Biomimetic Sniffing Improves the Detection Performance of a 3D Printed Nose of a Dog and a Commercial Trace Vapor Detector

Success in the Natural Detection Task is influenced by only a few factors generally believed to affect dogs' olfactory performance

Research into dogs' olfactory ability is growing rapidly. However, generalising based on scientific results is challenging, because research has been typically conducted on a few specially trained subjects of a few breeds tested in different environmental conditions. We investigated the effects of temperature and humidity (outdoors), age, test location, sex, neutering status, and repeated testing (outdoors and indoors) on the olfactory performance of untrained family dogs (N = 411) of various breeds. We employed the Natural Detection Task with three difficulty levels, from which we derived two performance metrics: Top Level and Success Score. Temperature (0-25 °C) and humidity (18-90%) did not affect olfactory performance. Young adult dogs surpassed other age groups in reaching the Top Level. Sex and neutering status showed no discernible influence on Top Level and Success Score. Dogs performed better in both metrics when tested indoors compared to outdoors. In the test-retest procedure no significant learning effect was observed. We confirmed on untrained companion dogs that olfactory performance declines with age and rejected some factors that have been previously hypothesised to significantly affect dogs' olfactory success. The influence of the testing environment was notable, emphasising the need to consider various factors in understanding dogs' olfactory capabilities.

Physical properties of odorants affect behavior of trained detection dogs during close-quarters searches

Trained detection dogs have a unique ability to find the sources of target odors in complex fluid environments. How dogs derive information about the source of an odor from an odor plume comprised of odorants with different physical properties, such as diffusivity, is currently unknown. Two volatile chemicals associated with explosive detection, ammonia (NH3, derived from ammonium nitrate-based explosives) and 2-ethyl-1-hexanol (2E1H, associated with composition C4 plastic explosives) were used to ascertain the effects of the physical properties of odorants on the search behavior and motion of trained dogs. NH3 has a diffusivity 3.6 times that of 2E1H. Fourteen civilian detection dogs were recruited to train on each target odorant using controlled odor mimic permeation systems as training aids over 6 weeks and then tested in a controlled-environment search trial where behavior, motion, and search success were analyzed. Our results indicate the target-odorant influences search motion and time spent in the stages of searching, with dogs spending more time in larger areas while localizing NH3. This aligns with the greater diffusivity of NH3 driving diffusion-dominated odor transport when dogs are close to the odor source in contrast to the advection-driven transport of 2E1H at the same distances.

Active Sensing in Bees Through Antennal Movements Is Independent of Odor Molecule

When sampling odors, many insects are moving their antennae in a complex but repeatable fashion. Previous studies with bees have tracked antennal movements in only two dimensions, with a low sampling rate and with relatively few odorants. A detailed characterization of the multimodal antennal movement patterns as function of olfactory stimuli is thus wanted. The aim of this study is to test for a relationship between the scanning movements and the properties of the odor molecule. We tracked several key locations on the antennae of bumblebees at high frequency and in three dimensions while stimulating the insect with puffs of 11 common odorants released in a low-speed continuous flow. Water and paraffin were used as negative controls. Movement analysis was done with the neural network Deeplabcut. Bees use a stereotypical oscillating motion of their antennae when smelling odors, similar across all bees, independently of the identity of the odors and hence their diffusivity and vapor pressure. The variability in the movement amplitude among odors is as large as between individuals. The main type of oscillation at low frequencies and large amplitude is triggered by the presence of an odor and is in line with previous work, as is the speed of movement. The second oscillation mode at higher frequencies and smaller amplitudes is constantly present. Antennae are quickly deployed when a stimulus is perceived, decorrelate their movement trajectories rapidly, and oscillate vertically with a large amplitude and laterally with a smaller one. The cone of airspace thus sampled was identified through the 3D understanding of the motion patterns. The amplitude and speed of antennal scanning movements seem to be function of the internal state of the animal, rather than determined by the odorant. Still, bees display an active olfactory sampling strategy. First, they deploy their antennae when perceiving an odor. Second, fast vertical scanning movements further increase the odorant capture rate. Finally, lateral movements might enhance the likelihood to locate the source of odor, similarly to the lateral scanning movement of insects at odor plume boundaries.

Nonequilibrium sensing of volatile compounds using active and passive analyte delivery

Although sensor technologies have allowed us to outperform the human senses of sight, hearing, and touch, the development of artificial noses is significantly behind their biological counterparts. This largely stems from the sophistication of natural olfaction, which relies on both fluid dynamics within the nasal anatomy and the response patterns of hundreds to thousands of unique molecular-scale receptors. We designed a sensing approach to identify volatiles inspired by the fluid dynamics of the nose, allowing us to extract information from a single sensor (here, the reflectance spectra from a mesoporous one-dimensional photonic crystal) rather than relying on a large sensor array. By accentuating differences in the nonequilibrium mass-transport dynamics of vapors and training a machine learning algorithm on the sensor output, we clearly identified polar and nonpolar volatile compounds, determined the mixing ratios of binary mixtures, and accurately predicted the boiling point, flash point, vapor pressure, and viscosity of a number of volatile liquids, including several that had not been used for training the model. We further implemented a bioinspired active sniffing approach, in which the analyte delivery was performed in well-controlled 'inhale-exhale' sequences, enabling an additional modality of differentiation and reducing the duration of data collection and analysis to seconds. Our results outline a strategy to build accurate and rapid artificial noses for volatile compounds that can provide useful information such as the composition and physical properties of chemicals, and can be applied in a variety of fields, including disease diagnosis, hazardous waste management, and healthy building monitoring.

Explosive Odor Signature Profiling: A Review of recent advances in technical analysis and detection

With the ever-increasing threat of improvised explosive devices (IEDs) and homemade explosives (HME) both domestically and abroad, detection of explosives and explosive related materials is an area of urgent importance for preventing terrorist activities around the globe. Canines are a common biological detector used in explosive detection due to their enhanced olfactory abilities, high mobility, efficient standoff sampling, and optimal identification of vapor sources. While other sensors based on different principles have emerged, an important concept for the rapid field detection of explosives is understanding key volatile organic compounds (VOCs) associated with these materials. Explosive detection technology needs to be on par with a large number of threats including an array of explosive materials as well as novel chemicals used in the manufacture of IEDs. Within this much needed area of research for law enforcement and homeland security applications, several studies have sought to understand the explosive odor profile from a range of materials. This review aims to provide a foundational overview of these studies to provide a summary of instrumental analysis to date on the various types of explosive odor profiles evaluated focusing on the experimental approaches and laboratory techniques utilized in the chemical characterization of explosive vapors and mixtures. By expanding upon these concepts, a greater understanding of the explosive vapor signature can be achieved, providing for enhanced chemical and biological sensing of explosive threats as well as expanding upon existing laboratory-based models for continued sensor development.

Sniffer Dogs Diagnose Lung Cancer by Recognition of Exhaled Gases: Using Breathing Target Samples to Train Dogs Has a Higher Diagnostic Rate Than Using Lung Cancer Tissue Samples or Urine Samples

INTRODUCTION

Sniffer dogs can diagnose lung cancer. However, the diagnostic yields of different samples and training methods for lung cancer remain undetermined.

OBJECTIVE

Six dogs were trained in three stages with the aim of improving the diagnostic yield of lung cancer by comparing training methods and specimens.

METHODS

The pathological tissues of 53 lung cancer patients and 6 non-lung cancer patients in the Department of Thoracic Surgery of Kaohsiung Chang Gung Hospital were collected, and the exhaled breath samples and urine samples were collected. Urine and exhaled breath samples were also collected from 20 healthy individuals. The specimens were sent to the Veterinary Department of Pingtung University of Science and Technology.

RESULTS

The dogs had a very low response rate to urine target samples in the first and second stages of training. The experimental results at the second stage of training found that after lung cancer tissue training, dogs were less likely to recognize lung cancer and healthy controls than through breath target training: the response rate to exhaled breathing target samples was about 8-55%; for urine target samples, it was only about 5-30%. When using exhaled air samples for training, the diagnosis rate of these dogs in lung cancer patients was 71.3% to 97.6% (mean 83.9%), while the false positive rate of lung cancer in the healthy group was 0.5% to 27.6% (mean 7.6%). Compared with using breathing target samples for training, the diagnosis rate of dogs trained with lung cancer tissue lung cancer was significantly lower (p < 0.05). The sensitivity and specificity of lung cancer tissue training (50.4% and 50.1%) were lower than the exhaled breath target training (91.7% and 85.1%). There is no difference in lung cancer diagnostic rate by sniff dogs among lung cancer histological types, location, and staging.

CONCLUSION

Training dogs using breathing target samples to train dogs then to recognize exhaled samples had a higher diagnostic rate than training using lung cancer tissue samples or urine samples. Dogs had a very low response rate to urine samples in our study. Six canines were trained on lung cancer tissues and breathing target samples of lung cancer patients, then the diagnostic rate of the recognition of exhaled breath of lung cancer and non-lung cancer patients were compared. When using exhaled air samples for training, the diagnosis rate of these dogs in lung cancer patients was 71.3% to 97.6% (mean 83.9%), while the false positive rate of lung cancer in the healthy group was 0.5% to 27.6% (mean 7.6%). There was a significant difference in the average diagnosis rate of individual dog and overall dogs between the lung cancer group and the healthy group (p < 0.05). When using lung cancer tissue samples for training, lung cancer diagnosis rate of these dogs among lung cancer patients was only 15.5% to 40.9% (mean 27.7%). Compared with using breathing target samples for training, the diagnosis rate of dogs trained with lung cancer tissue lung cancer was significantly lower (p < 0.05). The sensitivity and specificity of lung cancer tissue training (50.4% and 50.1%) were lower than the exhaled breath target training (91.7% and 85.1%). The diagnostic rate of lung cancer by sniffer dogs has nothing to do with the current stage of lung cancer, pathologic type, and the location of tumor mass. Even in stage IA lung cancer, well-trained dogs can have a diagnostic rate of 100%. Using sniffer dogs to screen early lung cancer may have good clinical and economic benefits.

Semiquantitative Classification of Two Oxidizing Gases with Graphene-Based Gas Sensors

Miniature and low-power gas sensing elements are urgently needed for a portable electronic nose, especially for outdoor pollution monitoring. Hereby we prepared chemiresistive sensors based on wide-area graphene (grown by chemical vapor deposition) placed on Si/Si3N4 substrates with interdigitated electrodes and built-in microheaters. Graphene of each sensor was individually functionalized with ultrathin oxide coating (CuO-MnO2, In2O3 or Sc2O3) by pulsed laser deposition. Over the course of 72 h, the heated sensors were exposed to randomly generated concentration cycles of 30 ppb NO2, 30 ppb O3, 60 ppb NO2, 60 ppb O3 and 30 ppb NO2 + 30 ppb O3 in synthetic air (21% O2, 50% relative humidity). While O3 completely dominated the response of sensors with CuO-MnO2 coating, the other sensors had comparable sensitivity to NO2 as well. Various response features (amplitude, response rate, and recovery rate) were considered as machine learning inputs. Using just the response amplitudes of two complementary sensors allowed us to distinguish these five gas environments with an accuracy of ~ 85%. Misclassification was mostly due to an overlap in the case of the 30 ppb O3, and 30 ppb O3 + 30 ppb NO2 responses, and was largely caused by the temporal drift of these responses. The addition of recovery rates to machine learning input variables enabled us to very clearly distinguish different gases and increase the overall accuracy to ~94%.

Advances in the Detection of Emerging Tree Diseases by Measurements of VOCs and HSPs Gene Expression, Application to Ash Dieback Caused by Hymenoscyphus fraxineus

Ash shoot dieback has now spread throughout Europe. It is caused by an interaction between fungi that attack shoots (Hymenoscyphus fraxineus) and roots (Armillaria spp., in our case Armillaria gallica). While detection of the pathogen is relatively easy when disease symptoms are present, it is virtually impossible when the infestation is latent. Such situations occur in nurseries when seedlings become infected (the spores are carried by the wind several dozen miles). The diseases are masked by pesticides, fertilisers, and adequate irrigation to protect the plants. Root rot that develops in the soil is also difficult to detect. Currently, there is a lack of equipment that can detect root rot pathogens without digging up root systems, which risks damaging trees. For this reason, the use of an electronic nose to detect pathogens in infected tissue of ash trees grown in pots and inoculated with the above fungi was attempted. Disease symptoms were detected in all ash trees exposed to natural infection (via spores) in the forest. The electronic nose was able to detect the pathogens (compared to the control). Detection of the pathogens in seedlings will enable foresters to remove diseased trees and prevent the path from nursery to forest plantations by such selection.

Influence of interface in electrical properties of 3D printed structures

The aligned bond interfaces resulting from the layer-by-layer nature of material extrusion-based additive manufacturing (MEAM) leads to anisotropic properties in printed parts. This study examines the anisotropy in electrical impedance and its variation with print parameters. Samples consisting of a stack of filaments are used to study the interfaces, which are the fundamental building block of MEAM, in a controlled manner. Anisotropy was quantified using the ratio of the impedance measured across (Z-specimen) and along (F-specimen) the fiber orientation. Although the conductivity of the material was found to change with extrusion temperature, the Z/F ratio was found to be constant (2.15 ± 0.23), regardless of the variation in thermal conditions imposed by varying extrusion temperature and print speed. By varying the distance over which impedance was measured, impedance scaling was understood. The scaling was found to be dependent on the extrusion temperature regardless of the variation of print speed by 266%; ~12.5 Ω per interface for 190 °C while ~6.5 Ω per interface for 230 °C, one-third of which was found to be contributed by fiber. While studying the cause for significant impedance at the interface, scanning electron microscopy study shows absence of airgaps at the interface, and energy dispersion spectroscopy shows absence of oxidation at the interface. The implications of specimen design and characterization proposed here allows for examination of a wide range of print parameters with reduction in material, time, and cost. Thus, by investigating the role of print parameters and scaling of impedance with interfaces, we seek to provide a framework to model and predict electrical behavior of electric sensors and actuators made with MEAM.

Sniffing speeds up chemical detection by controlling air-flows near sensors

Most mammals sniff to detect odors, but little is known how the periodic inhale and exhale that make up a sniff helps to improve odor detection. In this combined experimental and theoretical study, we use fluid mechanics and machine olfaction to rationalize the benefits of sniffing at different rates. We design and build a bellows and sensor system to detect the change in current as a function of odor concentration. A fast sniff enables quick odor recognition, but too fast a sniff makes the amplitude of the signal comparable to noise. A slow sniff increases signal amplitude but delays its transmission. This trade-off may inspire the design of future devices that can actively modulate their sniffing frequency according to different odors.

The emerging role of 3D-printing in ion mobility spectrometry and mass spectrometry

3D-printing is revolutionizing the rapid prototyping in analytical chemistry. In the last few years, we observed the development of 3D-printed components for ion studies, such as ion sources, ion transfer and ion mobility spectrometry (IMS) devices. Often, 3D-printed gadgets add functions to existing mass spectrometry (MS) systems. Custom adapters improve the sensibility for coupling with ambient ionization and upstream chromatography methods, and sample preparation units optimize the following MS analyses. Besides, 3D-printer parts are suitable for constructing custom analytical robots and mass imaging systems. Some of those assemblies implement new concepts and are commercially not available. An essential aspect of using 3D-printing is the fast turnover of design improvements, which is motivated by permissive licenses. The easy reproducibility and exchange of ideas lead to a community-driven development, which is accompanied by economic advantages for public research and education.

Flow visualization of an N95 respirator with and without an exhalation valve using schlieren imaging and light scattering

This work demonstrates the qualitative fluid flow characteristics of a standard N95 respirator with and without an exhalation valve. Schlieren imaging was used to compare an adult male breathing through an N95 respirator with and without a valve. The schlieren imaging technique showed the flow of warm air passing through these respirators but did not provide information about droplet penetration. For this, strategic lighting of fog droplets was used with a mannequin head to visualize the penetration of droplets through both masks. The mannequin exhaled with a realistic flow rate and velocity that matched an adult male. The penetration of fog droplets was also visualized with a custom system that seals each respirator onto the end of a flow tube. Results of these qualitative experiments show that an N95 respirator without an exhalation valve is effective at blocking most droplets from penetrating through the mask material. Results also suggest that N95 respirators with exhalation valves are not appropriate as a source control strategy for reducing the proliferation of infectious diseases that spread via respiratory droplets.

Recent Developments in the Field of Explosive Trace Detection

Explosive trace detection (ETD) technologies play a vital role in maintaining national security. ETD remains an active research area with many analytical techniques in operational use. This review details the latest advances in animal olfactory, ion mobility spectrometry (IMS), and Raman and colorimetric detection methods. Developments in optical, biological, electrochemical, mass, and thermal sensors are also covered in addition to the use of nanomaterials technology. Commercially available systems are presented as examples of current detection capabilities and as benchmarks for improvement. Attention is also drawn to recent collaborative projects involving government, academia, and industry to highlight the emergence of multimodal screening approaches and applications. The objective of the review is to provide a comprehensive overview of ETD by highlighting challenges in ETD and providing an understanding of the principles, advantages, and limitations of each technology and relating this to current systems.

Bio-Inspired Strategies for Improving the Selectivity and Sensitivity of Artificial Noses: A Review

Artificial noses are broad-spectrum multisensors dedicated to the detection of volatile organic compounds (VOCs). Despite great recent progress, they still suffer from a lack of sensitivity and selectivity. We will review, in a systemic way, the biomimetic strategies for improving these performance criteria, including the design of sensing materials, their immobilization on the sensing surface, the sampling of VOCs, the choice of a transduction method, and the data processing. This reflection could help address new applications in domains where high-performance artificial noses are required such as public security and safety, environment, industry, or healthcare.

Role of ecology in shaping external nasal morphology in bats and implications for olfactory tracking

Many animals display morphological adaptations of the nose that improve their ability to detect and track odors. Bilateral odor sampling improves an animals' ability to navigate using olfaction and increased separation of the nostrils facilitates olfactory source localization. Many bats use odors to find food and mates and bats display an elaborate diversity of facial features. Prior studies have quantified how variations in facial features correlate with echolocation and feeding ecology, but surprisingly none have asked whether bat noses might be adapted for olfactory tracking in flight. We predicted that bat species that rely upon odor cues while foraging would have greater nostril separation in support of olfactory tropotaxis. Using museum specimens, we measured the external nose and cranial morphology of 40 New World bat species. Diet had a significant effect on external nose morphology, but contrary to our predictions, insectivorous bats had the largest relative separation of nostrils, while nectar feeding species had the narrowest nostril widths. Furthermore, nasal echolocating bats had significantly narrower nostrils than oral emitting bats, reflecting a potential trade-off between sonar pulse emission and stereo-olfaction in those species. To our knowledge, this is the first study to evaluate the evolutionary interactions between olfaction and echolocation in shaping the external morphology of a facial feature using modern phylogenetic comparative methods. Future work pairing olfactory morphology with tracking behavior will provide more insight into how animals such as bats integrate olfactory information while foraging.

Ventilation Modulation and Nanoparticle Deposition in Respiratory and Olfactory Regions of Rabbit Nose

The rabbit nose's ability to filter out inhaled agents is directly related to its defense to infectious diseases. The knowledge of the rabbit nose anatomy is essential to appreciate its functions in ventilation regulation, aerosol filtration and olfaction. The objective of this study is to numerically simulate the inhalation and deposition of nanoparticles in a New Zealand white (NZW) rabbit nose model with an emphasis on the structure-function relation under normal and sniffing conditions. To simulate the sniffing scenario, the original nose model was modified to generate new models with enlarged nostrils or vestibules based on video images of a rabbit sniffing. Ventilations into the maxilloturbinate and olfactory region were quantified with varying nostril openings, and deposition rates of inhaled aerosols ranging from 0.5 nm to 1000 nm were characterized on the total, sub-regional and local basis. Results showed that particles which deposited in the olfactory region came from a specific area in the nostril. The spiral vestibule played an essential role in regulating flow resistance and flow partition into different parts of the nose. Increased olfactory doses were persistently predicted in models with expanded nostrils or vestibule. Particles in the range of 5-50 nm are more sensitive to the geometry variation than other nanoparticles. It was also observed that exhaled aerosols occupy only the central region of the nostril, which minimized the mixing with the aerosols close to the nostril wall, and potentially allowed the undisruptive sampling of odorants. The results of this study shed new light on the ventilation regulation and inhalation dosimetry in the rabbit nose, which can be further implemented to studies of infectious diseases and immunology in rabbits.

High-speed imaging system to visualize particle removal/collection via wipe sampling and aerodynamic sampling

This work describes a high-speed imaging system that enables the microscopic visualization of the removal and collection of micrometer-sized particles from surfaces during wipe sampling and aerodynamic sampling events. The system features a high-speed digital camera, microlens, custom sample mount and sampling sled, and an illumination source. This imaging system enables direct visualization of wipe-particle and particle-particle interactions during sampling and provides insights relevant to the dynamics of particle removal and collection. Examples of common and adhesive-modified wipe materials sampling polymer microspheres and an explosive-laden fingerprint are given, along with visualization of particle removal via air jet impingement.

Reactive Olfaction Ambient Mass Spectrometry

Chemical ionization of organic compounds with negligible vapor pressures (VP) is achieved at atmospheric pressure when the proximal sample is exposed to corona discharge. The vapor-phase analyte is produced through a reactive olfaction process, which is determined to include electrostatic charge induction in the proximal condensed-phase sample, resulting in the liberation of free particles. With no requirement for physical contact, a new contained nano-atmospheric pressure chemical ionization (nAPCI) source was developed that allowed direct mass spectrometry analysis of complex mixtures at a sample consumption rate less than nmol/min. The contained nAPCI source was applied to analyze a wide range of samples including the detection of 1 ng/mL cocaine in serum and 200 pg/mL caffeine in raw urine, as well as the differentiation of chemical composition of perfumes and beverages. Polar (e.g., carminic acid; estimated VP 5.1 × 10^-25 kPa) and nonpolar (e.g., vitamin D2; VP 8.5 × 10^-11 kPa) compounds were successfully ionized by the contained nAPCI ion source under ambient conditions, with the corresponding ion types of 78 other organic compounds characterized.

Canine Olfactory Thresholds to Amyl Acetate in a Biomedical Detection Scenario

Dogs' abilities to respond to concentrations of odorant molecules are generally deemed superior to electronic sensors. This sensitivity has been used traditionally in many areas; but is a more recent innovation within the medical field. As a bio-detection sensor for human diseases such as cancer and infections, dogs often need to detect volatile organic compounds in bodily fluids such as urine and blood. Although the limits of olfactory sensitivity in dogs have been studied since the 1960s, there is a gap in our knowledge concerning these limits in relation to the concentration of odorants presented in a fluid phase. Therefore, the aim of this study was to estimate olfactory detection thresholds to an inert substance, amyl acetate presented in a liquid phase. Ten dogs were trained in a “Go/No go” single scent-detection task using an eight-choice carousel apparatus. They were trained to respond to the presence of solutions of amyl acetate diluted to varying degrees in mineral oil by sitting in front of the positive sample, and not responding to the 7 other control samples. Training and testing took place in an indoor room with the same handler throughout using a food reward. After 30 weeks of training, using a forward chaining technique, dogs were tested for their sensitivity. The handler did not assist the dog during the search and was blind to the concentration of amyl acetate tested and the position of the target in the carousel. The global olfactory threshold trend for each dog was estimated by fitting a least-squares logistic curve to the association between the proportion of true positives and amyl acetate concentration. Results show an olfactory detection threshold for fluid mixtures ranging from 40 parts per billion to 1.5 parts per trillion. There was considerable inter-dog difference in sensitivity, even though all dogs were trained in the same way and worked without the assistance of the handler. This variation highlights factors to be considered in future work assessing olfactory detection performance by dogs.

Nanoporous Silica-Dye Microspheres for Enhanced Colorimetric Detection of Cyclohexanone

Forensic detection of non-volatile nitro explosives poses a difficult analytical challenge. A colorimetric sensor comprising of ultrasonically prepared silica-dye microspheres was developed for the sensitive gas detection of cyclohexanone, a volatile marker of explosives 1,3,5-trinitro-1,3,5-triazinane (RDX) and 1,3,5,7-tetranitro-1,3,5,7-tetrazocane (HMX). The silica-dye composites were synthesized from the hydrolysis of ultrasonically sprayed organosiloxanes under mild heating conditions (150 °C), which yielded microspherical, nanoporous structures with high surface area (~300 m2/g) for gas exposure. The sensor inks were deposited on cellulose paper and given sensitive colorimetric responses to trace the amount of cyclohexanone vapors even at sub-ppm levels, with a detection limit down to ~150 ppb. The sensor showed high chemical specificity towards cyclohexanone against humidity and other classes of common solvents, including ethanol, acetonitrile, ether, ethyl acetate, and ammonia. Paper-based colorimetric sensors with hierarchical nanostructures could represent an alternative sensing material for practical applications in the detection of explosives.

Sorbent Film-Coated Passive Samplers for Explosives Vapour Detection Part A: Materials Optimisation and Integration with Analytical Technologies

A new thin-film passive sampler is presented as a low resource dependent and discrete continuous monitoring solution for explosives-related vapours. Using 15 mid-high vapour pressure explosives-related compounds as probes, combinations of four thermally stable substrates and six film-based sorbents were evaluated. Meta-aramid and phenylene oxide-based materials showed the best recoveries from small voids (~70%). Analysis was performed using liquid chromatography-high resolution accurate mass spectrometry which also enabled tentative identification of new targets from the acquired data. Preliminary uptake kinetics experiments revealed plateau concentrations on the device were reached between 3–5 days. Compounds used in improvised explosive devices, such as triacetone triperoxide, were detected within 1 hour and were stably retained by the sampler for up to 7 days. Sampler performance was consistent for 22 months after manufacture. Lastly, its direct integration with currently in-service explosives screening equipment including ion mobility spectrometry and thermal desorption mass spectrometry is presented. Following exposure to several open environments and targeted interferences, sampler performance was subsequently assessed and potential interferences identified. High-security building and area monitoring for concealed explosives using such cost-effective and discrete passive samplers can add extra assurance to search routines while minimising any additional burden on personnel or everyday site operation.

The Influence of Sniffing on Airflow and Odorant Deposition in the Canine Nasal Cavity

Nasal airflow plays a critical role in olfaction by transporting odorant from the environment to the olfactory epithelium, where chemical detection occurs. Most studies of olfaction neglect the unsteadiness of sniffing and assume that nasal airflow and odorant transport are "quasi-steady," wherein reality most mammals "sniff." Here, we perform computational fluid dynamics simulations of airflow and odorant deposition in an anatomically accurate model of the coyote (Canis latrans) nasal cavity during quiet breathing, a notional quasi-steady sniff, and unsteady sniffing to: quantify the influence of unsteady sniffing, assess the validity of the quasi-steady assumption, and investigate the functional advantages of sniffing compared to breathing. Our results reveal that flow unsteadiness during sniffing does not appreciably influence qualitative (gross airflow and odorant deposition patterns) or quantitative (time-averaged olfactory flow rate and odorant uptake) measures of olfactory function. A quasi-steady approximation is, therefore, justified for simulating time-averaged olfactory function in the canine nose. Simulations of sniffing versus quiet breathing demonstrate that sniffing delivers about 2.5 times more air to the olfactory recess and results in 2.5-3 times more uptake of highly- and moderately-soluble odorants in the sensory region per unit time, suggesting one reason why dogs actively sniff. Simulations also reveal significantly different deposition patterns in the olfactory region during inspiration for different odorants, and that during expiration there is little retronasal odorant deposition in the sensory region. These results significantly improve our understanding of canine olfaction, and have several practical implications regarding computer simulation of olfactory function.

Use of Mass Spectrometric Vapor Analysis To Improve Canine Explosive Detection Efficiency

Canines remain the gold standard for explosives detection in many situations, and there is an ongoing desire for them to perform at the highest level. This goal requires canine training to be approached similarly to scientific sensor design. Developing a canine training regimen is made challenging by a lack of understanding of the canine's odor environment, which is dynamic and typically contains multiple odorants. Existing methodology assumes that the handler's intention is an adequate surrogate for actual knowledge of the odors cuing the canine, but canines are easily exposed to unintentional explosive odors through training material cross-contamination. A sensitive, real-time (∼1 s) vapor analysis mass spectrometer was developed to provide tools, techniques, and knowledge to better understand, train, and utilize canines. The instrument has a detection library of nine explosives and explosive-related materials consisting of 2,4-dinitrotoluene (2,4-DNT), 2,6-dinitrotoluene (2,6-DNT), 2,4,6-trinitrotoluene (TNT), nitroglycerin (NG), 1,3,5-trinitroperhydro-1,3,5-triazine (RDX), pentaerythritol tetranitrate (PETN), triacetone triperoxide (TATP), hexamethylene triperoxide diamine (HMTD), and cyclohexanone, with detection limits in the parts-per-trillion to parts-per-quadrillion range by volume. The instrument can illustrate aspects of vapor plume dynamics, such as detecting plume filaments at a distance. The instrument was deployed to support canine training in the field, detecting cross-contamination among training materials, and developing an evaluation method based on the odor environment. Support for training material production and handling was provided by studying the dynamic headspace of a nonexplosive HMTD training aid that is in development. These results supported existing canine training and identified certain areas that may be improved.

The Boom in 3D-Printed Sensor Technology

Future sensing applications will include high-performance features, such as toxin detection, real-time monitoring of physiological events, advanced diagnostics, and connected feedback. However, such multi-functional sensors require advancements in sensitivity, specificity, and throughput with the simultaneous delivery of multiple detection in a short time. Recent advances in 3D printing and electronics have brought us closer to sensors with multiplex advantages, and additive manufacturing approaches offer a new scope for sensor fabrication. To this end, we review the recent advances in 3D-printed cutting-edge sensors. These achievements demonstrate the successful application of 3D-printing technology in sensor fabrication, and the selected studies deeply explore the potential for creating sensors with higher performance. Further development of multi-process 3D printing is expected to expand future sensor utility and availability.

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.