Statistical Experimental Design Research Articles

Chemical recycling of post-consumer poly(ethylene terephthalate) (PET) driven by the protic ionic liquid 2-HEAA: Performance, kinetics and mechanism

The circular economy is a paradigm for the upcoming industrial era, in which plastic wastes must be focused on as new resources. Chemical valorisation permits deepening into waste-to-gate schemes by obtaining new chemical platforms to be reintroduced in the production market. In this context, the potential of the protic ionic liquid 2-hydroxyethyl ammonium acetate (2-HEAA) to be used as a homogeneous catalytic co-solvent for the glycolytic conversion of post-consumer poly(ethylene terephthalate) (PET) was validated from different perspectives. Studies were performed for the reaction triplet framed under the experimental conditions (i) temperature T [160,170,180 ºC], (ii) plastic-to-solvent mass ratio P/S [1:3, 1:4,1:5] and (iii) plastic-to-ionic liquid mass ratio P/IL [2:1, 2:2, 2:3]. The reaction was confirmed in terms of the transformation of PET into BHET (bis(2-hydroxyethyl terephthalate) and a proposal of mechanism induced by the amine group of the 2-HEAA is given. The thermal kinetics were modelled and a first-order equation and an apparent activation energy of 60.5 kJ·mol-1 were obtained. A statistical Box-Behnken design of experiments explained the relationship between the factors of the glycolysis triplet by a response surface, with a maximum around {T = 170 ºC, P/S = 1:3.75 and P/IL = 2:1.75}, being T and P/S statistically relevant, whereas only the presence of 2-HEAA and not its amount P/IL was significant. Finally, the reusability of 2-HEAA after 90-min glycolytic chemical valorisations was confirmed up to 4 cycles. The results position 2-HEAA as a promising catalytic co-solvent for the scale-up of chemical valorisation of PET.

Optimization of ultrasound-assisted extraction using box-Behnken design, method validation, and analysis of phytochemicals from drying treatments in the application of Etlingera elatior inflorescence

Background: Etlingera elatior inflorescence, a potential source for herbal tea, undergoes a drying process that could enhance the active ingredients and health benefits. This study introduces the use of ultrasound-assisted extraction (UAE) to improve conventional extraction and increase the yield of phytochemicals, thereby presenting a novel approach to functional foods and nutrition. Objective: This study aims to optimize the UAE method using the Box-Behnken Design (BBD), a statistical experimental design widely used in the field of functional foods and nutrition. The determination of phytochemicals was validated using the optimized UAE. Chlorogenic acid from the extract was analyzed using HPLC-DAD and compared with that from Indonesia. According to the development of herbal tea, the phytochemical contents and inhibition of DPPH scavenging antioxidant activity were examined for the three drying treatments compared to freeze-drying. Methods: Box-Behnken Design (BBD) was used to optimize the condition of UAE with three variables: solvent concentrations (70%, 85%, 100%), solid-to-solvent ratios (1:20, 1:15, 1:10), and temperatures (30°C, 50°C, 70°C). The TPCs and TFCs of the ethanol extract were analyzed as observed responses. Repeatability precision (%CV) and recovery were validated for the optimized UAE. HPLC-DAD analyzed the chlorogenic acid of the extract and compared it to the Thai E. elatior extract and Indonesia. In applying E. elatior tea, phytochemical contents, and DPPH∙, scavenging antioxidant activity was examined for three drying treatments and compared to the freeze-drying treatment. Results: The suggested condition of optimized UAE extraction was 70% ethanol, 50°C, and a 1:20 solid-to-solvent ratio. %Repeatability precision of TPCs and TFCs for the extract was significantly <5%, and %recovery >90%. Freeze-drying and cabinet-drying treatments had significantly higher TPCs than others. Especially in freeze-drying treatment, the TFCs of the extract from Indonesia were significantly greater than those in Thailand (p<0.05). For DPPH∙ antioxidant activity, all treatments except freeze-drying of the extracts from Indonesia had higher inhibition of DPPH∙ antioxidant activity than those from Thailand. Conclusion: The optimized UAE extraction method was validated with high precision and accuracy. All drying treatments influenced the phytochemical contents and Inhibition of DPPH antioxidant activity in the inflorescences of both Thailand and Indonesia. Keywords: Box-Behnken Design, drying treatment, tea, method validation, phenolic.

Optimization of the concentration of ozone generated by DBD using PSO algorithm for water treatment process

The water treatment process with ozone is influenced by various operating parameters and environmental factors that can impact its efficiency. In this study, experiments were conducted using a Venturi pumping frame to investigate the effects of three controllable variables: oxygen flow height, applied voltage level, and water flow rate. The tests aimed to develop a mathematical model that accurately represents the relationship between these input variables and the resulting ozone concentration in the treated water. The experimental data was analyzed using the MODDE 5.0 software, a specialized application for statistical modeling and design of experiments. By fitting the data to appropriate model equations, a mathematical model was obtained that quantifies the influence of each variable and their interactions on the ozone concentration response. To optimize the process performance, a particle swarm optimization (PSO) algorithm was employed to extract the best-fit parameters for the mathematical model. PSO is a computational technique inspired by the social behavior of bird flocks or fish schools, utilizing a population of candidate solutions that evolve iteratively to converge on the global optimum solution. In this case, PSO searched for the model parameter values that minimized the error between predicted and experimentally measured ozone concentrations, rapidly converging to an accurate solution. The optimized mathematical model enables predicting the ozone concentration under any combination of oxygen flow height, voltage, and water flow rate within the experimental range. This predictive capability facilitates identifying the optimum operating conditions to maximize ozone concentration, thereby enhancing the efficiency of the water treatment process. The model serves as a valuable tool for process control, monitoring, and optimization, ensuring consistent treatment quality while minimizing resource consumption and operational costs.

Producing two-dimensional dust clouds and clusters using a movable electrode for complex plasma and fundamental physics experiments.

We report a Bidirectional Electrode Control Arm Assembly (BECAA) for precisely manipulating dust clouds levitated above the powered electrode in RF plasmas. The reported techniques allow the creation of perfectly 2D dust layers by eliminating off-plane particles by moving the electrode from outside the plasma chamber without altering the plasma conditions. The tilting and moving of electrodes using BECAA also allows the precise and repeatable elimination of dust particles one by one to achieve any desired number of grains N without trial and error. Simultaneously acquired top and side view images of dust clusters show that they are perfectly planar or 2D. A demonstration of clusters with N = 1-28 without changing the plasma conditions is presented to show the utility of BECAA for complex plasma and statistical physics experimental design. Demonstration videos and 3D printable part files are available for easy reproduction and adaptation of this new method to repeatably produce 2D clusters in existing RF plasma chambers.

Scenario Design for Infectious Disease Projections: Integrating Concepts from Decision Analysis and Experimental Design

Across many fields, scenario modeling has become an important tool for exploring long-term projections and how they might depend on potential interventions and critical uncertainties, with relevance to both decision makers and scientists. In the past decade, and especially during the COVID-19 pandemic, the field of epidemiology has seen substantial growth in the use of scenario projections. Multiple scenarios are often projected at the same time, allowing important comparisons that can guide the choice of intervention, the prioritization of research topics, or public communication. The design of the scenarios is central to their ability to inform important questions. In this paper, we draw on the fields of decision analysis and statistical design of experiments to propose a framework for scenario design in epidemiology, with relevance also to other fields. We identify six different fundamental purposes for scenario designs (decision making, sensitivity analysis, situational awareness, horizon scanning, forecasting, and value of information) and discuss how those purposes guide the structure of scenarios. We discuss other aspects of the content and process of scenario design, broadly for all settings and specifically for multi-model ensemble projections. As an illustrative case study, we examine the first 17 rounds of scenarios from the U.S. COVID-19 Scenario Modeling Hub, then reflect on future advancements that could improve the design of scenarios in epidemiological settings.

Influence of defect geometry on putty performance in pipeline composite repair assessments

The effective repair of pipelines is crucial to ensuring the integrity of infrastructure. However, the effect of defect geometries on the efficiency of pipeline composite repair systems is a major concern in the industry. This study investigated the effects of geometric properties on the performance of composite repaired pipes and putty components in the context of the efficiency of composite repair systems using parametric analysis with various defect geometries as well as two putty formulations. The study involved the development of a finite element model and the analysis of numerical simulations based on a statistical experimental design matrix. Specifically, a design of experiments approach with a specific emphasis on response surface methodology utilizing the Box–Behnken design was employed to identify factor settings tailored to different defect geometries. The analysis revealed that defect depth, length, and width had a significant negative impact on the strength of putty. Defect depth had a greater impact on the putty performance and steel pipe burst pressure compared to defect length and width. However, defect length and width had mixed influences on putty performance, with different geometries resulting in different responses for both types of putty, indicating the existence of complex interactions between these two parameters. The strength capacity of Putty-A in the repair system was significantly influenced by the interaction between defect width, depth, and length, while Putty-B, the interaction was more significant when it came to length and width of the defect. Further statistical analysis confirmed the individual significance of defect depth, length, and width, as well as their interactions on putty strength capacity. The increased sensitivity of Putty-A to changes in defect geometry compared to Putty-B introduces further complexity to material considerations. These findings highlight the importance of selecting appropriate putty properties depending on the defect geometry for effective pipeline repair. This research provides valuable insights that will guide material selection and the development of new putty material, improving the resilience and reliability of future pipeline repair technologies.

Statistical simplex centroid experimental design for evaluation of pectin, modified chitosan and modified starch as encapsulating agents on the development of vitamin E-loaded microparticles by spray-drying

Vitamin E encapsulation into biopolymer-based microparticles, obtained by spray-drying technology, was proposed to improve the encapsulation efficiency and the controlled release of fat-soluble vitamin. Binary and ternary blends of pectin, modified chitosan and modified starch, modified starch + modified chitosan, modified starch + pectin, modified chitosan + pectin and modified starch + modified chitosan + pectin ((0.33, 0.33, 0.33), (0.70, 0.15, 0.15), (0.15, 0.70, 0.15) and (0.15, 0.15, 0.70)) were proposed to produce and evaluate different carrier-based delivery systems. Vitamin E-loaded microparticles and empty microparticles were created with a product yield between 9 and 49 %. The mean diameter among all microparticles varied between 3.74 ± 0.02 and 421 ± 21 μm (differential volume distribution). Oval, spherical or irregular microparticles, with a variable morphology from a smooth to a high rough surface structure, with concavities, were produced. All vitamin E-loaded microparticles exhibited an encapsulation efficiency higher than 70 %. The slower vitamin E controlled release was observed from microparticles composed by modified chitosan (>36 h), while the faster release was achieved from microparticles individually composed by pectin (39 min). In general, the Fickian diffusion is the main release mechanism involved in the microparticles produced with modified chitosan, other formulations combine also other mechanisms such as swelling.

Fabrication of gastro-floating sustained-release etoricoxib and famotidine tablets: design, optimization, in-vitro, and in-vivo evaluation

In this study, a new gastro-floating sustained-release tablet (GFT) with a combination of Etoricoxib (ET) and Famotidine (FM) was successfully developed. GFTs were prepared by using a combination of hydrophilic swellable natural/semi-synthetic polymers as a controlled-release layer. Through a 24 full factorial statistical experimental design, the effects of formulation factors on the release of GFTs were conducted. The ideal floating tablet (FT) comprised konjac-gum (150 mg), guar-gum (26.57 mg), xanthan-gum (54.17 mg), and HPMC-K15-M (69.25 mg). The ideal FT exhibited a high swelling index (SI) (297.7%) and rapid FLT (around 50 s) in 0.1 N HCl as well as controlled release of ET (22.43% in 1 h and 77.47% in 8 h) and FM (24.89% in 1 h and 93.82% in 8 h) with the absence of any drug-excipient interactions. The AUC0∼72 (ng h/mL) of ET and FM in the GFTs were approximately double-fold of the market, respectively. The relative bioavailability was (207.48 ± 12.02% and 208.51 ± 13.11%) compared with commercial tablets. The X-ray imaging showed a promising buoyancy ability for approximately 8 h. These findings revealed the successful preparation of the sustained-release floating tablet with improved dual drug delivery.

Investigation of Deposition Parameters for Near-Beta Alloy Ti-55511 Fabricated by Directed Energy Deposition

The directed energy deposition (DED) parameters were determined for near-β alloy Ti-55511 by employing statistical design of experiments (DOEs) methods. Parameters resulting in fully dense freeform deposits were identified using two sequential DOEs. Single laser tracks were printed with several laser power, traverse rate, and powder feed rate settings in an initial DOE to identify promising build parameters. The capture efficiency and effective deposition rate were used to characterize and rank the single track deposits. The best parameters were then used to print a solid cube with various X–Y and Z overlaps (different hatch spacing, HS, and layer thickness, ZS) in a second DOE. Suitable deposition parameters were selected based on the cube density and microstructure and were used to fabricate larger tensile samples for mechanical testing. Multiple parameter sets were found to provide dense Ti-55511 deposits with acceptable mechanical properties and the parametric models showed statistical significance.

Modelling of Turning Process for Prediction of Energy Consumption

In this article, technological parameters such as cutting speed, feed rate and depth of cut and their relationships with average power are investigated and modelled using statistical design of experiments. This allows a quantitative and qualitative description of the relationship between average power and process parameters. The analytical knowledge gained from the tests provides the conditions for optimising the energy consumption of the turning process.

A Practical Recipe for Federated Learning Under Statistical Heterogeneity Experimental Design

A Practical Recipe for Federated Learning Under Statistical Heterogeneity Experimental Design

Analysis of Fluid Pressure Drop through a Globe Valve using Computational Fluid Dynamics and Statistical Techniques

Fluid mechanics plays a crucial role in everyday life, enabling the selection of accessories, materials, and various components essential for a system through which fluid flows. Pressure drop stands out as one of the most relevant factors in the design of fluid flow systems. However, analytical and experimental physical methods can increase these analyses' costs and time. Hence, in this study, statistical tools are employed to carry out specific experiments supported by numerical fluid simulation, aiming to comprehend the pressure drop behavior in a fluid as it passes through a globe valve. This valve, in turn, possesses distinct operating and manufacturing characteristics. The methods employed encompass a complete factorial system of response surface as support to construct the experimental design path through computational fluid dynamics. Among the key findings, it is demonstrated that, for systems with relatively low flow rates, the valve opening percentage does not exhibit a significant relationship with fluid pressure drop. Conversely, significant effects are observed for systems with relatively high flow rates regarding the valve opening percentage and pressure drop, reaching values of up to 73% pressure drop in this study. It can be inferred that the integration of statistical experimental design techniques and computational fluid dynamics constitutes a valuable resource for studying the pressure drop of a fluid passing through a system.

Optimized Bioleaching Pre-treatment of UG-2 PGM Flotation Concentrate Using Design of Experiments

AbstractThe depletion of the Merensky ore has led the South African platinum industry into largely mining and processing Upper Group Two (UG-2) ore for the extraction of Platinum Group Metals (PGMs). However, the processing of the UG-2 material is not fully amenable to the conventional pyrometallurgical route due to the high chrome content. Therefore, in this study, a bio-based process for base metal extraction from UG-2 flotation concentrates was investigated. This study represents only part of the work done in a broader investigation to develop a completely biological two-stage process for the extraction of base metals and PGEs. In this paper, only the first stage of the process is presented. This study evaluated a mixture of indigenous thermoacidophile archaebacteria namely, Acidianus brierleyi, Sulfolobus sp., and Metallosphaera sedula. A statistical Design of Experiments (DOE) was used for finding optimal conditions. Factors investigated included particle size, pH, pulp density, inoculum dosage, and temperature. Optimal extraction efficiencies of 92% for Co, 97% for Cu, and 99% for Ni were predicted at correlation coefficients of 92.5%, 93.2%, and 88.0%, respectively, thus, verifying the fitness of the model. Optimal base metal extractions obtained were 99.3% for Co, 90.1% for Cu, 41.58% for Fe, and 99.5% for Ni. The results showed a substantial extraction of base metals from UG-2 PGM flotation concentrate suggesting a potentially feasible option for industrial bioprocessing of PGM concentrates. To the best of the authors’ knowledge, this is the first report on bioleaching of base metals from UG-2 flotation concentrates. Graphical Abstract

Quality by Design Based Development of Electrospun Nanofibrous Solid Dispersion Mats for Oral Delivery of Efavirenz

Poor aqueous solubility often results in poor dissolution behavior and, consequently, poor bioavailability for those drugs whose intestinal absorption is dissolution rate limited. It is essential for formulation scientists to identify strategies to improve the solubility and dissolution rate of candidate drugs in order to improve their bioavailability. The present study investigated electrospun polymeric nanofibers for efavirenz (an antiretroviral drug), a Class II drug in the Biopharmaceutical Classification System. In order to fabricate nanofibers, hydrophilic spinnable polymer like Soluplus was used. Statistical design of experiments was used to optimize electrospinning parameters. Scanning electron microscopy (SEM) studies confirmed the presence of nanofibrous material in the mat. The x-ray diffraction (XRD) and differential scanning calorimetry (DSC) studies advocated the amorphization of efavirenz in the nanofiber samples. The optimized nanofiber-based platform significantly improved in vitro dissolution of efavirenz (89.0 ± 3.2% in 120 minutes) compared to pure efavirenz crystals (27.3 ± 2.4%).

Hydrothermal synthesis of hydroxyapatite crystals with and without seed crystals and surfactant

To the best of our knowledge for the first time the hydroxyapatite (HA) crystals were synthesized with different doses of HA seed crystals. HA crystals were synthesized from solutions containing the stoichiometric amounts of ammonium dihydrogen phosphate and calcium hydroxide. The various interactions of the NH4H2PO4 concentrations (0.5–5.5 Molar), surfactant {amino tris (methylene phosphonic acid) [N(CH2PO3H2)3] (ATMP)} [ATMP] concentrations (0–100 ppm), and HA seed crystals doses (0–50%) were investigated and their effects on the HA mean diameter and hardness were studied using the Box-Behnken experimental statistical design. Results have shown that no correlations were obtained between the mean diameters of the HA crystals and the obtained HA hardness. HA synthesis in the absence of surfactant resulted in formation of HA rod-like and/or tabular crystals whereas agglomerated crystals were obtained with surfactant. The results indicate that with increasing the % of HA crystal seed dose, an increase in the HA mean diameter was obtained. Moreover, with increase of surfactant concentration, a high increase in HA hardness was achieved. HA crystal particle sizes were ranged from about 11–18 µm whereas the crystallite sizes were ranged from 22 to 46 nm.

Innovative approach for semi‐continuous production of puerarin palmitate via transesterification with novel immobilized lipase

BackgroundPuerarin, a flavonoid abundantly found in the roots of Pueraria lobata, exhibits antioxidant, anti-cancer, anti-inflammatory, and anti-aging properties. Despite its numerous benefits, the low bioavailability of puerarin hinders its widespread industrial application. To improve this, flavonoid acylation is required. Lipase is a biocatalyst primarily used for flavonoid acylation; immobilized lipase is preferred given the limited stability of free lipase. Although research on flavonoid acylation for structural modification is actively being conducted, there is a need to explore continuous production for enhancing the industrial application of flavonoid esters. Therefore, in this study, we aimed to produce puerarin palmitate innovatively by selecting an effective lipase, developing an immobilized lipase, characterizing the enzymatic reaction, and designing a semi-continuous reactor system.ResultsLipase from Thermomyces lanuginosus (TL) was found to be the most suitable for the synthesis of puerarin palmitate; it was successfully immobilized on glutaraldehyde-activated silica gel (GASG). TL GASG showed greater solvent, thermal, and operational stability than those of commercial immobilized lipases. Furthermore, TL GASG use resulted in a puerarin palmitate conversion rate of 97.17% within 3 h. Additionally, the reusability of TL GASG for this reaction was higher than that of commercially available immobilized lipases. Upon using a semi-continuous reactor, the cumulative conversion rate of puerarin palmitate remained above 85% after more than ten substrate injections.ConclusionsThe results support the feasibility of the continuous production of flavonoid esters, underscoring their diverse industrial applications. A biorefinery strategy is anticipated to be proposed to utilize P. lobata extract biomass for flavonoid ester production. Moreover, optimizing continuous reactors through statistical experimental design is expected to enhance flavonoid ester production efficiency; these aspects will be explored in future research.Graphical

Nanoparticle depressants in froth flotation – The effect of colloidal silica with different size and surface modifications on the selective separation of semi-soluble salt type minerals

Colloidal silica has been presented as a selective depressant in froth flotation separation of scheelite and calcite by our group in 2020. Here we analyze the effects of colloidal silica dosage, specific surface area (i.e. size), and modification with microflotation on pure scheelite, calcite, fluorite, and apatite minerals. In a reagents scale-up procedure batch flotation experiments were conducted on a low-grade scheelite ore using statistical experimental design methodology. Microflotation experiments showed colloidal silica selectively depressing calcite flotation with increasing intensity with reduced size of colloidal silica. The nanoparticulate depressant did not affect the recoveries of scheelite, apatite, and fluorite – typical ore minerals that occur associated with calcite. Batch flotation of a low-grade scheelite ore confirmed the observations made at the microscale: colloidal silica significantly improves the scheelite-calcite selectivity index. Here, we observe a series of relations between colloidal silica specific surface area and modification on different process indicators such as scheelite-calcite selectivity index, recoveries, and froth properties. These relations are assumed to be due to the different aggregation mechanisms of the colloidal silica dispersions. The aluminate-modified colloidal silica, which tends to form a coherent gel network in the presence of Ca2+, shows the strongest effect on reducing calcite recovery accompanied by a significant reduction in scheelite recovery compared to the non-functionalised and silane-modified colloidal silica.

A novel approach for designing efficient and sustainable cooling cycles with low global warming potential refrigerants

With the current legislation on the phase-out of 3rd generation refrigerants, new cooling cycles are expected to operate with 4th generation refrigerants, hence, the need for optimal system performance with these new working fluids. In this study, an innovative optimization approach was applied for the design of cooling cycles with 4th generation refrigerants based on integrating statistical analysis design of experiments (DoE) with molecular modeling using the polar soft-SAFT model. First, a detailed multi-criteria assessment was applied for the selection of 4th generation refrigerants in medium–low temperature applications. Results demonstrated the potentiality of trans-1,3,3,3-tetrafluoroprop-1-ene (R1234ze(E)) or cis-1,2,3,3,3-pentafluoroprop-1-ene (R1225ye(Z)) in terms of environmental, safety, and technical criteria in basic cooling cycles under specific operating conditions. Multi-objective optimization guided using statistical analysis tools were implemented to study potential enhancement in cooling cycle performance using these promising refrigerants in terms of energy and exergy efficiency. This included evaporator and condenser temperature, fluid choice, compression yield, superheating/subcooling degrees, and cycle type. The evaporation and condenser temperature, and the compressor efficiency are shown to monopolize more than three-quarters of the cumulative contribution on system efficiency for those operated with R1234ze(E) in advanced liquid-to-suction line heat exchangers (LL/SL-IHX). Further optimization through examining the effect of heat transfer phenomena assisted in determining optimal operating conditions for new systems operating with low GWP refrigerants, instilling annual cost savings of $1.59 K and reduction in CO2 emissions by 1.02 tCO2-eq compared to the baseline system.

Comparing Designed Training Sets to Optimize Multivariate Regression Models for Pr, Nd, and Nitric Acid Using Spectrophotometry

Chemometric regression models were developed for the quantification of praseodymium (Pr, 0–1000 µg/mL), neodymium (Nd, 0–1000 µg/mL), and nitric acid (HNO3, 0.1–5 M) using spectrophotometry. Designed calibration sets were composed of 20 samples each: 10 model points and 10 lack-of-fit (LOF) points. The D-optimal designs effectively minimized the number of samples required to build models, and each design resulted in similar prediction performance, suggesting that statistical design of experiments can provide a reliable framework for selecting training set samples in three-variable systems. Partial least squares regression (PLSR) models were validated against a one-factor-at-a-time validation set composed of 125 samples (three variables, five levels). The top PLS-1 models resulted in average percent root mean square error of prediction error values of 3.5%, 1.7%, and 1.2% for Pr(III), Nd(III), and HNO3, respectively. Power set augmentations of the model and LOF samples were investigated to optimize the number of training set samples. PLSR models built using just required model points (10) had similar predictive capabilities as models including the LOF points (20) but with fewer samples. The number of validation samples was also varied systematically to learn how many samples are needed to validate regression models. This work addresses long-standing questions in the field of chemometrics to help make this approach amenable to the near-real-time quantification of hazardous species in remote settings.

Combinatorial optimization of pathway, process and media for the production of p-coumaric acid by Saccharomyces cerevisiae.

Microbial cell factories are instrumental in transitioning towards a sustainable bio-based economy, offering alternatives to conventional chemical processes. However, fulfilling their potential requires simultaneous screening for optimal media composition, process and genetic factors, acknowledging the complex interplay between the organism's genotype and its environment. This study employs statistical design of experiments to systematically explore these relationships and optimize the production of p-coumaric acid (pCA) in Saccharomyces cerevisiae. Two rounds of fractional factorial designs were used to identify factors with a significant effect on pCA production, which resulted in a 168-fold variation in pCA titre. Moreover, a significant interaction between the culture temperature and expression of ARO4 highlighted the importance of simultaneous process and strain optimization. The presented approach leverages the strengths of experimental design and statistical analysis and could be systematically applied during strain and bioprocess design efforts to unlock the full potential of microbial cell factories.