Chemical Detection Research Articles

Binary metal oxide (NiO/SnO2) composite with electrochemical bifunction: Detection of neuro transmitting drug and catalysis for hydrogen evolution reaction

The synergetic effect between dual oxides in binary metal oxides (BMO) makes them promising electrode materials for the detection of toxic chemicals, and biological compounds. In addition, the interaction between the cations and anions of diverse metals in BMO tends to create more oxygen vacancies which are beneficial for energy storage devices. However, specifically targeted synthesis of BMO is still arduous. In this work, we prepared a nickel oxide/tin oxide composite (NiO/SnO2) through a simple solvothermal technique. The crystallinity, specific surface area, and morphology were fully characterized. The synthesized BMO is used as a bifunctional electrocatalyst for the electrochemical detection of dopamine (DPA) and for the hydrogen evolution reaction (HER). As expected, the active metals in the NiO/SnO2 composite afforded a higher redox current at a reduced redox potential with a nanomolar level detection limit (4 nm) and excellent selectivity. Moreover, a better recovery rate is achieved in the real-time detection of DPA in human urine and DPA injection solution. Compared to other metal oxides, NiO/SnO2 composite afforded lower overpotential (157 mV @10 mA cm−2), Tafel slope (155 mV dec−1), and long-term durability, with a minimum retention rate. These studies conclude that NiO/SnO2 composite can act as a suitable electrode modifier for electrochemical sensing and the HER.

Dual-mode Janus Structural-Color films toward an integrated sensing device with synergistic optical and electrical outputs

Real-time sensing technologies have shown significant importance for environmental management, chemical monitoring, and industrial production. Current chemical sensors with high sensing performances toward gases or liquids have been realized individually; however, a simultaneous detection of targets in the both forms along with a low detection limit and a wide detection range remains a big challenge. Here, we present a novel switchable dual-mode Janus-structured sensor with integrated structural colors and electrical conductivity for chemical detection. The photonic layer formed by the self-assembly of cellulose photonic crystals shows highly selective responses to high-concentration targets via the color-changing channel, while the electrically conductive layer generated by the formation of carbon nanotube networks demonstrates target perceptions at low concentration and even ppm levels. Notably, the integrated sensor is further designed as a wearable sensing system for chemical monitoring in different application scenarios. These findings offer new thinking to design switchable multi-mode sensors for environmental and industrial surveillance.

SR-Unet: A Super-Resolution Algorithm for Ion Trap Mass Spectrometers Based on the Deep Neural Network.

The mass spectrometer is an important tool for modern chemical analysis and detection. Especially, the emergence of miniature mass spectrometers has provided new tools for field analysis and detection. The resolution of a mass spectrometer reflects the ability of the instrument to discriminate between adjacent mass-to-charge ratio ions, and the higher the resolution, the better the discrimination of complex mixtures. Quadrupole ion traps are generally considered as a low-resolution mass spectrometry method, but they have gained wide attention and development in recent years because of their suitability for miniaturization and high qualitative capability. For an ion trap mass spectrometer, the mass sensitivity and resolution can be mutually constrained and need to be balanced by setting an appropriate scanning speed. In this study, a super-resolution U-net algorithm (SR-Unet) is proposed for ion trap mass spectrometry, which can estimate the possible ions from the overlapping ion peaks of low-resolution spectra and improve the equivalent resolution while ensuring sufficient sensitivity and analysis speed of the instrument. By determining the mass spectra of a linear ion trap mass spectrometer (LTQ XL) in Turbo and Normal scan modes, the same unit mass resolution as that at a scan speed of 16,667 Da/s was successfully obtained at 125,000 Da/s. Also, the experiments demonstrated that the algorithm is capable of the mass-to-charge ratio and instrument migration. SR-Unet can be migrated and applied to a miniature mass spectrometer for cruise detection of volatile organic compounds (VOCs), and the identification of VOC species in Photochemical Assessment Monitoring Stations (PAMS) was improved from 31 to 50 species with the same monitoring and analysis speed requirement. Further, super-unit mass resolution peptide detection was achieved on a miniature mass spectrometer with the help of the SR-Unet algorithm, which reduced the full width at half-maxima (FWHM) of bradykinin divalent ions (m/z 531) from 0.35 to 0.15 Da at a scan speed of 375 Da/s and improved the equivalent resolution to 3540. The proposed method provides a new idea to enhance the field mixture detection capability of miniature ion trap mass spectrometers.

Rapid detection of residual chlorpyrifos and pyrimethanil on fruit surface by surface-enhanced Raman spectroscopy integrated with deep learning approach

Chlorpyrifos and pyrimethanil are widely used insecticides/fungicides in agriculture. The residual pesticides/fungicides remaining in fruits and vegetables may do harm to human health if they are taken without notice by the customers. Therefore, it is important to develop methods and tools for the rapid detection of pesticides/fungicides in fruits and vegetables, which are highly demanded in the current markets. Surface-enhanced Raman spectroscopy (SERS) can achieve trace chemical detection, while it is still a challenge to apply SERS for the detection and identification of mixed pesticides/fungicides. In this work, we tried to combine SERS technique and deep learning spectral analysis for the determination of mixed chlorpyrifos and pyrimethanil on the surface of fruits including apples and strawberries. Especially, the multi-channel convolutional neural networks-gate recurrent unit (MC-CNN-GRU) classification model was used to extract sequence and spatial information in the spectra, so that the accuracy of the optimized classification model could reach 99% even when the mixture ratio of pesticide/fungicide varied considerably. This work therefore demonstrates an effective application of using SERS combined deep learning approach in the rapid detection and identification of different mixed pesticides in agricultural products.

High temperature X-ray and γ-ray spectroscopy with a diamond detector

A single crystal chemical vapour deposition diamond detector was electrically characterised and then investigated as a spectroscopic photon counting X-ray and γ-ray detector across the temperature range, T, −20 °C ≤ T ≤ 100 °C. The detector was connected to a custom-built charge-sensitive preamplifier of low electronic noise and illuminated in turn by 55Fe radioisotope X-ray and 109Cd radioisotope X-ray and γ-ray sources. In combination, the radiation sources provided characteristic soft (e.g. 5.9 keV) and hard (e.g. 22.16 keV) X-rays and 88.03 keV γ-ray emissions. The Mn Kα (5.9 keV) and Kβ (6.49 keV) X-ray emissions from the 55Fe radioisotope X-ray source were detected (and separated from the zero energy noise peak) at temperatures of −20 °C ≤ T ≤ 60 °C; the Ag Kα (22.16 and 21.99 keV) and Kβ (24.94, 24.99, and 25.46 keV) X-ray emissions and 88.03 keV γ-ray emissions were detectable across the entire temperature range investigated (−20 °C ≤ T ≤ 100 °C). The detector and the preamplifier were operated without cooling across the entire temperature range. The energy resolution (full width at half maximum) at 22.16 keV (Ag Kα1) was 4.57 keV ± 0.26 keV at 100 °C and 2.70 keV ± 0.18 keV at −20 °C. Noise analysis indicated that the combination of dielectric noise and any incomplete charge collection noise present dominated the other noise components at 5.9 keV. When the detector was illuminated with the 109Cd radioisotope X-ray and γ-ray source, a high count rate introduced parasitic effects (possibly baseline shift) which reduced the optimum shaping time of the spectrometer.

Promotion of a quality standard for Paris polyphylla var. yunnanensis based on the efficacy-oriented effect-constituent index

Multi-component determination and bioassays used for the quality control of traditional Chinese medicine (TCM) may have certain shortcomings. The effect-constituent index (ECI) is a quality evaluation index weighted by chemical composition analysis and effect detection. This index can be established by the dose-effect relationship of the active ingredients in TCM. In this study, Paris polyphylla var. yunnanensis (PY) was selected as the representative drug. Chemical evaluation and bioactivity evaluation were combined to establish the ECI, to compensate for the deficiency of a single evaluation method to some extent, and can be related to the efficacy of PY, in order to improve its quality standard. The ECI not only reflects the contribution of component content to the quality of PY, but also relates to clinical efficacy and reflects the influence of different components on the biological activity. Moreover, this study provided a reference method for the quality control of other TCMs.

Comparative Study of Photonic Platforms and Devices for On-Chip Sensing

Chemical and biological detection is now an indispensable task in many fields. On-chip refractive index (RI) optical sensing is a good candidate for mass-scale, low-cost sensors with high performance. While most literature works focus on enhancing the sensors’ sensitivity and detection limit, other important parameters that determine the sensor’s yield, reliability, and cost-effectiveness are usually overlooked. In this work, we present a comprehensive study of the different integrated photonic platforms, namely silica, silicon nitride, and silicon. Our study aims to determine the best platform for on-chip RI sensing, taking into consideration the different aspects affecting not only the sensing performance of the sensor, but also the sensor’s reliability and effectiveness. The study indicates the advantages and drawbacks of each platform, serving as a guideline for RI sensing design. Modal analysis is used to determine the sensitivity of the waveguide to medium (analyte) index change, temperature fluctuations, and process variations. The study shows that a silicon platform is the best choice for high medium sensitivity and a small footprint. On the other hand, silica is the best choice for a low-loss, low-noise, and fabrication-tolerant design. The silicon nitride platform is a compromise of both. We then define a figure of merit (FOM) that includes the waveguide sensitivity to the different variations, losses, and footprint to compare the different platforms. The defined FOM shows that silicon is the best candidate for RI sensing. Finally, we compare the optical devices used for RI sensing, interferometers, and resonators. Our analysis shows that resonator-based devices can achieve much better sensing performance and detection range, due to their fine Lorentzian spectrum, with a small footprint. Interferometer based-sensors allow engineering of the sensors’ performance and can also be designed to minimize phase errors, such as temperature and fabrication variations, by careful design of the interferometer waveguides. Our analysis and conclusions are also verified by experimental data from other published work.

An Unmanned Vehicle-Based Remote Raman System for Real-Time Trace Detection and Identification

Raman spectroscopy is a type of inelastic scattering that provides rich information about a substance based on the coupling of the energy levels of their vibrational and rotational modes with an incident light. It has been applied extensively in many fields. As there is an increasing need for the remote detection of chemicals in planetary exploration and anti-terrorism, it is urgent to develop a compact, easily transportable, and fully automated remote Raman detection system for trace detection and identification of information, with high-level confidence about the target’s composition and conformation in real-time and for real field scenarios. Here, we present an unmanned vehicle-based remote Raman system, which includes a 266 nm air-cooling passive Q-switched nanosecond pulsed laser of high-repetition frequency, a gated ICMOS, and an unmanned vehicle. This system provides good spectral signals from remote distances ranging from 3 m to 10 m for simulating realistic scenarios, such as aluminum plate, woodblock, paperboard, black cloth, and leaves, and even for detected amounts as low as 0.1 mg. Furthermore, a convolutional neural network (CNN)-based algorithm is implemented and packaged into the recognition software to achieve faster and more accurate detection and identification. This prototype offers a proof-of-concept for an unmanned vehicle with accurate remote substance detection in real-time, which can be helpful for remote detection and identification of hazardous gas, explosives, their precursors, and so forth.

Design Analysis of Mid IR DIAL System for Detection of Hazardous Chemical Species

Nowadays, both military and public agencies are concerned with the remote detection of toxic gases and chemical warfare agents in the atmosphere. A promising method for the remote detection of such harmful chemicals in the atmosphere is Differential Absorption Lidar (DIAL). In the current paper, system design analysis has been carried out to build a DIAL system for the detection of toxic chemical warfare agents, chemical warfare simulants, explosive precursors, and pollutants. The proposed DIAL system comprises an Optical Parametric Oscillator (OPO) based tuneable laser, a 203 mm diameter Cassegrain telescope, a TE-cooled MCT detector, suitable data acquisition hardware, etc. The DIAL output parameters like return signals, SNR, and minimum measurable concentrations have been simulated under different weather conditions such as clear sky, moderately hazy sky, and hazy atmospheric conditions for given system input parameters (pulse energy, detectivity, bandwidth, DAQ resolution, etc.). We have considered chemicals such as Sarin, Thiodiglycol (TDG), acetone, and methane to be detected using the system. Analysis has been carried out for these chemicals present at different locations with varying concentrations. Our analysis reveals that the DIAL system with a laser transmitter of 5 mJ energy and 203 mm receiver telescope is capable of detecting a few ppm concentrations of toxic chemicals present anywhere between the ranges from a few tens of meters to 2 km with topographic target present. The sensitivity of the system in terms of minimum detectable concentrations for the considered chemicals is also estimated for different atmospheric conditions. It is seen that the minimum detectable concentration of TDG is 3.2 ppm in clear weather conditions which increases to 9.2 ppm under a hazy atmosphere. A similar analysis has been carried out for other toxic chemicals and has been discussed in the paper.

Visualisation of drug distribution in skin using correlative optical spectroscopy and mass spectrometry imaging

A correlative methodology for label-free chemical imaging of soft tissue has been developed, combining non-linear optical spectroscopies and mass spectrometry to achieve sub-micron spatial resolution and critically improved drug detection sensitivity. The approach was applied to visualise the kinetics of drug reservoir formation within human skin following in vitro topical treatment with a commercial diclofenac gel. Non-destructive optical spectroscopic techniques, namely stimulated Raman scattering, second harmonic generation and two photon fluorescence microscopies, were used to provide chemical and structural contrast. The same tissue sections were subsequently analysed by secondary ion mass spectrometry, which offered higher sensitivity for diclofenac detection throughout the epidermis and dermis. A method was developed to combine the optical and mass spectrometric datasets using image registration techniques. The label-free, high-resolution visualisation of tissue structure coupled with sensitive chemical detection offers a powerful method for drug biodistribution studies in the skin that impact directly on topical pharmaceutical product development.

Investigation of the SERS application of gold films deposited on uncured polydimethylsiloxane with tunable LSPR

We present an approach to investigate the localized surface plasmon resonance and surface-enhanced Raman scattering of gold films deposited on uncured polydimethylsiloxane via thermal evaporation. Differing from solid substrates, the liquid surface of uncured polydimethylsiloxane can serve as an isotropic substrate on which gold atoms nucleate and disperse to form characteristic microstructures in a controlled manner. By adjusting experimental parameters during film deposition, the absorption of resonant plasmon modes can be tuned in the visible spectral range due to the control of particle size and distribution in Au films. Furthermore, Raman measurements are conducted to investigate the enhancement of Raman signals in these films, and the experimental results are verified by simulation analysis. This work exhibits tunability of surface plasmon resonance frequency and enhanced Raman detection capability by depositing metal films on liquid surfaces, thus providing potential applications of these films in flexible biosensors and chemical detection.

Recent Advances in the Development of Non‐Invasive Imaging Probes for Cancer Immunotherapy

AbstractThe last two decades have witnessed a major revolution in the field of tumor immunology including clinical progress using various immunotherapy strategies. These advances have highlighted the potential for approaches that harness the power of the immune system to fight against cancer. While cancer immunotherapies have shown significant clinical successes, patient responses vary widely due to the complex and heterogeneous nature of tumors and immune responses, calling for reliable biomarkers and therapeutic strategies to maximize the benefits of immunotherapy. Especially, stratifying responding individuals from non‐responders during the early stages of treatment could help avoid long‐term damage and tailor personalized treatments. In efforts to develop non‐invasive means for accurately evaluating and predicting tumor response to immunotherapy, multiple affinity‐based agents targeting immune cell markers and checkpoint molecules have been developed and advanced to clinical trials. In addition, researchers have recently turned their attention to substrate and activity‐based imaging probes that can provide real‐time, functional assessment of immune response to treatment. Here, we highlight some of those recently designed probes that image functional proteases as biomarkers of cancer immunotherapy with a focus on their chemical design and detection modalities and discuss challenges and opportunities for the development of imaging tools utilized in cancer immunotherapy.

Recent Advances in the Development of Non-Invasive Imaging Probes for Cancer Immunotherapy.

The last two decades have witnessed a major revolution in the field of tumor immunology including clinical progress using various immunotherapy strategies. These advances have highlighted the potential for approaches that harness the power of the immune system to fight against cancer. While cancer immunotherapies have shown significant clinical successes, patient responses vary widely due to the complex and heterogeneous nature of tumors and immune responses, calling for reliable biomarkers and therapeutic strategies to maximize the benefits of immunotherapy. Especially, stratifying responding individuals from non-responders during the early stages of treatment could help avoid long-term damage and tailor personalized treatments. In efforts to develop non-invasive means for accurately evaluating and predicting tumor response to immunotherapy, multiple affinity-based agents targeting immune cell markers and checkpoint molecules have been developed and advanced to clinical trials. In addition, researchers have recently turned their attention to substrate and activity-based imaging probes that can provide real-time, functional assessment of immune response to treatment. Here, we highlight some of those recently designed probes that image functional proteases as biomarkers of cancer immunotherapy with a focus on their chemical design and detection modalities and discuss challenges and opportunities for the development of imaging tools utilized in cancer immunotherapy.

A pH-Stable Tb-MOF as Luminescence Sensor for Highly Sensitive Detection of Amino Acids through Diverse Sensing Mechanism.

A luminescent Tb-MOF with excellent stability and dual-emitting properties was constructed with an amide-functionalized tetracarboxylate ligand. Tb-MOFs were initially assembled on one-dimensional Tb3+ chains, then formed a two-dimensional double-decker layer through the synergistic linking of organic ligands and bridging formic acid anions, and further fabricated the final three-dimensional structure through the connection of the organic ligands. Powder X-ray diffraction experiments revealed that Tb-MOFs not only exhibited excellent stability in water but also maintained structural integrity in the pH range of 2-12. Importantly, this Tb-MOF provided the first example of a metal-organic framework (MOF)-based luminescence sensor that can simultaneously detect two acid amino acids (aspartic and glutamic acids) through a turn-off sensing mechanism and two basic amino acids (lysine and arginine acids) through unusual turn-on and turn-off-on sensing mechanisms. Moreover, high sensitivity, low detection limit, and excellent recyclability of this sensor endow Tb-MOFs with great potential as a highly efficient amino acid fluorescence sensor in chemical detection and biological environments.

Femtosecond laser multibeam parallel processing for variable focal-length optofluidic chips.

Optofluidic chips are frequently utilized in applications such as biological observation, chemical detection, dynamic displays, imaging, holography, and sensing. Yet, developing continuously zoomable technology has been challenging in the production of optical devices. Using a spatial light modulator to shape a femtosecond laser to achieve multibeam parallel pulse punching, we propose an easy-to-fabricate, stable, and reliable tuning technique in this Letter. We then propose the addition of a liquid medium with a continuously variable refractive index to achieve controllable zooming without changing the position and morphology of the microlens. By pumping various concentrations of the liquid medium into the optofluidic chip, continuous tunability of the device was experimentally verified.

Surface nanostructuring and wettability of low energy Ar+ irradiated Au/V2O5/Au multilayer system for SERS detection of rhodamine-6G

Detection of rhodamine-6G by SERS (Surface Enhanced Raman Scattering) on different-thickness of oxide layer sandwiched between gold (Au) layers exposed to an ion beam is reported. Thermal evaporation was used to deposit Au/V2O5/Au multilayers of varying V2O5 thicknesses (5 and 10 nm) on a glass substrate. After being exposed to 10 keV Ar+ at varying fluences, the surface morphology can be tuned with development of Au-nanostructures (Au-NS). The growth of Au-NS is governed by ion beam-induced sputtering and diffusion mechanisms. In addition to validating the thickness of oxide layer, Rutherford Backscattering Spectroscopy (RBS) confirms the elemental composition of Au/V2O5/Au on the glass substrate. Sputtering and surface diffusion are two competing statistical elements that determine the wettable properties of Au-NS surfaces. A relationship between rms roughness, water contact angle, and the detection of rhodamine-6G (R6G) by surface enhanced Raman scattering (SERS) is provided. Understanding the mechanism(s) through which SERS chemical detection works on metallic-oxide multilayer system is advanced by the present study.

High-performance self-powered ultraviolet photodetector based on PVK/amorphous-WO3 organic-inorganic heterojunction

Ultraviolet (UV) photodetectors have found wide-ranging applications, ranging from optical communications to chemical detection. High performance UV photodetectors that can be self-powered are highly desirable in many applications as they can minimize energy consumption during operation. Herein, a self-powered UV photodetector, which consisted of poly(9-vinylcarbazole) (PVK)/amorphous-WO3 organic-inorganic heterojunction with PEDOT:PSS as a hole transport layer, was fabricated using a two-step method at low temperature. The effect of WO3, PVK and PEDOT:PSS films on the performances of the photodetector was also investigated. Under optimized parameters, the PEDOT:PSS/PVK/WO3 photodetector exhibited a maximum responsivity of 12.41 AW−1, specific detectivity of 1.80 × 1013 Jones, photo-dark current ratio of 103 at reverse bias and typical rectification characteristic when exposed to 365 nm light irradiation. The photoelectric conversion mechanism of this novel PVK/WO3 heterojunction is discussed using energy band diagrams. This work presents a method to produce a high performance WO3-based heterostructure at low temperature, which has the potential for UV imaging.

Endocrine disrupting chemicals and male fertility: from physiological to molecular effects.

The deleterious effects of chemical or non-chemical endocrine disruptors (EDs) on male fertility potential is well documented but still not fully elucidated. For example, the detection of industrial chemicals' metabolites in seminal plasma and follicular fluid can affect efficiency of the gametogenesis, the maturation and competency of gametes and has guided scientists to hypothesize that endocrine disrupting chemicals (EDCs) may disrupt hormonal homoeostasis by leading to a wide range of hormonal control impairments. The effects of EDCs exposure on reproductive health are highly dependent on factors including the type of EDCs, the duration of exposure, individual susceptibility, and the presence of other co-factors. Research and scientists continue to study these complex interactions. The aim of this review is to summarize the literature to better understand the potential reproductive health risks of EDCs in France.

Analysis of a highly temperature-sensitive gold-coated plasmonic biosensor for analyte detection

A temperature-sensitive gold coated PCF-based surface plasmon resonance (SPR) biosensor was examined for detecting analytes based on their refractive indices. The proposed sensor attained maximum amplitude sensitivities (AS) of 1432 RIU−1 and 1291 RIU−1, wavelength sensitivities (WS) of 13,500 nm/RIU and 13,000 nm/RIU in X and Y- polarized mode individually in RI spectrum of 1.34–1.4. Furthermore, the proposed sensor produced ultimate figure of merit (FOM) values of 546.93 RIU−1 and 521.4601 RIU−1 in x and y polarization modes. High birefringence of 1.5 × 10−3 was also computed for the suggested sensor. Additionally, the proposed sensor shows high temperature sensitivity of 4.5833 nm/°C with a comparable resolution of 2.18××10−2 °C and a maximum FOM value of 0.101 °C−1 in the detection range of −114 °C to 78 °C in the presence of ethanol as a sensing medium. The reported sensor therefore can be considered as a notable solution for any chemical or biological analytes detection.

Identification of Chemical and Structural Characteristics of Acrylic Paint Layer Using Terahertz Metasurfaces.

The precise investigation and monitoring of the internal structural change within complex layered systems are crucial, as the emergence of undesirable defects or formation of secondary internal structures significantly exerts a profound influence on the overall properties of the system. We demonstrate an advanced sensing platform utilizing terahertz metasurfaces, allowing chemical detection and precise identification within an acrylic paint layer with a noticeable sensitivity, reaching down to several hundreds of nanometers, in nondestructive and noncontact manners. The identification of solid and mixed paint samples was achieved by analyzing their optical properties, including the refractive index and absorption coefficient. Notably, the presence of internal pore defects within the mixed acrylic paint led to geometric distortions, affecting the state of the overall system. Intriguingly, even in cases where acrylic paint exhibited identical colors perceptible under visible light, distinct discrimination and identification of chemical compositions were successfully proposed.