Current advances in liquid-liquid mixing in static mixers: A review

Author links open overlay panel-Juan P. Valdés

, Lyes Kahouadji

, Omar K. MatarShow moreAdd to MendeleyShareCite

https://doi.org/10.1016/j.cherd.2021.11.016Get rights and content

Highlights

  • Static mixers are a promising alternative to stirred vessels for emulsification.
  • Robust numerical codes have enabled the optimization and innovation of new mixers.
  • Most available performance predictive models are limited and cannot be generalized.
  • Further inquiry into fundamental concepts is required (e.g. surfactant-laden flows).

Abstract

This review article revisits the role of static mixers in the process industry nowadays and summarizes the most relevant developments and literature available on this type of mixer handling liquid-phase systems. In particular, this review seeks to discuss in depth the progress that has been made in the hydrodynamic understanding of immiscible liquid–liquid dispersions and emulsion formation using motionless types of mixers, both through experimental and computational approaches. Models and correlations on key process parameters, such as mean droplet size and pressure drop, proposed over the last couple of decades, are compiled and discussed. The latest progress in computational modeling through numerous frameworks is also thoroughly covered. In addition, this paper includes a brief review of the fundamental concepts in liquid static mixing and emulsion formation to further enrich the discussion on the innovations made in this field.

Introduction

Mixing is a key feature of most modern industrial processes, covering a broad spectrum of applications from consumer goods in the food, pharmaceutical, and cosmetic industries to the chemical and petrochemical, pulp and paper, polymer, mineral processing, and biotechnology sectors (Paul et al., 2004, Harnby et al., 1997). This unit operation is sought to reduce the inhomogeneity of a system caused by a gradient of phase, viscosity, concentration, or temperature, to achieve a desired process objective (Ghotli et al., 2013, Paul et al., 2004). Mixing processes are fundamental in determining a product’s yield, quality, and physicochemical properties, as well as the heat/mass transfer and reaction rates of a given process (Ghanem et al., 2014). In addition, mixing represents a substantial part of the energy requirements for the overall industrial process and a considerable source of expenditure in both capital and running costs of the operations (Harnby et al., 1997, Nere et al., 2003).

Given the intrinsic complexity behind the fluid mechanics in industrial mixing processes, design, and scale-up procedures are mostly based on empirical correlations and models suitable for a limited set of cases and conditions (Nere et al., 2003). Unlike other industrial operations (e.g., shell and tube heat exchangers), little effort has been made to standardize mixing technologies, as there are no universally accepted selection methodologies or design codes available for mixing (Harnby et al., 1997, Edwards and Baker, 1997). Blind application of empirical models can pose a multitude of risks to the manufacturing process since many mixing scenarios require a more thorough and robust evaluation due to the appearance of complex physical properties of the fluid such as non-Newtonian rheology or even handling simultaneously a multitude of components such as multiphase flow physics. Insufficient understanding of such phenomena may cause significant disruptions in the process like major adjustments to the plant, inflated costs due to over-design, and even complete failure of the process due to lacking quality or inadequate product properties (Nere et al., 2003, Paul et al., 2004, Ghotli et al., 2013).

Estimates in the U.S. during 1989 revealed costs in the order of U.S. $1–10 billion per annum due to improper understandings of mixing in the chemical sector alone (Harnby et al., 1997). In 1993, a large multinational chemical company reported losses on the order of $100 million per year due to poor quality of mixing. Moreover, yield losses in such scenarios oscillate around 5% (Paul et al., 2004). Similar situations occur in the pharma industry, where poor mixing commonly leads to losses from lower yield (∼$100 million), complications in the scale-up and process development (∼$500 million), and lost opportunity with unsuccessful products that never reach the market (Paul et al., 2004). Often, poor mixing can be readily identified and addressed accordingly by assessing the product’s quality and properties. The introduction of medium consistency technology to the pulp and paper industry in the 1980s is an example of this, generating chemical savings of up to 15% (Paul et al., 2004). However, there is no means of detecting over-design, which usually occurs as a counter-measure for the lack of knowledge of a given mixing process (Harnby et al., 1997). Over-design can be easily overlooked, leading to severe economic consequences as mentioned above.

Although mixing, in general, has always been a major area of academic and industrial interest, liquid–liquid mixing, in particular, poses the highest challenges, making it one of the least understood mixing mechanisms despite the large existing literature on it (Ghotli et al., 2013, Paul et al., 2004). Nowadays, this type of mixing can be extensively found in multiple industrial applications such as (petro) chemical, mineral processing, personal care and home products, pharmaceutical, and food in the form of immiscible liquid–liquid dispersions (Castellano et al., 2018, Gao et al., 2016), emulsions (Gallo-Molina et al., 2017, Wong et al., 2015, Tadros, 2013) and miscible blending of non-Newtonian fluids (Alberini et al., 2014, Forte et al., 2019a). Emulsions are arguably the most noteworthy systems in this category due to their inherent complexity and recurrent appearance in the aforementioned industries.

Emulsions can be either desirable (e.g., ‘structured’ emulsions in consumer goods, which are carefully manufactured at a microscopic scale to achieve targeted product properties (Håkansson, 2019, Almeida-Rivera and Bongers, 2010)) or undesirable (e.g., crude oil-water emulsions affecting Oil & Gas (O&G) processes by flow blockage, inefficient separation affecting crude oil quality and corrosion (Wong et al., 2015, Goodarzi and Zendehboudi, 2019)) depending on the context of application. Regardless of the scenario considered, the research interest for all these sectors converges on the same focus: improving the fundamental understanding of liquid-phase mixing and emulsification mechanisms. Fortunately, these fundamentals are essentially the same across all areas involved and can be used simultaneously to improve the mixing process efficiency and product quality or to develop suitable mitigation and prevention mechanisms for undesirable circumstances (Wong et al., 2015, Goodarzi and Zendehboudi, 2019).

The conditions for the formation of a kinetically stable emulsion have been exhaustively studied and two criteria have been identified: (i) the presence of surface-active agents and (ii) the incorporation of energy via mixing to guarantee a sufficiently small droplet size distribution (DSD) (Wong et al., 2015, Leal-Calderon et al., 2007). It is well agreed that the DSD plays a fundamental role in the hydrodynamics of the system, the stability and rheology of the emulsion, as well as interface momentum, heat, and mass transfer rates (Gao et al., 2016, Goodarzi and Zendehboudi, 2019, Naeeni and Pakzad, 2019, Chabanon et al., 2017, Derkach, 2009). In addition, DSD is a crucial parameter in the design and scale-up of mixing systems and in the power consumption required to process liquid dispersions in general (Håkansson, 2019, Naeeni and Pakzad, 2019, Roudsari et al., 2012).

The relationships between the DSD and the macroscopical properties of emulsions are well understood and have been broadly discussed in previous literature (Mougel et al., 2006, Pradilla et al., 2015, Otsubo and Prud’homme, 1994, Pal, 1996, Derkach, 2009, Malkin et al., 2004, Gallo-Molina et al., 2018). However, the principles behind the mechanisms and phenomena that govern the emulsification process and the DSD behavior per se are still lacking. Previous studies have shown that emulsification is strongly driven by the hydrodynamics and turbulence of the system, as well as the properties and phase distribution of the liquid phases (Liao and Lucas, 2009, Liao and Lucas, 2010, Gallassi et al., 2019, Ashar et al., 2018). Nevertheless, Håkansson (2019) argues in his review that the current fundamental understanding of these mechanisms is limited to ideal scenarios such as isotropic and homogeneous turbulence, non-interacting spherical droplets, and binary breakup, among others. In particular, Håkansson (2019) proposes that the common assumption of a single turbulent stress regime (either inertial or viscous) governing droplet breakup is misleading since droplets at certain scales can be expected to interact with both types of stresses. This implies that the knowledge of such phenomena under industrially relevant conditions is still unsatisfactory and that continuation of the ongoing lines of investigation (mostly empirical) will not be sufficient to further advance in this field.

In general, describing quantitatively the flow dynamics of mixing systems handling complex flows such as liquid dispersions or emulsions can be rather complicated and often inaccurate. Thus, there is a growing need to expand and improve the current fundamental understanding behind such mixing processes. This review is intended to summarize and discuss the most relevant developments made in this expanding area. Given the broadness of this field, this paper will focus solely on static mixing applications, which have consistently shown potential as an attractive alternative to conventional stirred vessels but have not received as much attention as their traditional counterpart.

The rest of this paper is organized as follows. Section 2 provides an overview of the relevance of static mixing in the process industry and details the static mixer’s features, types, and applications. Section 3 focuses on the most relevant fundamentals behind static mixing operations handling liquid systems (mostly immiscible), as well as basic concepts of emulsion classification, formation, and stability. Section 4 discusses the most relevant experimental and computational studies carried out on liquid dispersions and emulsions. The final section, Section 5, examines the current state-of-the-art and proposes possible future endeavors to be pursued in this field. Heat transfer and chemical reactions in static mixers are beyond the scope of this article.

Static mixers in the process industry

Static or motionless mixers consist of a series of identical inserts or elements, arranged in a structured configuration, which can be installed in pipes, channels, columns, or reactors. These inserts are added to promote a chaotic mixing behavior by dividing and redistributing the flow streamlines sequentially, following radial and tangential directions to the main flow (Thakur et al., 2003, Ghanem et al., 2014). Besides pure mixing, motionless mixers are also largely used to enhance heat/mass

Pressure drop

Even though pressure drop is not a measure of mixing per se, it is still a relevant indicator of the efficacy of static mixers, given that it dictates the pumping energy that will be required for the process, thus determining the associated costs (Heniche et al., 2005, Stec and Synowiec, 2017b). Besides, pressure results can be used as an adequate criterion to evaluate the correctness of the velocity fields obtained in numerical simulations, especially for pressure-velocity formulations such as

Static mixing of immiscible dispersions and emulsions

Although static mixers were initially developed for laminar blending applications, most of the research in the past four decades has been strongly directed toward dispersion/interface generation processes in multiphase flows. This has been encouraged by the fact that key parameters for immiscible liquid mixing are much more difficult to predict than mixing effectiveness for miscible systems (Thakur et al., 2003). A major portion of the work in this area has been performed experimentally by

Conclusion and Future Perspectives

Static mixers have been a topic of research interest for the past couple of decades. As pointed out by Thakur et al. (2003), the first generation of mixers was designed mostly for miscible mixing based on physical insight and intuition, leading to a scarce understanding of their internal dynamics. However, recent improvements in experimental techniques and the consolidation of computational-assisted design and modeling have enabled researchers to elucidate the fluid mechanics behind these

Conflict of interest

None declared.

Declaration of Competing Interest

The authors report no declarations of interest.

Acknowledgments

The authors would like to acknowledge the funding provided by the Engineering & Physical Sciences Research Council, United Kingdom through the PREMIERE (EP/T000414/1) Colombian Ministry of Science, Technology and Innovation MINCIENCIAS, through a doctoral studentship for JPV.

References (193)

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