Experimental Methodology Research Articles

From Molecule to Aggregate: Understanding AIE through Multiscale Experimental and Computational Techniques.

Aggregation-induced emission (AIE) phenomena have garnered significant attention due to their applications in various fields, ranging from materials science to biomedicine. Despite substantial progress, the underlying mechanism governing the AIE activity of molecules remains elusive. This study employs a comprehensive and multiscale approach, combining experimental and theoretical methodologies, to discern the determinants of AIE activity. Our investigations involve synthesizing four organic molecules with D-π-A-D architecture, accompanied by quantum mechanics (QM) and molecular dynamics (MD) simulations, providing a deep understanding of the interactions within aggregates. The symmetry-adapted perturbation theory (SAPT) calculations further corroborate our findings, revealing a clear correlation between AIE activity and the type of aggregate formed. Specifically, we demonstrate that AIE-active molecules exhibit a distinctive J-type aggregation characterized by enhanced emission from the S1 state. In contrast, AIE-inactive molecules adopt an H-type aggregate configuration, where the emission from the S1 state is constrained. In addition, we investigated the subcellular localization of the molecules, revealing localization within the lipid droplets. Our findings contribute to the fundamental understanding of AIE phenomena and provide insights into the design principles for AIE-active materials with potential applications in advanced sensing and imaging technologies.

Evaluating semantic control with transcranial magnetic stimulation: a systematic review with meta-analysis

BackgroundThis meta-analysis investigates the role of specific brain regions in semantic control processes using Transcranial Magnetic Stimulation (TMS). According to the Controlled Semantic Cognition framework, control processes help manage the contextually appropriate retrieval of semantic information by activating a distributed neural network, including the inferior frontal gyrus, the posterior middle temporal gyrus, and inferior parietal lobule. Lesions in these areas can lead to difficulties in manipulating weakly activated or competing semantic information. Researchers have used TMS to simulate such deficits in healthy individuals.MethodBy synthesizing results from TMS studies that targeted these regions, we aimed to evaluate whether neurostimulation over these areas can effectively impair participants’ performance under high semantic control demands.ResultsResults from different meta-analytical approaches consistently showed no significant effects of TMS, especially after correcting for publication bias. Nevertheless, variability in experimental methodologies was evident.ConclusionThese findings raise questions about the effectiveness of TMS in simulating deficits in semantic control and highlight the need for methodological improvements in future studies to enhance reliability and interpretability.

Trisodium Citrate‐Assisted Synthesis of Edge‐Abundant Nickel‐Iron Layered Double Hydroxides for Efficient Oxygen Evolution Reaction

AbstractThe edges of layered double hydroxides (LDHs) display an exceptionally more efficient oxygen evolution reaction (OER) activity than the (001) basal plane as demonstrated by both theoretical calculations and experimental studies. However, a controllable synthesis method of LDHs with abundant edges has yet to be described. Herein, we report a strategy enabling the synthesis of nickel‐iron LDHs with abundant edges (NiFe LDHs‐E) based on the use of citrate anions as the structure‐directing agent. The edge density is characterized using spectroscopy techniques and its OER performance is compared with that of nickel‐iron LDHs with abundant basal planes (NiFe LDHs‐B). In alkaline electrolyte (1 M KOH), NiFe LDHs‐E exhibits excellent OER activity with very low overpotential (235 mV at 10 mA cm−2) and current densities (at η = 320 mV) up to sixfold higher than those of NiFe LDHs‐B. Density functional theory (DFT) calculations confirm the high OER activities ascribed to the abundant side‐plane edges with optimal strength of binding of OER intermediates. Overall, a comprehensive investigation, employing both experimental and computational methodologies, yields new insights to fabricate superior catalysts meticulously designed with specific crystal planes and unveils the crucial structural attributes, thus unleashing the limitless potential of the catalytic domain.

Extracellular Lipases of Yarrowia lipolytica Yeast in Media Containing Plant Oils—Studies Supported by the Design of Experiment Methodology

Lipases are enzymes of great application importance in the food industry, in the cosmetic and detergent industries, in pharmacy and medicine, and in organic chemistry. Among lipases of various origins, those from microorganisms are currently the most commonly used. An excellent producer of lipases seems to be the nonconventional Yarrowia lipolytica yeast, but the biosynthesis of valuable metabolites depends on many factors. This study aimed to investigate the biodiversity of extracellular enzymes produced by four strains of Y. lipolytica, and to determine the optimal conditions of catalysis for the enzymes, according to temperature and pH, in a model hydrolysis reaction. Based on the obtained results, the biodiversity and strain dependence in lipase biosynthesis were observed. Using a Central Composite Design, it was found that temperature is the main factor in determining lipase activity. The enzymes produced by four different strains exhibited other substrate specificity, which was investigated using Latin square design methodology. Only two examined yeast strains, KKP 379 and W29, produced extracellular lipases at a high activity level towards medium- and long-chain fatty acid esters. Moreover, extracellular lipase from wild-type strain KKP 379 was further characterized, followed by exploring the activity of whole-cell biocatalyst and lyophilized enzyme solutions, and it was acknowledged that it was a “true” lipase with the highest affinity to p-nitrophenyl oleate.

Insight Into Factors Influencing the Aggregation Process in Wild-Type and P66R Mutant SOD1: Computational andSpectroscopic Approaches.

Disturbances in metal ion homeostasis associated with amyotrophic lateral sclerosis (ALS) have been described for several years, but the exact mechanism of involvement is not well understood. To elucidate the role of metalation in superoxide dismutase (SOD1) misfolding and aggregation, we comprehensively characterized the structural features (apo/holo forms) of WT-SOD1 and P66R mutant in loop IV. Using computational and experimental methodologies, we assessed the physicochemical properties of these variants and their correlation with protein aggregation at the molecular level. Modifications in apo-SOD1 compared to holo-SOD1 were more pronounced in flexibility, stability, hydrophobicity, and intramolecular interactions, as indicated by molecular dynamics simulations. The enzymatic activities of holo/apo-WT SOD1 were 1.30 and 1.88-fold of the holo/apo P66R mutant, respectively. Under amyloid-inducing conditions, decreased ANS fluorescence intensity in the apo-form relative to the holo-form suggested pre-fibrillar species and amyloid aggregate growth due to occluded hydrophobic pockets. FTIR spectroscopy revealed that apo-WT-SOD1 and apo-P66R exhibited a mixture of parallel and intermolecular β-sheet structures, indicative of aggregation propensity. Aggregate species were identified using TEM, Congo red staining, and ThT/ANS fluorescence spectroscopy. Thermodynamic analyses with GdnHCl demonstrated that metal deficit, mutation, and intramolecular disulfide bond reduction are essential for initiating SOD1 misfolding and aggregation. These disruptions destabilize the dimer-monomer equilibrium, promoting dimer dissociation into monomers and decreasing the thermodynamic stability of SOD1 variants, thus facilitating amyloid/amorphous aggregate formation. Our findings offer novel insights into protein aggregation mechanisms in disease pathology and highlight potential therapeutic strategies against toxic protein aggregation, including SOD1.

Study on the carbon sequestration effect of biochar in vegetable fields

This study was conducted using a field experiment methodology aimed at assessing the effects of biochar application on tomato growth and soil properties in greenhouse greenhouses. Biochar, a carbon-rich material produced by pyrolysis of biomass under anoxic conditions, has attracted attention for its potential in soil amelioration, carbon sequestration, and soil fertility enhancement. In this experiment, three biochar application levels of 0, 20, and 40 t/ha were designed to investigate the effects of different application rates on soil chemical properties and tomato growth.The study results showed that biochar application significantly increased soil pH by 0.05 to 0.1 units, which was beneficial in regulating acidic soil. Meanwhile, biochar application significantly increased total soil carbon content by 7.5 to 28.8%, indicating its effectiveness in enhancing soil carbon sequestration capacity. Although the enhancement of total soil nitrogen content by biochar was small (3.1 to 7.8%), this increase had a positive effect on crop growth. Considering the cost-effectiveness, this study recommends a one-time application of 40 t/ha of biochar, which can maintain the effect for at least 2 years, reducing the need for frequent applications and the associated economic costs.This study provides recommendations for optimization of biochar application and provides a scientific basis for sustainable agricultural development. By improving soil properties and increasing crop yields, this study contributes to the promotion of green development of agriculture and ecological civilization, and the realization of carbon and nutrient cycling in agroecosystems.The significance of this research focuses on evaluating the effects of biochar on soil properties and tomato production, thereby providing a scientific basis for fine-tuning application levels. Such optimization promotes sustainable farming practices, reduces agricultural waste emissions, enhances carbon and nutrient dynamics within agroecosystems, and reinforces the scientific foundation essential for progressing green agricultural development and building an ecological civilization.

Functional Feed for Laying Hens: Application of Saffron Extract as Eco-Friendly Supplement With Cholesterol-Lowering Properties.

Saffron has been utilized in numerous studies as an additive to augment egg quality and to enhance the oxidative stability of egg yolk.However, there is limited knowledge on the responses of hens to dietary supplementation with saffron petals on egg chemical composition, fecal mineral excretion, and ammonia emission. The objective of this study was to investigate the influence of saffron petal extract-enriched diet on egg quality, blood metabolites and odorous gas emission from excreta in laying hens. The experimental methodology involved a feeding trial conducted over a period of 12 weeks, using 200 Hy-line W36 laying hens aged 39 weeks. The dietary intervention included a basic diet (serving as a control with no supplementation), as well as diets fortified with 40, 60 or 80 parts per million (ppm) of hydroalcoholic saffron petal extract in a completely randomized design. Results showed that the inclusion of saffron petal extract in the diet did not significantly affect the egg crude protein, fat and ash content. However, a significant reduction (p<0.05) in yolk cholesterol concentration was observed. No substantial effect was noted on feed intake, feed conversion ratio (FCR) and egg weight (p>0.05). On the other hand, a significant increase (p<0.05) was documented in the egg production percentage of hens fed on the 80ppm saffron petal extract diet compared to the control. Furthermore, saffron petal extract supplementation resulted in a significantly lower yolk cholesterol together with reduced serum cholesterol content (p<0.05). Blood glucose and triglyceride concentrations also demonstrated a decrease subsequent to the inclusion of 80ppm saffron petal extract. The excretion of faecal minerals did not show any significant alterations due to the dietary interventions (p>0.05). Notably, hens supplemented with 60 and 80ppm saffron petal extract displayed significantly diminished concentrations of faecal ammonia (NH3) emissions (p<0.05) compared to the control. The study suggests that the inclusion of 80ppm saffron petal extract in the diet of laying hens may serve as a functional food source to mitigate cholesterol levels in egg yolk and blood serum, as well as to reduce faecal ammonia emissions.

University and Quality Systems. Evaluating faculty performance in face-to-face and online programs

The assessment of faculty or teaching staff performance is key in quality systems in the university context. This assessment is usually done through student satisfaction surveys that use Likert or BARS (Behavioral Anchored Rating Scales) instruments to measure student perceptions of teaching staff effectiveness. This paper examines the ambiguity, clarity, and precision of these two types of instruments. The authors, using an experimental methodology and with the participation of 2,223 students from four Spanish universities, during six academic years (between 2019 and 2024), analyze the three aspects mentioned (ambiguity, clarity, and precision) in both types of questionnaires. The results confirm the existence of significant differences between the instruments. The results also show that although doubts about the ambiguity, lack of clarity and precision of Likert-type questionnaires are justified, these aspects can be improved by BARS-type instruments. The conclusions drawn invite administrators and policymakers, quality agencies, and university managers to consider which of these two instruments is more appropriate for gathering the information they need to make better decisions about faculty promotion.

STDNet: Spatio-Temporal Decompose Network for Predicting Arctic Sea Ice Concentration

In the context of global warming, the accurate prediction of Arctic Sea Ice Concentration (SIC) is crucial for the development of Arctic shipping routes. We have therefore constructed a lightweight, non-recursive spatio-temporal prediction model, the Spatio-Temporal Decomposition Network (STDNet), to predict the daily SIC in the Arctic. The model is based on the Seasonal and Trend decomposition using Loess (STL) decomposition idea to decompose the model into trend and seasonal components. In addition, we have designed the Global Sparse Attention Module (GSAM) to help the model extract global information. STDNet not only extracts seasonal signals and trend information with periodical correspondence from the data but also obtains the spatio-temporal dependence features in the data. The experimental methodology involves predicting the next 10 days based on the first 10 days of data. The prediction results provided the following metrics for the 10-day forecast of STDNet: Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), and coefficient of determination of 1.988%, 3.541%, 5.843%, and 0.979, respectively. The average Binary Accuracy (BACC) at the beginning of September for the period 2018–2022 reached 93.85%. The proposed STDNet model outperforms and is lighter than existing deep-learning-based SIC prediction models.

Coupled Aero–Hydrodynamic Analysis in Floating Offshore Wind Turbines: A Review of Numerical and Experimental Methodologies

Floating offshore wind turbines (FOWTs) have received increasing attention as a crucial component in renewable energy systems in recent years. However, due to the intricate interactions between aerodynamics and hydrodynamics, accurately predicting the performance and response remains a challenging task. This study examines recent advancements in the coupled aero–hydrodynamic numerical simulations for horizontal-axis FOWTs, categorizing existing research by coupling methods: uncoupled, partially coupled, and fully coupled. The review summarizes models, methodologies, and key parameters investigated. Most partially coupled analyses rely on forced oscillation, while the interplay between aerodynamics and elasticity, as well as interactions among multiple FOWTs, remain under-explored. Additionally, this review describes relevant physical model tests, including wave basin tests, wind tunnel tests, and real-time hybrid tests (RTHT). Although RTHT faces issues related to system time delays, they have garnered significant attention for addressing scale effects. The paper compares the three coupling methods, emphasizing the importance of selecting the appropriate approach based on specific design stage requirements to balance accuracy and computational efficiency. Finally, it suggests future research directions, offering a meaningful reference for researchers engaged in studying the aero–hydrodynamic behavior of FOWTs.

Statistical models for predicting the higher heating value of torrefied kesambi leaves

The study investigates the effects of temperature and residence time on the energy density of kesambi leaves through experimental torrefaction, proximate analysis, and response surface methodology with a central composite design (RSM-CCD). The torrefaction process enhances the energy density of kesambi leaves by increasing fixed carbon content while reducing volatile matter. The RSM-CCD models developed in this research are both statistically significant and exhibit robust predictive accuracy for estimating higher heating value (HHV), providing valuable insights into optimal torrefaction conditions. Surface plots effectively illustrate the relationships between HHV, temperature, and residence time, enabling the identification of ideal process parameters. Additionally, a desirability analysis reveals opportunities to enhance correlations between HHV and key measured properties, such as moisture content, ash, and volatile matter. This research makes a significant contribution to understanding and optimising the torrefaction process for kesambi leaves, with practical implications for improving energy density and advancing the development of sustainable biofuel sources. By offering a novel approach to predicting HHV in kesambi leaf-based biofuels, the findings highlight the potential for optimising torrefaction processes to enhance the viability of renewable energy resources. Further research is suggested to refine these predictive models and explore additional factors influencing HHV, aiming to bolster the production of sustainable biofuels.

Experimental, numerical simulation and design methodology of axial compression performance of combined steel columns for modular buildings

Load-supporting columns of modular buildings are their key load-bearing components, but fewer research studies have been conducted so far. To investigate the effects of initial defects of components, bolt-hole sizes, end stiffness, and component slenderness ratios on the axial compressive performance of load-supporting columns, this paper carries out a full-scale modeling experimental study and parametric finite element analysis. Subsequently, the test and finite element results were compared with the predicted results of the specifications in China (GB 50017-2017), the United States (ANSI/AISC 360-22), and Australia (AS 4100-2020) to assess the appropriateness of the specifications. The results show: It is recommended that small-section high-strength bolts be used to connect the load-supporting columns. When the overall and local defect magnitude meets the accuracy requirements, the magnitude size has little effect on the component bearing capacity. The direction of the overall bending defect has little effect on the initial stiffness and peak load-carrying capacity of the steel tube spandrel column. When the regularized slenderness ratio of the components is less than 0.4, the reduction of the hinged restraint capacity is less than 10% compared with that of the stiffened restraint capacity. The Chinese specification can be used for component design and its predictions are on the conservative side. As the section width-to-thickness ratio becomes larger, the predictions of the U.S. specification change from an accurate prediction to one with too large an error. The Australian specification predictions were all on the unsafe side, but most components had errors of 10% or less. The results of this paper help to promote the development of modular building technology.

Investigating day-to-day route choices based on multi-scenario laboratory experiments, Part II: Route-dependent attraction-based stochastic process model

Laboratory experiments are one of the important means used to investigate travel choice behavior under strategic uncertainty. Many experiment-based studies have shown that the Nash equilibrium can predict aggregated route choices, while the fluctuations, whose mechanisms are still unclear, continue to exist until the end. To understand the fluctuations, this paper proposes a route-dependent attraction-based stochastic process model, which shares exactly the same behavioral foundation introduced in Part I of the study (Qi et al., 2023), i.e., route-dependent inertia and route-dependent preference. The model predictions are carefully compared with the experimental observations obtained from the congestible parallel-route laboratory experiments containing 312 subjects and eight decision-making scenarios (Qi et al., 2023). The results show that the proposed stochastic process model can precisely reproduce the random oscillations both in terms of flow switching and route flow evolution. Subsequently, an approximated model is developed to enhance the efficiency in evaluating the equilibrium distribution, providing a practical tool to evaluate the impacts of transportation policies in both long- and short-term runs. To the best of our knowledge, this paper is the first attempt to model and explain experimental phenomena by introducing stochastic process theories, as well as a successful example of applying experimental economics methodology to improve our understanding of human travel choice behavior.

Enhancing high-performance concrete with local andesite and calcined marl: Insights from heat treatment and untreated conditions

This study explores the incorporation of local Algerian andesite and calcined marl as supplementary cementitious materials in high-performance concrete (HPC), with a special focus on the effects of heat treatment. Advanced analytical techniques, including X-ray diffraction (XRD), X-ray fluorescence (XRF), scanning electron microscopy (SEM), and thermogravimetric analysis (TGA), were used for material characterization. The Sherbrooke method was utilized for mix design optimization, and thermal curing effects were critically evaluated. Key results demonstrated that both andesite and calcined marl significantly enhance HPC performance. Fresh mixtures showed excellent workability and consistent density. In the hardened state, these admixtures reduced porosity and water absorption capacity, improving durability. Heat-treated samples exhibited substantial early strength gains, while non-heat-treated samples showed superior long-term strength due to ongoing pozzolanic activity. Ultrasonic pulse velocity (UPV) measurements confirmed the high quality of the concrete. Tomography revealed a dense pore structure and strong interfacial transition zones, contributing to overall performance. Statistical modeling using the Design of Experiments (DOE) methodology validated the experimental findings and identified optimal conditions for maximizing compressive strength. Sulfuric acid exposure tests indicated good chemical resistance, with balanced performance in maintaining residual strengths and managing weight losses. This research underscores the potential of using local andesite and calcined marl to enhance HPC, promoting sustainable construction practices in Algeria by reducing reliance on imports and utilizing regional resources. In summary, this study contributes to sustainable HPC development by demonstrating the effectiveness of local mineral admixtures. The dual benefits of heat treatment for early strength gain and non-heat-treated conditions for long-term durability offer valuable insights for optimizing HPC formulations, advancing our understanding of pozzolanic materials, and promoting environmental stewardship and economic efficiency in the construction industry.

Characterization of high-performance composite bricks fabricated from recycled HDPE/PS blends and brick powder

Abstract This study explores the feasibility and benefits of utilizing plastic waste in the production of construction materials, specifically composite bricks. The escalating accumulation of plastic waste poses significant environmental challenges, which necessitates innovative approaches for recycling and re-utilization to mitigate pollution and reduce landfill use. Our research focuses on the synthesis of bricks by incorporating high-density polyethylene (HDPE) and polystyrene (PS) with sand brick powder, utilizing a compatibilizer (SBS-g-MA) to enhance interfacial adhesion and mechanical integrity. The experimental methodology involved the preparation of composite materials through melt mixing, followed by molding to form brick specimens. These were analyzed for their mechanical properties, including tensile strength, Young’s modulus, and elongation at break, as well as thermal properties such as degradation temperature and crystallization behavior. Results showed that the inclusion of sand brick powder significantly enhances the thermal stability of the composites, as evidenced by the higher degradation temperatures observed. Specifically, the degradation temperature increased from 300.59 °C in pure HDPE/PS blends to 420.39 °C in composites with 7% brick powder, suggesting the formation of a protective barrier against thermal decomposition. Moreover, mechanical testing revealed that composites with up to 7% brick powder exhibited improved tensile strength and Young’s modulus compared to pure polymer blends.

Comparative Study of Silicon and Silicon Carbide Semiconductors

This research paper provides an in - depth comparison of intrinsic and extrinsic semiconductors, focusing on their electrical properties, mechanisms of operation, and implications for technological applications. Through a detailed examination of band theory, charge carrier dynamics, and the impact of doping, this study elucidates the fundamental differences between these two types of semiconductors. Utilizing silicon as the primary material, the paper explores how these differences influence the efficiency and functionality of semiconductor devices, addressing potential uncertainties in experimental methodologies and highlighting recent breakthroughs in the field.

Antidiabetic Effectiveness Test of Bitter melon (Momordica charantia L) Extract Suspension in Male White Mice (Mus musculus)

Diabetes mellitus is a metabolic disorder characterised by the inability of the pancreas to produce the hormone insulin in accordance with the body's requirements. Diabetes mellitus is a lifelong disease and, as yet, there is no cure. The costs associated with diabetes mellitus drugs are currently quite expensive. The utilisation of traditional medicinal practices involving the use of medicinal plants represents an alternative treatment option that employs natural ingredients with minimal side effects. One such example is the use of bitter melon (Momordica charantia L.), which has been demonstrated to possess antidiabetic properties. The objective of this study was to ascertain the antidiabetic efficacy of a bitter melon fruit extract suspension formula. This study employed an experimental methodology, whereby a suspension formulation of bitter melon fruit extract was prepared with three distinct doses. A total of 25 male white mice, induced with alloxan, were selected as test animals and divided into five treatment groups. Group X1 received a dose of 150 mg/kg b.w., Group X2 received a dose of 300 mg/kg b.w., Group X3 received a dose of 450 mg/kg b.w., while the negative control and positive control groups were also included. The data were subsequently analysed using the statistical software package SPSS (version 27), which included tests for normality, homogeneity, one-way ANOVA and the T-test. The findings of this study indicate that the treatment group, which received a suspension of bitter melon fruit extract at a dose of 450 mg/kg bw, exhibited a superior efficacy in reducing blood glucose levels, approaching the level observed in the positive control group.

Multivariate image analysis for assessment of textural attributes in transglutaminase-reconstituted meat

The control of sensorial textural attributes has high interest to the meat industry focused on the recovery of the value of meat by-products by developing reconstituted meat pieces with added sensory and nutritional values. Sensorial analysis of foods is still a quite subjective methodology, highly dependent of a well-trained team of inspectors, which is simulated by textural analysis in order to measure objective physical properties. This work presents a non-destructive and contactless experimental methodology to predict the physical properties of a reconstituted meat product, based on integrating multispectral imaging and multivariate image analysis (MIA). The experiment was based on reconstituting grounded meat with different concentrations of transglutaminase (0.1, 1, 3, 6 and 10 %), from which textural properties and multispectral imaging data were measured. Multispectral images (UV, VIS and NIR wavelengths) were processed with chemometric procedures to obtain the distribution maps and score images, from which different blocks of features were extracted to generate feature vectors (basic statistics and co-occurrence matrix) for each image. The obtained regression models built with these features predicted all physical properties of the meat with Q2 > 0.90, after feature selection using VIPs. These results evidenced the capacity of multispectral imaging, combined with chemometric procedures, to capture the variability of physical properties induced by transglutaminase in a derivate meat product. It could represent the base of a potential contactless application for a meat industrial inspection, where work environments have strong hygienic requirements.

Diode Laser Absorption Spectroscopy and DSMC Calculations for the Determination of Species-Specific Diffusion Coefficients of a CO2-N2O Gas Mixture in the Transition Gas Regime

Multicomponent gas mixture diffusion in a microscale confined flow in the transition gas regime at Knudsen numbers (Kn) above 0.1 has potential engineering applications in gas-phase microfluidics. Although the calculation of the diffusion coefficient accounts for the influence of the concentration of other species in a multicomponent gas mixture, the higher rate of gas-wall collision at 0.1 &lt; Kn ≤ 10 introduces additional complications not predicted by conventional calculation methods. Thus, simultaneous measurement of diffusion coefficients for multiple gas species ensures accurate estimation of the diffusion coefficient of a particular species that includes the effect of interactions with other species and wall surface conditions in a multicomponent gas mixture at Kn &gt; 0.1. However, most experimental methods for measuring the diffusion coefficient are not species-specific and therefore cannot directly differentiate between the species diffusing in a gas mixture. Thus, this paper demonstrates a new experiment methodology consisting of a two-bulb diffusion configuration accompanied by a tunable diode laser absorption spectroscopy detection technique for species-specific, in-situ, simultaneous measurement of the effective diffusion coefficient for a CO2-N2O gas mixture in the transition gas regime. The experimental results are compared against direct simulation Monte Carlo calculations and the Bosanquet approximation showing a deviation that has not been reported in the literature before.

Impact of structural characteristics on energy-absorption of 3D-printed thermoplastic polyurethane line-oriented structures

Purpose Additive manufacturing offers the ability to produce complex, flexible structures from materials like thermoplastic polyurethane (TPU) for energy-absorption applications. However, selecting optimal structural parameters to achieve desired mechanical responses remains a challenge. This study aims to investigate the influence of key structural characteristics on the energy absorption and dissipation behavior and the deformation process of 3D-printed flexible TPU line-oriented structures. Design/methodology/approach Samples with varying line orientations and infill densities were fabricated using material extrusion and subjected to quasi-static compression tests. The design of experiments methodology explored the significance of design variables and their interaction effects on energy absorption and dissipation. Findings The results revealed a statistically significant interaction between infill density and orientation, highlighting their combined influence; however, the effect was less pronounced compared to infill density alone. For low-density structures, changing the orientation from 0°/90° to 45°/−45° and increasing infill density enhanced energy absorption and dissipation, while high-density structures exhibited unique energy absorption behavior influenced by deformation patterns and heterogeneity levels. This study facilitates the prediction of mechanical responses and selection of suitable TPU line-oriented printed parts for energy absorbing applications. Originality/value To the best of the authors’ knowledge, the present work have investigated for the first time the energy-related responses of flexible line-oriented TPU structures highlighting the distinction between the low and high density structures.