Toward the Responsible Development and Commercialization of Sensor Nanotechnologies

A look at radiation detectors and their applications in medical imaging

The effectiveness and precision of disease diagnosis and treatment have increased, thanks to developments in clinical imaging over the past few decades. Science is developing and progressing steadily in imaging modalities, and effective outcomes are starting to show up as a result of the shorter scanning periods needed as well as the higher-resolution images generated. The choice of one clinical device over another is influenced by technical disparities among the equipment, such as detection medium, shorter scan time, patient comfort, cost-effectiveness, accessibility, greater sensitivity and specificity, and spatial resolution. Lately, computational algorithms, artificial intelligence (AI), in particular, have been incorporated with diagnostic and treatment techniques, including imaging systems. AI is a discipline comprised of multiple computational and mathematical models. Its applications aided in manipulating sophisticated data in imaging processes and increased imaging tests' accuracy and precision during diagnosis. Computed tomography (CT), positron emission tomography (PET), and Single Photon Emission Computed Tomography (SPECT) along with their corresponding radiation detectors have been reviewed in this study. This review will provide an in-depth explanation of the above-mentioned imaging modalities as well as the radiation detectors that are their essential components. From the early development of these medical instruments till now, various modifications and improvements have been done and more is yet to be established for better performance which calls for a necessity to capture the available information and record the gaps to be filled for better future advances.

Recent advances in nanobiosensors for sustainable healthcare applications: A systematic literature review

The need for novel healthcare treatments and drugs has increased due to the expanding human population, detection of newer diseases, and looming pandemics. The development of nanotechnology offers a platform for cutting-edge in vivo non-invasive monitoring and point-of-care-testing (POCT) for rehabilitative disease detection and management. The advancement and uses of nanobiosensors are currently becoming more common in a variety of scientific fields, such as environmental monitoring, food safety, biomedical, clinical, and sustainable healthcare sciences, since the advent of nanotechnology. The identification and detection of biological patterns connected to any type of disease (communicable or not) have been made possible in recent years by several sensing techniques utilizing nanotechnology concerning biosensors and nanobiosensors. In this work, 2218 articles are drawn and screened from six digital databases out of which 17 were shortlisted for this review by using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) technique. As a result, this study uses a systematic methodology to review some recently developed extremely sensitive nanobiosensors, along with their biomedical, point-of-care diagnostics (POCD), or healthcare applications and their capabilities, particularly for the prediction of some fatal diseases based on a few of the most recent publications. The potential of nanobiosensors for medicinal, therapeutic, or other sustainable healthcare applications, notably for ailments diagnostics, is also recognized as a way forward in the manifestation of future trends.

Selection of cryoprotectants for freezing and freeze-drying of gold nanoparticles towards further uses in various applications

Recently, cryopreservation of AuNPs without aggregation has been attempted to improve their long-term stability. This study investigated criteria to select cryoprotectants for AuNPs using a variety of materials, including sugar (sucrose), surfactant (Tween 20), polymers (polyvinyl alcohol (PVA) and polyvinylpyrrolidone (PVP)), and biopolymer (pectin). For cryoprotective performance, UV-vis spectroscopy reveals the potential of all cryoprotectants for preventing citrate-capped AuNPs (cit-AuNPs) from irreversible aggregation under freezing. While sucrose, PVP, and pectin were more suitable than Tween 20 and PVA as cryoprotectants for lyophilization of AuNPs with the maintained redispersability. For storage and further use, Luria-Bertani agar plate, dynamic light scattering (DLS), and transmission electron microscopy (TEM) results indicate impacts of the cryoprotectant coexisted with AuNPs after resuspension and imply that washing of the restored AuNPs is encouraged. Otherwise, running the restored AuNPs through applications, such as functionalization, protein conjugation, and surface-enhanced Raman scattering (SERS), without washing the cryoprotectant could lead to inaccurate results. This study also serves as a guideline for a comprehensive practice flow of AuNP handling, encompassing the synthesis step, cryopreservation, and use after resuspension.

Real-Time and In Situ Monitoring of the Synthesis of Silica Nanoparticles

The real-time and in situ monitoring of the synthesis of nanomaterials (NMs) remains a challenging task, which is of pivotal importance by assisting fundamental studies (e.g., synthesis kinetics and colloidal phenomena) and providing optimized quality control. In fact, the lack of reproducibility in the synthesis of NMs is a bottleneck against the translation of nanotechnologies into the market toward daily practice. Here, we address an impedimetric millifluidic sensor with data processing by machine learning (ML) as a sensing platform to monitor silica nanoparticles (SiO₂NPs) over a 24 h synthesis from a single measurement. The SiO₂NPs were selected as a model NM because of their extensive applications. Impressively, simple ML-fitted descriptors were capable of overcoming interferences derived from SiO₂NP adsorption over the signals of polarizable Au interdigitate electrodes to assure the determination of the size and concentration of nanoparticles over synthesis while meeting the trade-off between accuracy and speed/simplicity of computation. The root-mean-square errors were calculated as ∼2.0 nm (size) and 2.6 × 10¹⁰ nanoparticles mL^-1 (concentration). Further, the robustness of the ML size descriptor was successfully challenged in data obtained along independent syntheses using different devices, with the global average accuracy being 103.7 ± 1.9%. Our work advances the developments required to transform a closed flow system basically encompassing the reactional flask and an impedimetric sensor into a scalable and user-friendly platform to assess the in situ synthesis of SiO₂NPs. Since the sensor presents a universal response principle, the method is expected to enable the monitoring of other NMs. Such a platform may help to pave the way for translating "sense-act" systems into practice use in nanotechnology.

Identification of Chemical Vapor Mixture Assisted by Artificially Extended Database for Environmental Monitoring

A fully integrated sensor array assisted by pattern recognition algorithm has been a primary candidate for the assessment of complex vapor mixtures based on their chemical fingerprints. Diverse prototypes of electronic nose systems consisting of a multisensory device and a post processing engine have been developed. However, their precision and validity in recognizing chemical vapors are often limited by the collected database and applied classifiers. Here, we present a novel way of preparing the database and distinguishing chemical vapor mixtures with small data acquisition for chemical vapors and their mixtures of interest. The database for individual vapor analytes is expanded and the one for their mixtures is prepared in the first-order approximation. Recognition of individual target vapors of NO₂, HCHO, and NH₃ and their mixtures was evaluated by applying the support vector machine (SVM) classifier in different conditions of temperature and humidity. The suggested method demonstrated the recognition accuracy of 95.24%. The suggested method can pave a way to analyze gas mixtures in a variety of industrial and safety applications.

Rapid detection of SARS-CoV-2 using graphene-based IoT integrated advanced electrochemical biosensor

Unique characteristics like large surface area, excellent conductivity, functionality, ease of fabrication, etc., of graphene and its derivatives, have been extensively studied as potential candidates in healthcare applications. They have been utilized as a potential nanomaterial in biosensor fabrication for commercialized point-of-care (POC) devices. This review concisely provided innovative graphene and its derivative-based-IoT (Internet-of-Things) integrated electrochemical biosensor for accurate and advanced high-throughput testing of SARS-CoV-2 in POC setting.

Rapid detection of SARS-CoV-2 using graphene-based IoT integrated advanced electrochemical biosensor

Unique characteristics like large surface area, excellent conductivity, functionality, ease of fabrication, etc., of graphene and its derivatives, have been extensively studied as potential candidates in healthcare applications. They have been utilized as a potential nanomaterial in biosensor fabrication for commercialized point-of-care (POC) devices. This review concisely provided innovative graphene and its derivative-based-IoT (Internet-of-Things) integrated electrochemical biosensor for accurate and advanced high-throughput testing of SARS-CoV-2 in POC setting.

Engineering DNA quadruplexes in DNA nanostructures for biosensor construction

DNA quadruplexes are nucleic acid conformations comprised of four strands. They are prevalent in human genomes and increasing efforts are being directed toward their engineering. Taking advantage of the programmability of Watson-Crick base-pairing and conjugation methodology of DNA with other molecules, DNA nanostructures of increasing complexity and diversified geometries have been artificially constructed since 1980s. In this review, we investigate the interweaving of natural DNA quadruplexes and artificial DNA nanostructures in the development of the ever-prosperous field of biosensing, highlighting their specific roles in the construction of biosensor, including recognition probe, signal probe, signal amplifier and support platform. Their implementation in various sensing scenes was surveyed. And finally, general conclusion and future perspective are discussed for further developments.

Bimetallic molecularly imprinted nanozyme: Dual-mode detection platform

Molecularly imprinted polymer nanozyme (MIL-101(Co,Fe)@MIP) with bimetallic active sites and high-efficiency peroxidase-like (POD-like) activity were synthesized for the ratiometric fluorescence and colorimetric dual-mode detection of vanillin with high selectivity and sensitivity. Compared with the monometallic nanozyme, the POD-like activity of bimetallic nanozyme was greatly enhanced by changing the electronic structure and surface structure. Ratiometric fluorescence and colorimetric dual-mode detection of vanillin in aqueous solution was realized by vanillin entering specific imprinted cavities and blocking the molecular channels on the surface of MIL-101(Co,Fe)@MIP and the dual-mode visual detection was also realized. The limits of detection were as low as 104 nM and 198 nM, respectively. The method proposed in this paper was applied to the real samples of ice cream and candy. And the recoveries were between 93.3% and 105.5%, which also reached a satisfactory degree. The further detection of dexamethasone and prednisone, two drugs belonging to glucocorticoid, proved that the nanozyme analysis method based on MIL-101(Co,Fe)@MIP could be developed into a sensing platform.

Challenges and potential solutions for nanosensors intended for use with foods

Nanotechnology-adapted detection technologies could improve the safety and quality of foods, provide new methods to combat fraud and be useful tools in our arsenal against bioterrorism. Yet despite hundreds of published studies on nanosensors each year targeted to the food and agriculture space, there are few nanosensors on the market in this area and almost no nanotechnology-enabled methods employed by public health agencies for food analysis. This Review shows that the field is currently being held back by technical, regulatory, political, legal, economic, environmental health and safety, and ethical challenges. We explore these challenges in detail and provide suggestions about how they may be surmounted. Strategies that may have particular effectiveness include improving funding opportunities and publication venues for nanosensor validation, social science and patent landscape studies; prioritizing research and development of nanosensors that are specifically designed for rapid analysis in non-laboratory settings; and incorporating platform cost and adaptability into early design decisions.

Application of DNA-Nanosensor for Environmental Monitoring: Recent Advances and Perspectives

PURPOSE OF REVIEW

Environmental pollutants are threat to human beings. Pollutants can lead to human health and environment hazards. The purpose of this review is to summarize the work done on detection of environmental pollutants using DNA nanosensors and challenges in the areas that can be focused for safe environment.

RECENT FINDINGS

Most of the DNA-based nanosensors designed so far use DNA as recognition element. ssDNA, dsDNA, complementary mismatched DNA, aptamers, and G-quadruplex DNA are commonly used as probes in nanosensors. More and more DNA sequences are being designed that can specifically detect various pollutants even simultaneously in complex milk, wastewater, soil, blood, tap water, river, and pond water samples. The feasibility of direct detection, ease of designing, and analysis makes DNA nanosensors fit for future point-of-care applications.

SUMMARY

DNA nanosensors are easy to design and have good sensitivity. DNA component and nanomaterials can be designed in a controlled manner to detect various environmental pollutants. This review identifies the recent advances in DNA nanosensor designing and opportunities available to design nanosensors for unexplored pathogens, antibiotics, pesticides, GMO, heavy metals, and other toxic pollutant.

Bio-inspired gas sensing: boosting performance with sensor optimization guided by "machine learning"

The performance of existing gas sensors often degrades in field conditions because of the loss of measurement accuracy in the presence of interferences. Thus, new sensing approaches are required with improved sensor selectivity. We are developing a new generation of gas sensors, known as multivariable sensors, that have several independent responses for multi-gas detection with a single sensor. In this study, we analyze the capabilities of natural and fabricated photonic three-dimensional (3-D) nanostructures as sensors for the detection of different gaseous species, such as vapors and non-condensable gases. We employed bare Morpho butterfly wing scales to control their gas selectivity with different illumination angles. Next, we chemically functionalized Morpho butterfly wing scales with a fluorinated silane to boost the response of these nanostructures to the vapors of interest and to suppress the response to ambient humidity. Further, we followed our previously developed design rules for sensing nanostructures and fabricated bioinspired inorganic 3-D nanostructures to achieve functionality beyond natural Morpho scales. These fabricated nanostructures have embedded catalytically active gold nanoparticles to operate at high temperatures of ≈300 °C for the detection of gases for solid oxide fuel cell (SOFC) applications. Our performance advances in the detection of multiple gaseous species with specific nanostructure designs were achieved by coupling the spectral responses of these nanostructures with machine learning (a.k.a. multivariate analysis, chemometrics) tools. Our newly acquired knowledge from studies of these natural and fabricated inorganic nanostructures coupled with machine learning data analytics allowed us to advance our design rules for sensing nanostructures toward the required gas selectivity for numerous gas monitoring scenarios at room and high temperatures for industrial, environmental, and other applications.

Molecular Features for Probing Small Amphiphilic Molecules with Self-Assembled Monolayer-Protected Nanoparticles

The sensing of small molecules poses the challenge of developing devices able to discriminate between compounds that may be structurally very similar. Here, attention has been paid to the use of self-assembled monolayer (SAM)-protected gold nanoparticles since they enable a modular approach to tune single-molecule affinity and selectivity simply by changing functional moieties (i.e., covering ligands), along with multivalent molecular recognition. To date, the discovery of monolayers suitable for a specific molecular target has relied on trial-and-error approaches, with ligand chemistry being the main criterion used to modulate selectivity and sensitivity. By using molecular dynamics, we showcase that either individual molecular characteristics and/or collective features such as ligand flexibility, monolayer organization, ligand local ordering, and interfacial solvent properties can also be exploited conveniently. The knowledge of the molecular mechanisms that drive the recognition of small molecules on SAM-covered nanoparticles will critically expand our ability to manipulate and control such supramolecular systems.

Nanosensors and particles: a technology frontier with pitfalls

As we are approaching 20 years after the US National Nanotechnology Initiative has been announced, whereby most of that funding was spend to engineer, characterize and bring nanoparticles and nanosensors to the market, it is timely to assess the progress made. Beyond revolutionizing nonmedical applications, including construction materials and the food industry, as well as in vitro medical diagnostics, the progress in bringing them into the clinic has been far slower than expected. Even though most of the advances in nanosensor and nanoparticle research and development have been paid for by disease-oriented funding agencies, much of the gained knowledge can now be applied to treat or learn more about our environment, including water, soil, microbes and plants. As the amount of engineered nanoparticles that enter our environment is currently exponentially increasing, much tighter attention needs to be paid to assessing their health risk. This is urgent as the asbestos story told us important lessons how financial interests arising from a rapid build up of a flourishing industry has blocked and is still preventing a worldwide ban on asbestos, nearly 100 years after the first health risks were reported.

A review on graphene-based nanocomposites for electrochemical and fluorescent biosensors

Biosensors with high sensitivity, selectivity and a low limit of detection, reaching nano/picomolar concentrations of biomolecules, are important to the medical sciences and healthcare industry for evaluating physiological and metabolic parameters.

High Sensitivity Plasmonic Sensing of Hydrogen over a Broad Dynamic Range Using Catalytic Au-CeO2 Thin Film Nanocomposites

Next-generation gas-sensor technologies are needed for diverse applications including environmental surveillance, occupational safety, and industrial process control. However, the dynamic range using existing sensors is often too narrow to meet demands. In this work, plasmonic films of Au-CeO₂ that detect hydrogen with 0.38% and 60% lower and upper detection limits in an oxygen-free atmosphere experiment are demonstrated. The observed 15 nm peak shift was 4 times stronger versus other plasmonic H₂ sensors. The proposed sensing mechanism that involves H₂ dissociation by Au^δ+ nanoparticles was validated using XPS, kinetics, and Arrhenius studies. Our understanding of this remarkable sensing behavior in oxygen-free conditions opens new horizons for packaging, art conservation, industrial process control, and other applications where conventional oxygen-dependent sensors lack broad dynamic range.

A Single Input Multiple Output (SIMO) Variation-Tolerant Nanosensor

Successful transition to commercialization and practical implementation of nanotechnology innovations may very well need device designs that are tolerant to the inherent variations and imperfections in all nanomaterials including carbon nanotubes, graphene, and others. As an example, a single-walled carbon nanotube network based gas sensor is promising for a wide range of applications such as environment, industry, and biomedical and wearable devices due to its high sensitivity, fast response, and low power consumption. However, a long-standing issue has been the production of extremely high purity semiconducting nanotubes, thereby contributing to the delay in the market adoption of those sensors. Inclusion of even less than 0.1% of metallic nanotubes, which is inevitable, is found to result in a significant deterioration of sensor-to-sensor uniformity. Acknowledging the coexistence of metallic and semiconducting nanotubes as well as all other possible imperfections, we herein present a novel variation-tolerant sensor design where the sensor response is defined by a statistical Gaussian measure in contrast to a traditional deterministic approach. The single input and multiple output data are attained using multiport electrodes fabricated over a relatively large area single nanotube ensemble. The data processing protocol discards outlier data points and the origin of the outliers is investigated. Both the experimental demonstration and complementary analytical modeling support the hypothesis that the statistical analysis of the device can strengthen the credibility of the sensor constructed using nanomaterials with any imperfections. The proposed strategy can also be applied to physical, radiation, and biosensors as well as other electronic devices.

Molecularly Imprinted Polymers in Electrochemical and Optical Sensors

Molecular imprinting is the process of template-induced formation of specific recognition sites in a polymer. Synthetic receptors prepared using molecular imprinting possess a unique combination of properties such as robustness, high affinity, specificity, and low-cost production, which makes them attractive alternatives to natural receptors. Improvements in polymer science and nanotechnology have contributed to enhanced performance of molecularly imprinted polymer (MIP) sensors. Encouragingly, recent years have seen an increase in high-quality publications describing MIP sensors for the determination of biomolecules, drugs of abuse, and explosives, driving toward applications of this technology in medical and forensic diagnostics. This review aims to provide a focused overview of the latest achievements made in MIP-based sensor technology, with emphasis on research toward real-life applications.

A Future with Ubiquitous Sensing and Intelligent Systems

In this paper, we discuss the relevance of sensing and biosensing for the ongoing revolution in science and technology as a product of the merging of machine learning and Big Data into affordable technologies and accessible everyday products. Possible scenarios for the next decades are described with examples of intelligent systems for various areas, most of which will rely on ubiquitous sensing. The technological and societal challenges for developing the full potential of such intelligent systems are also addressed.

Nanosensors for water quality monitoring

Nanomaterial-enabled sensors are being designed for high-efficiency, multiplex-functionality and high-flexibility sensing applications. Many existing nanosensors have the inherent capacity to achieve such goals; however, they require further development into consumer- and operator-friendly tools with the ability to detect analytes in previously inaccessible locations, as well as at a greater scale than heretofore possible. Here, I discuss how nanotechnology-enabled sensors have great, as yet unmet, promise to provide widespread and potentially low-cost monitoring of chemicals, microbes and other analytes in drinking water.

Monitoring the Surface Chemistry of Functionalized Nanomaterials with a Microfluidic Electronic Tongue

Advances in nanomaterials have led to tremendous progress in different areas with the development of high performance and multifunctional platforms. However, a relevant gap remains in providing the mass-production of these nanomaterials with reproducible surfaces. Accordingly, the monitoring of such materials across their entire life cycle becomes mandatory to both industry and academy. In this paper, we use a microfluidic electronic tongue (e-tongue) as a user-friendly and cost-effective method to classify nanomaterials according to their surface chemistry. The chip relies on a new single response e-tongue with association of capacitors in parallel, which consisted of stainless steel microwires coated with SiO₂, NiO₂, Al₂O₃, and Fe₂O₃ thin films. Utilizing impedance spectroscopy and a multidimensional projection technique, the chip was sufficiently sensitive to distinguish silica nanoparticles and multiwalled carbon nanotubes dispersed in water in spite of the very small surface modifications induced by distinct functionalization and oxidation extents, respectively. Flow analyses were made acquiring the analytical readouts in a label-free mode. The device also allowed for multiplex monitoring in an unprecedented way to speed up the tests. Our goal is not to replace the traditional techniques of surface analysis, but rather propose the use of libraries from e-tongue data as benchmark for routine screening of modified nanomaterials in industry and academy.

Programmable DNA switches and their applications

DNA switches are ideally suited for numerous nanotechnological applications, and increasing efforts are being directed toward their engineering. In this review, we discuss how to engineer these switches starting from the selection of a specific DNA-based recognition element, to its adaptation and optimisation into a switch, with applications ranging from sensing to drug delivery, smart materials, molecular transporters, logic gates and others. We provide many examples showcasing their high programmability and recent advances towards their real life applications. We conclude with a short perspective on this exciting emerging field.

Interpreting Mobile and Handheld Air Sensor Readings in Relation to Air Quality Standards and Health Effect Reference Values: Tackling the Challenges

The US Environmental Protection Agency (EPA) and other federal agencies face a number of challenges in interpreting and reconciling short-duration (seconds to minutes) readings from mobile and handheld air sensors with the longer duration averages (hours to days) associated with the National Ambient Air Quality Standards (NAAQS) for the criteria pollutants-particulate matter (PM), ozone, carbon monoxide, lead, nitrogen oxides, and sulfur oxides. Similar issues are equally relevant to the hazardous air pollutants (HAPs) where chemical-specific health effect reference values are the best indicators of exposure limits; values which are often based on a lifetime of continuous exposure. A multi-agency, staff-level Air Sensors Health Group (ASHG) was convened in 2013. ASHG represents a multi-institutional collaboration of Federal agencies devoted to discovery and discussion of sensor technologies, interpretation of sensor data, defining the state of sensor-related science across each institution, and provides consultation on how sensors might effectively be used to meet a wide range of research and decision support needs. ASHG focuses on several fronts: improving the understanding of what hand-held sensor technologies may be able to deliver; communicating what hand-held sensor readings can provide to a number of audiences; the challenges of how to integrate data generated by multiple entities using new and unproven technologies; and defining best practices in communicating health-related messages to various audiences. This review summarizes the challenges, successes, and promising tools of those initial ASHG efforts and Federal agency progress on crafting similar products for use with other NAAQS pollutants and the HAPs. NOTE: The opinions expressed are those of the authors and do not necessary represent the opinions of their Federal Agencies or the US Government. Mention of product names does not constitute endorsement.

Toward high value sensing: monolayer-protected metal nanoparticles in multivariable gas and vapor sensors

This review provides analysis of advances in multivariable sensors based on monolayer-protected nanoparticles and several principles of signal transduction that result in building non-resonant and resonant electrical sensors as well as material- and structure-based photonic sensors.