Mixture Design Research Articles

Generative artificial intelligence and optimisation framework for concrete mixture design with low cost and embodied carbon dioxide

This research presents a generative Artificial Intelligence (AI) and design framework that integrates machine learning (ML) and optimisation methodologies to discover new concrete mixture designs. Unlike traditional ML models that predict based on existing data, this framework innovatively generates new concrete mix designs that meet specific requirements such as strength, cost-efficiency, and reduced embodied CO2. To propose a powerful and reliable generative AI model, several advanced ML algorithms were considered, e.g., CatBoost, XGBoost, and LGBM. These models were trained on a unique dataset consisting of 4,936 data points collected from five different batching plants and have not been published yet. Bayesian Optimisation was employed to fine-tune model hyperparameters, resulting in the most effective models attaining R2 values of 0.94 and 0.89 for raw and grouped data, respectively. To verify the trained generative AI model, a case study was conducted, in which the model was requested to provide designs of a mix with pre-determined strength and optimised cost and embodied CO2. The mix designs generated by the framework were successfully validated through experimental tests, corroborating the predictive outcomes. The research culminated in the development of a web application, a tool crafted to streamline the concrete mixture design and optimisation process. This generative AI design framework can be applied to many other aspects of material design and engineering problems.

A Novel Hydrogel Sponge for Three-Dimensional Cell Culture

Background/Objectives: Three-dimensional (3D) cell culture technologies allow us to overcome the constraints of two-dimensional methods in different fields like biochemistry and cell biology and in pharmaceutical in vitro tests. In this study, a novel 3D hydrogel sponge scaffold, composed of a crosslinked polyacrylic acid forming a porous matrix, has been developed and characterized. Methods: The scaffold was obtained via an innovative procedure involving thermal treatment followed by a salt-leaching step on a matrix-containing polymer along with a gas-forming agent. Based on experimental design for mixtures, a series of formulations were prepared to study the effect of the three components (polyacrylic acid, NaHCO3 and NaCl) on the scaffold mechanical properties, density, swelling behavior and morphological changes. Physical appearance, surface morphology, porosity, molecular diffusion, transparency, biocompatibility and cytocompatibility were also evaluated. Results: The hydrogel scaffolds obtained show high porosity and good optical transparency and mechanical resistance. The scaffolds were successfully employed to culture several cell lines for more than 20 days. Conclusions: The developed scaffolds could be an important tool, as such or with a specific coating, to obtain a more predictive cellular response to evaluate drugs in preclinical studies or for testing chemical compounds, biocides and cosmetics, thus reducing animal testing.

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.

The design of long afterglow pavement mixture by optimizing optical properties and basic road performance

This study designed two types of long-afterglow pavement mixtures with high transparency bright asphalt and polyurethane as cementing materials. The photoluminescence properties of long-afterglow luminescent gravel were designed to achieve self-luminescence effect for pavement use. The optimal amount of cementitious material was determined to be 6.2% by the Marshall method, and four kinds of pavement mixtures with luminous gravel content were designed, and the optical properties and basic road properties of each mixture were evaluated. In this study, the mix ratio design of long afterglow pavement mixture was studied from the perspective of optical properties and basic road performance, which provided a new reference and idea for the development of self-luminous pavement mixture. And the conclusion of the road optical properties and basic road performance suggests the possibility of the application of the long afterglow pavement mixtures.

Machine Learning Approach to Rapidly Evaluate Curling of Concrete Pavement

This paper focuses on the methodology for evaluating the degree of total curling in concrete pavement using machine learning. Deflection induced by falling weight deflectometer (FWD) testing is known as a direct correlation to total curling including built-in and daily curling. However, deflection measurement in the in-service road is also affected by others, such as environmental conditions, pavement geometry, subgrade stiffness, and mixture design. Thus, it is challenging to determine the level of curling from FWD data due to the complexity of influencing parameters. To navigate this complexity, prominent machine learning models are exploited to identify a non-linear relationship between curling and FWD deflections. A finite-element simulation of FWD is conducted to generate a vast data set, and a robust regression model is trained to estimate the total effective temperature difference (TETD) to quantify the effects of curling. Since input parameters for testing pavements can be measurable in the field, curling from TETD can be readily obtained using the proposed methodology. Comparative simulations highlight that the proposed models, with an MAE less than 0.5 °C significantly outperform the multiple regression performance, which registers an MAE of 3.45 °C in TETD, particularly in offering cost-effective and noise-tolerant prediction.

Evaluating the multifaceted impact of Cephalaria extract on dough quality: Antioxidant, antimicrobial, and cytotoxic properties

SummaryCephalaria syriaca, known as cephalaria, is an annual, pilose plant with pink‐purple flowers growing wild in wheat fields. Viscoelastic properties of gluten‐free doughs can be improved by adding cephalaria. However, this addition results in some undesirable properties in bread such as bitter taste and dark internal colour. This study aimed to reduce these effects by obtaining cephalaria obtained from distilled water and ethanol extracts and to increase the potential use of extracts in bread production. Different proportions of water and ethanol extracts obtained from oil‐free cephalaria were added to bread by creating a model with Mixture Design, and the optimum concentration was determined by farinograph trials. The antioxidative, antimicrobial, and cytotoxic effects of extract and the effect of cephalaria on yeast activity were examined. Cephalaria extracts had no measurable antimicrobial effect and no antifungal effect on Rhizopus stolonifer, while an antifungal effect was found against A. niger and P. expansum. The IC50 value was found to be 4.15 mg mL−1 for ethanol extract while the water extract had no effect on cells. The addition of extract had no negative effect on the number of yeasts in sourdough fermentation. The study has improved the usage of cephalaria by using water and ethanol extracts in dough.

Performance-Based Design of Ferronickel Slag Alkali-Activated Concrete for High Thermal Load Applications.

This study aimed to develop optimized alkali-activated concrete using ferronickel slag for high-temperature applications, focusing on minimizing environmental impact while maintaining high compressive strength and slump. A response surface methodology, specifically the mixture design of experiments, was employed to optimize five components: water, FNS-based alkali-activated binder, and three aggregate sizes. Twenty concrete mixes were tested for slump and compressive strength before and after exposure to 600 °C for two hours. The optimal mix achieved 88 MPa compressive strength before heat exposure and 34 MPa after, with a slump of 140 mm. An upscaled version with improved workability (210 mm slump) maintained similar unheated strength but showed reduced post-heating strength (23.5 MPa). Replacing limestone with olivine aggregates in the upscaled mix resulted in 65 MPa unheated and 32 MPa post-heating strengths. Life Cycle Analysis revealed that the optimized ferronickel slag alkali-activated concrete's CO2 emissions were 77% lower than those of ordinary Portland cement concrete of equivalent strength. This approach demonstrated the applicability of mixture design of experiments as an alternative design methodology for alkali activated concrete, providing a valuable performance-based design tool to advance the application of alkali-activated concrete in the construction industry, where no prescriptive standards for alkali-activated ferronickel concrete mix design exist. The study concluded that the developed ferronickel slag alkali-activated concrete, obtained through a performance-based mixture design methodology, offers a promising, environmentally friendly alternative for high-strength, high-temperature applications in construction.

Optimization of a mixture using coffee parchment, Jamaica flower and Stevia for functional infusions - hypoglycemic and antioxidant

Natural infusions have always been of great importance for the prevention and treatment of some diseases, because they are a very easy way to consume and availability of bioactive compounds with functional activity. Therefore, we proposed to optimise a mixture using coffee parchment (waste from the coffee industry), hibiscus flower and stevia. I-optimal mixture design (OMD) was used to optimise the proportions of the ingredients: coffee parchment (restriction from 57 to 60%), hibiscus flower (restriction from 37 to 40%) and stevia (restriction from 1 to 3%). The proportions were considered taking into account preliminary experimental tests, mainly on taste. The formulations were calculated on a 1.5 g basis. A sensory analysis was carried out on the three best treatments selected, and the average scores obtained for the attributes colour, odour and aroma were 4.13, 4.20 and 4.17 respectively, qualifying them with a "like", thus obtaining a functional infusion with coffee industry waste, organoleptically acceptable.

Design, modelling and optimisation of ultra high-performance fibre reinforced concrete incorporating waste materials

The adoption of ultra-high-performance fibre-reinforced concrete (UHPFRC) in modern-day construction has gradually increased because of its high compressive and flexural strength at the early production ages. The UHPFRC's high initial cost discourages its production and widespread use. This cost can be reduced by incorporating waste materials in UHPFRC production. This study aims to design, model, and optimise a three-day heat-cured UHPFRC incorporating waste materials. To produce a sustainable UHPFRC mixture, this study combines rice husk ash (RHA) and recycled tire steel fibre (RTSF) as the primary waste components, with Portland limestone cement, river sand, superplasticizer, and water. The concrete is heat-cured in a hot water bath at 90 °C for 3 days, resulting in rapid strength development. A D-optimal mixture design technique was used to optimise the mix proportions, and mathematical models were developed to predict the compressive and flexural strengths. The non-significant lack-of-fit results and the high values of coefficient of determination (R2) revealed the accuracy of the models in predicting the compressive and flexural strengths of the UHPFRC. The low values of standard deviation (SD) and coefficient of variation (CV) confirmed the consistency and reliability of the prediction models. A numerical optimisation revealed that it is possible to design a UHPFRC mixture with a lower cement content of 38.29% of the UHPFRC mix, resulting in a compressive strength of 117.62 MPa and a flexural strength of 36.32 MPa. The study reveals that integrating RHA and RTSF into UHPFRC can yield high-performance properties, offering innovative solutions for resource scarcity and environmental sustainability in the construction sector.

Enhancing anti-carbonation properties of oil well cement slurry through nanoparticle and cellulose fiber synergy

The anti-carbonation property of oil well cement (OWC) is critical for sealing efficiency of wellbores under geological CO2 sequestration. However, gas migration through OWC around wellbores may lead to a deterioration and failure of the entire storage system. Developing carbon-resistant cement has been the emerging trend in the research community. Previous studies mainly focused on nanoparticles alone to enhance performance of OWC, and the purpose of the research is to explore the synergy of nanoparticles and cellulose fiber (CF) in enhancing engineering properties (e.g., carbonation resistance) of oil well cement slurry. The focus was on investigating compressive strength, permeability, pore structure, and carbonation depth associated with the micro-level texture in a CO2 corrosion environment using X-ray diffraction, Scanning Electron Microscopy, and thermogravimetric analysis methods. Four nanoparticles, namely, nano-SiO2 (NS), nano-TiO2 (NT), nano-Al2O3 (NA), and nano-CaCO3 (NC), were selected for the mixture design. Results indicated that the incorporation of 1∼2 % NPs into the OWC paste resulted in a notable decrease in portlandite and an increase in calcium silicate hydrates, thereby enhancing compressive strength and hydration process. In addition, the single admixture of CF could minimize the formation of cracks in the cement matrix and reduce the average carbonation depth by 54 %. More importantly, the synergy of CF and NP significantly improved the resistance of OWC to carbonation, and the OWC mixed with CF and NS displayed the highest carbonation resistance.

Superhydrophobic foamed concrete based on response surface method: Mix design and its potential application in roofing systems

This study employs the response surface method to optimize the mixture design of superhydrophobic foamed concrete. The study investigates the influence of calcium stearate (CS, dosage 1 %∼5 %), polydimethylsiloxane (PDMS, dosage 2 %∼8 %), and hydroxypropyl methylcellulose (HPMC, dosage 0.05 %∼0.2 %) on various properties of foamed concrete, including density, compressive strength, contact angle, and water absorption. Additionally, the research explores the application of superhydrophobic foamed concrete in integrated roofing systems and assesses its thermal and structural performance through finite element analysis. Results reveal that foamed concrete achieves a contact angle greater than 150° when formulated with a mix ratio of CS (3 %), PDMS (8 %), and HPMC (0.05 %), or CS (3 %), PDMS (5 %), and HPMC (0.125 %). A negative linear correlation between the heat transfer coefficient and the thickness of foamed concrete is found. Furthermore, the heat transfer coefficient is inversely related to the spacing between the concave and convex drainage boards. Specifically, for a toe spacing of 50 mm and foamed concrete thickness exceeding 70 mm, the heat transfer coefficient of the roof measures 0.788 W/(m²·K). When the roof thickness increases from 70 mm to 100 mm, the roof heat transfer coefficient drops to 0.69 W/(m2∙K). When the toe spacing is increased from 50 mm to 60 mm, the heat transfer coefficient of the roof drops sharply to about 0.66 W/(m2∙K) at the thickness of 50 mm. The insulation requirements for the roof are satisfactorily met to 0.8 W/(m²·K). Under applied roof loads, the maximum von Mises stress experienced by the integrated roof is 0.6 MPa at a toe spacing of 50 mm. With the increase of the roof thickness, the maximum value of the DAMAGEC damage coefficient gradually decreases from 0.3 to 0.17. The maximum damage position has always been at the weak position of the four corners, which is consistent with the actual use status. The research findings on superhydrophobic foamed concrete have significant theoretical and engineering application value. Moreover, the construction of an "insulation/hydrophobic integrated" roof system demonstrates the feasibility of an integrated roof system and the potential for insulation/hydrophobic integration in roof system construction.

Hybrid extreme gradient boosting regressor models for the multi-objective mixture design optimization of cementitious mixtures incorporating mine tailings as fine aggregates

The design of cementitious mixtures incorporating mine tailings as fine aggregates is a multi-objective optimization (MOO) problem, in which both the uniaxial compressive strength (UCS) and cost of the mixtures need to be considered simultaneously. Given that data-driven methods have shown promising results when solving similar MOO problems, this study developed an extreme gradient boosting regressor (XGBR) model on a dataset extracted from the literature to predict the UCS. Among the efforts taken to improve the models, a genetic algorithm (GA)-based XGBR model demonstrated the optimal prediction performance, with an R2 of 0.959. Next, the GA-XGBR model and a cost equation were used as objective functions in the MOO problem. The non-dominated sorting genetic algorithm with elite strategy (NSGA-II) was selected to solve the optimization problem. A case study was conducted, generating mixture designs that offered improved trade-offs between cost and UCS compared to experimental designs. Finally, a graphical user interface was developed to provide access to the prediction model and optimization method. Overall, this work can be used as a guide for optimal mixture designs as it facilitates informed decision-making before the actual applications.

Design of a new low-noise pavement

This paper presents the results obtained from the tests carried out on the different asphalt mixes that have been developed as part of the PERSEUS project. This project aims to develop a low-noise pavement in which, in addition to traditional parameters such as texture or absorption, which have been defined based on aggregate size and void content, the aim has been to improve the acoustic response by introducing rubber as a substitute for part of the aggregate in the recipes. Within the framework of the project, porous mixtures and also stone mastic are being developed to determine the solution with the best acoustic characteristics and durability. The paper presents the results of acoustic characterization tests carried out (absorption, airflow resistance) in the phase of design of mixtures, as well as those obtained from the mechanical impedance test, which together with the results of the mechanical tests will conclude which is the ideal mixture to be tested on a stretch of road with real traffic.

Recommendations for Accurate Lipid Annotation and Semi-absolute Quantification from LC-MS/MS Datasets.

Recent developments in LC-MS instrumentation and analytical technologies together with bioinformatics tools supporting high-throughput processing of large omics datasets significantly enhanced our capabilities and efficiency of identification and quantification of lipids in diverse biological materials. However, each biological matrix is characterized by its unique lipid composition, thus requiring optimization of analytical and bioinformatics workflows for each studied lipidome. Here, we describe an integrated workflow for deep lipidome profiling, accurate annotation, and semi-absolute quantification of complex lipidomes based on reversed phase chromatography and high resolution mass spectrometry. This chapter provides details on selection of the optimal extraction protocol, acquisition of LC-MS/MS data for accurate annotation of lipid molecular species, and design of lipidome-specific mixtures of internal standards to assist quantitative analysis of complex, native lipidomes.

Synthesis and optimization of molecular weight of chitosan and carboxymethyl cellulose based polyurethanes

For the first time in this research, using a mixture design approach, polyurethanes (PUs) based on chitosan (CSN) and carboxymethyl cellulose (CMC) were synthesized to develop a high molecular weight polymer. In the synthesis process, a reaction between isophorone diisocyanate (IPDI) and hydroxyl-terminated polybutadiene was carried out to synthesize a prepolymer containing free NCO groups at the corners. This prepolymer was further reacted with changing moles ratio of CSN and CMC following the principles of statistical mixture design. The structural confirmation of the developed PUs was carried out through spectroscopic techniques (FTIR and NMR). The molecular weights of the PU specimens were characterized using gel permeation chromatography. The findings demonstrated that the interaction between CMC and CSN led to a notable increase in the molecular weights of the samples, supported by a significant p-value of 0.006. Additionally, the analysis of variance (ANOVA) disclosed that the employed mixture design and the resulting interaction model effectively account for 98 % of the total variation observed in the molecular weights. The sample labeled as PUS-3 (CMC0.50:CSN0.50) emerged as the most significant formulation, exhibiting a noteworthy 27.9 % improvement in the polymer molecular weight compared to the base sample, denoted as PUS-1 (CMC1.00:CSN0.00).

Advanced moisture control in porous aggregates for improved lightweight high-performance concrete

The porous lightweight aggregates in concrete experience a process of water absorption and desorption. This study aims to improve the performance of water-sensitive low water/binder (w/b) systems by effectively utilizing these water regulations. The effects of expanded shale (ES) substitutions and saturation levels (dry, half saturation, and saturation) on the fresh and hardened properties of mixtures with a w/b of 0.18 were investigated. The results indicated that, during the fresh stage, water absorption reduced workability and shortened the setting time. In the hardening stage, the released water improved hydration, increased internal relative humidity, and caused volumetric expansion, which reduced autogenous shrinkage. A comprehensive evaluation revealed that the optimal condition for ES was half-saturation with 4.0 wt.% pre-absorbed water. This condition achieved the best internal curing effect, improved workability, and optimal structural efficiency (strength/density). This study provides practical insights for the effective integration of porous aggregates in the mixture design and engineering applications.

Performance of natural asphalt as a paving material: A laboratory and field evaluation

The ever-growing need to build roads to meet the necessary transportation demands is challenging, especially for developing countries. Low-volume roads (LVRs) are usually the backbone of catalyzing economic growth in these countries. With impediments surrounding Petroleum bitumen (price fluctuations) and environmental concerns, scientists are putting their effort into finding an alternative. The presented research is an attempt to check if Natural asphalt can be used as a full or partial replacement of the Petroleum bitumen. To the best of the authors' knowledge, only limited studies have focused on characterizing and understanding the engineering properties of Natural asphalt. The available techniques do not provide reliable information to the road authorities and hence they are discouraged from using it in practice. Particularly for countries, where the Natural asphalt source is available, the overall dependence on importing the Bitumen could be substantially reduced. Empirical and experience-based design criteria may not be sufficient as the standards were never developed for such materials, hence, a scientific approach is required before bringing it into practice. In this research, Natural asphalt sourced from different locations in Nigeria was assessed. Before performing the mixture level tests using Marshall and Cantabro design methods, the rheological and fatigue properties of the extracted Natural bitumen were examined in the laboratory. In the design of the experiment, various percentages of Natural asphalt were added between 0 % and 20 % by total mix weight; implying that the remaining required fraction of binder was fulfilled by the addition of petroleum bitumen. By using a ranking system (supported by statistics), an optimal design of mixture was obtained which was used in the field (exposed to normal traffic) at 30 different sections. Overall, results showed a good correlation between laboratory and field performance as compared to the petroleum-based mixture which was used as a reference mixture

Optimization of novel sustainable Dictyota mertensii alginate films with beeswax using a simplex centroid mixture design

The environmental risks of synthetic polymers drive the need for innovative and sustainable film and packaging solutions. This study optimized the formulation of films composed of alginate derived from the brown seaweed Dictyota mertensii (ADM), glycerol, beeswax, and tween 80, aiming to improve their properties. A simplex-centroid blend design was employed to develop and optimize the composite films. The films were characterized based on their morphological properties, moisture content (MC), contact angle (CA), solubility (S), water vapor permeability (WVP), color parameters (L*, a*, and b*), opacity, tensile strength (TS), elongation at break (EB), and elastic modulus (E). Contour surfaces were plotted from the studied variables, fourth-order polynomial models were predicted, the influence of the blend components was analyzed, and the response variables were subjected to analysis of variance (ANOVA) and the F test with 95% confidence. The predicted conditions were experimentally validated. MC, WVP, solubility, opacity, a*, and b* were minimized, whereas CA, L*, TS, EB, and E were maximized, resulting in MC=6.85%, WVP=16.37 g.mm/h.kPa.m2, S=28.87%, CA=83.86°, Opacity=5.60 AU.nm.mm-1, L*=70.31, a*=4.79, b*=21.00, TS=11.76 MPa, EB=12.70%, and E=96.47 MPa. The overall desirability index was 0.70, resulting in an optimal biopolymer matrix of 75.00% ADM, 5.00% glycerol, 7.50% beeswax, and 12.50% Tween 80. The results highlight the potential of alginate films made from the brown seaweed Dictyota mertensii and the sustainable use of natural marine resources.

Maximization of Micractinium sp., biomass and use of Dual-Purpose reduced graphene supported vanadium oxide nanoparticles for harvesting and subsequent biodiesel production

A sustainable media composition comprising of nanourea (NU), groundnut de-oiled cake (GDOC), and seaweed Extract (SE) was formulated using a mixture design for the cultivation of Micractinium sp. Maximum biomass yield and productivity of 5.52 ± 0.09 g/L and 0.72 ± 0.03 g/L d−1 were observed at 1.67 mM NU, 0.134 g/L GDOC and 0.250 mL L−1 SE, respectively. The highest lipid yield of 2.73 ± 0.24 g/L was also observed, respectively. The reduced graphene-supported vanadium oxide nanoparticles (RGO-VNPs) with a net surface charge of + 34.10 mV were developed, which acted as a % as well as a catalyst for transesterification. A maximum flocculation efficiency of 98 % was observed with 200 ppm of RGO-VNPs. The Fatty Acid Methyl Ester (FAME) yield of 96.81 ± 1.61 % was observed. Thus, the present study could provide a plausible solution for one-pot harvesting and synthesis of biodiesel utilizing microalgal lipids.

A sustainable recycling process and its life cycle assessment for valorising post-consumer textile materials for thermal insulation applications.

The textile industry along with construction, electronics and plastic generate huge amounts of waste posing challenges to the adoption of the circular economy. This research presents a sustainable and low-cost recycling technology for conversion of post-consumer textile (denim) wastes to useful insulation materials. To accomplish the objective, nonwoven materials were produced using varying proportions of post-consumer recycled denim (r-denim) fibre and hollow polyester (PET) fibre using different punch densities in the needle punching process. Kowalski, Cornell and Vining mixture design, a special type of design of experiments, was adopted to develop the samples. Developed nonwoven materials were characterised for thermal resistance and tensile properties. The results show that nonwoven materials containing the minimum proportion (20%) of r-denim fibres exhibited the highest thermal resistance (0.131 W-1m2K). However, by adjusting the process parameter of the nonwovens, that is, the punch density, the same thermal resistance (0.131 W-1m2K) is also achieved even with 39% r-denim fibres. Additionally, the nonwovens produced from this blend proportion (r-denim:PET = 39:61) demonstrate a reasonable strength of 2.43 cN/tex. Environmental benefits of the developed r-denim/PET nonwovens have been evaluated by the life cycle assessment approach. Results show that the use of ~40% r-denim fibre has reduced the environmental burden significantly. Therefore, the nonwoven materials produced from post-consumer textile wastes hold tremendous potential as an alternative to synthetic fibres in thermal insulation applications. This recycling approach has immense potential to contribute to the efficient utilisation of post-consumer textile waste materials paving the way for environmental sustainability.