Theoretical Evaluation Research Articles

A systematic review on career interventions for high school students

IntroductionThis study presents a systematic literature review of career interventions for high school students, exploring the theoretical framework, intervention modality, evaluation and outcomes of the intervention.MethodsFive keywords, three databases and five inclusion criteria were defined. Of the 419 documents collected, 25 remained for meta-synthesis.ResultsThe results showed that (1) the theoretical framework mainly consisted of career construct theory, social cognitive career theory, and cognitive information processing theory. (2) The intervention modality was mainly group counseling (8 sessions, 45 min). (3) The evaluation system mainly consisted of a pre-and post-test for the experimental and control group, and (4) the intervention outcomes were mainly focused on the positive development of career adaptability and career decision-making.DiscussionThe discussion offers recommendations for future research and practice in high school career interventions. (1) Social cognitive career theory should be given attention. (2) A three-tiered high school career development guidance model of career curriculum, career group counseling and individual counseling could be developed. (3) Career interventions should be shifted to mixed quantitative and qualitative studies, tracer studies, and special groups. (4) Outcome expectations should be given equal attention.

Unravelling the interaction of ethyl cinnamate in 2-hydroxypropyl and methyl-β-cyclodextrin by spectroscopic and theoretical evaluation for enhanced antibacterial activities

Essential oil components are the most common agents used to inhibit pathogens. Ethyl cinnamate (ECIN) is a hydrophobic essential oil component with well-known antibacterial properties but is poorly soluble in water, which limits its applications. In this study, inclusion complexes (ICs) were prepared by encapsulating ECIN in β-cyclodextrin (βCD), 2-hydroxypropyl-βCD, or methyl-βCD using an ultrasonication method to enhance water solubility and thermal and antibacterial properties. UV–Vis absorption and fluorescence spectral results indicated strong non-covalent interactions between ECIN and βCD derivatives in aqueous solution, and double reciprocal profiles revealed a guest:host stoichiometry of 1:1. Fourier-transform infrared and proton nuclear magnetic resonance spectroscopy investigations revealed that the phenyl ring of ECIN is located deeply in the CD nanocavities. X-ray diffraction, ultraviolet–visible diffuse reflectance spectroscopy, photoluminescence, and field emission scanning electron microscopy were performed to obtain crystalline, optical, and morphological information on solid ECIN-CDs. Thermogravimetric/differential thermal studies confirmed the improved stability of ECIN in solid CD-ICs by detecting an increase in the degradation temperature of ECIN from 50–140 °C to 310–410 °C. Further, the geometrical and frontier molecular orbital structures of the ECIN-CDs were theoretically evaluated using parametric method-3. Finally, antibacterial assays conducted against the foodborne pathogens Staphylococcus aureus and Escherichia coli revealed that encapsulated ECIN had a greater inhibitory effect, which suggested the devised nanocarriers promote the solubilization of essential oil components in aqueous solutions.

When Invariant Representation Learning Meets Label Shift: Insufficiency and Theoretical Insights.

As a crucial step toward real-world learning scenarios with changing environments, dataset shift theory and invariant representation learning algorithm have been extensively studied to relax the identical distribution assumption in classical learning setting. Among the different assumptions on the essential of shifting distributions, generalized label shift (GLS) is the latest developed one which shows great potential to deal with the complex factors within the shift. In this paper, we aim to explore the limitations of current dataset shift theory and algorithm, and further provide new insights by presenting a comprehensive understanding of GLS. From theoretical aspect, two informative generalization bounds are derived, and the GLS learner are proved to be sufficiently close to optimal target model from the Bayesian perspective. The main results show the insufficiency of invariant representation learning, and prove the sufficiency and necessity of GLS correction for generalization, which provide theoretical supports and innovations for exploring generalizable model under dataset shift. From methodological aspect, we provide a unified view of existing shift correction frameworks, and propose a kernel embedding-based correction algorithm (KECA) to minimize the generalization error and achieve successful knowledge transfer. Both theoretical results and extensive experiment evaluations demonstrate the sufficiency and necessity of GLS correction for addressing dataset shift and the superiority of proposed algorithm.

Evaluating Justice in Accessibility to Urban Opportunities: Introducing Justice Analysis Frameworks Based on Theoretical Perspectives and Transportation Costs

Accessibility analysis plays a crucial role in urban and transportation planning. However, the modeling and interpretation of accessibility can vary significantly across theoretical frameworks, which offer diverse considerations and measurement approaches. These distinctions profoundly influence planning evaluations and policy- and decision-making activities. Therefore, this article explores the impact of intellectual theories—specifically Bentham, Marx, Rawls, and Al-Sadr's perspectives—on justice assessments regarding accessibility to urban opportunities via public and private transportation. To achieve this, a gravity-based accessibility model that incorporates both internal and external costs is developed. Subsequently, quantifiable frameworks for justice assessment are introduced. Next, five scenarios are evaluated, and accessibility values are calculated for a selected study area. Finally, the results are ranked and analyzed within the context of the theoretical frameworks. The findings reveal that theoretical justice evaluation frameworks significantly influence the prioritization of scenarios. Additionally, incorporating internal and external transportation costs into the accessibility computation process not only affects accessibility values but also enhances the reflection of theoretical perspectives on justice. The results further demonstrate that the proposed accessibility model and justice evaluation frameworks can enable planners to embed justice-oriented approaches more comprehensively in the planning processes.

Retrieval of refractivity fields from GNSS tropospheric delays: theoretical and data-based evaluation of collocation methods and comparisons with GNSS tomography

This paper focuses on the retrieval of refractivity fields from GNSS measurements by means of least-squares collocation. Collocation adjustment estimates parameters that relate delays and refractivity without relying on a grid. It contains functional and stochastic models that define the characteristics of the retrieved refractivity fields. This work aims at emphasizing the capabilities and limitations of the collocation method in modeling refractivity and to present it as a valuable alternative to GNSS tomography. Initially, we analyze the stochastic models in collocation and compare the theoretical errors of collocation with those of tomography. We emphasize the low variability of collocation formal variances/covariances compared to tomography and its lower dependence on a-priori fields. Then, based on real and simulated data, we investigate the importance of station resolution and station heights for collocation. Increasing the network resolution, for example, from 10 to 2 km, results in improved a-posteriori statistics, including a 10% reduction in the error statistic for the retrieved refractivity up to 6 km. In addition, using additional stations at higher altitudes has an impact on the retrieved refractivity fields of about 1 ppm in terms of standard deviation up to 6 km, and a bias reduction of more than 3 ppm up to 3 km. Furthermore, we compare refractivity fields retrieved through tomography and collocation, where data of the COSMO weather model are utilized in a closed-loop validation mode to simulate tropospheric delays and validate the retrieved profiles. While tomography estimates are less biased, collocation captures relative changes in refractivity more effectively among the voxels within one height level. Finally, we apply tomography and collocation to test their capabilities to detect an approaching weather front. Both methods can sense the weather front, but their atmospheric structures appear more similar when the GNSS network has a well-distributed height coverage.

Theoretical Analysis and Experimental Evaluation of Wide-Lane Combination for Single-Epoch Positioning with BeiDou-3 Observations

Multi-frequency signals can enable some wide-lane (WL) observations to achieve instantaneous ambiguity resolution (AR) in complex scenarios, but simply adding WL observations will also place additional pressure on real-time kinematic data transmission. With the official service of the third-generation Beidou Navigation Satellite System, which broadcasts five-frequency signals, this dilemma has become increasingly evident. It is significant to explore multi-frequency observation combination methods that take into account both positioning precision and data transmission burden. In this work, we use the least squares method to derive the theoretical precision of the single-epoch WL combination of 16 schemes with varying frequency numbers (three or more) under the ionosphere-fixed model and the ionosphere-float model. The baseline solutions of 4.3 km and 93.56 km confirm that the positioning results are broadly consistent with the theoretical derivations under both models. In the ionosphere-fixed mode, the five-frequency scheme (B1C, B1I, B3I, B2b, B2a) yields the best positioning performance, improving the 3-dimensional positioning error standard deviation, circle error probable (CEP), and spherical error probable at 75% probability by 7.8%, 11.5%, and 6.7%, respectively, compared with the optimal triple-frequency scheme (B1C, B3I, B2a). Under the ionosphere-float model, the quad-frequency scheme (B1C, B3I, B2b, B2a) provides the best positioning performance, with only the CEP at 75% improving by 1.3% over the triple-frequency scheme. Given that the optimal triple-frequency scheme has a lower data volume, this work recommends it as the preferred scheme.

Synthesis, characterization, theoretical, and evaluation of eco-friendly phenytoin-based corrosion inhibitors for mild steel

This study explores the corrosion inhibition potential of two newly synthesized phenytoin-based compounds, (E)-2-(2-(2-chlorobenzylidene)hydrazineyl)-5,5-diphenyl-3,5-dihydro-4H-imidazol-4-one (2-ClPh-DDI) and (E)-2-(2-(2,4-dichlorobenzylidene)hydrazineyl)-5,5-diphenyl-3,5-dihydro-4H-imidazol-4-one (2,4-diClPh-DDI), in 1 M HCl solution. Both compounds exhibited remarkable inhibition efficiencies, reaching 97.7 % and 98.6 %, respectively. Comprehensive structural characterization was conducted using fourier-transform infrared spectroscopy, nuclear magnetic spectroscopy, and high-resolution mass spectrometry, both inhibitors demonstrated high purity and stability. Theoretical evaluations, including Monte Carlo simulation and density functional theory calculations, confirmed high reactivity and strong inhibition capabilities. Electrochemical measurements demonstrated a concentration-dependent inhibition effect, sustained up to 328 K. Adsorption isotherms revealed that these inhibitors effectively displace water molecules, forming a robust adsorbed layer that protects the mild steel surface. Surface analysis using microscopy confirmed the formation of protective layers and the presence of iron-inhibitor complexes, highlighting the compounds’ effectiveness in mitigating corrosion. The combined experimental and theoretical insights underscore the promising role of these phenytoin derivatives as eco-friendly corrosion inhibitors for mild steel.

Cultural resilience of heritage sites: Dimension exploration and scale development

Heritage sites are in a state of instability, facing various disturbances or environmental changes, which may lead to a crisis in cultural protection and inheritance. Importantly, cultural resilience is the key to dissipating these disturbances or even transforming them into sustainable development opportunities, but few studies have conducted theoretical exploration and evaluation on this topic. Therefore, this study aims to conceptualize and develop scales for cultural resilience of heritage sites (CRHS) using online and offline investigations (in-depth interviews, big data mining, and questionnaires). The results from grounded theory procedures reveal that cultural resilience consists of 5 dimensions: cultural resistance, restoration, learning ability, adaptability, and growth. Moreover, a cultural resilience scale with 17 items was developed and proved reliable and valid. This study lays an empirical foundation for the theoretical system development of CRHS and provides resilience ideas and strategies for their cultural protection, inheritance, and sustainable development.

Effects of Waste Glass Bottle Nanoparticles and High Volume of Waste Ceramic Tiles on Concrete Performance When Exposed to Elevated Temperatures: Experimental and Theoretical Evaluations

This article reports the durability performance of modified concrete with silica nanoparticles and a high volume of waste ceramic tiles under varying elevated temperatures. Ordinary Portland cement (OPC) was replaced with 60% waste ceramic tiles powder (WTCPs) and supplemented with 2, 4, 6, 8, and 10% nanopowders from waste glass bottles (WGBNPs) as a rich source of silica. The natural aggregates (both coarse and fine) were fully replaced by the crushed waste ceramic tiles (WTCAs). After 28 days of curing, the modified specimens were exposed to varying elevated temperatures (200, 400, 600, and 800 °C) in a furnace followed by air cooling. Tests such as residual compressive strength, weight loss, ultrasonic plus velocity, visual appearance, and microstructural analysis were conducted. Additionally, analysis of variance (ANOVA) was used to validate the performance of the proposed predictive equations, as well as their terms, using p-values and F-values. It was discerned that OPC substitution with WTCPs and WGBNPs significantly improved the concrete’s performance under elevated temperatures. It is observed that the addition of 2, 4, 6, 8, and 10% WGBNPs lowered the concrete deterioration by increasing the residual strength and reducing both internal and external cracks. This study provides some new insights into the utilization of WTCPs and WGBNPs to produce sustainable and eco-friendly modified concrete with high spalling resistance characteristics at elevated temperatures.

Binary hydrocarbon mixtures of Joule-Thomson refrigeration cycle based for -70 C freezer: Theoretical and experimental evaluation

Recently, with the increasing worldwide demand for low-temperature freezers, applying natural working medium hydrocarbon refrigerants has been widely concerned. For obtaining a −70 °C freezer, the Joule-Thomson refrigeration cycle of two kinds of binary hydrocarbon mixtures, R1150/R600 and R170/R600, were analyzed and experimentally verified. The theoretical analyses results indicated that the thermodynamic performance of R1150/R600 mixed refrigerant was better than that of R170/R600 when it was used in Joule-Thomson refrigeration system of −70 °C freezer. The coefficient of performance (COP) and the volume cooling capacity of using R1150/R600 was improved by 37.9 % and 50.7 %, respectively, compared with that of R170/R600. For further verify the results of theoretical analysis, two kinds of mixed refrigerants were tested with a low-temperature freezer prototype. The experimental results demonstrate that the lowest cabinet temperature that R170/R600 could reach was −66.9 °C at an ambient temperature of 32 °C with a refrigerant charge of 150g. On the other hand, when the concentration of R1150 is 27.5 %, the average temperature in the cabinet could reach −72 °C, indicating that the application of R1150/R600 in a low-temperature freezer at −70 °C has great potential. In summary, under the existing system configuration, the R1150/R600 was more suitable for −70 °C freezer than the R170/R600. This study could provide theoretical and experimental guidance for the selection of refrigerants for low-temperature freezers based on the Joule-Thomson refrigeration system.

A Simple 18‐Pulse Uncontrolled Star Rectifier by Adopting Dual Passive Injection Circuits at DC Side

ABSTRACTThis research introduces a simple 18‐pulse star rectifier, which is a combination of a conventional double‐star rectifier and two new passive injection circuits. The proposed passive injection circuits are constituted with a specially tapped interphase transformer (STIPT) and four diodes. The proposed passive injection circuits can simultaneously increase the step number of the input line current and the pulse number of the load voltage. The first passive injection circuit (FPIC) doubles the pulse number of the traditional double‐star rectifier converting it into an asymmetrical 12‐pulse star rectifier while the second passive injection circuit (SPIC) further converts the 12‐pulse star rectifier into 18‐pulse star rectifier. For tripling the pulse number of the double‐star rectifier, the STIPT requires to be designed optimally. For designing purpose, the proper tap ratios of the STIPT are determined depending on the minimum total harmonic distortion (THD) of the input line current. When designed optimally, the proposed rectifier simultaneously reduces the THD of the input line current and ripple of the output voltage with increasing pulses. In order to provide experimental validation for the theoretical evaluation, a laboratory prototype is constructed. The theoretical THD of the input line current is about 10.1%, whereas the experimental THD is about 5.42%.

Research on the Application of Scenario Simulation Teaching Method in Business Negotiation Course

Business negotiation is an important part of modern business activities, and business negotiation course is one of the key courses in business education. However, traditional business negotiation teaching methods often fail to effectively cultivate students' practical ability and ability to cope with complex negotiation scenarios. Scenario simulation teaching method is a teaching method that simulates real scenarios, which can effectively improve students' practical ability and coping ability. This paper explores the application of scenario simulation teaching method in business negotiation courses, including its theoretical basis, teaching design, implementation process and effect evaluation.

High-Efficiency Triple-Junction Polymer Solar Cell: A Theoretical Approach.

This study presents the theoretical design and evaluation of a triple-junction polymer solar cell architecture, incorporating oligomers of PDCBT, PPDT2FBT, and PDPP3T as donor materials and PC71BM as the electron acceptor. Using density functional theory (DFT) simulations and time-dependent DFT (TD-DFT) methods, the investigation covers essential photovoltaic parameters, including molecular geometries, UV-Vis spectra, and charge transport properties. The device is structured to maximize solar energy absorption across the spectrum, featuring front, middle, and back junctions with band gaps of 1.9 eV, 1.63 eV, and 1.33 eV, respectively. Each layer targets different regions of the solar spectrum, optimizing light harvesting and charge separation. This innovative multi-junction design offers a promising pathway to enhanced power conversion efficiencies in polymer solar cells, advancing the integration of renewable energy technologies.

SOGCN: Prediction of key properties of MR-TADF materials using graph convolutional neural networks

The exploration of the structure and properties of the luminescent materials in OLED devices using Multiple Resonance Thermally Activated Delayed Fluorescence (MR-TADF) is constrained by challenges related to long cycles and high experimental costs, making it a key obstacle in the development of new materials. In response to this challenge, we propose an innovative approach by constructing a graph convolutional neural network model named SOGCN to quickly determine whether an unsynthesized material has the potential to become an MR material, and accurately predict its energy gap and half-peak width, thereby expediting the development process of MR-TADF materials. We constructed the MR220 dataset for training the model based on 220 MR-TADF molecules reported in experiments. To ensure the reliability of the SOGCN model in predicting new samples, we have established a rigorous set of theoretical calculation evaluation standards, providing crucial references for the model. In the prediction of the properties of 37 new samples of MR-TADF molecules, SOGCN successfully predicted the singlet–triplet energy gap (ΔEST) of some samples, demonstrating a good trend in FWHM prediction as well. Finally, we have synthesized our designed molecule, Design3 (DtCzB-Boz), the organic light-emitting diodes based on DtCzB-Boz exhibit an emission peak at 508 nm, with the FWHM is 27 nm. The result of photophysical characterization is highly consistent with the predicted value of SOGCN. Notably, the mean absolute errors (MAE) between our model predictions and experimental/computational values were as low as 0.037 eV and 10 nm, respectively. This indicates that SOGCN exhibits higher efficiency and accuracy in predicting the properties of MR-TADF materials.

Exploration and Development of Quantum Computing Algorithms for Optimization, Cryptography, and Machine Learning Applications

Quantum computing, with its potential to revolutionize computation, relies fundamentally on the development of efficient algorithms to leverage its unparalleled processing capabilities. This research delves into the creation, exploration, and refinement of quantum computing algorithms, focusing on their applications in optimization, cryptography, and machine learning. Quantum algorithms such as Shor's and Grover's have demonstrated remarkable advantages in factorization and search problems, while more recent innovations are tackling complex challenges in global optimization and data analysis. By integrating principles of quantum mechanics—such as superposition, entanglement, and interference—these algorithms promise exponential speed-ups over classical counterparts in specific domains. This study critically analyzes existing quantum algorithms, proposes advancements in hybrid quantum-classical frameworks, and explores their implications for practical problem-solving. Through simulations and theoretical evaluations, it aims to bridge the gap between quantum theory and real-world applications, contributing to the evolution of quantum computing as a transformative technology.

Resilience in maritime logistics: Theoretical framework, research methodology, and indicator system

Maritime logistics, essential for global trade, faces increasing vulnerability due to operational complexity and disruptions such as extreme weather, geopolitical conflicts, and pandemics. Although maritime logistics resilience (MLR) has garnered growing attention, the field still lacks a unified theoretical framework and standardized evaluation indicator system, exposing a significant research gap. This study seeks to fill this gap by conducting a systematic review of 163 papers from Scopus, Web of Science, and Google Scholar, covering the period from 2009 to August 2023. The study defines maritime logistics resilience, identifies its four key attributes—robustness, vulnerability, redundancy, and rapidity—and explores their interrelationships, establishing a theoretical framework. Based on this foundation, an innovative evaluation indicator system is proposed for the first time, designed to assess resilience across the three main clusters of the maritime logistics system: ports, shipping networks, and the maritime supply chain. The proposed framework and indicator system provide a novel, comprehensive approach to evaluating MLR, offering both theoretical contributions and practical tools for industry practitioners. This research fills a critical gap in the field and lays the groundwork for future empirical studies and policy development.

Digitally Driven Urban Governance: Framework and Evaluation in China

With the rapid development of digital technology, the role of digitalisation in urban governance continues to emerge. Building a theoretical analysis framework and evaluation system of digitally driven urban governance has important theoretical and practical significance for stimulating the efficiency of digital technology tools and improving the energy level of urban digital governance. This paper aims to explore the mechanism of urban governance enabled by digital technology, innovatively change the previous thinking mode that only attaches importance to facility construction and e-government platforms, adopt ecological thinking, and comprehensively consider the role of “soft elements” such as strategic support, industrial support, the security environment, talent support, and the market environment. Then, the extreme value variance method and the coefficient of variation method are used to calculate the overall capacity and secondary index scores of each city, and the standard deviation of secondary index scores is used to represent the sub-environmental balance of the cross-sectional data of China’s provinces. In order to further explore which indicators restrict the improvement of China’s urban digital governance capacity, this study also constructs an obstacle degree model. The results show the following: (1) The overall capability of China’s digitally driven urban governance is low, with a total score of 27.25, indicating that China’s digitally driven urban governance is in its infancy. (2) There is a significant development imbalance among Chinese provinces, with Beijing ranking first with a score of 81.16, and Tibet, Qinghai, Xinjiang, Heilongjiang, and Ningxia scoring less than 13.30 points, ranking as the bottom 5 among the 31 provinces. (3) The shortcomings of talent support, industrial support, and the security environment restrict the improvement of the entire digital ecological governance ability.

DFT-guided synthesis of N, B dual-doped porous carbon from saccharina japonica for enhanced oxygen reduction catalysis.

The oxygen reduction reaction (ORR) is a crucial determinant of the energy transformation capacity of fuel cells. This study investigates the performance of N and B dual-doped carbon in ORR. Six models using density functional theory (DFT) are developed to compare the performance of different doping strategies. A highly efficient dual-doped carbon ORR catalyst (S-850-1) is synthesized from Saccharina japonica, containing 4.54 at% N and 1.05 at% B atom. Electrochemical analysis reveals that S-850-1 significantly outperforms the nitrogen mono-doped carbon S-850, exhibiting a higher half-wave potential of 0.861V and a greater limited current density of -5.60mAcm⁻2, compared to S-850's 0.838V and -5.24mAcm⁻2. Furthermore, S-850-1 surpasses the performance of 20% Pt/C, demonstrating enhanced durability and exceptional resistance to CO and methanol. The 1.40V open circuit voltage produced by S-850-1 when integrated into a Zn-air battery can power an LED light. Both theoretical and practical evaluations validate the excellent ORR performance of nitrogen and boron dual-doped carbon, as evidenced by the agreement between the electrochemical results and DFT calculations. This work not only extends the range of ORR catalysts derived from biomass but also provides guidance on creating and producing affordable, effective catalysts that utilize natural resources.

Theoretical Evaluation of Complex Dielectric Constant for Gamma Relaxation of Poly(methyl methacrylate), A Study of Quantum Chemistry and Linear Response Theory.

It is widely accepted that the γ relaxation of poly(methyl methacrylate) (PMMA) arises from the hindered rotational motion of the side chain around the C-C bond, which links to the main chain. However, the physical model to explain this process has been unknown. The hybrid density functional theory calculation showed that the PMMA intramolecular hindered rotation has an activation energy of 6.53 kcal/mol. This activation energy causes the friction coefficient to the intramolecule to hinder rotation. The qualitative value of the friction coefficient was evaluated on the basis of linear response theory by using the calculated value of the activation energy. The Lorentz model is adopted to calculate the complex dielectric constant of the γ relaxation using the calculated value of the friction coefficient. The calculated value of the complex dielectric constant agreed reasonably well with experimental results.

Insights into the corrosion inhibition performance of essential oil of Teucrium luteum subsp. flavovirens for carbon steel in 1.0 M HCl medium: experimental and theoretical evaluations

The objective of this research work was to assess Teucrium luteum subsp. flavovirens essential oil (EOTL), for the first time, as novel and eco-friendly corrosion inhibitor for carbon steel (CS) in 1.0 M HCl medium. Electrochemical impedance spectroscopy (EIS), potentiodynamic polarization (PDP) and surface analysis were employed to assess the effectiveness of the EOTL. The findings indicate that the EOTL reduces the corrosion of CS in hydrochloric acid and offered an inhibition efficiency (IE) of 91% at a dosage of 2.00 g/L at 298 K. The PDP data showed that EOTL behaved as a mixed-type corrosion inhibitor. The effect of immersion time and temperature on the corrosion inhibition performance of EOTL was also studied. It was found that the IE increased only up to 24 h and decreased with prolonged immersion time. In addition, the IE diminished with increasing temperature. The EOTL molecules adsorbed on the CS surface following Langmuir adsorption isotherm, with an adsorption energy ranging from −16 to −27 kJ/mol, an indication of physico-chemical adsorption mechanisms. The SEM/EDX results provide evidence of the presence of a protective film of the inhibitor on the surface of the CS. Theoretical studies using DFT, Monte Carlo simulations, molecular dynamics simulations and mean square displacement were conducted to given insight into the contributions of the four main components of EOTL. This work not only introduces a sustainable alternative to conventional corrosion inhibitors but also provides a robust understanding of the underlying mechanisms, hence contributing to advancement in corrosion science.