Enhancing deep eutectic solvent systems for efficient fermentable sugar recovery from lignocellulosic fiber.

Efficient conversion of sugars into fermentable sugars is a critical challenge in the cost-effective production of lignocellulosic biopolymers and biofuels. This study focuses on various sugar quantification techniques applied to Furcraea Foetida (Mauritius Hemp) samples, utilizing natural deep eutectic solvents (NADES) and deep eutectic solvents (DES) like urea, glycerol, citrates, pyrogallol (PY), and cetyltrimethylammonium bromide (CTAB). Employing a Taguchi-designed experiment, operational conditions were fine-tuned to evaluate the influence of time, concentration, and temperature on each deep eutectic solvent-based process. The emerging green solvent extraction approach demonstrated significant results, achieving notably high sugar yields compared to traditional techniques such as alkali, hot-water, and acid-mediated extraction. At a CTAB:PY molar ratio of 1:3, optimized for 60 min at 50 °C, the highest fermentable sugar (FS) yield of 0.6891 ± 0.0123 g FS/g LCB was attained-2 to 6 times higher than non-optimized values and 0.2 to 0.3 times higher than optimized traditional methods. In light of this, this research study emphasizes the pivotal significance of efficient sugar conversion through optimized deep eutectic solvent-based extraction methods, with a particular focus on Furcraea Foetida fibers, offering promising outcomes for the biofuel and biopolymer production industry.

Impact of infill density on morphology and mechanical properties of 3D printed ABS/CF-ABS composites using design of experiments.

Metal Extrusion (MEX) is a leading 3D printing technology for polymers, enabling intricate designs and personalized products in various applications. The current study evaluate how infill density affects the tensile, flexural, compressive, Izod impact and fracture behaviour of Acrylonitrile Butadiene Styrene (ABS) and Carbon Fiber Reinforced-Acrylonitrile Butadiene Styrene (CF-ABS) specimens manufactured using the MEX method. Different infill densities of 20, 40, 60 and 80 % are used in the production of honeycomb infill pattern samples for investigating the mechanical as well as fracture behaviour of MEX ABS/CF-ABS components. The experimental runs of fabricated composites were tested using a digital Izod impact tester and servo-controlled hydraulic universal testing machine, following ASTM standard procedures. The experimental findings show that CF-ABS specimens with an 80 % infill density and honeycomb fill pattern showed significant improvements in tensile strength, modulus, yield strength and elongation. The flexural strength (64.74 %), flexural modulus (209.15 %), compressive strength (125.21 %), compressive modulus (108.34 %) and impact strength (38.91 %) of these specimens are comparable to those of 3D printed ABS specimens and other infill densities. The research shows that precise management of processing variables can greatly improve the mechanical properties of 3D-printed ABS samples, providing valuable insights for a range of applications.

Enhancing real-time cell culture monitoring: Automated Raman model optimization with Taguchi method.

Raman spectroscopy has found widespread usage in monitoring cell culture processes both in research and practical applications. However, commonly, preprocessing methods, spectral regions, and modeling parameters have been chosen based on experience or trial-and-error strategies. These choices can significantly impact the performance of the models. There is an urgent need for a simple, effective, and automated approach to determine a suitable procedure for constructing accurate models. This paper introduces the adoption of a design of experiment (DoE) method to optimize partial least squares models for measuring the concentration of different components in cell culture bioreactors. The experimental implementation utilized the orthogonal test table L25(56). Within this framework, five factors were identified as control variables for the DoE method: the window width of Savitzky-Golay smoothing, the baseline correction method, the order of preprocessing steps, spectral regions, and the number of latent variables. The evaluation method for the model was considered as a factor subject to noise. The optimal combination of levels was determined through the signal-to-noise ratio response table employing Taguchi analysis. The effectiveness of this approach was validated through two cases, involving different cultivation scales, different Raman spectrometers, and different analytical components. The results consistently demonstrated that the proposed approach closely approximated the global optimum, regardless of data set size, predictive components, or the brand of Raman spectrometer. The performance of models recommended by the DoE strategy consistently surpassed those built using raw data, underscoring the reliability of models generated through this approach. When compared to exhaustive all-combination experiments, the DoE approach significantly reduces calculation times, making it highly practical for the implementation of Raman spectroscopy in bioprocess monitoring.

Computational fluid dynamics based Taguchi analysis on shear stress in microfluidic cerebrovascular channels.

The cerebrovascular blood vessels feed necessary agents such as oxygen, glucose, and so forth. to the brain which maintains the smooth functioning of the human body. However, the blood-brain barrier as a vascular border restricts the entry of drugs that can be necessary for the treatment of neurological disorders. The fluid shear stress in the cerebrovascular blood vessels may regulate the drug delivery in the interface between the cerebrovascular blood vessels and the brain. The intensity of influence by various factors that affects the shear stress in the cerebrovascular blood vessels is scarcely addressed in the present study. A hybrid approach of computational fluid dynamics and Taguchi analysis is proposed to evaluate the influence of various geometrical and operating factors on the shear stress in the microfluidic cerebrovascular channel. Furthermore, the non-Newtonian behavior of blood flow is considered to evaluate the shear stress in the microfluidic cerebrovascular channel. The Newtonian and six non-Newtonian fluids models of Carreau, Carreau-Yasuda, Casson, Cross, Ostwald-de Waele, and Herschel-Bulkley are numerically tested under various conditions of the flow rate, width, and height of the channel to find the viscosity influence on the shear stress. The Taguchi analysis consisting of range and variance analyses is applied to the L16 orthogonal array to evaluate the effect of various factors on shear stress in terms of influence order, range, F value, and percentage contribution. The parameters for the considered six non-Newtonian fluid models are proposed to accurately map the viscosity behavior with shear strain compared to the actual blood flow behavior. The Newtonian, Carreau, and Carreau-Yasuda non-Newtonian fluid models are found accurately with maximum errors between the experimental and numerical shear stress results as 2.17%, 1.30%, and 1.48%, respectively. The shear stress decreases with an increase in the width and height of the channel and a decrease in the viscosity for all flow rates. The porosity is evaluated as a highly influential factor followed by the flow rate, width, and height of the channel in decreasing order based on their effects on the shear stress. The modified shear stress equation is proposed with an accuracy of 0.96 by integrating the effect of porosity in addition to width, height, flow rate, and viscosity. The in-vitro microfluidic cerebrovascular model could be designed and manufactured based on the proposed results on influence order, F value, and percentage contribution of various factors in direction of achieving the in-vivo level shear stress.

Functionality Versus Sustainability for PLA in MEX 3D Printing: The Impact of Generic Process Control Factors on Flexural Response and Energy Efficiency.

Process sustainability vs. mechanical strength is a strong market-driven claim in Material Extrusion (MEX) Additive Manufacturing (AM). Especially for the most popular polymer, Polylactic Acid (PLA), the concurrent achievement of these opposing goals may become a puzzle, especially since MEX 3D-printing offers a variety of process parameters. Herein, multi-objective optimization of material deployment, 3D printing flexural response, and energy consumption in MEX AM with PLA is introduced. To evaluate the impact of the most important generic and device-independent control parameters on these responses, the Robust Design theory was employed. Raster Deposition Angle (RDA), Layer Thickness (LT), Infill Density (ID), Nozzle Temperature (NT), Bed Temperature (BT), and Printing Speed (PS) were selected to compile a five-level orthogonal array. A total of 25 experimental runs with five specimen replicas each accumulated 135 experiments. Analysis of variances and reduced quadratic regression models (RQRM) were used to decompose the impact of each parameter on the responses. The ID, RDA, and LT were ranked first in impact on printing time, material weight, flexural strength, and energy consumption, respectively. The RQRM predictive models were experimentally validated and hold significant technological merit, for the proper adjustment of process control parameters per the MEX 3D-printing case.

Optimization of Fatigue Performance of FDM ABS and Nylon Printed Parts.

This research work aims to proceed with the optimization of Fused Deposition Modeling (FDM) printing parameters for acrylonitrile butadiene styrene (ABS) and polyamide (Nylon) to improve fatigue resistance. For that purpose, the methodology of the paper involves two main approaches: experimental study and finite element analysis. The experimental part of the paper used the Taguchi method to find the effects of printing internal geometry, printing speed, and nozzle diameter on the fatigue life of ABS and Nylon plastic materials. ANCOVA multiple linear regression and sensitivity analysis was used to investigate the effects of printing parameters on the fatigue life of materials. The analysis of the results revealed: Nylon performed better than ABS, but had a higher slope; the 'tri-hexagon' structure resulted in the highest fatigue life, but the effect was statistically significant only for ABS material; the fatigue life of both materials increased with decreasing the nozzle diameter; the printing speed had no statistically significant influence neither on ABS nor Nylon. The experimental results then were validated by numerical simulations and the difference between the values was within ±14% depending on the experiment. Such differences might occur due to numerical and experimental errors.

Energy Consumption vs. Tensile Strength of Poly[methyl methacrylate] in Material Extrusion 3D Printing: The Impact of Six Control Settings.

The energy efficiency of material extrusion additive manufacturing has a significant impact on the economics and environmental footprint of the process. Control parameters that ensure 3D-printed functional products of premium quality and mechanical strength are an established market-driven requirement. To accomplish multiple objectives is challenging, especially for multi-purpose industrial polymers, such as the Poly[methyl methacrylate]. The current paper explores the contribution of six generic control factors (infill density, raster deposition angle, nozzle temperature, print speed, layer thickness, and bed temperature) to the energy performance of Poly[methyl methacrylate] over its mechanical performance. A five-level L25 Taguchi orthogonal array was composed, with five replicas, involving 135 experiments. The 3D printing time and the electrical consumption were documented with the stopwatch approach. The tensile strength, modulus, and toughness were experimentally obtained. The raster deposition angle and the printing speed were the first and second most influential control parameters on tensile strength. Layer thickness and printing speed were the corresponding ones for the energy consumption. Quadratic regression model equations for each response metric over the six control parameters were compiled and validated. Thus, the best compromise between energy efficiency and mechanical strength is achievable, and a tool creates significant value for engineering applications.

Performance analysis of autonomous UV disinfecting robot (UV bot) using Taguchi method.

As a result of the COVID-19 epidemic, there is a growing demand for robots to perform various operations which include service bots, cleaning, and disinfection bots. Viral contamination has been one of the major causes of human fatality which has abruptly increased in this situation. Availability of existing technologies is always surpassed by an effective one so as is the UV-Bot developed in this project. This bot aims for a highly accurate percentage of up to 96.8% of germ clearance at pre-defined conditions which are user-friendly. Also, the robot is designed in a compact size and effective shape to achieve maximum efficiency. The robot is deployed in hospital pathway and rooms for disinfection whereas human detection and obstacle avoidance has been included with a custom-developed algorithm that supports autonomous navigation and corner tracking facility. The robot also supports live streaming of the disinfecting site with an emergency alarm and stop in human detection. This type of robot is highly capable of destroying viral infections at a particular point which is validated using Taguchi analysis and also the robot is 3D modelled and tested using static and dynamic obstacles. Thus UV-Bot is manually controllable or autonomous which uses the A* algorithm to store or retrieve the disinfecting site map which is recorded if used frequently.

Analyzing musculoskeletal risk-severity among small scale casting workers using ergonomic assessment tools: A statistical approach.

BACKGROUND: Work-related musculoskeletal disorders (WMSDs) are leading cause of injuries among economically backward workers employed under small scale metal casting units especially in developing countries. In India, most casting unit's falls under small and medium enterprises having inadequacy of advanced technological equipment's due to several economic constraints and rely intensively on manual labour. Foundry work is very much prone to WMSDs involving much physical interaction of workers with their jobs which includes several risk factors. OBJECTIVE: The study objectives were to analyse the musculoskeletal risk prevalence among small scale casting workers using ergonomic assessment tools and statistical approach. METHODS: In present study, WMSDs risk prevalence has been examined using Rapid Entire Body Assessment (REBA) and virtual ergonomics. Further, risk evaluations were analysed using Mann-Whitney U test and Taguchi L25 orthogonal array. RESULTS: Results revealed manual handling task as being most vulnerable followed by the fettling section. Statistically significant differences were observed (p-value < 0.05) among all the work-sections except lift-lower task and molding section (p = 0.361; p > 0.05) for left side region; and lift-lower task and fettling section (p = 0.230; p > 0.05) for the right side region, where differences were not statistically significant. ANOVA results indicated that workstation height followed by population percentile and object weight were dominant factors significantly affecting the response parameter i.e. L4-L5 spine compression (p-value < 0.01); however workstation width (p-value > 0.05) had no significant effect. CONCLUSION: The present study may guide foundry industrialists in analysing the mismatch between the workers' job profile and redesigning existing workstation layouts in small scale foundries based on minimizing the WMSDs risk severity associated with the work tasks.

Optimization of selected casting parameters on the mechanical behaviour of Al 6061/glass powder composites.

Aluminum alloy and its composites have versatile applications and can be produced via a cost-effective stir casting technique. However, stir casting is faced with some challenges including segregation, occurrence of intermetallic phases, agglomeration, and inducement of residual stress. In view of minimizing these defects, casting should be done applying optimal parameters that will yield the desired outcome. The present study focused on the optimization of stirring parameters of temperature, speed, and time in the production of Al 6061/glass powder composite. Evaluated responses are tensile strength, compressive strength, impact strength, and hardness. The results showed that the process parameters had statistical significance on all properties at 95 % confidence level. Combined interactions of these parameters also presented significant effects on the property responses. Optimum setting for process factors as regards tensile strength were evaluated to be 600 °C, 400 rpm, and 30 min for temperature, speed, and time, respectively. For compressive strength, it is 600 °C, 500 rpm, and 30 min; for hardness, the optimum settings are 700 °C, 400 rpm, and 30 min, while in the case of impact strength, the optimum settings are 500 °C, 400 rpm, and 30 min respectively. Optimization of the combined characteristics was obtained at the optimum conditions of 500 °C, 400 rpm, and 30 min for stirring temperature, speed, and time. Moreso, the significance of the parameters on the composite in descending order is temperature, time, and speed.

Three-dimensional hierarchical porous carbon derived from lignin for supercapacitors: Insight into the hydrothermal carbonization and activation.

Three-dimensional hierarchical porous carbon is prepared by utilizing enzymatic hydrolysis lignin as a carbon source via hydrothermal carbonization and activation. The complicated operational parameters including temperature, time, concentration and pH in the hydrothermal carbonization are systemically investigated. We employed the hydrochar as electrode for supercapacitors. Accordingly, we not only achieve a high-performance specific capacitance for supercapacitors but also rationalize the effects of hydrothermal conditions on the specific capacitance via various characterizations. The activation process of hydrochar is also studied by comparing various activators and the activator/hydrochar ratios. The obtained materials possess a three-dimensional interconnected hierarchical structure with rational pore size distribution and a specific surface area reach up to 1504 m2 g-1. Then the corresponding supercapacitors achieve a large specific capacitance of 324 F g-1 as the current density is 0.5 A g-1. These supercapacitors acquire an outstanding cycling stability with 99.7% capacitance retention after 5000 cycles. The assembled symmetrical supercapacitors also show a high energy density of 17.9 W h kg-1 and can maintain at 5.6 W h kg-1 even at an ultra-high power density of 50,400 W kg-1.

Degradation of pentachlorophenol by hydroxyl radicals and sulfate radicals using electrochemical activation of peroxomonosulfate, peroxodisulfate and hydrogen peroxide.

The present study is to investigate the reactivity of free radicals (SO4(-) and HO) generated from common oxidants (peroxomonosulfate (PMS), peroxodisulfate (PDS) and hydrogen peroxide (HP)) activated by electrochemically generated Fe(2+)/Fe(3+) ions which furthermore are evaluated to destroy pentachlorophenol (PCP) in aqueous solution. The effect of solution pH and amount of oxidants (PMS, PDS and HP) in electrocoagulation (EC) on PCP degradation is analyzed in detail. The experimental results reveal that, optimum initial solution pH is 4.5 and PMS is more efficient oxidant addition in EC. 75% PCP degradation is achieved at 60min electrolysis time from PMS assisted EC. According to the first order rate constant, faster PCP degradation rate is obtained by PMS assisted EC. The PCP degradation rate by oxidant assisted EC is observed in the following order: EC/PMS>EC/PDS>EC/HP>EC. Further to identify the influences of experimental factors involved in PCP degradation by oxidant assisted EC, an experimental design based on an orthogonal array (OA) L9 (3(3)) is proposed using Taguchi method. The factors that most significantly affect the process robustness are identified as A (oxidant) and B (pH) which together account for nearly 86% of the variance.