Background: The production of photocatalytic nanoparticles such as TiO2 has received increasing interest for biomedical and wastewater treatment applications. However, the conventional synthesis of such materials faces several environmental concerns.
Methods. In this work, green synthesis is addressed to prepare TiO2 nanoparticles at large scale using Lemongrass (Cymbopogon citratus) and titanium isopropoxide (TTIP). This process was designed and modeled using computer-aided process engineering (CAPE) in order to obtain the extended mass/energy balances, as well as operating parameters. Process simulation was carried out using the commercial software Aspen PlusR . In addition, energy performance of large-scale nanoparticle production was analyzed to identify alternatives for process improvement from an exergetic point of view.
Results. The production capacity of the plant was estimated as 1,496 t/y of TiO2 nanoparticles by the conversion of 32,675 t/y lemongrass and 5,724 t/y TTIP. Hence, the overall production yield is 0.26 kg TiO2/kg TTIP. Exergy analysis reported an overall exergy efficiency of 0.27% and an exergy loss of 159,824.80 MJ/h. These results suggest that such a process requires the implementation of process improvement strategies to reach a more sustainable design from energy and thermodynamic viewpoints.
Lemongrass, TiO2 nanoparticles, Exergy analysis, Process simulation, Green Chemistry
In recent years, several research contributions have been reported about sustainable and green chemistry-based pathways to produce novel materials widely applied in different industries. Among such applications, wastewater treatment is recognized as a key issue around the world to preserve the quality of water resources. Moreover, appropriate technologies for wastewater (industrial and domestic) treatment have attached a great interest in order to meet environmental regulations (Bhojwani et al., 2019). On the other hand, advanced oxidation processes are promising alternatives for wastewater treatment purposes since these technologies use photocatalytic reaction systems to degrade pollutants in water under solar or radiation influence (Bustillo-Lecompte, Kakar & Mehrvar, 2018). For such technology, titanium dioxide (TiO2) is the most used photocatalyst because of its high efficiency to remove pollutants from water (Acosta-Herazo et al., 2019). Despite the efforts towards a more sustainable synthesis of titanium dioxide, there is a knowledge gap in large-scale production of such photocatalytic nanoparticles via green chemistry methods.
Anastas and Warner introduced guidelines to make greener processes and products through twelve design principles of green chemistry, which can be summarized as follows: waste prevention, atom economy, safer synthesis, safer products, safer auxiliaries, energy efficiency, renewable feedstocks, derivative reduction, catalysis, degradability, and pollution prevention (Anastas & Warner, 1998). These principles are mainly focused on reducing the hazard of chemicals and designing products that easily biodegrade after their useful life. Green chemistry is an innovative concept associated with the natural change of pollution prevention towards the synthesis of novel products considering sustainable parameters. Processes meeting green chemistry principles usually employ operations that require less energy consumption, which helps to increase economic profits by reducing operational costs (Hendershot, 2015). Recently, green chemistry concepts were also applied to conversion operations of high-value products to increase process efficiency (Deyris & Grison, 2018).
Nanotechnology is a revolutionary science related to the handling of substances at the molecular or atomic level. The development of manufacturing processes from nanotechnology principles is an interesting research topic to design novel pathways for industrial production of nanomaterials (Wang et al., 2016). Several works have been conducted related to the green synthesis and characterization of metal oxide nanoparticles due to their potential application in different fields (Nwankwo et al., 2019). Karpagavinayagam & Vedhi (2019) presented a novel green synthesis of iron oxide nanoparticles using Avicennia marina flower extract. Arya, Mishra & Chundawat (2019) developed a green synthesis of silver nanoparticles from Botryococcus braunii and evaluated the catalytic behavior of such nanoparticles for benzimodazoles production. This research reveals a growing interest in producing nanoparticles through green chemistry methods for several uses, e.g., green TiO2 nanoparticles are commonly used as photocatalyst for pollutant degradation and virus sterilization among other applications (Haider et al., 2017).
Scaled-up technologies demand industrial utilities and a water supply that can be reduced by incorporating process improvements towards sustainable practices. Many contributions reported in the literature address the assessment of chemical processes using computer-aided tools, e.g., exergy analysis methods to estimate energy performance. Exergy is defined as the available theoretical work of a system through a process that can be obtained by bringing the system into equilibrium with a heat reservoir or the environment (Martínez González, Silva Lora & Escobar Palacio, 2019). All thermodynamic processes present irreversibilities; hence, the exergy of such systems is not conserved. This is explained by the dissipation of potentially useful energy to generate work. An exergy assessment allows one to identify system components or equipment (of any process) with the highest exergy losses. Another important feature of exergy analysis is the estimation of inefficiencies and identification of the sources responsible for such inefficiencies (Querol, Gonzalez-Regueral & Perez-Benedito, 2013). The first and second laws of thermodynamics are the basis of exergy analysis. These theoretical foundations provide insights about the direction of processes, their irreversibilities, the maximum reversible work, and its thermodynamic efficiency.
To date, limited research literature exists to simulate and evaluate the green synthesis of photocatalytic nanoparticles at large-scale and several contributions are restricted to lab-scale preparation of such nanomaterials. The novelty of this work lies in the scaling-up and exergy assessment of a green chemistry-based process for TiO2 nanoparticles to estimate the overall production yield and identify improvement opportunities. Process modeling and simulation of TiO2 nanoparticle production is performed through CAPE tools, which requires process information as mass/energy balances, operating conditions, such as temperature or pressure, reactions yield, and stoichiometry, as well as others (Hernández et al., 2014). The information and data required for the simulation of TiO2 nanoparticle production via green chemistry are taken from the literature and experimental results published by authors at lab-scale (Meramo-Hurtado et al., 2018). The application of exergy analysis and energetic sensitivity analysis will provide insights into the implementation of this process at a large scale for producing high-value nanomaterials.
In this work, an exergy analysis was developed for a large-scale TiO2 production via green chemistry to identify potential improvement opportunities based on an energy viewpoint. It is important to highlight that this first approach to a large-scale, production route under green chemistry concepts was developed to synthesize a green catalyst which can be employed for wastewater treatment systems. Results revealed that this process is thermodynamically inefficient with a global energetic efficiency of 0.27%. The calcination stage showed the lowest exergy efficiency because of the heat requirements for performing this operation. Also, large quantities of residues (10,354.76 t/y) at high temperature (550 ◦C) are associated with this stage. In the cleaning stage, significant quantities of exergy are lost as outlet waste, so it is recommended to add a co-generation system to avoid exergy losses. Finally, it is recommended that future works incorporate process integration or intensification strategies in order to obtain the most suitable design in terms of energy.
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Professor Siavosh Kaviani was born in 1961 in Tehran. He had a professorship. He holds a Ph.D. in Software Engineering from the QL University of Software Development Methodology and an honorary Ph.D. from the University of Chelsea.