One-step statistical design of experiment for the screening and optimization of magnetite nanoparticles yields from solvothermal synthesis

https://doi.org/10.1016/j.micromeso.2020.110775Get rights and content

Highlights

  • Response models explain 98% variability in the 16.4-nm mean sized Fe3O4 NPs yields.

  • Diagnostic charts depict the significance of time and temperature effects on yields.

  • Fe3O4 NPs yields are maximized at 220 °C, 2.5 h and composite desirability of one.

  • Most Fe3O4 NPs samples exhibit H1 hysteresis loop and Type IV adsorption isotherm.

Abstract

One-step custom design of experiment was employed for the simultaneous screening and optimization of raw yield (Y1) and percent yield (Y2) with heating temperature, T (190–220 °C) and reaction time, t (1.0–2.5 h) as the predictors in a conventional solvothermal magnetite nanoparticles (NPs) synthesis. Two accurate models capable of explaining 98.3% variability in the data were developed. A strong correlation exists between the actual yields (Y1, Y2) and their predicted counterparts (r = 0.99). T, t, Tt and t2 terms have a significant synergistic effect on the yields the at α = 0.05. The diagnostic plots depicted the effects in the order t > T > Tt > t2. Surface and contour plots show maximum Y1 (0.295 g) and Y2 (105%) at T = 219 °C and t = 2.5 h. The optimizer plot shows maximized Y1 (109.94%) and Y2 (0.31 g) at the highest predictor values (T = 220 °C, and t = 2.5 h) at composite desirability of 1. NPs characterization using various techniques revealed nanocubes and nanospheres with a mean diameter of 23.9 ± 7.9 nm, the crystallite size of 8.3 ± 1.4–20.4 ± 4.9 nm, a pore size of 9.07–24.47 nm, and surface area of 35.80–93.57 m2 g−1. The NPs exhibit stretching Fe–O vibrations at 571 cm−1 for tetrahedral and at 428 cm−1 for octahedral geometries in the infrared spectra and are thermally stable within the range 30–700 °C with low weight loss (8.81–32.92%) typical of mesoporous magnetite phase.

Introduction

Over the last few decades, a variety of magnetic nanomaterials based on cobalt, iron, iron oxide, metallic alloys, nickel, and metal ferrites with specific morphological, structural, physical, and chemical characteristics have been fabricated through various strategies. Well-defined magnetite (Fe3O4) nanostructures are the most important magnetic nanomaterials with widespread applications in many fields including biomolecular separation, medical diagnosis and therapy, drug delivery, biomedicine/biotechnology, catalysis, gas sensor, energy storage, environmental remediation, hyperthermia, magnetic resonance imaging and microwave absorption [1]. Several methods employed in the preparation of Fe3O4 nanoparticles included sol-gel [[2], [3], [4]], reverse micelle [5,6], γ-ray irradiation [7,8], non-aqueous route [9,10], microwave plasma synthesis [11,12], coprecipitation [13,14], thermal decomposition [[15], [16], [17], [18]], microemulsion [5,[19], [20], [21]], hydrothermal process [[22], [23], [24]] and solvothermal method [[25], [26], [27]].

The advantage of the coprecipitation method includes the use of water as solvent and proceeding of the reaction under mild condition. However, the morphology of the particles cannot be controlled. Thermal decomposition offers the best synthetic route for obtaining nanoparticles with controlled size and morphology. However, most of the reported publication of the synthesis of magnetic nanoparticles involved the use of high-cost and poisonous organometallic precursors such as iron pentacarbonyl (Fe(CO)5), metal cupferronates, and metal acetylacetonates under extreme temperature conditions [28]. Microemulsions can produce monodispersed nanoparticles with specific morphology but consume large amounts of organic solvent and surfactants necessary for controlling the size and shape of the nanomaterial [29].

The solvothermal method is well-known for its capability to produce nanostructured inorganic materials such as metals and their oxides by raising the solubility and speed of the reaction under the influence of higher pressures and temperatures at the critical point of the solvents or even higher despite low product yields. The reactant was completely solubilized by the heating process and under the pressure produced high-quality nanomaterials [30].

Among these methods, the solvothermal technique is well-known to produce well-crystallized and mono-dispersed ferrite nanostructured inorganic materials through the effective control of their morphology, size, crystallinity, and shape [[31], [32], [33], [34], [35], [36]]. Changes in morphologies and structure of the product can be efficiently monitored by varying the chemical reaction conditions such as reaction time, heating temperature, amounts of surfactant, protective reactions, and amounts of iron during the solvothermal approach. In a typical setup, Yan et al. [37] employed sodium acetate trihydrate (NaAc•3H2O) as a surfactant to produce Fe3O4 nanoparticles (NPs) and microspheres with a particle size distribution of 72–447 nm via the solvothermal method. Similarly, Yan et al. [38] have reported nanoparticles with particle sizes ranging within 15–190 nm when sodium dodecyl sulphate (SDS) and polyethylene glycol (PEG) were utilized as protective agents in the synthesis Fe3O4 NPs.

Numerous works have reported the several efficient synthesis routes in the production of shape-controlled, stable, monodispersed, and mesoporous magnetite NPs using one-factor-at-a-time (OFAT) or one-variable-at-a-time (OVAT) design. For example, Hu et al. [29] investigated the effects of heating temperature (400–700 °C) and holding time (2–8 h) on crystalline phase composition and magnetic properties of Fe3O4 nanoparticles prepared by an OVAT designed carbothermal reduction method. During solvothermal process optimization using OFAT or OVAT design, one of the independent parameters is first chosen and varied for screening to ascertain its optimum value corresponding to the highest response. The established optimum for the first parameter is then utilized as the starting point in the next experiment to orthogonally screen and realize the optimum of the second variable. Similar experimentations are repeated sequentially to attain the optima for all other parameters in the design. The response at which all the parameters are at their optima is eventually recognized as the region of the best performance for the process. As the number of the parameters in such a simple experimental design approach increases, an increased cost due to a higher number of experimental runs and amounts of resources required results. System complexity arising from increased correlations and interactions among the parameters could lead to missing the optimum process responses [39]. Whereas fewer efforts were channelled towards the utilization of response surface design of experiments to optimize the effects of independent factors (e.g. reaction time, temperature, amounts of Fe (III) precursor, sodium acetate (NaAc) nucleating agent, etc.) on the Fe3O4 yields of the conventional solvothermal process, robust optimization of the magnetite yields obtained under the conventional solvothermal synthesis conditions using one-step screening and optimization design of experiment has not been considered. For instance, Hernández-Hernández et al. [25] have reported the microwave-solvothermal synthesis of magnetite nanoparticles involving the evaluation of the effects of the holding time and the gradient time on percent yield using Plackett-Burman screening design as well as the effects of amount of ammonium acetate precursor, the holding time, and the microwave system temperature on the crystallite particle size using Box-Behnken design optimization. The present study was aimed at the application of a one-step custom response surface design of an experiment to screen, optimize and evaluate the effects as well as the statistical significance of reaction time, heating temperature and their interaction on the raw and percent yields of the as-synthesized samples of mesoporous Fe3O4 nanoparticles during a conventional solvothermal synthesis procedure. The morphological and structural properties of the as-prepared samples from experimental runs with reasonable yields were also further characterized using several instrumental techniques to ensure the fabrication of shape-controlled, stable, monodispersed, and mesoporous magnetite NPs.

Section snippets

Materials

All the chemical reagents used in the synthesis procedures were of analytical grade and were utilized as received without any further purification process. Ferric chloride hexahydrate (FeCl3·6H2O), sodium acetate (CH3COONa) and ethylene glycol ((HOCH2)2) were procured from Bendosen Laboratory Chemicals, Malaysia. Ethylenediamine ((H2NCH2)2) and denatured ethanol (C2H5OH, 95%) were supplied from HmbG Chemicals, Malaysia. The graphs, models, and tables obtained from statistical analyses were

Characterization of magnetite nanoparticles

The as-synthesized samples of magnetite nanoparticles with significant yield values of at least 40% are Fe3O4-T190t2.5, Fe3O4-T205t2.0, Fe3O4-T205t2.5, Fe3O4-T220t2.0, and Fe3O4-T220t2.5 obtained under the solvothermal conditions of heating temperature/reaction time pair of [190 °C, 2.5 h], [205 °C, 2.0 h], [205 °C, 2.5 h], [220 °C, 2.0 h] and [220 °C, 2.5 h], respectively. Their yields were evaluated following a one-step custom response surface design of the experiment.

Conclusions

One-step custom design of experiment for the simultaneous screening of independent variables and response optimization was successfully applied in the solvothermal synthesis of magnetite nanoparticles to screen the heating temperature and reaction time as well as to optimize the raw and percent yields of the magnetite nanoparticles. The instrumental techniques SEM, EDX, FT-IR, XRD, TGA/DTG and BET porosimetry analyses employed have effectively characterized the morphology, elemental

CRediT authorship contribution statement

Sadiq Sani: Conceptualization, Methodology, Investigation, Resources, Funding acquisition, Data curation, Writing - original draft, Visualization, Validation, Formal analysis. Rohana Adnan: Supervision, Project administration, Funding acquisition, Conceptualization, Methodology, Resources, Validation, Writing - review & editing. Mohammad Anwar Mohamed Iqbal: Methodology, Resources.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

The authors would like to recognize and appreciate the support of the Nigerian Tertiary Education Trust Fund (TETFUND) under the Academic Staff Training and Development (AST&D) Scheme with the award reference TETF/ES/UNIV/DUTSIN-MA/ASTD/2018 and Universiti Sains Malaysia through the RUI Grant no. 1001/PKIMIA/8011117 towards the successful completion of this work.

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