Design Of Experiments Research Articles

An integrated approach using discrete event simulation and design of experiments for working capital management in the fuel retail trade

ABSTRACT This study introduces an innovative approach to Working Capital Management (WCM) in the fuel retail sector, using Discrete Event Simulation (DES) and Design of Experiments (DOE). Efficient WCM is essential for small businesses, particularly in fuel retailing with its tight margins and intense competition. Unlike static financial tools relying on historical data, DES interacts with indicators such as Working Capital Requirement (WCR) and Liquidity Ratios, providing stochastic and accurate information. The study examined three variables (Supplier Payment Deadline, Credit Card Receipt Deadline, and Customer Payment Profile) across 16 experimental scenarios. The Payment Term to Suppliers emerged as the key factor in reducing WCR. Despite lower liquidity potential, the company balanced short-term obligations, identifying optimal WCM scenarios. The study shifts WCM analysis from static data to forecasted, real-time data, supporting dynamic business decision-making. It concludes that DES is a valuable tool for effective WCM in fuel retail, encouraging further research.

Hydroxy-Carboxylic Acids as Green and Abundant Ligands for Sustainable Recovery of Copper from a Multimetallic Powder: A Proof of Concept.

The recovery of copper and other valuable metals had become increasingly strategic for the future of the global economy, particularly in regions lacking abundant mineral resources, such as most European countries. In this study, we investigated the viability of utilizing environmentally friendly, cost-effective, abundant and bio-based ligands, specifically carboxylic acids and their derivatives, for copper leaching in a low-temperature hydrometallurgical process. Our investigation focused on elucidating the impact of substituents in the α position of hydroxy-carboxylic acids on copper solubilization efficacy. Notably, hydroxy-carboxylic acids, like malic acid and lactic acid, were evidenced as particularly promising ligands for leaching copper from a custom-made multimetallic powder. By thoroughly characterizing the obtained complexes (Raman, UV-Vis) and by supporting the experimental efforts by a Design of Experiment (DoE) approach, we optimized the leaching process. The influence of experimental parameters such as pH, temperature, leaching time, and Cu/ligand molar ratio on process yield (determined through Inductively Coupled Plasma - Optical Emission Spectroscopy, ICP-OES, analysis) was thoroughly investigated. Additionally, we developed a subsequent copper recovery step by precipitating copper (II) hydroxide in an alkaline environment, guided by speciation diagrams tailored for each copper-ligand system.

Design and damping characterization of sandwich composite made of particle-filled hollow spheres and steel sheets

Sandwich composites made of particle-filled hollow sphere structures (PHSS) and steel sheets offer excellent lightweight and damping properties, ideal for high-speed machine tool components under dynamic loads. Previous research has focused on single particle-filled hollow sphere (PHS) and small PHSS, leaving a gap understanding of PHSS/steel sandwich composites. In this study a test rig was developed, and Design of Experiments and Response Surface Analysis were used to investigate the effects of sheet and core thickness (design parameters), filling ratio, and particle size (particle parameters) on the damping performance of PHSS/steel sandwiches. The results indicate that the design parameters have a significant influence on damping performance. The interaction between design and particle parameters also substantially affects damping. Minimizing particle size, increasing filling ratio, thinning the face layer, and thickening the core layer significantly improve structural damping. To address manufacturing tolerances, a finite element (FE) model-based optimization was developed to accurately determine PHSS material parameters. These parameters were used in an FE model of the PHSS-steel composite, with identified contact parameters minimizing measurement and simulation differences. The homogenized material model and the linear model using global damping parameters accurately reproduce the dynamic properties of the PHSS-steel sandwich composite in low vibration modes.

From forensic chemistry: an educational experience

Abstract The study of forensic chemical analysis not only aids justice in the investigation of accidental or criminal events but also trains chemistry students in analysing hypothetical scenes, such as the design of scientific experiments, and alerting them to potential dangers. In this way, it contributes to generating awareness about safety and security, ethics, and the professional responsibilities of chemists. These, although ambitious, are some of the objectives that have led to the development of this course on Chemical Analysis in Forensic Investigation, whose thematic units and teaching details are developed. This work presents a detailed programme for the Forensic Chemistry course offered at the Faculty of Exact and Natural Sciences at the University of Buenos Aires. It includes examples of activities and bibliography, allowing it to be used as a template for similar courses or to adapt some of the thematic units to other chemistry courses. The suggested bibliography supports the education of both students and educators in the field of forensic chemistry. The incorporation of topics such as fires, explosives, chemical warfare agents (CWA), and environmental crimes aims to develop professional profiles for a new generation of chemists more committed to the societal impact of their work.

Effect of Citric Acid and Tromethamine on the Stability of Eyedrops Containing Lifitegrast

Background/Objectives: Lifitegrast is an effective treatment for dry eye disease, reducing inflammation and improving the ocular surface condition. Owing to its high sensitivity to oxidation and hydrolysis, formulation studies are required to maintain the physicochemical stability of lifitegrast. This study aimed to overcome the instability of lifitegrast by developing a more stable eyedrop formulation by using citric acid and tromethamine to prevent the degradation of lifitegrast. Methods: Based on the Design of Experiment (DoE) approach, formulations were prepared at various concentrations of two stabilizers, citric acid and tromethamine. The stabilizers were carefully controlled to reduce the generation of degradation products. The eyedrops were stored under accelerated test conditions, and parameters such as appearance, pH, drug content, and impurities were evaluated. Results: The results showed that all critical quality attributes (CQAs) including appearance, pH, drug content, and impurities were maintained at stable levels under accelerated conditions, meeting established criteria. In addition, it was suggested that citric acid provided protection against oxidative stress, while tromethamine prevented hydrolysis caused by pH fluctuations. Conclusions: Consequently, it was concluded that the developed lifitegrast-containing eyedrop formulation exhibited improved physicochemical stability, validated through statistical analyses. These findings contribute to the development of stable eyedrops and provide a foundation for commercial production and clinical applications.

ATR-FTIR characterisation of daily-use plastics mycodegradation

Synthetic polymers, such as plastics, have permeated all aspects of modern life, and nowadays plastic pollution is a major environmental problem. Mycodegradation of these polymers could represent part of the solution to this problem since it calls on a broad toolbox of enzymes and applies non-enzymatic mechanisms to degrade and deteriorate recalcitrant materials. However, not enough is known about this ability for most of the representatives of the fungal kingdom. Another bottleneck is the harmonisation of technologies to analyse plastic degradation. This work involved the design of a biodegradation experiment, where the potential of four fungi representative of Dikarya and Penicillia (Funalia floccosa, Trametes versicolor, Pycnoporus cinnabarinus and Penicillium oxalicum) were tested on their ability to deteriorate the six most used plastics based on gravimetry and attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR). The following correlation between changes in the band signals and the loss of mass after treatment was determined using polyethylene terephthalate, polypropylene, polyethylene, poly vinyl chloride, high density polyethylene, low density polyethylene and nylon. After treatment, the decrease in absorbance of the characteristic bands of the plastics was taken as an indication of the degradation of the corresponding bonds/functionalities. The four fungi used could transform CH, CH2, CH3, CO, CO, CN, NH and CCl bonds. The best result was obtained using the fungus F. floccosa with 90-day treatments for high density polyethylene (∼ 62.0 %), low density polyethylene (∼ 23.6 %) and nylon (∼ 35.6 %). Therefore, mycodegradation could open up new doors in the fight against plastic pollution.

A novel pedicle screw design to maximize screw-bone interface strength using finite element analysis and design of experiment techniques.

Basic study. This study aimed to utilize finite element (FE) analysis and design of experiment (DoE) techniques to propose and optimize a novel pedicle screw design and compare its pull-out force with that of a control device. Pedicle screw-based fixation is the gold-standard treatment for spine diseases, particularly in fusion procedures. However, pedicle screw loosening and breakage still occur in osteoporotic and non-osteoporotic patients. This research investigates screw design modifications to enhance screw-bone interface strength and reduce the likelihood of loosening. We conceptualized a novel pedicle screw considering vertebral bone morphology and strength differences. A validated FE model was developed and used in conjunction with DoE to determine the screw՚s optimum geometrical parameters. The FE model was validated through simulation and laboratory experiments using the control device. The optimized thread profiles for cortical bone and cancellous bone were determined, with pull-out force as the primary factor for screw design evaluation. FE analysis results for the control device closely matched experimental results, with less than 5% difference. The chosen unique pitch/depth ratio showed maximum pull-out force for cortical bone, while DoE enabled the optimization of design parameters for cancellous bone. The optimized pedicle screw exhibited a 15% increase in pull-out force compared to the control device. The study proposes a novel pedicle screw design with better pull-out strength than the control device. Combining FE analysis with DoE is an effective approach for screw design optimization, reducing the need for extensive prototyping tests. A two-variable analysis suffices for optimizing cortical bone design parameters, while a multi-variable analysis is more effective for optimizing cancellous bone design parameters.

Multiobjective design of automated order fulfillment systems: A case study for an existing surgical complex

We present a case study that introduces a systematic framework for designing an automated guided vehicle (AGV) order fulfillment system. The multi-stage framework integrated discrete event simulation (DES), super-efficiency data envelopment analysis (S-DEA) model, and Design of Experiments (DOE) methodologies for the design of an AGV system in an existing large-scale surgical complex within a comprehensive hospital in Singapore. Performance metrics derived from this model were consolidated into a single relative efficiency score using the S-DEA model. This efficiency score was then utilized in a DOE methodology, combined with a post-hoc model selection process, to robustly identify appropriate models for evaluating alternative system designs. The proposed framework optimizes AGV deployment by first identifying opportunities for AGVs to add value within the surgical system through a value-stream mapping approach. It then derives the optimal system design by balancing cost efficiency, manpower reallocation, and order fulfillment rates, facilitated by the S-DEA model augmented with the DOE approach and post-hoc model selection. Application of this framework to the surgical complex revealed several insights that can significantly enhance AGV efficiency prior to actual deployment. However, a key limitation of this case-study-based approach is its limited generalizability across different systems. Despite this, the methodology provides a robust foundation for AGV system design in similar healthcare environments.

Multifunctional TiO2(R)/Fe2O3 Photocatalytic Composites Obtained from Ilmenite Ore

AbstractThe commercialization of the photocatalysis technology requires that the synthesis of the photocatalytic material is easy to scale up. Thus, the synthesis from earth‐abundant minerals represents one plausible solution to obtain materials by a scalable process with a lower environmental impact. So far, the most promising photocatalyst for this application is titanium dioxide (TiO2), which can be obtained from ilmenite ore; however, its synthesis usually implies toxic solvents and complicated reaction conditions. Thus, here is proposed an optimized method to extract higher amounts of TiO2 by a multivariable Plackett‐Burman design of experiments considering the mass of the ore precursor, the addition of phosphoric acid (H3PO4), the digestion temperature, the amount of base to adjust the pH, and the final thermal treatment. From this design, it was possible to minimize the heat treatment and the amount of base used to favor higher TiO2 (rutile) content with the presence of additional phases of iron oxides (Fe2O3) that act as co‐catalyst to enhance the photocatalytic activity. The photocatalytic activity of the TiO2/Fe2O3 composites obtained was investigated in four model reactions to obtain solar fuels (H2 evolution and CO2 reduction) and to remove endocrine water pollutants (bisphenol A and dyeing water), using visible and natural solar irradiation, respectively.

Influence of different wire materials on the machining of Albromet W130 by WEDM

Wire Electrical Discharge Machining (WEDM) is an unconventional machining technology, widely spread in different sectors of many industries. The machining uses periodically repeating electrical impulses, which allows all materials with at least a minimum electrical conductivity to be machined. The machining tool is a thin wire that can be made of many different materials. Wire electrode material requirements vary from industry to industry. This study aimed to increase the efficiency of WEDM through an analysis of the influence of the type of wire material on the machining of Albromet W130 copper alloy. The analysis comprised a molybdenum, brass and a copper wire of a 0.25 mm diameter and a Box-Behnken design of experiment totalling 42 rounds. The design of experiment results analysis covered cutting speed, machined surfaces’ topography and morphology, and the subsurface layer condition. Furthermore, an analysis of the wire electrodes used in the experiment was carried out. The highest cutting speed was achieved using a copper wire and the lowest R a values were achieved in samples machined with a molybdenum wire.

An Analysis Comparing the Taguchi Method for Optimizing the Process Parameters of AA5083/Silicon Carbide and AA5083/Coal Composites that Are Fabricated via Friction Stir Processing

Aluminium metal matrix composites are widely used in automotive, aerospace, marine, and structural engineering due to their high strength-to-weight ratio and superior mechanical properties. Optimizing friction stir process parameters is critical to enhancing the performance of these materials. This study investigates the effects of FSP parameters such as rotational speed, tilt angle, and traverse speed, on the mechanical properties of AA5083/Silicon carbide and AA5083/Coal composites. Using a Taguchi L9 design of experiments, signal-to-noise ratio, and analysis of variance, this study identifies the optimal process settings for maximizing ultimate tensile strength, microhardness, and elongation. From the results, the study revealed that for AA5083/Silicon carbide composites, rotational speed was the most significant factor affecting tensile strength, while for AA5083/Coal composites, tilt angle played a more critical role. Rotational speed consistently influenced microhardness and elongation for both materials. The signal-to-noise ratio analysis indicates that optimal FSP parameters vary depending on the reinforcement material used. This study highlights the importance of tailoring FSP settings to specific reinforcements to achieve optimal mechanical properties. These findings contribute to the advancement of friction stir processing techniques for fabricating high-performance aluminium metal matrix composites, particularly for applications in industries requiring strong, lightweight, and corrosion-resistant materials.

Multi-objective optimization towards cooling performance of teardrop section Kagome trusses array jet impingement composite cooling structure with cross-flow

Teardrop Section Kagome trusses array can be a spoiler for a new generation of advanced combustion chambers. In this study, multi-objective optimizations are applied to optimize a jet impingement composite cooling structure with cross-flow. Four structural parameters with five levels and three performance parameters are calculated in design of experiment and fitted by response surface methodology. The database is expanded by non-dominated sorting genetic algorithm-II, and then technique for order preference by similarity to an ideal solution is used to calculate the optimal structures under different operating conditions by different weights of the performance parameter. The conclusions are as follows: The minimal Equality of variances and fitting accuracy are 35.4371 and 93.6%. Diameter of the cross-section has the largest positive main effect on average Nusselt number and pressure loss coefficient, while angle between the rod and the horizontal plane has the largest positive effect on temperature uniformity coefficient. The interaction of trailing edge angle with angle between the front rod and the back rod in the horizontal plane is large. Case15 is chosen, where the weight ratio is 1:5:5, improvement of the corresponding optimized performance parameters of the simulation results with respect to the Origin of three performance parameters are 26.72%, −2.93%, 91.59% respectively. It provides a feasible reference for future advanced combustion chambers and accelerates their development process.

Optimization of the Homogenization Process of Ginseng Superfine Powder to Improve Its Powder Characteristics and Bioavailability.

As consumer demands evolve for health supplements, traditional ginseng products are facing challenges in enhancing their powder characteristics and bioavailability. The objective of this study was to prepare a novel ginseng superfine powder using a high-pressure homogenization (HPH) process. Response surface methodology was employed to determine the effects of HPH parameters (pressure, number of passes, and concentration) on particle size and the dissolution of the saponin components of the superfine powders. The Box-Behnken design of experiments was applied to ascertain the optimal HPH parameters for the smallest particle size and the highest dissolution of the saponin components. For the powders obtained at different parameters, the characterization of tap density, bulk density, flowability, water-holding capacity, appearance, and taste were observed. The optimized experimental conditions for the HPH process were as follows: 15,000 psi (pressure), 3 (number of passes), and 1 kg/L (concentration). The optimized values were 55 μm (particle size) and 83 mg/g (dissolution of the saponin components), respectively. The method offered technical support for the application of the HPH process in the preparation of ginseng powders. The objects of this research could be broadened to include a diverse array of botanical materials, addressing contemporary demands for cost-effectiveness and sustainability within the industry.

Optimization of Reactive Ink Formulation for Controlled Additive Manufacturing of Copolymer Membrane Functionalization.

Multifunctional, nanostructured membranes hold immense promise for overcoming permeability-selectivity trade-offs and enhancing membrane durability in challenging molecule separations. Following the fabrication of copolymer membranes, additive manufacturing technologies can introduce reactive inks onto substrates to modify pore wall chemistries. However, large-scale implementation is hindered by a lack of systematic optimization. This study addresses this challenge by elucidating the membrane functionalization mechanisms and optimal manufacturing conditions using a copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC) "click" reaction. Leveraging a data science toolkit (e.g., nonlinear regression, uncertainty quantification, identifiability analyses, model selection, and design of experiments), we developed two mathematical models: (1) algebraic equations to predict equilibrium concentrations after preparing reactive inks by mixing copper sulfate, ascorbic acid (AA), and an alkynyl-terminated reactant; and (2) reaction-diffusion partial differential equations (PDEs) to describe the functionalization process. The ink preparation chemistry with side reactions was validated through pH and UV-vis measurements, while the diffusion and kinetic parameters in the PDE model were calibrated using time-series conversion of the azide moieties inferred from Fourier-transform infrared spectroscopy. This modeling framework avoids redundant experimental efforts and offers a functionalization protocol for scaling up designs. Ink optimization problems were proposed to reduce the use of expensive and environmentally insulting ink materials, i.e., Cu(II), while ensuring the desired chemical distributions. With optimal ink formulation Cu(II)/AA/alkyne = 1:1:2 identified, we uncovered trade-offs between Cu(II) usage and functionalization time; for example, in continuous roll-to-roll manufacturing with a conserved functionalization bath setup, our optimal operational conditions to achieve ≥90% functionalization enable at least a 20% reduction in total copper investment compared to previous experimental results. The data science-enabled ink optimization framework is extendable for on-demand multifunctional membranes in numerous future applications such as metal recovery from wastewater and brine.

Shell Materials for Chewable Capsules, From Design of Experiments to Optimal Dosage Form Manufacturing

AbstractInnovations in chewable dosage forms provide solutions for swallowing difficulties faced by certain patient populations. Chewable softgel capsules (SGC) offer opportunities to expand the benefits of SGC, excelling in the delivery of lipid‐based formulations by optimizing the mechanical properties of the shell material without compromising industrial‐scale manufacturing. This study employs an original approach, with a target product profile that aims to combine processability and chewability, to develop optimized chewable dosage forms. Through a mixture design of experiments, key factors such as plasticizer content and the addition of acid‐modified thin‐boiling corn starch are explored, focusing on response parameters critical to achieving the desired properties of the capsule shell material. Optimal shell compositions—one starch‐free and another containing 9% w/w starch, with respective gelatin/non‐volatile plasticizer ratios of 0.81 and 0.67 are determined and evaluated by manufacturing chewable SGC at pilot scale using rotary die technology. The successful manufacturing and resulting capsules, which exhibit the intended properties, highlight the efficiency of this approach in striking the right balance between processability, soft texture, and quick disintegration time.

Evaluation of Basmati Rice (Oryza sativa L.) Genotypes for Seedling Growth and Leaf Physiology Under High‐Temperature Stress

ABSTRACTRice, a staple food crop for over half of the global population, is facing a serious threat of rising temperature due to climate change, especially in the areas producing Basmati rice. The main objectives of the study were to compare the promising cultivars of Basmati rice for heat stress tolerance and to assess how elevated temperature affects leaf physiological and morphological parameters of fine rice at seedling stage. A 2‐year‐controlled pot experiment was carried out to evaluate how different Basmati rice varieties respond to heat stress. The experiment was carried out at the Agronomic research area, University of Agriculture Faisalabad, Pakistan, during 2022 and 2023. The design of experiment was completely randomised design (CRD) with split treatment structure and four replications. Plant morphology, leaf temperature, chlorophyll contents, relative cell injury and relative water contents were evaluated for both experimental years. Heat stress significantly affected all morphological and physiological attributes such as chlorophyll contents, relative water contents and relative cell injury across different varieties. There was variation in the behaviour of different varieties under stress conditions as compared to no heat, but from the results it was very clear that Kisan Basmati and PK‐1121 Aromatic constantly showed poor performance under both conditions for all the recorded parameters. However, in almost each parameter evaluated, Basmati‐515, Super Basmati and NIAB‐16 exhibited Superior thermo tolerance and better performance. On the basis of observed morphological and physiological attributes, Kisan and PK‐1121 Aromatic Basmati were graded as sensitive varieties, while Basmati‐515, Super Basmati and NIAB‐16 showed tolerance to heat stress as compared to other varieties. However, further research is needed to explore the underlying mechanisms and genetic factors contributing to the sensitivity or tolerance observed in these varieties.

Optimization of electrode thickness of lithium-ion batteries for maximizing energy density

AbstractThe demand for high capacity and high energy density lithium-ion batteries (LIBs) has drastically increased nowadays. One way of meeting that rising demand is to design LIBs with thicker electrodes. Increasing electrode thickness can enhance the energy density of LIBs at the cell level by reducing the ratio of inactive materials in the cell. However, after a certain value of electrode thickness, the rate of energy density increase becomes slower. On the other hand, the impact of associated limitations becomes stronger, reducing the practical applicability of LIBs with thicker electrodes. Hence, an optimum value of thickness is of utmost importance for the practicability of thicker electrode design. In this paper, both the cathode thickness and the anode thickness of an NCM LIB cell were optimized by applying response surface methodology (RSM) with a Box-Behnken design (BBD) to maximize the energy density. Moreover, the influence of electrode porosity, together with the interaction of porosity with cathode and anode thickness, was incorporated into the optimization. A full factorial design of 3-level, 3-factor was used to generate 15 simulation conditions in accordance with the design of experiment (DoE) achieved through BBD. Then, those conditions were used to achieve 15 responses by simulating a reduced-order electrochemical model. Finally, the statistical technique analysis of variance (ANOVA) was used to analyze and validate the results of RSM. The results show that the RSM-BBD optimization method, coupled with ANOVA, has successfully optimized the thicknesses of both positive and negative electrodes for maximum energy density, despite the nonlinearity of the electrochemical system. The findings suggest an optimized cathode thickness of 401.56 µm and anode thickness of 186.36 µm for a maximum energy density of 292.22 of an NCM LIB cell, while electrode porosity is preferred to be 0.2.

Comparative Analysis of Machine Learning Techniques for Identifying Multiple Force Systems from Accelerometer Measurements.

The knowledge of the forces acting on a structure enables, among many other factors, assessments of whether the component's useful life is compromised by the current machine condition. In many cases, a direct measurement of those forces becomes unfeasible, and an inverse problem must be solved. Among the solutions developed, machine learning techniques have stood out as powerful predictive tools increasingly applied to engineering problem-solving. This study evaluates the ability of different machine learning models to identify parameters of multi-force systems from accelerometer measurements. The models were assessed according to their prediction potential based on correlation coefficient (R2), mean relative error (MRE), and processing time. A computational numerical model using the finite element method was generated and validated by vibration measurements performed using accelerometers in the laboratory. A robust database created by the response surface methodology in conjunction with Design of Experiment (DOE) was used for the evaluation of the ability of machine learning models to predict the position, frequency, magnitude, and number of forces acting on a structure. Among the six machine learning models evaluated, k-NN was able to predict with a 0.013% error, and Random Forests showed a maximum error of 0.2%. The innovation of this study lies in the application of the proposed method for identifying parameters of multi-force systems.

Design of experiments optimization of N,N,N-trimethyl chitosan synthesis using N,N-diisopropylethylamine base

This study presents a novel synthesis method of N,N,N-trimethyl chitosan (TMC) by using a non-nucleophilic base and optimizing the solvent system for enhanced scalability, while addressing critical factors such as viscosity management and stirring efficiency. The study objectives also included achieving high N,N,N-trimethylation without O-methylation while minimizing reagent use. Eight bases, three solvent systems, and varying levels of dilution were explored to mitigate viscosity challenges and gas evolution. 1H NMR spectroscopy was used to characterize the TMC products. The integral values of the peaks at 3.3, 3.0, and 2.8 ppm, corresponding to trimethyl, dimethyl, and monomethyl groups, were used to quantify the methylation degrees. The most promising initial results were obtained with N,N-diisopropylethylamine (DIPEA) base, and DMF as solvent. Using 6 eq methyl iodide (MeI) relative to chitosan and DIPEA as base, up to 68 % DTM was achieved. Applying Design of Experiments (DoE), the method was further optimized under diluted conditions, crucial for industrial scalability and viscosity control. Results from a full factorial design (32) revealed that diluted medium effectively prevented viscosity concerns, achieving a notably low viscosity of 5.9 cP in the reaction mixture, a 16-fold decrease in viscosity, compared to initial experiments. It was also established that both the MeI reagent and the base addition are significant factors for the DTM response, with both factors showing quadratic effects. The DoE model demonstrated high significance (R = 0.97), high precision for future prediction (Q2 = 0.87), good model validity (0.84) and excellent reproducibility (0.96). The results mark a notable advancement in TMC synthesis, offering an efficient and practical method with significant implications for industrial applications.

Neutronics design of shutdown and control systems for a Zero Power Experiments of chloride-based molten salt fast reactor.

Nuclear power's role as a reliable, baseload, low-carbon source and its importance in achieving clean energy goals are being increasingly recognized with growing urgency around decarbonization of the global energy systems. However, to deliver a long-term sustainable solution, it is essential to develop innovative nuclear technologies for improving the fuel utilization and reducing the nuclear waste disposal challenge. Zero Power Reactors (ZPR) are an essential initial step for developing new nuclear technologies because they allow for testing and refinement in a safe environment before large-scale deployment. This paper discusses the design of a ZPR experiments for the development of iMAGINE, a novel chloride-based molten salt reactor technology. The paper presents a detailed analysis of the neutronic design for the shutdown and control systems of an experimental ZPR based on the iMAGINE molten salt reactor technology. The study concludes that a split-core design with a lower corner reflector as an extension of the lower annular reflector offers the most robust ZPR configuration, offering optimum operational margins and maneuverability. This design ensures safety, regulatory compliance, and sufficient control and shutdown performance for the successful development of the iMAGINE technology.