The preceding chapters gave an overview of the many advances in chemical separations and other fields that have emerged in the last 3 decades. Despite the advances, critical challenges remain for the separations community to confront. This chapter describes the current gaps and challenges, which form the basis of the research agenda that will be defined in Chapter 5. Thematically, key challenges can be grouped into topics associated with selectivity, capacity, and throughput and with the temporal changes in separation systems in operating environments.
Selectivity, capacity, and throughput are intrinsic characteristics of a separation system,1 but their relative importance depends on a given system’s eventual application. What those characteristics have in common is that many outstanding, fundamental questions are related to measuring and improving them in complex, highly variable environments—environments that are different from the simplified test cases that form much of the current fundamental-research portfolio.
The evolution of separation systems during operation almost always adversely affects system performance; degradation and aging are two ubiquitous examples. Far from being an engineering detail divorced from fundamental research, the evolution of materials in separation systems poses vital fundamental research challenges. There are substantial gaps in the current understanding of the processes that control the evolution, especially in complex and variable environments. Closing those gaps and developing synthesis or regeneration techniques to mitigate the adverse effects as separation systems evolve are likely to have enormous dividends.
In addition to the broad research themes described, two cross-cutting topics that are important in materials chemistry have particular resonance in chemical separations: establishing standards to enhance reproducibility and multimodal characterization of complex materials and adapting data-science methods to accelerate development of separation systems. Those challenges are discussed below.
Selectivity, capacity, and throughput are arguably the key defining features of separation processes, so developing fundamental approaches that improve performance in these factors lies at the heart of separation science. The relative importance of the three factors varies in different contexts. In analytical settings, for example, the ability to detect trace species with exquisite selectivity in the presence of many confounding analytes might be more critical than the rate at which the separation can be achieved. In contrast, in large-scale process settings where flow rates might be measured in tons per hour, the capacity and throughput of a process are paramount. In general, however, all three factors contribute to the success of a separation process.
Moreover, in many situations, trade-offs exist: improvements in one factor are typically associated with declines in the others. That difficulty has been extensively explored, for example, in membrane-based gas separations (see Box 4-1). Observations have implied that efforts that focus exclusively on one of the factors (selectivity, capacity or throughput) are likely to have small long-term effects. The following sections detail multiple aspects of this critical challenge.
Advancing the Understanding of Complex Mixtures
Samples and process streams encountered in separation problems are almost always complex mixtures that have many chemical components. Idealized concepts of pure feeds with clean carriers and single-product chemis-
1Separation system refers to an entire process or procedure that yields a separation; it can include the separation material, devices, and other components.
tries are appropriate for initial consideration in investigating separation options. To solve the problem, the complex mixture must be considered.
When components of interest are present at low concentrations, as is the case in many analytical settings, understanding and controlling the response of the separation process to the full spectrum of analytes that might confound it are critical. When components of interest are present at high concentrations, as typified by many large-scale chemical processes, nonadditive and nonideal interactions among components can dramatically influence selectivity, capacity, and throughput. Those effects do not necessarily scale linearly with the concentrations of the components. In the physisorption of molecules in nanopores, for example, the adsorbed concentration can vary roughly exponentially with the molecular weight of the adsorbing species, making the presence of high-molecular-weight contaminants in input streams important.
Critical scientific challenges exist in developing a fundamental understanding of the effects of complex mixtures on the behavior of separation systems. Tackling those challenges early in considering new approaches can avoid wasteful failures caused by the “show-stopping” complications inherent in complex mixtures.
In addition to overcoming expected challenges, studies of mixtures can yield insights that lead to new domains of use. For example, a study of the use of membranes to separate olefins from paraffins (ethylene from ethane and propylene from propane) focused on the main components found in typical steam-cracker separations (Koros et al., 2016). As a part of the study, the more complex actual stream in a manufacturing operation was tested. Use of the actual stream added several components to the study, including hydrogen, methane, ethyne, propyne, and propadiene. A preference for the permeation of hydrogen, ethylene, and propylene was confirmed, but the alkynes and diene exhibited even greater permeance than hydrogen. Those observations offered new knowledge of the behavior of the membrane system. More important, the unexpected performance suggested commercial applications of the separation technology that were unimagined before.
Exploring the Array of Thermodynamic and Kinetic Mechanisms
Because the abstract task of separating chemical mixtures is so broad, an enormous array of physical mechanisms can be used. It can be useful to distinguish between examples in which separations are controlled by aspects of thermodynamic equilibrium and examples in which kinetics are crucial. In both cases, fundamental challenges limit the ability to achieve high selectivity, capacity, and throughput.
For equilibrium-based separations, enthalpic or entropic contributions or a combination thereof can dominate performance. Combining approaches that traditionally focus on just one thermodynamic contribution is likely to improve known methods and even lead to the development of fundamentally new separation mechanisms.
Some separations rely on kinetic effects, such as mass-transfer rates through interfaces between liquid phases or diffusion rates in porous or structured materials. Accurately characterizing the rates of relevant processes presents challenges. Establishing nontrivial structure–property–performance relationships to predict kinetic parameters on multiple relevant length scales is also challenging.
Separating Trace Compounds and Using Multistep Processes
In more and more new applications, trace compounds must be found and removed. Examples include ultratrace analysis, desalination, nuclear-waste cleanup, and the study of transactinide isotopes. Achieving sufficiently high concentration factors requires high affinity and, because high concentrations of competing species are common, high selectivity. If the only option is to regenerate the separation agent for repeated use, a mechanism is needed to release the bound target species efficiently.
Recovery of trace species can be critical because of the need for regulatory compliance or value recovery. A regulatory example is the picomolar levels of technetium (Tc) in the form of pertechnetate anion in groundwater emanating from U.S. Department of Energy nuclear sites, where the radioactivity of the Tc raises a concern. In another example, nonradioactive oxoanions that raise concerns at trace concentrations in drinking-water sources include perchlorate and arsenate–arsenite. Regarding value recovery, developing chemistry to separate valuable metals from highly dilute sources will address issues of supply security and valorization. Examples are gold from ores, uranium from seawater, and gallium from tailings. In all those cases, in keeping with Sherwood’s concept (Keller, 1987; Seader et al., 2016), cost increases with dilution, and the economics of the processes are poor or marginal at best. Approaches that mitigate this challenge are needed.
Trace analysis is important in many scientific fields. Examples are ultratrace analysis of pesticides in fruits and vegetables and similar ultratrace analysis of pharmaceutical compounds, such plasticizers as phthalate esters, and nanoparticles in natural waters. In this context, a multistep process is used in which preconcentration is critical before separation and detection are feasible.
Current multistep analytical procedures include different forms of preconcentration or removal of high levels of matrices. Preconcentration methods, such as liquid–liquid extraction or solid-phase extraction followed by highly efficient liquid chromatography, are capable of measuring many target compounds of interest in a range from nanograms per liter to micrograms per liter (see Box 4-2). Improvements in the extraction, chromatography, and mass-spectrometry portions of those multistep methods have allowed the low detection limits to be achieved.
Nevertheless, such detection limits cannot be reached for all compounds of interest, and often the limits are still not low enough. In addition, achieving those limits in the case of many nontarget compounds remains challenging. It is important to find means to achieve the highly targeted selectivity required to make progress in this field.
Achieving Separations with a Wide Dynamic Range
Mixtures usually have multiple species at various concentrations. The ratio of the concentration of the most concentrated species to the least concentrated species of interest is the dynamic range. The need for separations with a wide dynamic range can be illustrated by the detection of the proteins in human blood plasma. Because post-translational modifications of proteins are good biomarkers of disease, this is a topic of considerable interest. The dynamic range of protein concentrations in human
blood plasma is expected to be about 1010–1012 (Anderson and Anderson, 2002). No current multistep process that involves preconcentration, separation, and detection can analyze proteins across such a large dynamic range. Various methods, such as prefractionation of high-concentration proteins, have been attempted, but some of the lower-concentration proteins are also removed with these methods (Rassi and Puangpila, 2017; Wu et al., 2016).
If a particular biomarker is identified, a method of selectively preconcentrating and detecting it is possible. However, nontarget analysis is still difficult or impossible. Similar problems of dynamic range are encountered with metals. For example, traces of plutonium must be measured at sub-parts-per-trillion in biological samples, and reprocessing of used nuclear fuel is performed at kilogram quantities. New ideas for addressing the challenges associated with effective separations of complex mixtures that have wide dynamic ranges must be developed.
In addition to developing separation systems with wide dynamic ranges, there is a gap in development of models that can reliably predict the performance of separation systems over a much wider range of conditions than that on which direct experimental data are available. Models that could identify the tradeoffs that inevitably appear when one is considering separations over disparate conditions would be useful in addressing questions related to how effective particular separations need to be for utility in a given setting.
Understanding and Controlling Interfaces
Physical interfaces play a decisive role in the performance of many separation methods. Fundamental advances in the ability to characterize the structure and dynamics of the interfaces will achieve better separations. The detailed properties of interfaces often vary in critical ways between “clean” environments and the more relevant environments associated with complex mixtures. Impurities and other nonidealities in complex mixtures are likely to affect the long-term structure and properties of interfaces. Achieving more refined control of interfacial properties through synthesis, treatment, and regeneration methods will yield substantial dividends. Adaptation of current characterization techniques or development of new techniques that can generate molecular-level insight into interfaces in environments relevant to operating conditions would potentially have a large favorable effect. This concept is closely related to the ideas of operando techniques that have made enormous changes in chemical catalysis (Topsøe, 2003) and in contaminant transport in the environment (Henderson, 2002).
Understanding Physical Changes in Response to External Forces
Most chemical separations are controlled by a small number of driving forces (such as changes in concentration, temperature, pressure, and pH), but many other ex-
ternal stimuli can also play a decisive role. Those stimuli include electromagnetic effects (such as microwaves, optical fields, and magnetic fields) and mass-transport effects associated with complex or locally driven fluid-flow fields. They can act on chemical species that are being separated or on a separation material itself. In many instances that involve what might be termed nontraditional driving forces, it can be difficult to establish physical upper bounds on the performance that might be achievable and to demonstrate specific examples that create fundamental knowledge that can drive development. Determining the appropriate metrics with which to compare the performance of nontraditional approaches with established techniques can be difficult, but these metrics have great value.
To maximize their scientific or practical value, separation systems must be reliable when exposed to streams of broad and variable composition. The systems might encounter harsh work environments and are expected to operate stably for long periods. During operation, separation media generally undergo aging or degradation that results in loss of selectivity or capacity. Such changes can be caused by physical (thermal) and chemical aging of the materials themselves or can occur as a loss in surface characteristics due to fouling caused by accumulation, surface-catalyzed reactions, or other conditions.
Many pressing fundamental research issues are associated with the robustness of separation systems, including the achievement of detailed descriptions of the mechanisms of aging and fouling and the development of novel regeneration or “healing” procedures. A thorough understanding of aging through many separation cycles is needed with consideration of the influence of temperature and pressure and of the diversity of chemical effects that might occur because of impurities or components of the streams under consideration. In operating environments, such deviations from “typical” operating conditions are often associated with unplanned but unavoidable upsets. Because aging and degradation often occur over weeks or months, effort should be placed on developing accelerated aging concepts and techniques that are strongly grounded in the fundamental understanding of robustness.
Determining Changes from Nonequilibrium That Affect Chemical and Physical Properties of Separation Materials
In some classes of separation materials, materials in a nonequilibrium or metastable state are used. For example, glassy polymers are examples of nonequilibrium materials that have lower free energy states to which kinetic access might be extraordinarily slow. Polymorphs (often nonporous) with lower free energy can exist in crystalline porous materials, such as zeolites, but access to these more stable structures involves very high free-energy barriers, so the thermodynamically metastable crystals are stable from a practical viewpoint.
However, events associated with chemical separations can catalyze or accelerate changes in nonequilibrium or metastable materials. The events include excursions in temperature or pressure and chemical effects of molecules that are the target of the separation or of contaminants in mixtures that are being separated. Such events can dominate the viability of the separation process, so the ability to control the evolution of the separation materials via these mechanisms is critical. A central challenge is to understand the fundamental mechanisms that control the evolution of nonequilibrium states, particularly in complex environments. Without such understanding, efforts to implement accelerated testing protocols that speed the cycle of materials development or work to synthesize materials with intrinsically improved stability are likely to remain empirical and inefficient.
Determining Identities and Rates of Fundamental Chemical Reactions That Result in Changes in Separation Media and How the Reactions Are Influenced by Operating Conditions
The temporal evolution of nonequilibrium materials discussed above involves processes in which no change in the chemical stoichiometry of the underlying material occurs. An equally important way in which separation media can evolve is through chemical reactions, which are often irreversible. The degradation of materials in acidic environments is one of many examples. The influence of operating conditions and the difference between “clean” and “complex” conditions can be dramatic. Fundamental insights into the nature of the underlying chemical processes are needed if approaches to mitigate or avoid them are to be discovered.
Understanding the Fate of Unwanted Products
Chemical and physical interactions between separation materials and the mixtures to which they are exposed can generate products that are not readily removed from the system. When that happens, the identity and fate of the products can dominate the time scale on which the separation system can be used. Fouling of membranes during water purification is a dramatic example: foulant layers of chemical and physical complexity form and require aggressive regeneration procedures that in turn place strong constraints on the types of membrane media that can be used. Another example is the blockage of pores in acti-
vated-carbon adsorbents used in the removal of dyes and other contaminants from water, which causes a decrease in performance and capacity. Advancing the ability to characterize the location, chemistry, and structure of unwanted products during chemical separations, particularly in the presence of the complex mixture characteristic of operating conditions, is critical for expanding the scope of current separation systems and developing new systems.
Exploring Alternative Strategies for Addressing Temporal Changes in Separation Systems
The three topics described above highlight different routes by which separation systems can evolve during use: by leaving a nonequilibrium state, through chemical reactions, and through the buildup of byproducts. Those processes typically reduce separation performance. However, there are ways to use processes that would usually be viewed as damaging. For example, considerable activity has occurred in the field of self-healing materials (Cordier et al., 2008; Wu et al., 2008), and some of the ideas in this field might have considerable value for separation materials. Controlled degradation can be used as a tool to enable the synthesis of materials not readily made by direct means (Jayachandrababu et al., 2017). Because temporal changes in separation systems are of such importance, there is great value in exploring strategies to reverse or avoid the changes in ways that go beyond simply slowing down or passivating materials against apparently inevitable processes.
The diversity and complexity of materials and processes that can be used in chemical separations are both signs of the opportunities and a challenge to the research community. To maximize the effectiveness of research on chemical separations and to drive the development of advanced techniques, community efforts to enhance the reliability and reproducibility of data and to create well-defined model systems that can be characterized by an array of orthogonal tools are needed. The associated challenges cut across all aspects of chemical separations.
The importance of data reproducibility is relevant in all fields of scientific research; separation science is no exception. There are already examples in which well-defined material standards have been established for specific applications through interlaboratory studies (Nguyen et al., 2018). Finding effective ways to define standards of that kind that are widely adopted and that address key potential sources of variance among experiments would have great value. The challenge intersects with the challenges already listed above. For example, efforts to define “standard” mixtures that represent key aspects of the complex mixtures in a particular field of interest or to define protocols for studying aging and degradation would be valuable. Efforts to use meta-analysis of the large amount of existing literature on many classes of separation materials might also point to efficient strategies to improve the reliability of available data (Park et al., 2017).
Developing Well-Characterized Model Systems
The opportunities associated with developing well-characterized model systems are distinct from those associated with data reliability. Such approaches as computational modeling can potentially be used to explore a wide array of materials or operating conditions. A key challenge is to validate the underlying computational methods and delineate the limits of their accuracy. In that and similar circumstances, enormous value comes from using well-defined materials that can be deeply characterized with a broad variety of experimental techniques. Model systems can also be fertile testing grounds for fundamental descriptions of the phenomena that control a material’s performance. Strong connections between fundamental and applied researchers and among experts able to apply and use diverse scientific tools and well-defined model systems will create many opportunities to accelerate development of fundamental understanding and application-inspired insights.
The recent emergence of powerful and readily accessible machine learning and data-science methods has created interest in diverse research disciplines. In many ways, chemical separations are ripe for advances based on those methods inasmuch as the number of separation materials and operating environments and the span of chemical challenges are far larger than can be systematically addressed through direct experiments. In principle, data science has the potential to accelerate progress in all aspects of chemical separations. Initial efforts have been made, but the use of data-science methods in chemical separations is nascent at best.
The gaps that exist in applying these methods to chemical separations are not in the existence and availability of computational methods—appropriate methods are widely accessible—but rather in the availability of appropriate data. Early experience in using data-science methods in various chemical fields suggests that the insightful engagement of people who have deep domain
expertise and can curate the available data will be critical for success. If data-science efforts are to lead to long-term successes in chemical separations, approaches that mesh these efforts with the domain-specific challenges outlined earlier in this chapter will be required.
Chemical separations are entering an era in which fundamental advances will be possible. In broad terms, this fertile intellectual landscape will include challenges associated with the intrinsic characteristics of separations—selectivity, capacity, and throughput—and challenges associated with the evolution of separation systems during use. There are large gaps in both areas, and progress in both will be critical for major advances in the field. A factor that is common to both is the need to consider complex environments rather than clean, model separations. The difficulties of understanding and controlling the phenomena that appear in complex chemical environments and in situations that span large dynamic ranges should become defining features of fundamental work in chemical separations.
The research community’s ability to address the challenges described above will be greatly enhanced if efforts are made to adopt approaches that maximize the utility of new work. Seeking community standards that enhance data reproducibility is an example that will have value throughout the field. In a similar vein, carefully selected model materials or separation systems that are thoroughly characterized by multimodal experiments and can provide a firm basis for modeling and simulation or development of enhanced experimental methods will have great value. Finally, the tools of data science are likely to be valuable in chemical separations, provided that they are thoughtfully combined with a domain-driven formulation of research questions and extensive efforts to curate data that can provide confidence in the applicability of the models that will emerge.
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