Handbook of Smart Materials in Analytical Chemistry, 2 Volume Set

By Miguel de la Guardia

A comprehensive guide to smart materials and how they are used in sample preparation, analytical processes, and applications

This comprehensive, two-volume handbook provides detailed information on the present state of new materials tailored for selective sample preparation and the legal frame and environmental side effects of the use of smart materials for sample preparation in analytical chemistry, as well as their use in the analytical processes and applications. It covers both methodological and applied analytical aspects, relating to the development and application of new materials for solid-phase extraction (SPE) and solid-phase microextraction (SPME), their use in the different steps and techniques of the analytical process, and their application in specific fields such as water, food, air, pharmaceuticals, clinical sciences and forensics.

Every chapter in Handbook of Smart Materials in Analytical Chemistry is written by experts in the field to provide a comprehensive picture of the present state of this key area of analytical sciences and to summarize current applications and research literature in a critical way. Volume 1 covers New Materials for Sample Preparation and Analysis. Volume 2 handles Analytical Processes and Applications.

• Focuses on the development and applications of smart materials in analytical chemistry
• Covers both, methodological and applied analytical aspects, for the development of new materials and their use in the different steps and techniques of the analytical process and their application in specific fields
• Features applications in key areas including water, air, environment, pharma, food, forensic, and clinical
• Presents the available tools for the use of new materials suitable to aid recognition process to the sample preparation and analysis
• A key resource for analytical chemists, applied laboratories, and instrument companies

Handbook of Smart Materials in Analytical Chemistry, 2V Set is an excellent reference book for specialists and advanced students in the areas of analytical chemistry, including both research and application environments.

• Language: English
• Publisher: Wiley
• Release date: Jan 22, 2019
• ISBN: 9781119422617

Book preview

List of Contributors

M. Inês G.S. Almeida

School of Chemistry

The University of Melbourne

Australia

Aziz Amine

University Hassan II of Casablanca

Morocco

Amina Antonacci

Department of Chemical Sciences and Materials Technologies

Institute of Crystallography

National Research Council

Rome

Italy

Fabiana Arduini

Department of Chemical Science and Technologies

University of Rome Tor Vergata

Italy

Sergio Armenta

Department of Analytical Chemistry

University of Valencia

Burjassot

Spain

Juan H. Ayala

Departamento de Química (Unidad Departamental de Química Analítica)

Universidad de La Laguna

Spain

Behzad Baradaran

Immunology Research Center

Tabriz University of Medical Sciences

Iran

Adriano Francisco Barbosa

Laboratory of Toxicant and Drug Analysis

Federal University of Alfenas – Unifal‐MGBrazil

Rodjana Burakham

Materials Chemistry Research Center

Department of Chemistry and Center of Excellence for Innovation in Chemistry

Khon Kaen University

Thailand

Soledad Cárdenas

Departamento de Química Analítica

Instituto Universitario de Investigación en Química Fina y Nanoquímica IUIQFN

Universidad de Córdoba

Campus de Rabanales

Spain

Lailah Cristina de Carvalho Abrão

Laboratory of Toxicant and Drug Analysis

Federal University of Alfenas – Unifal‐MG

Brazil

Robert W. Cattrall

School of Chemistry

The University of Melbourne

Australia

Stefano Cinti

Department of Chemical Science and Technologies

University of Rome Tor Vergata

Italy

Eduardo Costa Figueiredo

Laboratory of Toxicant and Drug Analysis

Federal University of Alfenas – Unifal‐MG

Brazil

Francesc A. Esteve‐Turrillas

Department of Analytical Chemistry

University of Valencia

Burjassot

Spain

Henrique Dipe de Faria

Laboratory of Toxicant and Drug Analysis

Federal University of Alfenas – Unifal‐MG

Brazil

Gabriele Favaretto

Department of Chemical Sciences and Materials Technologies

Institute of Crystallography

National Research Council

Rome

Italy

Beatriz Fresco‐Cala

Departamento de Química Analítica

Instituto Universitario de Investigación en Química Fina y Nanoquímica IUIQFN

Universidad de Córdoba

Campus de Rabanales

Spain

Mariane Gonçalves Santos

Laboratory of Toxicant and Drug Analysis

Federal University of Alfenas – Unifal‐MG

Brazil

Providencia González‐Hernández

Departamento de Química (Unidad Departamental de Química Analítica)

Universidad de La Laguna

Spain

Miguel de la Guardia

Department of Analytical Chemistry

University of Valencia

Burjassot

Spain

David S. Hage

Department of Chemistry

University of Nebraska

Lincoln

NEUSA

Mohammad Hasanzadeh

Drug Applied Research Center

Tabriz University of Medical Sciences

Iran

Soodabeh Hassanpour

Immunology Research Center

Tabriz University of Medical Sciences

Iran

Maryam Hejazi

Zabol University of Medical Sciences

Iran

Israel S. Ibarra

Area Academica de Quimica

Universidad Autónoma del Estado de Hidalgo

Mexico

Adam Kloskowski

Department of Physical Chemistry

Gdansk University of Technology

Poland

Spas D. Kolev

School of Chemistry

The University of Melbourne

Australia

Takuya Kubo

Graduate School of Engineering

Kyoto University

Japan

Ángela I. López‐Lorente

Departamento de Química Analítica

Instituto Universitario de Investigación en Química Fina y Nanoquímica IUIQFN

Universidad de Córdoba

Campus de Rabanales

Spain

Rafael Lucena

Departamento de Química Analítica

Instituto Universitario de Investigación en Química Fina y Nanoquímica IUIQFN

Universidad de Córdoba

Campus de Rabanales

Spain

Łukasz Marcinkowski

Department of Physical Chemistry

Gdansk University of Technology

Poland

Jorge Cesar Masini

Instituto de Química

Universidade de São Paulo

Brazil

Ahad Mokhtarzadeh

Department of Biotechnology

Higher Education Institute of Rab‐Rashid Immunology Research Center

Tabriz University of Medical Sciences

Iran

Danila Moscone

Department of Chemical Science and Technologies

University of Rome Tor Vergata

Italy

Jacek Namieśnik

Department of Analytical Chemistry

Gdansk University of Technology

Poland

Koji Otsuka

Graduate School of Engineering

Kyoto University

Japan

Idaira Pacheco‐Fernández

Departamento de Química (Unidad Departamental de Química Analítica)

Universidad de La Laguna

Spain

Giuseppe Palleschi

Department of Chemical Science and Technologies

University of Rome Tor Vergata

Italy

Jorge Pasán

Departamento de Física (Laboratorio de Rayos X y Materiales Moleculares)

Universidad de La Laguna

La Laguna (Tenerife)

Spain

Verónica Pino

Departamento de Química (Unidad Departamental de Química Analítica)

Universidad de La Laguna

Spain

Saumen Poddar

Department of Chemistry

University of Nebraska

Lincoln

USA

David S.M. Ribeiro

LAQV/REQUIMTE

University of Porto

Portugal

S. Sofia M. Rodrigues

LAQV/REQUIMTE

University of Porto

Portugal

Elliott Rodriguez

Department of Chemistry

University of Nebraska

Lincoln

USA

José A. Rodriguez

Area Academica de Quimica

Universidad Autónoma del Estado de Hidalgo

Mexico

João L.M. Santos

LAQV/REQUIMTE

University of Porto

Portugal

Viviana Scognamiglio

Department of Chemical Sciences and Materials Technologies

Institute of Crystallography

National Research Council

Rome

Italy

José X. Soares

LAQV/REQUIMTE

University of Porto

Portugal

M. Laura Soriano

Departamento de Química Analítica

Instituto Universitario de Investigación en Química Fina y Nanoquímica IUIQFN

Universidad de Córdoba

Campus de Rabanales

Spain

Supalax Srijaranai

Materials Chemistry Research Center

Department of Chemistry and Center of Excellence for Innovation in Chemistry

Khon Kaen University

Thailand

Jelena Vasiljevic

Department of Chemical Sciences and Materials Technologies

Institute of Crystallography

National Research Council

Rome

Italy

Preface

Analytical chemistry was dramatically changed when in the middle of the last century classical analytical methods were replaced by instrumental ones. A general complaint emerged about the absence, or strong reduction, of chemical behavior in the new methodologies and it is practically true that the advance of spectrometry and electroanalytical methods drastically reduced the use of reagents and moved to another scale of sensitivity, thus confirming the advantages of relative methods of analysis ahead of classical procedures based on stoichiometric reactions.

However, one century on, despite tremendous advancements, the new instruments do not provide the sensitivity we are looking for, nor the capability for multi‐analyte determinations in a single sample. Moreover, there is a social demand for improved sensitivity and selectivity of measurements. So, nowadays we are forced to look again in our chemistry books to focus on the fundamentals of extraction, pre‐concentration, and matrix removal to be able to lower the limit of detection values for the determination of target analytes. Additionally, we must search for new materials capable of producing extraordinary improvements of selectivity and sensitivity, as compared with direct measurements, and that means a return to consideration of chemical reactions at the molecular level. Thus, once again, chemistry is in the spot light of our analysis.

Probably, some readers were a little confused on reading the title of this book and its context. For clarity, we have decided to extend the concept of smart materials and not only consider as smart those for which their characteristics and properties could be modulated by changes in external parameters like pH, ionic strength, temperature, or pressure. In fact, other materials, like enzymes, antibodies, molecularly imprinted polymers, restricted access materials, metal–organic frameworks, or aptamers, have been considered together with other nanomaterials, polymers, and composites due to the tremendous possibilities that they offer regarding analyte specific interactions, electronic properties, high surface area, magnetic behavior, size exclusion, signal enhancement, or robustness.

The main objective of this book is to explore the exciting possibilities offered by the new generation of materials capable of improving the performance of analytical determinations. New available reagents, obtained from natural sources or produced based on accurate selection and modification of raw ones, pave the way for the development of new platforms of analysis in which a balance is made between the use of instrumental techniques for detection and a series of reactions selected to create, or modify, smart materials in order to enhance the analytical features of methods.

The editors would like to acknowledge the positive response of all the invited authors which has made it possible to have 80 scientists with different areas of expertise collaborating across 20 different countries. It has been great to work with many people whose works are well known in international journals and further literature, even though in some cases we did not have the opportunity to meet them before writing this book. The main reason for this is the decision to select invited authors of chapters based on the author’s authority in their field and not on reasons of vicinity or friendship. However, we must confess that after collaborating on this project, we wish to meet all the authors and continue this fruitful cooperation in our everyday tasks and do not hesitate to view this project as just the beginning of a long story of cooperation in order to contribute to excellent analytical chemistry.

The present Handbook of Smart Materials in Analytical Chemistry is divided for practical reasons into two volumes; the first is devoted to the presentation of new materials for sample preparation and analysis, and the second is devoted to analytical processes and applications. Volume I is a small compendium of smart materials presently available always considering them in terms of their analytical chemistry advantages and uses. In this first volume we aim to give readers as complete an idea as possible about the new reagents as well as the advanced possibilities offered by the older ones. Thus, materials such as ionic liquids, porous monoliths, surfactants, molecularly imprinted polymers, enzymes and immunosorbents, nanomaterials, quantum dots, carbon based nanomaterials, restricted access materials, polymer membranes, and metal–organic frameworks are presented and evaluated through the 15 chapters. Volume II of the present handbook consists of a discussion of the role of smart materials in the improvement of analytical processes and applications. The first part of second volume depicts the use of novel materials in typical analytical procedures employed for both sample treatment and analytical determination, while the second part is focused on the presentation of the main applications of smart materials in different fields like environmental, food, clinical, and forensic. The editors hope that all the chapters included in the book provide plenty of ideas suitable to be employed in the laboratories of readers, to open up new ways in method development and application. Hence, we hope that the Handbook of Smart Materials in Analytical Chemistry will become a reference text in the field and that the efforts of all those who contributed to the book will be useful for you, the reader.

Finally, we would like to acknowledge the support and excellent work of the team of John Wiley & Sons who have helped us during all the steps of production of this book from the initial proposal to the final edition. Elsie Merlin, Emma Strickland, and Jenny Cossham, we are very happy to have had the opportunity to work with you.

We hope you enjoy the handbook.

Let our Analytical Chemistry become smart by working together.

Miguel de la Guardia and Francesc A. Esteve‐Turrillas

Valencia, April 2018

VOLUME 1

1

Smart Materials: Made on Measure Reagents

Francesc A. Esteve‐Turrillas and Miguel de la Guardia

Department of Analytical Chemistry, University of Valencia, Burjassot, Spain

1.1 Role of Smart Materials in Analytical Chemistry

Analytical chemistry can be considered, from an applied pragmatic point of view, as the development and application of chemical methods to find an appropriate answer to social and research and development challenges by solving underlying analytical problems [1]. Thus, analytical chemistry is a multidisciplinary science in continuous evolution that must be adapted to face new problems and limits. Modern analytical chemistry must be focused to provide validated methods and tools to fulfill solutions to present and future issues, in a rapid and efficient way without any reduction of the main figures of merit of available methods while reducing human and economic consumed resources, without forgetting to be environmentally conscientious. In this sense, the conception of Green Analytical Chemistry considers in its 12 principles aspects such as: (i) direct analytical techniques instead of sample treatment, (ii) sample and residue reduction, (iii) automatization and miniaturization, and (iv) multianalyte determination methods [2]. Improvements in current analytical instrumentation have allowed achievement of many of these milestones, but their use in combination with smart materials has allowed us to go a further step.

A specific definition of smart materials is that they have some properties that can be modulated significantly in a controlled way through external stimuli such as stress, temperature, pH, moisture, electric, or magnetic fields [3, 4]. However, in this book we have focused on the analytical process and define as smart materials those tailored, task‐specific, or designed materials that provide tremendous enhancements of practical properties, at any level of sample preparation and analytical determination, such as their selectivity, sensitivity, easy automation, or speediness. Consequently, their use can incorporate added value to well‐established analytical methods. Discoveries of novel functional materials have played very important roles in improving conventional analytical methods and in developing novel technologies and procedures, giving huge improvements in terms of sensitivity, selectivity, ease of use, rapidity, and miniaturization of modern analytical methods.

In recent years, the application of smart materials has attracted the attention of researchers, as shown by the high increase in published papers related to analytical determination using smart materials (Figure 1.1). Nanoparticles, carbon‐based materials, ionic liquids, enzymes, antibodies, aptamers, molecularly imprinted polymers (MIPs), restricted access materials (RAMs), or metal–organic frameworks (MOFs) are among these new tools suitable for modifying the characteristics of analytical methods. These smart materials have been applied in different steps of an analytical process, affording high efficacy sorbents in sample treatment, improved stationary phases in chromatography, main molecular recognizing components of electrochemical sensors and portable systems, among other functions. In this chapter and throughout both volumes of the Handbook of Smart Materials in Analytical Chemistry the main advantages and uses of these special reagents will be analyzed in detail.

Graph displaying 11 ascending curves representing published papers, including nanoparticles, CNTs, graphene, ILs, QDs, antibodies, immunomaterial, aptamer, MOFs, MIPs, and monoliths from 1997 to 2016.

Figure 1.1 Evolution of the number of articles published in per‐reviewed journals related to analytical determination using smart materials, such as nanoparticles, carbon nanotubes (CNTs), graphene, ionic liquids (ILs), quantum dots (QDs), antibodies, immunomaterials, aptamers, metal–organic frameworks (MOFs), and molecularly imprinted polymers (MIPs).

Source: Scopus (Elsevier B.V., Amsterdam, Netherlands).

1.2 Smart Materials for Sample Treatment

Usually, an analytical procedure has been considered as a succession of steps systematically organized, like a chain made up of several links, with the treatment of samples being the most crucial step, and also the weakest, link (see Figure 1.2). Moreover, it has been quantified that sampling and sample treatment steps involve 67% of the analysis time, but most importantly they give rise to 60% of error sources [5]. Sample preparation generally involves the clean‐up of the sample matrix and the enrichment of target analytes to provide an interference‐free signal enhancement. Consequently, both the sensitivity and selectivity enhancement of the method are the main challenges. In particular, sample preparation is the most critical step in the analysis of biological matrices, due to the complexity of the matrix and the presence of multiple interferents at diverse concentrations, such as protein, polypeptides, lipids, fatty acids, sugars, etc., together with analyte related species such as metabolites [6]. In this sense, the development and use of novel smart materials with improved properties for sample treatment is considered one of the most promising strategies to improve practical aspects and, in particular, to decrease analysis time and labor, together with an increase in the efficacy, selectivity, simplicity, and speed of the treatment. Obviously, the final analytical properties of the method not only depend on the sample treatment, they are strongly related to the employed separation method (liquid and gas chromatography, or capillary electrophoresis) and the detection technique. Thus, chromatography techniques coupled to mass spectrometry provide high selectivity and sample treatment is based on a simple clean‐up of extracts or sample matrix directly to remove macromolecules and proteins using inexpensive and low selective sorbents; while using detection systems with relatively low selectivity, such as UV–visible, fluorescence, or ion mobility spectrometry, the use of sorbents with high selectivity toward target analytes is required. Thus, the application of smart materials for sample treatment can be summarized as: (i) increased selectivity in the target analyte retention and pre‐concentration, (ii) high adsorption capacity due to the improved surface area to volume ratio, (iii) extension of novel chemical analyte–sorbent interactions with high extraction efficacy, and (iv) easy handling of materials and speed of processes related to the use of magnetic materials. On the other hand, the aforementioned advances provided by smart materials in the separation and determination steps focus on the improvement of selectivity including specificity in chiral analysis or the separation of strongly related chemical forms. In this sense, the use of smart materials for building column or capillary materials together with their use as mobile phases have been exciting possibilities in clinical, environmental, and food analysis.

Diagram of the steps of the analytical process, displaying a line connecting (top–bottom) problem, sample, sub-sample, preliminary steps, separation, and determination. On the right are their objectives and challenges.

Figure 1.2 Steps of the analytical process, their objectives and challenges, and the main advantages provided by the use of smart materials.

Figure 1.3 shows the most promising smart materials employed as sorbents for selective and non‐specific sample treatments. Smart materials employed for the selective extraction of target analytes include antibodies and aptamers, from biological sources, but also synthetic materials like MIPs, MOFs, and RAMs. In the case of non‐specific sorbents, many sample treatment approaches have been developed using materials like graphene, carbon nanotubes (CNTs), silica nanomaterials and monoliths, surfactant‐based compounds, or ionic liquids, which offer high extraction efficacies and could be also improved by the incorporation of modified surface activities for the selective extraction of target analytes. In fact, all the aforementioned smart materials have gained the attention of researchers to be employed as sorbent in different extraction techniques [7].

Radial diagrams of selective (left) and non‐specific (right) smart materials employed as sorbents for sample treatment. The diagram on the left includes MIPs and RAMs. The diagram on the right includes CNTs and graphene.

Figure 1.3 Selective (a) and non‐specific (b) smart materials employed as sorbents for sample treatment.

1.2.1 Solid‐Phase Extraction

Worldwide, one of the most frequently used sample treatment techniques in laboratories is solid‐phase extraction (SPE), where the target analytes are transferred to a solid sorbent from a liquid or dissolved sample; the analytes are released in a later step using elution solvents. SPE provides as main advantages simplicity, versatility, efficacy, low‐cost, and high recoveries. Traditional SPE sorbents are based on adsorption, reversed phase, normal phase, and ion exchange interactions, using silica gels with chemically bonded stationary phases or porous polymers. The development of novel sorbents for SPE has played an important role in recent decades, in order to improve extraction efficiency and selectivity [8].

The use of carbon‐based materials as SPE sorbents was introduced following the discovery of fullerene (C60) in 1985, with the use of materials like single‐ and multi‐walled CNTs, nanohorns, nanocones, nanofibers, graphene oxide, or graphene [9]. CNTs have been widely employed in recent years because of their π–π interactions with aromatic compounds, as well as their interesting properties like high surface area, easy functionalization, wide accessibility, and relatively low price [10]. The uses of graphene as SPE sorbent are reduced due to its lower water dispersibility. However, graphene oxide has gained great attention due to the surface incorporation of a wide range of functional groups like hydroxyls, carbonyls, or ketones, which improve the extraction efficacy [11]. Moreover, surface‐modified graphene oxides promote van der Waals interactions that allow the retention of both hydrophilic and polar analytes [12].

SPE support selectivity was increased by the linking of enzymes to solid supports and can be greatly enhanced by using antibody‐based materials, and also so‐called immunosorbents, which involve antigen–antibody interactions that provide a selective extraction of target analytes with a minimal coextraction of sample matrix [13]. Antibodies are usually covalently coated, via amino, carboxyl, or thiol groups, to materials like carbohydrate polymers, as agarose and cellulose, or synthetic acrylamide, polymethacrylate, and polyethersulfone polymers [14]. Immunosorbents have been employed for the robust, quantitative, and selective SPE of a wide variety of antibiotics, hormones, pesticides, and mycotoxins in complex samples such as urine, soil, or food [15, 16]. Additionally, some selective immunoaffinity materials are nowadays commercially available for mycotoxin extraction from R‐Biopharm AG (Darmstadt, Germany) and Merck (Darmstadt, Germany).

MIPs are cross‐linked synthetic polymers, with a three‐dimensional macromolecular structure, obtained by the co‐polymerization of a functional monomer and a cross‐linker in the presence of a template molecule. MIPs are considered as artificial biomimetic receptors with a high selectivity in the same range as that of antibodies and other biological receptors, but with an improved stability at extreme temperature and pH conditions, easy and low cost synthesis, and reusability [17]. The first reported use of MIPs, as selective sorbent for SPE, was made in 1994 [18]. Since then a rising number of MIPs have been synthetized for versatile use in sample preparation [19], including environmental [20] and food applications [21]. In fact, MIP‐based SPE sorbents are widely established in current analytical methods, and they are commercially available from standard supply companies like Merck (Darmstadt, Germany) or Affinisep (Petit Couronne, France).

Aptamers are synthetic oligonucleotides with up to 110 single stranded base pairs able to retain specifically target molecules with a high selectivity due to the combination of hydrogen bonds, van der Waals forces, and dipole interactions.

The selectivity of aptamers is comparable to that obtained with antibodies, but they can be produced in vitro, avoiding the use of experimental animals and, thus, provide relatively low cost biomaterials. Molecular recognition sorbents based on aptamers show promising properties for SPE because of their high specificity and binding affinity, low cost, good stability, and easy in‐vitro synthesis [22]. Applications of aptamer‐based materials for SPE include the analysis of mycotoxins, drugs, antibiotics, and even persistent organic pollutants such as polychlorinated biphenyls [23, 24].

RAMs show a dual surface; the inner layer retains small molecules by both hydrophobic and hydrophilic interactions, while the external layer exhibits a size exclusion effect over the sample matrix. Thus, it allows the simple and easy extraction of target analytes from biological fluids, avoiding the retention of macromolecules from the matrix. RAMs have been employed for SPE in biological fluids for the analysis of drugs [25] or pesticides [26], even including inorganic species like Cu(II) and Cd(II) [27].

MOFs are distinctive materials made from metal ions and organic ligands with unusual properties, like high surface area, porosity, selectivity, and thermal and chemical stability [28]. MOFs have been employed for the SPE of compounds such as non‐steroidal anti‐inflammatory drugs [29], naproxen and its metabolites [30], and naphthol enantiomers [31].

1.2.2 Solid‐Phase Microextraction

The solid‐phase microextraction (SPME) technique was proposed by Pawliszyn and Arthur in 1990. It consists of a fused silica fiber, coated with a thin layer of an extracting material, fixed inside of the needle of a syringe [32]. Analyte extraction is carried out directly from liquid or dissolved samples or after a head‐space thermal treatment from liquid or solid materials. Desorption of target analytes from the fiber is usually carried out by thermal desorption, which makes it easy to couple directly to gas chromatographic systems, but analysis by liquid chromatography or capillary electrophoresis is also possible. SPME provides great advantages for sample treatments, such as simplicity, versatility, sensitivity, short extraction time, reusability, solvent‐free technique, robustness, and easy automation [33].

Commercial SPME devices are mainly coated with polymeric sorbents such as polydimethylsiloxane (PDMS) and polyacrylate, alone or in combination with divinylbenzene and/or carboxen depending on the final application. Extraction efficiency and selectivity of standard devices have been improved by the use of several smart materials as fiber coating materials, such as ionic liquids, polymeric ionic liquids, graphene, CNTs, MIPs, and MOFs [34]. These materials provided enhanced properties because of their easy synthesis, sensitivity, high thermal and chemical stability, reproducibility of measurements, and wide linear range. Regarding selectivity, carbon‐based materials provide a moderate selectivity toward aromatic compounds due to their p‐electron‐rich structure, but a tunable selectivity for different analytes can be obtained by the use of ionic liquids, polymeric ionic liquids, MIPs, and MOFs [35]. Strategies to improve the extraction efficiency of SPME have focused on the use of nanomaterials, nanostructured polymers, and monolith packing capillaries [7].

Additionally, on‐line SPME techniques are based on the adsorption of target analytes at the inner surface of an internally coated capillary column that is directly coupled on‐line to a chromatography system. The extraction properties of the method mainly depend on the thickness and nature of the sorbent. Commercially available capillary columns have been traditionally employed for in‐tube SPME, but they have been replaced by new coating materials with improved properties such as MIPs, immunosorbents, ionic liquids, nanoparticle‐based materials, and monolithic capillary columns [36].

1.2.3 Magnetic Extraction

Dispersive SPE is an extraction method, where the extraction is carried out directly in the bulk sample solution instead of using a column filled with a solid material. The sorbent is dispersed into the sample solution to extract the target analytes or to remove matrix interferents. This technique has gained increased attention in recent years due to its high efficacy, speed, and simplicity. Dispersive SPE avoids the loading of large volumes of sample and increases the analyte mass transfer from the sample to the sorbent due to its large surface area‐to‐volume ratio and enhanced contact between material analytes and the solid [37]. However, the employed sorbent is usually isolated from the bulk solution, by using a centrifugation or filtering step, before being eluted by using a desorption solvent – this step has many weaknesses due to the potential loss of material, contaminations, and slow filtration. The synthesis and development of magnetic sorbent materials has contributed to the development of magnetic dispersive SPE (MSPE) that simplifies the overall extraction procedure. It involves the previous dispersive extraction of target analytes from the sample to the magnetic sorbent, which is easily collected from the medium using an external magnetic field (Figure 1.4a, b).

Image described by caption.

Figure 1.4 Images of a magnetic smart material dispersed (a) and recovered by a magnet (b). Scheme and smart materials employed in the layers of magnetic materials (c).

A huge number of magnetic materials have been synthetized recently for the development of MSPE procedures in different fields. Iron, nickel, cobalt, and their respective oxides have been employed as magnetic materials. However, the use of magnetite (Fe3O4) is usually preferred due to the ease of synthesis, biocompatibility, and low cost [38]. Magnetic nanoparticles are coated by a variety of organic and inorganic ligands following the classical core–shell model shown in Figure 1.4c. Nevertheless, other morphologies have also been employed, such as multicore, bead‐on‐bead, and brush morphology [39]. Recently, several smart materials have been applied to the development of magnetic nanoparticles, such as CNTs, graphene, graphene oxide, MIPs, surfactant coated nanoparticles, ionic liquids, organic polymer, antibodies, proteins, aptamers, and other functionalized nanoparticles [7, 40, 41].

Another analytical approach for sample treatment that combines SPME and magnetic materials is stir bar sorptive extraction (SBSE). This technique uses a standard stir bar magnet coated with PDMS, which is immersed in the sample solution in order that target analytes could be retained in the PDMS phase. Retained compounds are eluted by using solvents or thermal desorption systems. SBSE methods provide easy and rapid extractions of analytes from liquid samples and can easily be automatized using specific automatic samplers. Different smart materials have been employed as coating agents of stir bars in order to improve extraction efficiency like metal nanoparticles [42] or graphene oxide [43].

1.2.4 Automatization and Miniaturization

As previously noted, the pre‐treatment of samples usually consumes the most part of human resources and analysis time, and as a consequence decreases the sample throughput and increases the analysis cost. Thus, a new trend in sample treatments has focused on the development of miniaturized and automatized procedures for the treatment of samples, including all the steps of pre‐concentration, clean‐up, and direct analysis. In this sense, the singular properties and versatility of smart materials open up the possibility to develop new flow injection devices based on the use of nano‐scale, magnetic, or high selective materials [44].

On‐line SPE devices basically consist of an automatized or robotized SPE device directly coupled to a detection system, using traditional alkyl‐bonded silica and polymer columns. However, the use of RAMs, MIPs, and immunosorbents has also been reported in order to increase the selectivity of the procedure [45]. The use of multi‐well SPE plates, using 96, 384, and even 1536 wells, allows the simultaneous treatment of a great number of samples in reduced analysis time and it is highly valuable for clinical applications [8]. Additional advantages of automatized systems compared with off‐line SPE procedures are related to high precision, reusability, miniaturization, and the reduction of operator risks, sample contamination, and analyte degradation [45]. However, available instrumentation is still quite expensive, has low portability, and requires a deep optimization of the experimental conditions [12].

A strategy to miniaturize conventional SPE‐based methodologies consists of the use of polypropylene volumetric pipette tips packed with the corresponding sorbent. Analytes are retained in the sorbent by repeated aspiration cycles using single channel or multichannel pipettes. The main advantage of pipette tip SPE is the simplicity, speed, and reduction of the amount of sorbent and organic solvent consumption [8]. MIPs have been widely employed as pipette‐tip SPE sorbents [46], but other smart materials have been also employed such as polyacrylonitrile nanofibers [47] and cellulose acetate filters [48].

Miniaturization and automation of sample pre‐treatment methods have been carried out by using different types of flow systems, such as flow injection analysis (FIA), sequential injection analysis (SIA), multicommutation devices, or lab‐on‐valve (LoV) systems. The development of bead injection (BI) LoV systems allows the automatized use of small volumes of moveable sorbents to clean‐up and preconcentrate analytes from the sample [49, 50]. The main advantages of miniaturized systems are the extreme reduction of sample amount required, reagent consumption, and waste generation, reducing both the analysis cost and the environmental impact of methods. In this sense, conventional SPE phases and smart materials, like agarose, magnetic nanoparticles, or MIPs, have been employed as sorbents for BI‐LoV procedures [51].

1.3 Smart Materials for Analytical Determinations

Smart materials provide a wide variety of excellent properties that have contributed to the development of new and improved analytical methods. Figure 1.5 shows a summary of the main smart materials employed in the development of current analytical methods, such as stationary phases for chromatography and electrophoresis, sensors and chips, immunoassays, laser desorption ionization, and SERS (surface‐enhanced Raman spectroscopy) signal enhancement. As can be seen, assorted smart materials have been employed for the aforementioned analytical applications, considering material specific factors such as particle size, electronic properties, selectivity, stability, etc.

Diagram of smart materials employed in the design and development of recent analytical approaches: (left–right) chromatography, electrophoresis, sensors, immunoassays, SERS, and laser desorption ionization.

Figure 1.5 Main smart materials employed in the design and development of recent analytical approaches.

1.3.1 Stationary Phases

Chromatography separations are strongly dependent on the nature of the stationary phase, the column length, and the internal diameter. Furthermore, film thickness and particle size of the stationary phase also contribute to the efficacy of analytical separations in gas and liquid chromatography, respectively. Parameters like polarity, particle size, chemical and thermal stability, and homogeneity can be adjusted by using surface‐modified silica particles, polysiloxanes, and polymeric materials. In this sense, the use of smart materials with a wide range of physico‐chemical properties allows us to modulate the chromatographic separation providing enhanced resolution as compared with conventional stationary phases.

New stationary phases have been developed for high‐performance liquid chromatography (HPLC), achieving higher efficiency and unique selectivity using different chromatography modes like reversed‐phase, normal‐phase, ion‐exchange, or hydrophilic interaction liquid chromatography (HILIC). Conventional packed HPLC columns can be categorized as inorganic (bare silica, modified silica, inorganic oxides, and graphite), organic (nonporous or macroporous polymers), and inorganic–organic hybrids that show the merits of both material types increasing simultaneously thermal and chemical stability [52]. Porous spherical silica particles are the most extended and popular substrates employed for HPLC separations, containing pure alkyl chains (C8 or C18), or alkyl chains with reactive groups (such as amino, chloro, epoxy, mercapto, or isocyanate groups). The use of reactive groups allows the easy tethering of multifunctional ligands, such as cyclodextrin, calixarene, crown ethers, and ILs, which offer enhanced chromatography retention and selectivity, because of the heterogeneous interactions with the ligands based on hydrogen bonding, π–π, dipole‐induced dipole, and electrostatic interactions [53].

A wide variety of smart materials have been evaluated for their use as HPLC stationary phase. MIPs have been traditionally employed as HPLC stationary phase, with the column being packed with ground and sieved bulk polymer, or used as monolith, monodispersed spherical MIPs, and composite polymer beads [54]. The production of packed MIP columns is a tedious process, while the production of monolithic columns is simpler but efforts must be focused to increase their reproducibility and reusability [55]. Additionally, HPLC stationary phases have been modified with different carbonaceous nanomaterials like CNTs, fullerenes, graphene, and nanodiamonds, with a large surface‐area, easy derivatization, and average thermal, and mechanical stability [56]. MOFs have been also employed as stationary phases due to their exceptionally large surface area, tunable pore geometry, and versatile structure and chemistry [57]. The use of high specificity antibodies for affinity chromatography has an important role in characterizing immobilized proteins and provide direct measurements with multiple binding sites [58]. Effective enantioselective separations of pharmaceuticals [59] and even atropisomeric [60] compounds have been carried out using chiral columns based on gold nanoparticles, carbonaceous materials, MIPs, MOFs, ordered mesoporous silica, and capillary monoliths.

Monolithic capillary columns offer optimized porous structures in combination with a rich surface chemistry. The use of ILs as functional monomers and porogenic solvents provides improved selectivity and stability. The incorporation of nanoparticles, such as metal oxides, CNT, graphene, or MOFs, tunes monolith morphology and, as a consequence, enhances the separation efficiency [61]. Additionally, fiber‐based monoliths allow the packing of HPLC columns by aligned fibers, woven matrices, or contiguous fiber structures to achieve rapid and effective chromatographic separations [62].

In the same way, as indicated for chromatography, smart materials have also been employed for the improvement of capillary electrochromatography methods. Different materials have been covalently anchored to the capillary walls of open‐tubular capillaries in order to prevent analyte adsorption and to modify the rate of the electroosmotic flow [63]. MIP‐based applications have shown superior separation performances using multiple formats, such as packed particles, capillary coating, monoliths, and use of nanoparticle‐based pseudo‐stationary phases [54]. Carboxylated CNTs [64] and graphene [65] have also been widely employed because of enhanced hydrophobic, ionic, and hydrogen bonding interactions that take place simultaneously with the analyte. Ionic liquids covalently bound to the capillary surface were applied for this purpose [63]. Acrylamide‐, methacrylate‐, and silica‐based monolithic capillaries have also been employed for many capillary electrochromatography applications [66]. Enantiomeric separations have also been achieved by capillary electrochromatography using smart materials like MIPs and nanoparticles such as CNT, silica, TiO2, and Al2O3 coated with cyclodextrin to provide the stereoselectivity [59]. Cyclodextrin‐based capillary polymer monoliths have been efficiently employed as they provide enantioselective separations with a large surface area [61, 67].

1.3.2 Sensor Development

Optical and electrochemical sensors are widely employed in several analytical applications due to the rapid response, easy handling, low cost, portability, and miniaturization, giving also high sensitivity and selectivity. Consequently, the extended deployment of smart materials in this field has really improved their use and enhanced their analytical characteristics. Nanosensors have received a great attention due to the interaction with target analytes at a scale that makes them suitable for ultrasensitive detection. The exceptional photoelectric properties and size of nanoparticles allows their efficient use as electrode materials. Thus, gold nanoparticles, carbon‐based nanoparticles, and quantum dots QDs materials have played an important role in the development of a wide variety of sensors for analytical applications. Among others, gold nanoparticles are the most employed nanomaterial due to high stability and other particular characteristics like large surface area, size‐dependent optical properties, strong adsorption, and easy functionalization. Moreover, gold nanoparticles absorb in the visible spectrum region and can be employed for colorimetric detection [68].

Graphene and related materials have been employed for the fabrication of sensitive sensors and biosensors because of their extraordinary properties, such as electrical conductivity, large accessible surface area, and high electron transfer rate. Graphene shows low water solubility and a lack of surface functionality; thus, the use of graphene oxide provides more adequate properties for sensor development than graphene, and presents an improved capacity to immobilize biomolecules [69]. Graphene nanosheets, graphene oxide, and reduced graphene oxide have been employed in the development of chemiluminescence resonance energy transfer and luminescence quenching‐based sensors [70]. Graphene based sensors have been employed for clinical, environmental, and food science applications [69]. MIPS‐graphene oxide sensors have been also employed, based on their extremely high selectivity, in the design and development of selective sensors for several target compounds like dopamine, vanillin, epinephrine, benzenediol isomers, or sulfamethoxazole [70].

Biosensors are sensors that are coupled to a biomolecule, such as an antibody, enzyme, or similar, which provides an especially high selectivity for a series of target molecules, due to the high affinity between antibody and antigen, or substrate and enzyme. Potential applications of antibody‐based sensors (immunosensors) are focused on clinical and diagnostic areas for the analysis of several biomarkers at point‐of‐care application [71].

Electrochemical aptasensors are a new type of biosensor, based on the electrochemical transduction produced when the aptamer specifically recognizes a target analyte. These sensors provide a high selectivity and sensitivity, low cost, and require simple instrumentation. Aptasensors have been employed for the analysis of small molecules, proteins, and nucleic acids by their coupling to optical, electrochemical, and mass sensitive detectors [72]. The miniaturization of aptamer‐based sensors through the integration with nanotechnologies allows the production of sensors in array format, which allows the simultaneous multiplex analysis of several compounds [73].

Quantum dots (QDs) are luminescent semiconductor nanocrystals with high quantum yield, large extinction coefficient, high photostability, broad absorption, and narrow emission spectra [74]. Additionally, QDs fluorescence can be easily tunable by the selection of their chemical composition (binary and ternary alloys of heavy metals) and particle size (within the low nm diameter). Sensors have been developed measuring the enhancement or quenching of QD fluorescence as consequence of a direct interaction of target analyte with the surface of a QD particle. QD‐based sensors have been developed for the determination of different organic compounds like spirolactone, tiopronin, dopamine, glucose, TNT, anthracene, p‐nitrophenol, 1‐naphthol, methionine, and enoxacin [75]. These interactions are, in some cases, unspecific, and strongly dependent on the QD coating, and ratiometric sensors could be developed [76].

Selective sensors have been developed based on the Förster resonance energy transfer (FRET) phenomenon, which involves the transfer of resonant fluorescence energy from an excited donor to a ground‐state acceptor fluorophore [77]. The efficacy of the energy transfer depends on the Förster radius (distance between the fluorophores) and the spectral overlap between them. QDs show excellent properties such as those of a donor emission fluorophore because of its tunable emission wavelength, as well as wide absorption band, high quantum yield, and easy bioconjugation [78].

Carbon dots are carbon‐based fluorescent materials with excellent optical properties like QDs – tunable with the appropriate control of size, shape, and surface modification. These materials show a lower toxicity and higher biocompatibility than standard QDs, but a lower quantum yield. However, photoluminescence of carbon dots can be greatly enhanced by doping with nitrogen, sulfur, and phosphorus elements. Additional characteristics of carbon dots are simple synthesis, high aqueous solubility, low cost, and suitability for bioimaging [79]. Nanodiamonds, graphite, CNTs, or activated carbon have been applied for their high fluorescence in analytical sensors, with superior performance seen with the use of graphene carbon dots due to their exceptional electronic properties, high conductivity, and the high number of reactive sites [80].

1.3.3 Immunoassays

Immunoassays provide analytical methods for the analysis of both biomolecules and small‐size analytes, based on the extremely high specificity and selectivity of antibody–antigen interactions. One of the most extensively used immunoassays in analytical chemistry is the so‐called enzyme‐linked immunosorbent assay (ELISA) format, a plate‐bound detection based on the use of specific antibodies and enzymes. Different ELISA formats can be employed, such as sandwich, competitive, and antigen‐down assays, depending on the target analyte, the available immunoreagents, and the required dynamic range [81]. ELISA assays usually employ a total analysis time of 1 or 2 h. However, due to its simplicity and the use of 96‐well plates, the sample throughput is one of its main advantages. Typically, a horseradish peroxidase is conjugated to the antibody (or hapten) and, after the immunological reaction, a concentration‐related signal is generated by adding the appropriate enzymatic substrate.

Fluorescent detection has been also employed in immunosensors using organic dyes like fluorescein or rhodamine coupled to the immunoreagent, but a low quantum yield, and poor stability, is often obtained. In this sense, the use of QDs has been proposed as effective luminescent probes for the development of fluorescent immunoassays. Surface functionalized QDs can be easily conjugated to biomolecules like proteins, antibodies, antibody fragments, aptamers, etc. in order to obtain unique nanoparticles with both excellent optical properties and high specificity [77]. QDs are typically excited by a single wavelength and those with different emission wavelengths can be used as fluorescent labels for simultaneous multianalyte immunoassays (multiplexed) with negligible spectral interferences [82, 83].

Aptamers, as short single‐chain oligonucleotides that show high binding affinities against a wide range of target analytes with high selectivity, have been proposed to replace antibodies in many immunoassay systems. Aptamers are easier and cheaper to produce than antibodies and do not require the use of cells or experimental animals [84]. Aptamers are usually immobilized over different supports such as gold, silica and carbon nanoparticles, magnetic beads, graphene, Sepharose, and modified cellulose particles to be employed in biosensors [85].

Recombinant antibodies, often so‐called nanobodies, are variable domain of heavy chain antibodies (12–15 kDa approximate molecular weight) that selectively bind to specific antigens. Nanobodies have been employed in the development of immunoassays, moreover in FRET‐based approaches where the molecular distances between fluorophores must be reduced [86].

Lateral flow immunoassay is a simple and cost‐effective methodology usually employed for rapid point‐of‐care testing, based on the movement of the sample components through a membrane that enables the formation and separation of complexes after an immunochemical reaction, avoiding sample pre‐treatments or washing steps [87]. Lateral flow test strips have been widely employed in different areas such as clinical diagnostics, drug screening, or food analysis [88].

1.3.4 Signal Enhancement

Surface‐enhanced Raman spectroscopy (SERS) refers to an inelastic light scattering process from analytes in close proximity to a plasmonic substrate that provides rich vibrational spectroscopic information about the adsorbed molecule with three orders of magnitude enhancement of classical Raman signals. It has been considered a promising non‐destructive technique for chemical, biological, and structural analysis due to its simplicity, rapidity, extreme sensitivity, and high selectivity, even reaching single‐molecule limits of detection. SERS has been applied to quite different areas like electrochemistry, catalysis, biology, medicine, art conservation, and materials science [89].

Standard plasmonic substrates (Au and Ag) usually show a lack of thermal and pressure stabilities, and they have been replaced by metal oxides like Al2O3, TiO2, and SiO2. A remarkable SERS enhancement can be achieved by the use of capture agents, such as cross‐coupling with metal affinitive ligands, self‐assembled monolayers of thiolated molecules, polymer coatings, molecular recognition agents, aptamers, antibody fragments, and cage‐like molecular recognition materials (such as cucurbiturils, calixarenes, and cyclodextrins) [89]. Polymer containing nanoparticles have been also employed as capture layer to concentrate analytes with a moderate selectivity, leading to increasing attention in recent years to the use of MIPs to improve the specificity of SERS interactions [90]. Graphene quantum dots considerably enhance the SERS effect due to the abundant hydrogen atoms terminated on their surface, which promotes an efficient charge transfer [80]. Other smart materials like graphene oxide or Au─Ag core–shell nanorods have been also evaluated for application as SERS substrates [91].

Furthermore, a new platform, so‐called slippery liquid infused porous SERS (SLIPSERS) has been developed to extend the application of SERS to both aqueous and non‐aqueous media, based on the shape of a film of lubricating fluid on a substrate of Ag nanoparticles using an evaporating liquid droplet [92]. The combination of a SLIPSERS platform with a SERS mapping technique allows the ultrasensitive detection of chemical and biological analytes at the low attomolar level in common fluids.

1.3.5 Laser Desorption/Ionization Mass Spectrometry

Matrix‐assisted laser desorption/ionization mass spectrometry (MALDI‐MS) is a soft ionization technique attached to a mass spectrometry detector, usually a time‐of‐flight analyzer, widely employed for the analysis of proteomics, biological cells and tissues, polymers, and small molecules. Direct ionization occurs for molecules that have strong absorption of the laser energy, but non‐absorbing analytes require the use of a matrix that absorbs the laser energy and assists the laser desorption/ionization process of the target analyte. Conventional matrix compounds employed for MALDI‐MS are 2,5‐dihydroxybenzoic acid, cinnamic acid, sinapic acid, caffeic acid, ferulic acid, naphthalene, coumarin, or curcumin [93].

Smart materials based on organic matrices are promising sorbents that provide new functions for MALDI‐MS. The use of nanoparticles with a large surface area, variable pore sizes, and surface functionalization provides new functions and offers new applications for MALDI‐MS analyses, and even may improve the degree of selectivity of ionized analytes [93]. Gold nanoparticles have remarkable advantages, such as easy sample preparation, low background, high salt tolerance, and can be used for the analysis of molecules of less than 500 Da [94]. Carbon nanomaterials usually offer high efficiency and sensitivity in the desorption/ionization of analytes, reduce background noise, and can be applied to both large and small molecules [95]. The incorporation of functional groups to carbon nanomaterials allows an improvement of assay selectivity. Enzyme‐coupled nanoparticles constitute an effective affinity‐based tool for the study of specific interactions between enzymatic targets and small molecular weight analytes in complex mixtures [91]. The use of IL‐based organic matrices provides enhanced efficiency, tunable laser absorption, high ionizability, low vapor pressure, low flammability, and low toxicity [93]. MOF materials have also been employed as adsorption materials and due to their rich chemistry have a promising future for MALDI‐MS applications [96].

1.4 The Future Starts Now

The tremendous advances made in recent decades in material science, nanotechnology, and biotechnology have allowed us to extend the number of new materials with exceptional biological, physical, and chemical properties. The contribution and impact of smart materials considered as a whole, like nanoparticles, carbon‐based materials, quantum dots, MOFs, aptamers, or magnetic materials, in the analytical chemistry field has been tremendous and it is nowadays practically impossible to quantify the number of developed applications. Figure 1.6 shows a summary of the main improvements of smart materials‐based analytical methodologies. Moreover, the combination of different smart materials and their hyphenation with novel or classical instrumentation expands even more the possibilities within the reach of present scientific advancements. In this sense, analytical chemists must keep an eye on these findings in order to find potential applications or improvements for today’s analytical methods. However, a sure, successful advancement will be obtained from the close collaboration of chemists, biologists, and material scientists, working together in the development of tailor made materials that will allow us to improve current analytical procedures and to design new ones. Analytical chemists have been presented with a great gift – smart materials. We are taking the first steps of a future that starts now and we need to take a step further to move from the bench to real world applications. In the present book you will certainly find many exciting ideas to improve your everyday work. So, open your mind, take a deep breath, and let the magic begin!

Diagram displaying improved aspects of smart materials, namely, novel analyte interaction, high selectivity, simplicity and speed, sensitivity enhancement, environmental concern, and physico-chemical stability.

Figure 1.6 Main improvements with smart materials‐based analytical methodologies.

Acknowledgements

The authors gratefully acknowledge the financial support of the Ministerio de Economía y Competitividad (CTQ 2014‐52841‐P) and Generalitat Valenciana (project PROMETEO‐II 2014‐077).

References

1 Valcarcel, M. (1992). Analytical chemistry – today's definition and interpretation. Fresenius’ J. Anal. Chem. 343: 814–816.

2 Gałuszka, A., Migaszewski, Z., and Namiesnik, J. (2013). The 12 principles of green analytical chemistry and the SIGNIFICANCE mnemonic of green analytical practices. TrAC‐Trends Anal. Chem. 50: 78–84.

3 Spillman Jrdag, W.B., Sirkisddag, J.S., and Gardiner, P.T. (1996). Smart materials and structures: what are they? Smart Mater. Struct. 5: 247–254.

4 Cao, W., Cudney, H.H., and Waser, R. (1999). Smart materials and structures. Proc. Natl. Acad. Sci. U.S.A. 96: 8330–8331.

5 Namieśnik, J. and Szefer, P. (2008). Preparing samples for analysis – the key to analytical success. Ecol. Chem. Eng. 15: 167–244.

6 Kole, P.L., Venkatesh, G., Kotecha, J., and Sheshala, R. (2011). Recent advances in sample preparation techniques for effective bioanalytical methods. Biomed. Chromatogr. 25: 199–217.

7 Ahmadi, M., Elmongy, H., Madrakian, T., and Abdel‐Rehim, M. (2017). Nanomaterials as sorbents for sample preparation in bioanalysis: a review. Anal. Chim. Acta 958: 1–21.

8 Płotka‐Wasylka, J., Szczepanska, N., de la Guardia, M., and Namiesnik, J. (2016). Modern trends in solid phase extraction: new sorbent media. TrAC‐Trends Anal. Chem. 77: 23–43.

9 Wen, Y., Chen, L., Li, J. et al. (2014). Recent advances in solid‐phase sorbents for sample preparation prior to chromatographic analysis. TrAC‐Trends Anal. Chem. 59: 26–41.

10 Tang, S., Zhang, H., and Lee, H.K. (2016). Advances in sample extraction. Anal. Chem. 88: 228–249.

11 Liu, Q., Shi, J., and Jiang, G. (2012). Application of graphene in analytical sample preparation. TrAC‐Trends Anal. Chem. 37: 1–11.

12 Andrade‐Eiroa, A., Canle, M., Leroy‐Cancellieri, V., and Cerdà, V. (2016). Solid‐phase extraction of organic compounds: a critical review (part I). TrAC‐Trends Anal. Chem. 80: 641–654.

13 Pichon, V., Bouzige, M., Mieége, C., and Hennion, M.C. (1999). Immunosorbents: natural molecular recognition materials for sample preparation of complex environmental matrices. TrAC‐Trends Anal. Chem. 18: 219–235.

14 Moser, A.C. and Hage, D.S. (2010). Immunoaffinity chromatography: an introduction to applications and recent developments. Bioanalysis 2: 769–790.

15 Hage, D.S. and Phillips, T.M. (2006). Immunoaffinity chromatography. In: Handbook of Affinity Chromatography (ed. D.S. Hage), 136–190. New York: Taylor & Francis; Chapter 6.

16 Senyuva, H.Z. and Gilbert, J. (2010). Immunoaffinity column clean‐up techniques in food analysis: a review. J. Chromatogr. B: Anal. Technol. Biomed. Life Sci. 878: 115–132.

17 Masqué, N., Marcé, R.M., and Borrull, F. (2001). Molecularly imprinted polymers: new tailor‐made materials for selective solid‐phase extraction. TrAC‐Trends Anal. Chem. 20: 477–486.

18 Sellergren, B. (1994). Direct drug determination by selective sample enrichment on an imprinted polymer. Anal. Chem. 66: 1578–1582.

19 Martín‐Esteban, A. (2013). Molecularly‐imprinted polymers as a versatile, highly selective tool in sample preparation. TrAC‐Trends Anal. Chem. 45: 169–181.

20 Martín‐Esteban, A. (2016). Recent molecularly imprinted polymer‐based sample preparation techniques in environmental analysis. TrEAC‐Trends Environ. Anal. Chem. 9: 8–14.

21 Ashley, J., Shahbazi, M.A., Kant, K. et al. (2017). Molecularly imprinted polymers for sample preparation and biosensing in food analysis: progress and perspectives. Biosens. Bioelectron. 91: 606–615.

22 Augusto, F., Hantao, L.W., Mogollón, N.G.S., and Braga, S.C.G.N. (2013). New materials and trends in sorbents for solid‐phase extraction. TrAC‐Trends Anal. Chem. 43: 14–23.

23 Du, F., Guo, L., Qin, Q. et al. (2015). Recent advances in aptamer‐functionalized materials in sample preparation. TrAC‐Trends Anal. Chem. 67: 134–146.

24 Wang, W., Liu, S., Xue, Y. et al. (2017). Research progress of aptamer application in solid phase extraction technique. Chin. J. Chromatogr. 35: 99–104.

25 Wang, C., Li, M., Xu, H., and Wei, Y. (2014). Preparation of an internal surface reversed‐phase restricted‐access material for the analysis of hydrophobic molecules in biological matrices. J. Chromatogr. A 1343: 195–199.

26 He, J., Song, L., Chen, S. et al. (2015). Novel restricted access materials combined to molecularly imprinted polymers for selective solid phase extraction of organophosphorus pesticides from honey. Food Chem. 187: 331–337.

27 He, M., Huang, L., Zhao, B. et al. (2017). Advanced functional materials in solid phase extraction for ICP‐MS determination of trace elements and their species – a review. Anal. Chim. Acta 973: 1–24.

28 Cui, Y., Li, B., He, H. et al. (2016). Metal−organic frameworks as platforms for functional materials. Acc. Chem. Res. 49: 483–493.

29 Zhang, X., Liang, Q., Han, Q. et al. (2016). Metal‐organic frameworks@graphene hybrid aerogels for solid‐phase extraction of non‐steroidal anti‐inflammatory drugs and selective enrichment of proteins. Analyst 141: 4219–4226.

30 Hu, Y.L., Song, C.Y., Liao, J. et al. (2013). Water stable metal–organic frame‐work packed microcolumn for online sorptive extraction and direct analysis of naproxen and its metabolite from urine sample. J. Chromatogr. A 1294: 17–24.

31 Tang, B., Zhang, J.H., Zi, M. et al. (2016). Solid‐phase extraction with metal–organic frameworks for the analysis of chiral compounds. Chirality 28: 778–783.

32 Arthur, C.L. and Pawliszyn, J. (1990). Solid phase microextraction with thermal desorption using fused silica optical fibers. Anal. Chem. 62: 2145–2148.

33 Spietelun, A., Marcinkowski, Ł., de la Guardia, M., and Namieśnik, J. (2013). Recent developments and future trends in solid phase microextraction techniques towards green analytical chemistry. J. Chromatogr. A 1321: 1–13.

34 Xu, J., Zeng, J., Tian, J. et al. (2013). New materials in solid‐phase microextraction. TrAC‐Trend Anal. Chem. 47: 68–83.

35 Mehdinia, A. and Aziz‐Zanjani, M.O. (2013). Recent advances in nanomaterials utilized in fiber coatings for solid‐phase microextraction. TrAC‐Trends Anal. Chem. 42: 205–215.

36 Moliner‐Martinez, Y., Herráez‐Hernández, R., Verdú‐Andrés, J. et al. (2015). Recent advances of in‐tube solid‐phase microextraction. TrAC‐Trends Anal. Chem. 71: 205–213.

37 Castillo‐García, M.L., Aguilar‐Caballos, M.P., and Gomez‐Hens, A. (2016). Nanomaterials as tools in chromatographic methods. TrAC‐Trends Anal. Chem. 82: 385–393.

38 Beveridge, J.S., Stsephens, J.R., and Williams, M.E. (2011). The use of magnetic nanoparticles in analytical chemistry. Annu. Rev. Anal. Chem. 4: 251–273.

39 Aguilar‐Arteaga, K., Rodriguez, J.A., and Barrado, E. (2010). Magnetic solids in analytical chemistry: a review. Anal. Chim. Acta 674: 157–165.

40 Ibarra IS, Rodriguez JA, Galán‐Vidal CA, Cepeda A, Miranda JM. Magnetic solid phase extraction applied to food analysis. J. Chem. 2015, Article ID 919414, 13.

41 Ríos, A. and Zougagh, M. (2016). Recent advances in magnetic nanomaterials for improving analytical processes. TrAC‐Trends Anal. Chem. 84: 72–83.

42 Pebdani, A.A., Dadfarnia, S., Shabani, A.M.H. et al. (2016). Application of modified stir bar with nickel:zinc sulphide nanoparticles loaded on activated carbon as a sorbent for preconcentration of losartan and valsartan and their determination by high performance liquid chromatography. J. Chromatogr. A 1437: 15–24.

43 Fan, W., He, M., Wu, X. et al. (2015). Graphene oxide/polyethyleneglycol composite coated stir bar for sorptive extraction of fluoroquinolones from chicken muscle and liver. J. Chromatogr. A 1418: 36–44.

44 Trojanowicz, M. and Kołacińska, K. (2016). Recent advances in flow injection analysis. Analyst 141: 2085–2139.

45 Rodriguez‐Mozaz, S., Lopez de Alda, M.J., and Barceló, D. (2007). Advantages and limitations of on‐line solid phase extraction coupled to liquid chromatography–mass spectrometry technologies versus biosensors for monitoring of emerging contaminants in water. J. Chromatogr. A 1152: 97–115.

46 da Silva, A.T.M., de Oliveira, H.L., Silva, C.F. et al. (2017). Efficient molecularly imprinted polymer as a pipette‐tip solid‐phase sorbent for determination of carvedilol enantiomers in human urine. J. Chromatogr. B: Anal. Technol. Biomed. Life Sci. 1061–1062: 399–410.

47 Tavengwa, N.T., Nyamukamba, P., Cukrowska, E., and Chimuka, L. (2016). Miniaturized pipette‐tip‐based electrospun polyacrylonitrile nanofibers for the micro‐solid‐phase extraction of nitro‐based explosive compounds. J. Sep. Sci. 39: 4819–4827.

48 Teixeira Andrade, R., Santos da Silva, R.C., Pereira, A.C., and Borges, K.B. (2015). Self‐assembly pipette tip‐based cigarette filters for micro‐solid phase extraction of ketoconazole cis enantiomers in urine samples followed by high performance liquid chromatography/diode array detection. Anal. Methods 7: 7270–7279.

49 Miró, M., Oliveira, H.M., and Segundo, M.A. (2011). Analytical potential of mesofluidic lab‐on‐a‐valve as a front end to column‐separation systems. TrAC‐Trends Anal. Chem. 30: 153–164.

50 Miró, M. and Hansen, E.H. (2012). Recent advances and future prospects of mesofluidic Lab‐on‐a‐Valve platforms in analytical sciences – a critical review. Anal. Chim. Acta 750: 3–15.

51 Vidigal, S.S.M.P., Tóth, I.V., and Rangel, A.O.S.S. (2013). Sequential injection lab‐on‐valve platform as a miniaturisation tool for solid phase extraction. Anal. Methods 5: 585–597.

52 Wahab, M.F., Patel, D.C., Wimalasinghe, R.M., and Armstrong, D.W. (2017). Fundamental and practical insights on the packing of modern high‐efficiency analytical and capillary columns. Anal. Chem. 89: 8177–8191.

53 Zhang, M., Mallik, A.K., Takafuji, M. et al. (2015). Versatile ligands for high‐performance liquid chromatography: an overview of ionic liquid‐functionalized stationary phases. Anal. Chim. Acta 887: 1–16.

54 Cheong, W.J., Yang, S.H., and Ali, F. (2013). Molecular imprinted polymers for separation science: a review of reviews. J. Sep. Sci. 36: 609–628.

55 Chen, L., Wang, X., Lu, W. et al. (2016). Molecular imprinting: perspectives and applications. Chem. Soc. Rev. 45: 2137–2211.

56 Zhang, M. and Qiu, H. (2015). Progress in stationary phases modified with carbonaceous nanomaterials for high‐performance liquid chromatography. TrAC‐Trends Anal. Chem. 65: 107–121.

57 Yu, Y., Ren, Y., Shen, W. et al. (2013). Applications of metal‐organic frameworks as stationary phases in chromatography. TrAC‐Trends Anal. Chem. 50: 33–41.

58 Singh, N.S., Habicht, K.L., Dossou, K.S.S. et al. (2014). Multiple protein stationary phases: a review. J. Chromatogr. B: Anal. Technol. Biomed. Life Sci. 968: 64–68.

59 Sierra, I., Marina, M.L., Pérez‐Quintanilla, D. et al. (2016). Approaches for enantioselective resolution of pharmaceuticals by miniaturized separation techniques with new chiral phases based on nanoparticles and monoliths. Electrophoresis 37: 2538–2553.

60 Peluso, P., Mamane, V., Aubert, E., and Cossu, S. (2017). Recent trends and applications in liquid‐phase chromatography enantioseparation of atropisomers. Electrophoresis 38: 1830–1850.

61 Hong, T., Yang, X., Xu, Y., and J.Y. (2016). Recent advances in the preparation and application of monolithic capillary columns in separation science. Anal. Chim. Acta 931: 1–24.

62 Ladisch, M. and Zhang, L. (2016). Fiber‐based monolithic columns for liquid chromatography. Anal. Bioanal. Chem. 408: 6871–6883.

63 Kartsova, L.A., Bessonova, E.A., and Kolobova, E.A. (2016). Ionic liquids as modifiers of chromatographic and electrophoretic systems. J. Anal. Chem. 71: 147–158.

64 Pauwels, J. and Schepdael, A.V. (2012). Carbon nanotubes in capillary electrophoresis, capillary electrochromatography and microchip electrophoresis. Cent. Eur. J. Chem. 10: 785–801.

65 Liu, X., Liu, X., Li, M. et al. (2013). Application of graphene as the stationary phase for open‐tubular capillary electrochromatography. J. Chromatogr. A 1277: 93–97.

66 Moravcová, D., Rantamäki, A.H., Duša, F., and Wiedmer, S.K. (2016). Monoliths in capillary electrochromatography and capillary liquid chromatography in conjunction with mass spectrometry. Electrophoresis 37: 880–912.

67 Carrasco‐Correa, E.J., Simo‐Alfonso, E.F., Ramis‐Ramos, G., and Herrero‐Martinez, J.M. (2017). Application of organic monolithic materials to enantioseparation in capillary separation techniques. Curr. Med. Chem. 24: 781–795.

68 Fang, C., Dharmarajan, R., Megharaj, M., and Naidu, R. (2017). Gold nanoparticle‐based optical sensors for selected anionic contaminants. TrAC‐Trends Anal. Chem. 86: 143–154.

69 Justino, C.I.L., Gomes, A.R., Freitas, A.C. et al. (2017). Graphene based sensors and biosensors. TrAC‐Trends Anal. Chem. 91: 53–66.

70 Chen, H., Gao, Q., Li, J., and Lin, J.M. (2016). Graphene materials‐based chemiluminescence for sensing. J. Photochem. Photobiol. C: Photochem. Rev. 27: 54–71.

71 Justino, C.I.L., Duarte, A.C., and Rocha‐Santos, T.A.P. (2016). Critical overview on the application of sensors and biosensors for clinical analysis. TrAC‐Trends Anal. Chem. 85: 36–60.

72 Gooch, J., Daniel, B., Parkin, M., and Frascione, N. (2017). Developing aptasensors for forensic analysis. TrAC‐Trends Anal. Chem. 94: 150–160.

73 Hasanzadeh, M., Shadjou, N., and de la Guardia, M. (2017). Aptamer‐based assay of biomolecules: recent advances in electro‐analytical approach. TrAC‐Trends Anal. Chem. 89: 119–132.

74 Goldman, E.R., Medintz, I.L., and Mattoussi, H. (2006). Luminescent quantum dots in immunoassays. Anal. Bioanal. Chem. 384: 560–563.

75 Galian, R.E. and de la Guardia, M. (2009). The use of quantum dots in organic chemistry. TrAC‐Trends Anal. Chem. 28: 279–291.

76 González‐Carrero, S., de la Guardia, M., Galian, R.E., and Pérez‐Prieto, J. (2014). Pyrene‐capped CdSe@ZnS nanoparticles as sensitive flexible oxygen sensors in non‐aqueous media. ChemistryOpen 3: 199–205.

77 Esteve‐Turrillas, F.A. and Abad‐Fuentes, A. (2013). Applications of quantum dots as probes in immunosensing of small‐sized analytes. Biosens. Bioelectron. 41: 12–29.

78 Medintz, I.L., Clapp, A.R., Mattoussi, H. et al. (2003). Self‐assembled nanoscale biosensors based on quantum dot FRET donors. Nat. Mater. 2: 630–638.

79 Sun, X. and Lei, Y. (2017). Fluorescent carbon dots and their sensing applications. TrAC‐Trends Anal. Chem. 89: 163–180.

80 Benítez‐Martínez, S. and Valcárcel, M. (2015). Graphene quantum dots in analytical science. TrAC‐Trends Anal. Chem. 72: 93–113.

81 Sittampalam, G.S., Coussens, N.P., Brimacombe, K. et al. (2004–2017). Assay Guidance Manual. Bethesda: Eli Lilly & Company and the National Center for Advancing Translational Sciences.

82 Goldman, E.R., Clapp, A.R., Anderson, G.P. et al. (2004). Multiplexed toxin analysis using four colors of quantum dot fluororeagents. Anal. Chem. 76: 684–688.

83 Kuang, H., Zhao, Y., Ma, W. et al. (2011). Recent developments in analytical applications of quantum dots. TrAC‐Trends Anal. Chem. 30: 1620–1636.

84 Bazin, I., Tria, S.A., Hayat, A., and Marty, J.L. (2017). New biorecognition molecules in biosensors for the detection of toxins. Biosens. Bioelectron. 87: 285–298.

85 Nezlin, R. (2016). Use of aptamers in immunoassays. Mol. Immunol. 70: 149–154.

86 Liang, L., Hu, Z., Huang, Y. et al. (2016). Advances in nanobodies. J. Nanosci. Nanotechnol. 16: 12099–12111.

87 Raeisossadati, M.J., Danesh, N.M., Borna, F. et al. (2016). Lateral flow based