Experimental Process Optimization Research Articles

Design of Experiments for Process Optimization of the Direct Wacker-Type Oxidation of 1-Decene to n-Decanal

Design of Experiments for Process Optimization of the Direct Wacker-Type Oxidation of 1-Decene to n-Decanal

Extraction of rare earths from coal and coal by-products as a non-traditional source

Rare earth elements (REEs) are one of the critical metals used for modern technological applications and green technologies. Due to growing demand and limited availability, there is a huge supply risk associated with REEs. The primary resources of rare earths in India are limited and associated with many processing challenges. In this scenario, it is important and timely to explore the non-traditional sources of rare earths to meet the domestic demand of country in the future. India is rich in coal deposits. The studies are very limited and there is scarcity of the research work carried out on the extraction of rare earths from Indian coal and coal by-products. Therefore, the objective of the present research article is to highlight the presence of REEs in Indian coal along with coal by-products. The objective is to identify the sweet pots of rare earths in coal and coal by-products. The concentration of total REEs is in the range of 150–200 ppm in coal samples. Furthermore, coal ash contains the concentration of total REEs which is more than 600 ppm in the samples of study area. It is aimed to review the several methods to recover rare earths that can be economically applied for the extraction of rare earths from coal and its by-products. Column leaching experiments achieve a 50% recovery rate of REEs from coal, while thermal treatment of coal enhances the recovery rate by one and a half times compared to untreated samples. Process optimization experiments demonstrate the superiority of the flocculator jar test apparatus, resulting in a significant increase in REE recovery (52% from coal samples). It was found that there is a huge work is still needed to be done for the development of an energy efficient and economical recovery of rare earths from coal and its by-products.

Process optimization of 4H-SiC chemical mechanical polishing based on grey relational analysis

Ultra-smooth and low-damage processing of single-crystalline 4 H-SiC has become a research focus as a substrate for third-generation semiconductor wafers. However, the high hardness and strong chemical inertia significantly affect 4 H-SiC chemical-mechanical polishing (CMP) efficiency and accuracy. In this study, polishing process optimization experiments of 4 H-SiC are conducted based on the grey relational analysis method to achieve low surface roughness (Ra) and high material removal rate (MRR). First, MRR and Ra of Si surface (0001) are obtained by orthogonal experiments considering down force, rotation speed, slurry flow rate and abrasive particle size as four key factors. Then the grey relational coefficient and grey relational grade of MRR and Ra are calculated by data processing. The results show that significant factors of the single-objective process are rotation speed, down force, particle size, and flow rate, while the factors of the multi-objective process are down force, flow rate, rotation speed, and particle size in turn. Finally, the MRR of 208.12 nm h−1 and Ra of 0.391 nm are polished using multi-objective optimization process parameters. The polishing efficiency and accuracy were improved, confirming the applicability of grey relational analysis in CMP.

Application of Parametric Modeling in Atomic Layer Deposition

Atomic Layer Deposition (ALD) is sequential and conformal process that provides precise thickness control due to its self-limiting nature even in high aspect ratio structures. The exponential growth in the use of ALD is due the availability of hundreds of precursor chemistries for diverse technological applications beyond just semiconductors and microelectronics. However, one of recurring challenges is the problem of results disparity, and errors that underline the causes of disparity, primarily may be due to lack of consistency in process optimization and reproducibility. In this research, a Design of Experiment (DoE) approach is adopted for parametric optimization for synthesis of Al2O3 thin films using ALD. The objective of this work is to adopt DoE for reproducible ALD synthesis processes within statistical reliability.Briefly, the precursors used for Al2O3 ALD (Ultratech Veeco Thermal ALD) were Trimethylaluminum (TMA) and H2O with Ozone. The effect of four parameters, namely pulse duration of TMA and water, number of cycles, and temperature were evaluated for the response parameter of Al2O3 thickness on Si with 300 nm of SiO2. E-Chip DoE software was chosen for data modeling. E-Chip considers multivariate analysis to provide the parametric relationship for Analysis of Variances (ANOVA) and predictive surface response analysis, thus eliminating the need for extensive process optimization experiments that are required for full factorial design. Initially, screening experiments were conducted to determine the levels of input parameters. The pulse duration for TMA and H2O were 0.01-0.02 sec, the number of cycles were varied between 50 and 100, the temperature range was 100-200 0C. For each sample, five thickness and roughness readings were measured on an ex-situ ellipsometer and Atomic Force Microscope (AFM). The stoichiometry of Al2O3 thin films were evaluated using XPS.The data analysis reveals that the influential parameters are number of cycles, pulse duration, and temperature in the order of their significance. The direct relationship between number of cycles and Al2O3 thickness infers that flux available is effectively used for layer growth. The consistency of layer thickness is related not just to the conformality but also to the adsorption of reactive species effectively. Uneven pulse duration also contributes to the linear growth of layer thickness, which supports the effectiveness of reactive species saturation and purging of un-reactive elements. The temperature variation was also an influential parameter as it affected the vapor pressure for TMA and H2O. This mechanistic model based on DoE is a suitable tool to predict the ALD’s growth per cycle, which can further help in understanding of any chemisorption with substrate treatment or variation in film roughness characteristics. Study of other DoE parameters such as type of substrate, substrate functionalization, reactor size in relation to the size of substrate, and purge duration are ongoing. Figure 1 describes the ANOVA chart estimates and surface response graphs, which identifies the bounded parametric region along with the ability to predict the influence of change in parameters based on developed mechanistic model. Figure 1

COSMO-SAC model approach for deep eutectic solvent selection to extract quercetin from macela (A. satureioides) and experimental process optimization

COSMO-SAC model approach for deep eutectic solvent selection to extract quercetin from macela (A. satureioides) and experimental process optimization

Data-science driven autonomous process optimization

Autonomous process optimization involves the human intervention-free exploration of a range process parameters to improve responses such as product yield and selectivity. Utilizing off-the-shelf components, we develop a closed-loop system for carrying out parallel autonomous process optimization experiments in batch. Upon implementation of our system in the optimization of a stereoselective Suzuki-Miyaura coupling, we find that the definition of a set of meaningful, broad, and unbiased process parameters is the most critical aspect of successful optimization. Importantly, we discern that phosphine ligand, a categorical parameter, is vital to determination of the reaction outcome. To date, categorical parameter selection has relied on chemical intuition, potentially introducing bias into the experimental design. In seeking a systematic method for selecting a diverse set of phosphine ligands, we develop a strategy that leverages computed molecular feature clustering. The resulting optimization uncovers conditions to selectively access the desired product isomer in high yield.

Numerical modeling and simulation for laser beam welding of ultrafine-grained aluminium

Laser beam welding of aluminium offers huge potential for a wide variety of welding of different thickness parts with the method of thermal conductivity due to the relatively high difference between melting temperature and evaporation. However, due to the high melting temperature and good thermal conductivity of this light metal, the temperature gradients during the welding process are usually high, causing residual stresses in the weld, which can lead to undesirable deterioration of the weld pool properties and the quality of the process. Physical modelling and simulations of the laser welding process are powerful tools for gaining a fundamental understanding of the technological process. They are also a suitable tool for preliminary assessment of the intervals in which the real preliminary experiments for process optimization should take place. This work is devoted to the numerical modelling of the process of welding ultrafine-grained aluminium using a fibre laser. A three-dimensional model of the welding process was created, using the finite element method implemented in the program ABAQUS. The temperature fields at depth z and on the surface x, y in the welded samples is determined. The temperature change as a function of time for different coordinates of the weld is also analysed. During numerical calculations, the power, machining speed and diameter of the workplace are variable. The obtained results are compared with real experiments conducted in the laboratory by other researchers.

Application of tools and techniques of quality by design in pharmaceutical process

PurposeThe purpose of this article is to demonstrate the application of the tools and techniques of Quality by Design (QbD) approach in an Indian pharmaceutical drug product manufacturing company and to understand the challenges, managerial implications and lessons learned while implementing this initiative.Design/methodology/approachThis work adopts the Action Research methodology for impurity reduction in a drug product manufacturing company in India by using the tools and techniques of QbD approach. Various QbD tools like Design of experiments, process capability evaluation and control charts were effectively utilized for the study.FindingsAs a part of QbD implementation in the organization, a specific drug product was identified and the impurity level in the product was studied. Significant variables impacting the impurity were identified and the optimum levels for the significant variables were identified through design of experiments. The solutions were implemented and the impurity levels were reduced significantly.Research limitations/implicationsEven though the article is based on a single case study related to tools and techniques of QbD in a single organization in India, the identified problem is a generic product quality related issue for any pharmaceutical drug product manufacturing company. Hence the findings of this research are applicable to pharmaceutical drug manufacturing industry in general.Originality/valueThis article illustrates the systematic usage of various tools and techniques of QbD methodology in a pharmaceutical drug product manufacturing company. The usage of Design of Experiments for process optimization and application of other tools and techniques are ready references for the practitioners and novice users in the field.

Experimental investigation on a novel approach for laser surface hardening modelling

Laser surface hardening is rapidly growing in industrial applications due to its high flexibility, accuracy, cleanness and energy efficiency. However, the experimental process optimization can be a tricky task due to the number of involved parameters, thus suggesting for alternative approaches such as reliable numerical simulations. Conventional laser hardening models compute the achieved hardness on the basis of microstructure predictions due to carbon diffusion during the process heat thermal cycle. Nevertheless, this approach is very time consuming and not allows to simulate real complex products during laser treatments. To overcome this limitation, a novel simplified approach for laser surface hardening modelling is presented and discussed. The basic assumption consists in neglecting the austenite homogenization due to the short time and the insufficient carbon diffusion during the heating phase of the process. In the present work, this assumption is experimentally verified through nano-hardness measurements on C45 carbon steel samples both laser and oven treated by means of atomic force microscopy (AFM) technique.

Catalytic condition optimization in the conversion of nootkatone from valencene byYarrowia lipolytica

Yarrowia lipolytica was a widespread and promising object in biotechnology, which was used to increase the biotransformation of valencene into nootkatone in shake flasks in this study. The main objective of this work is to determine the optimum combination of transformation conditions in shake flasks on the basis of single factor process optimization experiment. The results showed that Y. lipolytica was cultured in medium for 36 hr (exponential phase) and the amount of added Y. lipolytica was 5% (v/v). The concentration of substrate valencene was 920 mg·L−1, and the transformation time was 36 hr after adding substrates. Dimethyl sulfoxide, a water-soluble organic solvent, was used as a co-solvent with a concentration of 0.8% (v/v). The maximum production of nootkatone was 628.41 ± 18.60 mg·L−1 and the conversion rate was 68.30 ± 2.02% at cultivation conditions of 32°C, 150 rpm, and PH 5.30. The results showed that optimizing the catalytic conditions can significantly increase the yield of nootkatone by Y. lipolytica. Practical applications Recently, natural nootkatone is increasingly important due to its flavoring and physiological effects, but the amount of nootkatone in plants is low and cannot meet the demand. Also, there were few studies about microbial transformation of valencene by Yarrowia lipolytica under certain catalytic conditions. We demonstrated that optimizing the catalytic conditions can significantly increase the yield of nootkatone. Therefore, it provides a basis for the subsequent use of genetic engineering to transform Y. lipolytica to produce nootkatone.

Study of flow-induced fiber in-plane deformation during high pressure resin transfer molding

High Pressure Resin Transfer Molding (HP-RTM) is a new variant of composite Resin Transfer Molding (RTM) process that enables a short cycle time and a high composite strength to weight ratio, thus presents a great potential for fabricating automotive structural parts. Due to the high injection pressure, fiber-tow washout is becoming one of the major defects which impact the properties of composite materials. To predict and mitigate the fiber-tow washout problem, approaches of both experimental process optimization and computational prediction are essential. In this paper, an experimental study of fiber-tow washout is undertaken to determine the flow injection limits beyond which the preform deformation can be observed at various fiber volume fractions. A feasibility map is developed for a specific fabric and resin combination. It provides a means to determine the injection rates and fiber volume fractions to fabricate a quality part with minimal in-plane fiber washout due to the hydrodynamically flow-induced force during the HP-RTM process.

Analysis of the Influence of Blaine Numbers and Firing Temperature on Iron Ore Pellets Properties Using RSM-I-Optimal Design: An Approach Toward Suitability

Cold compressive strength (CCS) and apparent porosity (AP) of pellets are essential properties regarding the burden of blast furnaces. The optimal required values for industries are 2.5 KN CCS and 21% AP. Blaine fineness and firing temperature are the decisive parameters analyzed here. During firing, microstructure phases such as silicate, hematite, and pore are formed. The phase’s grain density during induration influences the pellet’s CCS and AP. The influence of the factors over the response is evaluated by I-optimal (response surface methodology) design. Blaine fineness, firing temperature, pore phase grain density (PPGD), silicate phase grain density (SPGD), and hematite phase grain density (HPGD) affect the CCS and AP of pellets. The RSM-I-optimal predicted responses with a coefficient of determination (R2) of 0.89 for CCS and 0.91 for AP of iron ore pellets. Optimal conditions were Blaine no. = 1668 cm2/g, 1250 °C firing temperature, PPGD value 90 no/mm2, SPGD value 250 no/mm2, and HPGD value 490 no/mm2, with 4.5 KN CCS 27%. The induration processes were investigated through statistical design of experiments for process optimization. Statistical analysis indicated the direct and interactive influence over CCS and AP. In this study, RSM-I-optimal modeling is used for iron ore pellets processing. The I-optimal prediction could be applied to make the process economical because information is obtained through fewer experiments.

Valorization of solid waste from oil refining and biodiesel industries for the biorecovery of rare earth elements

Two types of solid waste generated in large amounts in oil refining and biocombustible industries, i.e., spent cracking catalyst and unprofitable raw glycerin were concomitantly valorized. Experiments for process optimization were carried out in two successive steps. First, a 24 full-factorial experimental design was adopted to estimate the effects of four variables and, their interaction, on the rare earth metal biorecovery from spent cracking catalyst using Yarrowia lipolytica cell-free fermented medium (growth as expenses of raw glycerin as the main carbon source): pulp density, bioleaching temperature, contact time, and raw glycerin concentration in microbial culture. Next, tests were executed to maximize the biorecovery, considering the previous results in the experimental design. The optimized process conditions were found to be pulp density, 0.4% (m/v); bioleaching temperature, 50 °C; contact time, 45 min; and bioleaching production using 56 g/L of biodiesel-derived glycerin in the mineral medium. In such process conditions, up to 90% of La, Nd, and Ce were recovered. All of the biomining tests were carried out in 500-mL Erlenmeyer flasks and contained 100 mL of the cell-free fermented medium. Thermally or chemically pretreated catalysts or raw glycerin was not used in this study and the yeast strain was not previously adapted to the contaminants (organics or metals). Other goals were to reduce the process stages, seeking economic viability for future larger-scale (scale-up) studies.

A low-molecular-weight ascophyllan prepared from Ascophyllum nodosum: Optimization, analysis and biological activities

In this study, a low-molecular-weight saccharide fragment (LMWAs-L) was prepared from alginate lyase (EC 4.2.2.3) hydrolyzed ascophyllan by ultra-filtration separation method. LMWAs-L was a homogeneous saccharide fraction with an average molecular weight of 6.96 kDa. Enzymolysis process optimization experiments revealed that the optimum process parameters for preparing LMWAs-L were the enzyme concentration 0.02 U/mL, initial pH 6.8, and enzymolysis temperature 43 °C. After optimization, the yield of LMWAs-L was increased to 9.74% higher than that without optimization. Interestingly, LMWAs-L exhibited stronger enhancing activities on the proliferation and migration of human skin fibroblasts cells in vitro and better antibacterial activities as compared to native ascophyllan at the same mass concentration. Our study establishes a simple way to prepare low-molecular-weight saccharide with beneficial bioactivities from ascophyllan efficiently. This is the first report to reveal that ascophyllan and its low-molecular-weight saccharide have the potentials to be developed as natural biological dressing and antibacterial agents.

Process Optimization Experiment of Preparing Light Ceramsite from Qinghai Reshui Coal Gangue

Qinghai has abundant coal resources, but the accumulation of coal gangue poses a certain threat to the fragile ecology of the area. In this paper, coal gangue light ceramsite was prepared by using coal gangue from Qinghai Reshui coal mine as raw material and sodium carbonate as auxiliary material. The optimized process conditions are as follows: the mass ratio coal of gangue and sodium carbonate = 50:1 (10% hydrochloric acid contamination); the drying temperature is 105±2°C; the drying time is 90min; preheating temperature is 450°C; the preheating time is 10 min; the calcination temperature is 950 °C; the roasting time is 15 min. The ceramsite prepared under this condition has a packing density of 423 kg/m3 and a bulk density of 889 kg/m3. The process does not use fly ash, and all the coal gangue raw materials were used without any residue, which can effectively reduce the environmental pressure brought by the accumulation of coal gangue, and has high industrial application value.

Transesterification of Pequi (Caryocar brasiliensis Camb.) bio-oil via heterogeneous acid catalysis: Catalyst preparation, process optimization and kinetics

The transesterification of Pequi (Caryocar brasiliensis Camb.) bio-oil was conduct with a heterogeneous acid catalyst prepared with the fruit’s carbonized rinds. The newly-developed catalyst was characterized by TGA/DSC, XRD diffraction, and FTIR analysis. Experiments for process optimization of biodiesel production and catalyst reusability were carried out, also investigating the kinetics involved in bio-oil mass conversion. Crude FAME content was analyzed with GC-FID gas chromatographer and its fuel properties compared to worldwide standards. Main finds were a crude FAME majorly composed by methyl esters of palmitic acid, linoleic acid, and stearic acid, representing about 49.93, 13.24, and 10.16 wt.%, respectively. Optimized conditions for maximum FAME synthesis from Pequi bio-oil (99.4 ± 0.33%) were 18:1 M ratio of methanol to bio-oil, 60 °C of temperature, 100 min of reaction, catalyst load of 2.5 wt.%, and stirring speed of 600 rpm. Kinetics of the bio-oil mass conversion through transesterification presented reaction rates varying from 0.016 to 0.091 min−1, 63.07 kJ kg−1 of activation energy (Ea), and pre-exponential value (A) of 11.4E105. Catalyst efficiency decreased to 34.9% after 10 reuse cycles. Fuel properties of the crude FAME met worldwide standards of biodiesel quality, thus indicate that Pequi bio-oil is a viable, sustainable, and widely available feedstock option in Brazil.

Application of design of experiments for laser shock peening process optimization

Laser shock peening—a very promising life enhancement technique—has demonstrated great success regarding the improvement of fatigue behavior via deep compressive residual stresses. However, the prediction and adaption of residual stress fields on basis of the laser peening parameters are still not comprehensively established. The aim of the current work is to investigate the effects of the laser pulse energy, the number of treatment overlaps as well as the laser spot size on the resulting residual stress distribution, characterized by following quantities: the residual stress close to the surface, the maximum compressive residual stress, and the integral compressive stress area over the specimen depth. For a systematic investigation of all main and interaction-based process parameter effects, and a subsequent parameter optimization, the general full factorial design is employed. The results show that laser shock peening with different process parameter combinations, inducing residual stresses with comparable integral stress area, can lead to a minimum fatigue life extension of approx. 100,000 cycles, representing a minimum fatigue life of 250% of the base material. The experimental scatter in the number of cycles to failure follows the Weibull distribution which qualitatively correlates with the standard deviation of the integral stress area.

INFLUENCE OF SPRAY DRYING PROCESS ON THE QUALITY OF AVOCADO POWDER: A FUNCTIONAL FOOD WITH GREAT INDUSTRIAL POTENTIAL

Background: Colombia is the fifth largest producer of avocado and its agribusiness chain lacks value-added diversified products; therefore, at the governmental level, there has been promotion of internationalization policies aimed at opening up new markets and innovation with improved technology and food consumption patterns. The spray drying is an alternative conservation for avocado, a highly perishable fruit. Objectives: the aim of this study was to optimize the spray drying process for obtaining Hass avocado powder with better physicochemical properties and processing. Methods: an experimental design “Optimal” was used in the response surface methodology based on four factors: (A) maltodextrin (MD) concentration (2.81 to 11.25% w/w), (B) air inlet temperature (140-160°C), (C) outlet air temperature (80-90°C) and (D) atomizer disk speed (20000-26000 rpm). Results: the response variables where statistically significant differences (p<0.05) were found including: moisture, water activity, solubility, color coordinates (L*, a*, b*) hygroscopicity, wettability, extractable oil and deposit formation versus factors studied. Optimized value factors were: (A) 6.93% (B) 160°C (C) 84°C and (D) 26000 rpm. Conclusions: the experimental process optimization is presented as an effective tool for agribusiness, which improves product quality in terms of the factors that affect it, and in the case of avocado, allows the development of new value-added products, with potential uses in the food industry, pharmaceutical, cosmeceutical, among others.

锥形光纤SERS探针的工艺优化和拉曼光谱增强实验

锥形光纤SERS探针的工艺优化和拉曼光谱增强实验

Kinetics based reaction optimization of enzyme catalyzed reduction of formaldehyde to methanol with synchronous cofactor regeneration.

Enzymatic reduction of carbon dioxide (CO2 ) to methanol (CH3 OH) can be accomplished using a designed set-up of three oxidoreductases utilizing reduced pyridine nucleotide (NADH) as cofactor for the reducing equivalents electron supply. For this enzyme system to function efficiently a balanced regeneration of the reducing equivalents during reaction is required. Herein, we report the optimization of the enzymatic conversion of formaldehyde (CHOH) to CH3 OH by alcohol dehydrogenase, the final step of the enzymatic redox reaction of CO2 to CH3 OH, with kinetically synchronous enzymatic cofactor regeneration using either glucose dehydrogenase (System I) or xylose dehydrogenase (System II). A mathematical model of the enzyme kinetics was employed to identify the best reaction set-up for attaining optimal cofactor recycling rate and enzyme utilization efficiency. Targeted process optimization experiments were conducted to verify the kinetically modeled results. Repetitive reaction cycles were shown to enhance the yield of CH3 OH, increase the total turnover number (TTN) and the biocatalytic productivity rate (BPR) value for both system I and II whilst minimizing the exposure of the enzymes to high concentrations of CHOH. System II was found to be superior to System I with a yield of 8 mM CH3 OH, a TTN of 160 and BPR of 24 μmol CH3 OH/U · h during 6 hr of reaction. The study demonstrates that an optimal reaction set-up could be designed from rational kinetics modeling to maximize the yield of CH3 OH, whilst simultaneously optimizing cofactor recycling and enzyme utilization efficiency.