation metrics, such as the determination coefficient, mean absolute error, root-mean-square error, objective function, scatter index, and a-20 index, were employed to ensure the accuracy of the compressive strength estimates. Additionally, empirical equations were utilized to predict flexural and tensile strengths based on the compressive strength of the cement mortar for tile adhesive applications.

Quantitative inversion of soil trace elements from spectroscopic effects across multiple crop growth periods

Human health is directly impacted by trace components found in soil, for which hyperspectral remote sensing technology offers a novel way to rapidly assess dynamic soil environmental quality. In most studies, the premise of quantitative inversion on soil elements is that the known target elements will cause growth stress. However, such stress is unusual in non-polluted areas. Consequently, broad-area soil trace element monitoring in non-contaminated areas remains challenging. Spectral inversion of plant material has a longer time window and is more sensitive to elemental changes than soil spectral inversion (bare soil period). In this work, we conducted a wheat pot experiment with concentration gradients of four trace elements (Fe, B, Mo, and Zn), analyzed leaf (jointing stage) and spike (maturity period) samples using spectral measurements and chemical tests, and filtered the characteristic positions and inverse modeling using the spectra of the element-accumulating preference organs in plant canopies. The canopy aggregation sites differed for each element, and both simple linear regression (SLR) and multiple linear regression (MLR) models based on the spectra of canopy aggregation sites achieved high accuracy. The results of this study enable the construction of an inverse model of plant spectra-plant element content-elements in soil, which can serve as a reference for soil monitoring and assessment in typical crop cover areas.

Electrocoagulation process with Fe/Al electrodes to eliminate pollutants from real and synthetic wastewater

This work investigated the effect of a victorious parameter of electrocoagulation (EC) on the removal of turbidity through batch reactor using Fe and Al electrodes. Synthetic (Sol 1, Sol 2) and natural wastewater (Sol 3) with different sodium chloride content were examined under different current densities (CD) and operating time. For the examined solutions conductivity, pH, total suspended solids (TSS) dissolved oxygen (DO) and energy consumption were measured. A novel approach examined the effect of solutions with selected operating parameters on Fe and Al corrosion using chemical and electrochemical tests. Using experimental data collected during the various parameters, a mathematical model of the electrocoagulation process was generated and assessed. FE-SEM images and EDX analyses for Fe and Al electrodes and XRD of coagulant particles, floc, generated by EC were also investigated. According to the findings, the ideal circumstances for the turbidity elimination from the examined solution were found to be as CD = 11 mA/cm2, pH ⁓ 7, and operating time = 20 min. Under these optimal circumstances, Al electrodes showed superior efficacy in removing than Fe electrodes for all examined solutions. The turbidity removal efficiency and the energy consumption were also found to be affected by NaCl content. The turbidity removal efficiencies reached their maximum value of 99 % for sol 3 where NaCl content was 3.45 × 10−1 M and energy consumption was 1.667 kWh/m3 by using Al anode.

Students’ Chemical Literacy Ability of Senior High School in Gowa Regency

This research aims to describe chemical abilities in terms of content knowledge, chemical context, and higher-order learning skills of students on chemical equilibrium. This research is quantitative research with a survey method. The subjects of this research were students in six schools in Gowa Regency. The population in this study were all state high schools in Gowa Regency. The sampling technique is using random sampling after grouping schools based on accreditation. The instruments in this research were a chemical literacy ability test in the form of 20 multiple-choice objective questions. Chemists and chemical education experts carried out instrument validation. Empirical validation was carried out in class XI MIPA. The research results show that chemical literacy abilities in terms of content knowledge, chemical context, and higher-order learning skills are in the medium category.

Efficacy, safety, and response predictors of Astragalus in patients with mild to moderate Alzheimer's disease: A study protocol of an assessor-blind, statistician-blind open-label randomized controlled trial

BackgroundThis pragmatic clinical trial aims to determine the efficacy and safety of add-on Astragalus membranaceus (AM) for cognition and non-cognition in patients with of mild to moderate Alzheimer's disease complicated with orthostatic hypotension in orthostatic hypotension, elucidate the underlying mechanisms, identify related response predictors, and explore effective drug components. MethodsThis is an add-on, assessor-blinded, parallel, pragmatic, randomized controlled trial. At least 66 adults with mild to moderate Alzheimer's disease (AD) and OH aged 50–85 years will be recruited. Participants will be randomized in a 1:1:1 ratio to receive 24 weeks of routine care or add-on low dose AM or add-on high dose AM group. The primary efficacy outcome will be measured by the Alzheimer's Disease Assessment Scale-Cognitive Subscale, Chinese version. Secondary efficacy outcome assessment will include neuropsychological tests, blood pressure, plasma biomarkers, multimodal electroencephalograms, and neuroimaging. Safety outcome measures will include physical examinations, vital signs, electrocardiography, laboratory tests (such as hematologic and blood chemical tests), and adverse event records. Ethics and disseminationThis trial was approved and supervised by Fujian Medical University Union Hospital (2021KJCX040). Independent results, findings will be published in peer-reviewed journals and presented at national and international conferences. Trial registration numberNCT05647473; ClinicalTrials.gov Identifier.

A new approach for identification of dispersivity class of soils by combining physical and chemical tests

The safety and performance of embankment dams after impounding water are highly related to the characteristics of the selected dam material. Impermeability is achieved by using clay soils as the core material in embankment dams. It has been observed that there are many collapsed dams, especially when dispersive soils with very low internal erosion resistance are used in the impermeable zone. For this reason, such soils should be determined at the design stage and not used in the construction of embankment dams. The dispersion mechanism is known to be controlled by clay mineralogy and cations in the pore fluid of soil. The physicochemical behaviour of the clay-water system is crucial to clarify the dispersion mechanism. Physical and chemical tests used for determining the dispersibility potential of soils are extensive and time-consuming methods. An alternative method has been proposed within the scope of this study. Three user-friendly and practical models based on Gene Expression Programming (GEP) were produced using chemical and double hydrometer test results to predict dispersion percentage (D%). In addition, a new classification criteria was proposed to identification of dispersivity class based on pinhole test data. If the dispersion percentage is less than 12% is soil is classified as non-dispersive, the dispersion percentage is between 12% and 30% and greater than 30%, it is defined as intermediate and dispersive, respectively. With this proposed criterion, more consistent and successful results were obtained for the dispersivity class.

A detection method of Saposhnikovia divaricata seed vigor based on near-infrared spectral feature extraction

Saposhnikovia divaricata is an important Chinese herbal medicine, the rapid detection of seed vigor is of great significance and practical value for the breeding selection and cultivation production of Saposhnikovia divaricata varieties. It was difficult to solve the problem of rapid testing technology of Saposhnikovia divaricate seed of the shortcomings of traditional chemical testing methods, such as cumbersome operation, time-consuming, easy to cause seed damage, and so on. In this paper, a rapid method for detecting seed vigor was processed for the Saposhnikovia divaricata based on near-infrared spectral feature extraction. First, 612 sets of near-infrared spectral data were obtained using a Fourier transform near-infrared spectrometer, and randomly divided into a calibration set and prediction set according to the ratio of 3:1. Then, the spectral data were preprocessed by the multivariate scatter correction method (MSC), the successive projection algorithm (SPA) was used to extract the feature wave numbers of spectral data. A total of 5 feature wave numbers were selected from the original 1845 wave numbers, with a streamlining rate of 99.73 %. Finally, a detection method of seed vigor was constructed based on the radial basis function neural network (RBF) with 5 feature wave numbers as input data. A network structure of the model MSC-SPA-RBF is of type 5-48-3, the accuracy of seed vigor detection was 99.0 %, and the detection time was 0.0033 s. The result indicates that the established model is a fast, non-destructive, and accurate method for detecting seed vigor of Saposhnikovia divaricata, which provides a theoretical basis and technical support for the rapid detection of Saposhnikovia divaricata seed vigor.

Optimization Of Carica Fruit Jelly Candy Formula: Study Of Proportions Of Carica Fruit Pure And Bovine Gelatin

Carica is one of the fruits that can be found in the Dieng Plateau, Wonosobo Regency. Carica fruit has a unique taste, distinctive aroma and chewy flesh. It has a sour, bitter and gum taste which can cause itching, so this fruit is only good for consumption if it has been processed first. One example is by processing it into jelly candy. This study aims to: (1) determine the proportions of puree carica and gelatine to produce carica jelly candy products that have a response of elasticity, cohesiveness, carica taste, softness, and maximum preference, yellow color in range, and minimum stickiness; (2) knowing the sensory characteristics of the jelly candy product with the formula recommended by the Design Expert program; (3) determination of the price of rubber between the optimum formula jelly candy product and the control. This study used the RSM (Response Surface Methodology) method with a CCD (Central Composite Design) experimental design consisting of 2 factors and 2 blocks to obtain 14 treatment combinations. The data obtained were analyzed using Design Expert software V.10 and SPSS IBM Statistics V.25 using a 95% T-test. The results of this study were the optimum carica fruit jelly candy formula with the proportion of carica fruit puree 28.85% and gelatine 12.75% with a desirability value of 0.75. Increasing the proportion of pure carica fruit causes an increase in the intensity of carica taste and yellow color. While the addition of gelatin gave an increase in the elasticity, cohesiveness, stickiness and level of preference of the panelists. The results of chemical tests on carica fruit jelly candy with optimum formula and control were the optimum product had higher moisture content, ash content, protein content, and vitamin C than the control product.

Chemical and UV Durability of Hydrophobic and Icephobic Surface Layers on Femtosecond Laser Structured Stainless Steel

Femtosecond laser processing significantly alters the surface structure and chemical composition, impacting its wetting properties. Post-treatments such as immersion in a hydrocarbon liquid (petrol) or storage in a vacuum can significantly reduce ice adhesion, making the surfaces interesting for anti-ice applications. This study investigates their durability against acetone, ethylene glycol, and UV radiation. The laser-structured surfaces were immersed in the respective liquids for up to 48 h. The results indicate limited durability of the superhydrophobic and icephobic layers when submerged in acetone and ethylene glycol, with more favorable results for petrol treatment than vacuum treatment. Similar results were obtained after 100 h of UV exposure, showing a decrease in superhydrophobic properties and an increase in ice adhesion. However, repeated vacuum treatments conducted after the chemical durability tests revealed the potential for partial recovery of the hydrophobic and icephobic properties. XPS analysis was performed throughout the experiments to evaluate changes in surface chemistry resulting from the post-laser treatments and the durability tests.

'What Happened?': Perceptions of Patients with Hypertension of Conflicting Results between Self-Reported Medication Adherence and Chemical Adherence Testing: A Qualitative Study.

To explore the perceptions of outpatients with hypertension regarding the conflicting results between their self-reported medication adherence and chemical adherence testing. An exploratory generic qualitative study design with semi-structured interviews was conducted. Thirteen adult patients being treated with antihypertensives were interviewed. Patients had a negative chemical adherence test for at least one prescribed antihypertensive, while they reported to adhere to their medication. Audio-recorded interviews were thematically analyzed. Six themes emerged: (1) becoming frustrated with medication intake, (2) being uncomfortable with addressing medication nonadherence, (3) feeling ashamed and angry about their nonadherence, (4) feeling falsely accused of nonadherence, (5) experiencing results as a wakeup call and (6) wanting to be heard and listened to. Participants reacted differently to the adherence test results. Two distinct groups were identified among the participants: the first group felt shameful, disappointed, and angry at themselves for being nonadherent; the second group felt falsely accused and rejected the adherence test results. No differences between both groups were found in their reasons for becoming frustrated with medication intake and their behavior after the adherence test results. Patients felt that communication with clinicians is key in the treatment support of patients with hypertension. Clinicians need to consider the reasons for nonadherence and the different responses of patients to the chemical adherence test results in their support to optimize treatment for patients with hypertension.

Restoration of a wet corrosion-resistant composite filament for material extrusion process

PurposeMaterial extrusion (MEX) is one of the most known techniques in the additive manufacturing (AM) sector to produce components with a wide range of polymeric and composite materials. Moisture causes alterations in material properties and for filaments strongly hygroscopic like nylon-based composites this means greater ease of deterioration. Drying the filament to reduce the moisture content may not be sufficient if the humidity is not controlled during printing. The purpose of this study is to achieve the recovery of a commercial nylon-based composite filament by applying process optimization using an open source MEX machine.Design/methodology/approachA statistical approach based on Taguchi’s method allowed to achieve an ultimate tensile strength (UTS). A verification of the geometrical capabilities of the process has been performed according to the standard ISO/ASTM 52902-2019. Chemical tests were also carried out to test the resistance to corrosion in acid and basic solutions.FindingsAn UTS of 71.37 MPa was obtained, significantly higher than the value declared by the filament’s manufacturer (Stratasys Inc., USA). The best configuration of process parameters leads to good geometrical deviations for flat surfaces, in a range of 0.01 and 0.38 for flatness, while cylindrical faces showed more important deviations from the nominal values. The good applicability of the material in corrosive environments has been confirmed.Originality/valueThis study examined the performance restoration potential of a nylon composite filament that was significantly affected by storage conditions. For the filament manufacturer, if the material remains in ambient air for an hour or idle in the machine for more than 24 h, the material may no longer be suitable for printing. The study highlighted that the drying of the filament must not be temporary but constant to guarantee printability, and, by acting on the process parameters, it is possible to obtain better mechanical properties than declared by the manufacturer.

Novel single well chemical tracer test design: shut-in time determination for test feasibility

The well shut-in time (t soak) in a single-well chemical tracer test (SWCTT) after injection of the primary tracer depends on its reactivity under reservoir conditions. In this paper, a novel SWCTT design is proposed to determine the well shut-in time to minimize the risk of loss of test results based on different secondary tracer generation rates considering the oil saturation of the reservoir. The developed method in this paper was approximated to conduct SWCTT in oilfield A in predicting the minimum t soak after ethyl acetate injection for different S or. The paper shows that the field test tracer production curves are consistent with hydrodynamic modeling data at the same t soak. When t soak is reduced according to the model data, the concentration profile of the secondary tracer is in the low detection range, indicating that the test was properly organized when the well shut-in to minimum t soak. Thus, the novel test design showed how the time of all well operations can be optimized and the costs associated with equipment mobilization and service company operations can be reduced.

Identification of 6,9-dihydro-5H-pyrrolo[3,2-h]quinazolines as a new class of F508del-CFTR correctors for the treatment of cystic fibrosis

Although substantial advances have been obtained in the pharmacological treatment of cystic fibrosis (CF) with the approval of Kaftrio, a combination of two correctors (VX-661, VX-445) and one potentiator (VX-770), new modulators are still needed to rescue F508del and other CFTR mutants with trafficking defects. We have previously identified PP compounds based on a tricyclic core as correctors with high efficacy in the rescue of F508del-CFTR on native epithelial cells of CF patients, particularly in combination with class 1 correctors (VX-809, VX-661). Compound PP028 was found as a lead candidate for the high rescue of F508del-CFTR and used for mechanistic insight indicating that PP028 behaves as a class 3 corrector, similarly to VX-445.From the exploration of the chemical space around the hit structure, based on iterative cycles of chemical synthesis and functional testing, the class of 6,9-dihydro-5H-pyrrolo [3,2-h]quinazolines with corrector activity was discovered. Within a series of 38 analogues, two derivatives emerged as promising candidates and used for further insight to assess the mechanism of action. Both compounds, decorated with a benzensulfonylamino group at the pyrimidine moiety, were able to generate a dose-dependent increase in CFTR function, particularly in the presence of VX-809. Half-effective concentrations (EC50) were in the single digit micromolar range and decreased in the presence of VX-809 thus indicating a synergistic interaction with class 1 correctors. Synergy was also observed with corr-4a (class 2 corrector) but not with VX-445 and PP028 (class 3 correctors) indicating that the new compounds behave as class 3 correctors. These results suggest that tricyclic pyrrolo-quinazolines interact with CFTR at a site different from that of VX-809 and represent a novel class of CFTR correctors suitable for combinatorial pharmacological treatments for the basic defect in CF.

Pemanfaatan Tepung Mocaf Dalam Pembuatan Sponge Cake

Sponge cake is a sweet cake snack that is often consumed throughout the world and is made from flour, sugar, eggs, emulsifier, and others. In this research, sponge cake was innovated by using mocaf flour as a substitute for wheat flour. This research aims to determine: 1) the potential of mocaf flour as a substitute for wheat flour in making sponge cake through organoleptic tests; 2) the nutritional content contained in sponge cake made from mocaf flour; and 3) selling price for mocaf flour sponge cake. The research method used in this research was an experimental method which was tested on 30 panelists and then analyzed using a single ANOVA with the SPSS program, testing the nutritional content of mocaf flour sponge cake using chemical tests in the laboratory and to determine the selling price it was analyzed using conventional methods. The results of this research show that: 1) the ratio of mocaf flour and wheat flour 80:20 has a higher average value than the other comparison values, then there is a significant change in color and texture, and there is no significant change in taste, odor, pores, and scale; 2) the nutritional content of the mocaf flour sponge cake based on laboratory tests shows that per 100 grams it has a total of 234.80 kcal calories, 46.15% carbohydrates, 8.11% protein content, 2.05% fat content, 1.62% fiber %, water content 39.88%, and ash content 1.67%; and 3) the selling price for mocaf flour sponge cake products is IDR 4,914.76/50gram.

Innovation of Processed Baronang Fish as One of The Local Food Products in Gebang Village, Pesawaran

Gebang Pesawaran Village is an area that occupies a coastal area and has quite abundant marine products, but the potential for utilization is less than optimal and there is no food made from any of the existing marine products. This research aims to explore the potential of rabbitfish itself and to create local food products that are losng-lasting but still nutritious in Gebang Pesawaran Village. It is also an effort to create a variety of food dishes that do not only depend on one type of ingredient, but also utilize a variety of food ingredients. The product made in this research was serundeng with coconut and rabbitfish as the basic ingredients, which was named Seronang. The method used in this research is qualitative with a descriptive approach. The results of the research show that the baronang fish serundeng product is a new food innovation in Gebang Village. This product has passed food chemical test analysis and has a nutritional value information label to make it easier for consumers to consume the product. From the results of chemical food tests, it is known that the nutritional content contained in baronang fish serundeng products includes air content of 5.4481%, glucose 6.1474%, fat 32.8965%, carbohydrates 31.8109%, protein 23.6970%, and vitamins 8.8597%.

Utilization of marble waste as fine aggregate in the composition of high performance concrete containing mineral additions

This study investigates the effect of adding marble waste as fine aggregate on the properties of high-performance concrete. To achieve this objective, 10%, 20%, 30%, and 40% of marble waste fine aggregate were substituted for ordinary fine aggregate in the composition of high-performance concrete mixtures containing silica fume and ground blast furnace slag. The fresh properties were studied using slump, fresh density and air content tests, while the hardened properties were assessed using compressive and flexural strengths, ultrasonic pulse velocity, water absorption, and chemical acid attack tests. The results obtained revealed that the addition of marble waste fine aggregate significantly improved the properties of high-performance concrete and increased its resistance to chemical acid attacks. The composition-based ground blast furnace slag containing 40% marble waste fine aggregate outperformed all other compositions, increasing compressive strength by 30.98%.

Study on the adsorption mechanism of fluorescent nano-tracer in sandstone core

Chemical tracer testing technology has increasingly become the preferred method for reservoir monitoring in oil fields due to its low cost and high efficiency. Understanding the migration behavior and adsorption mechanisms of chemical tracers in porous media is crucial for designing tracer injection processes and enhancing the accuracy of tracer test interpretation. This study employs an enhanced Stöber sol-gel method to synthesize fluorescent silica nanoparticles. After surface modification with the silane coupling agent γ-(methacryloyloxy) propyltrimethoxysilane (KH570) and doping with two fluorescent dyes, a multicolor fluorescent nano-tracer (PMFN) was synthesized. This study conducted dynamic and equilibrium adsorption experiments to investigate the adsorption behavior of PMFN on sandstone surfaces. To elucidate the adsorption mechanism of PMFN, we fitted the adsorption equilibrium experimental data using the Langmuir, Freundlich, and Temkin isothermal adsorption models. The adsorption kinetics were studied using the Lagergren, Elovich, and pseudo-first-order kinetic models. Additionally, we assessed the influence of ionic strength and particle size on the adsorption of PMFN by calculating the DLVO interaction forces between PMFN and the sandstone surface. The results showed that PMFN adsorption on sandstone primarily occurs in the pre-contact stage and is characterized by monolayer adsorption. When the ionic strength of the solution is 0.001 mol/L, the maximum repulsive energy barrier between PMFN and the sandstone surface hinders adsorption.

Screening (ant)agonistic activities of xenobiotics on the retinoic acid receptor alpha (RARα) using in vitro and in silico analysis

Retinoic acid receptors (RARs) are known as crucial endocrine receptors that could mediate a broad diversity of biological processes. However, the data on endocrine disrupting effects of emerging chemicals by targeting RAR (ant)agonism are far from sufficient. Herein, we investigated the RARα agonistic or antagonistic activities for 75 emerging chemicals of concern, and explored their interactions with this receptor. A recombinant two-hybrid yeast assay was used to examine the RARα activities of the test chemicals, wherein 7 showed effects of RARα agonism and 54 exerted potentials of RARα antagonism. The representative chemicals with RARα agonistic activities, i.e. 4-hydroxylphenol (4-HP) and bisphenol AF (BPAF), significantly increased the mRNA levels of CRABP2 and CYP26A1, while 4 select chemicals with RARα antagonistic potentials, including bisphenol A (BPA), tetrabromobisphenol A (TBBPA), 4-tert-octylphenol (4-t-OP), and 4-n-nonylphenol (4-n-NP), conversely decreased the transcriptional levels of the test genes. The in silico molecular docking analysis using 3 different approaches further confirmed the substantial binding between the chemicals with RARα activities and this nuclear receptor protein. This work highlights the promising strategy for screening endocrine-disrupting effects of emerging chemicals of concern by targeting RARα (ant)agonism.

An Investigation of Molecular Property Prediction and Classification Based on Machine Learning Algorithms

With the rapid advancement of science and technology, chemical and physical research has entered an era of complexity and high dimensionality, where traditional research paradigms struggle to optimize vast chemical parameter searches. The Machine Chemist platform was developed in this context, leveraging big data and intelligent models to automate chemical synthesis, characterization, and testing processes. This study aims to predict the y1, y2 and y3 properties and classes of 2,580 molecules based on their physicochemical properties and improve model accuracy through data analysis and modeling. Data preprocessing involved removing missing values, duplicates, and outliers using the quartile method, resulting in an analyzable dataset. A scatter plot of y2 and id suggested a univariate polynomial function relationship, leading to the construction of a univariate nonlinear regression model. The model achieved a high prediction accuracy, with a low root mean square error and a high coefficient of determination. Additionally, the relationship between class and y1~y3 , x1~x100 indicators was examined, revealing mostly nonlinear relationships. A random forest model was established to classify 2,580 molecules into 1 to 4 classes based on the properties of 200,000 chemical molecules. The model's performance was evaluated using decision trees, confusion matrices, precision, and recall metrics. Finally, the SHAP method assessed the impact of feature indicators on classification outcomes, contributing to the development of a reliable molecular category prediction model.