Standoff Detection Research Articles

Performance upgrade of a microbial explosives’ sensor strain by screening a high throughput saturation library of a transcriptional regulator

We present a methodology for a high-throughput screening (HTS) of transcription factor libraries, based on bacterial cells and GFP fluorescence. The method is demonstrated on the Escherichia coli LysR-type transcriptional regulator YhaJ, a key element in 2,4-dinitrotuluene (DNT) detection by bacterial explosives’ sensor strains. Enhancing the performance characteristics of the YhaJ transcription factor is essential for future standoff detection of buried landmines. However, conventional directed evolution methods for modifying YhaJ are limited in scope, due to the vast sequence space and the absence of efficient screening methods to select optimal transcription factor mutants. To overcome this limitation, we have constructed a focused saturation library of ca. 6.4 × 107 yhaJ variants, and have screened over 70 % of its sequence space using fluorescence-activated cell sorting (FACS). Through this screening process, we have identified YhaJ mutants exhibiting superior fluorescence responses to DNT, which were then effectively transformed into a bioluminescence-based DNT detection system. The best modified DNT reporter strain demonstrated a 7-fold lower DNT detection threshold, a 45-fold increased signal intensity, and a 40 % shorter response time compared to the parental bioreporter. The FACS-based HTS approach presented here may hold a potential for future molecular enhancement of other sensing and catalytic bioreactions.

Continuous-wave terahertz quantum cascade laser based on a hybrid bound to bound quantum design

We report a low threshold power density and high power output terahertz quantum cascade laser emitting at ∼3.9 THz operating in continuous-wave mode. The high output power and wall-plug efficiency are achieved based on a hybrid bound-to-bound quantum active design. A record output power of 312 mW and a low threshold power density of 0.8 kW/mm3 (threshold current density of 109 A/cm2) in continuous-wave mode at 20 K is demonstrated for a 300-μm-wide and 2-mm-long single-ridge device. The highest wall-plug efficiency is 1.38% and the slope efficiency is 684 mW/A with an internal quantum efficiency of ∼120 photons per injected electron. The demonstration of this low-threshold and high-power THz laser will promote THz-based remote sensing and standoff detection for pharmaceutical and health industry applications.

Simultaneous standoff sensing for methane and hydrogen sulfide using wavelength-modulated laser absorption spectroscopy with non-cooperative target

Standoff detection of flammable and toxic gases simultaneously is important for leakage warning and safe production in oil and gas industries. A portable and robust single-ended laser sensor is developed to retrieve path-averaged gas concentrations of methane (CH4) and hydrogen sulfide (H2S) by collecting the backscattered light from a distant non-cooperative target. Time-division multiplexing of two semiconductor lasers with pigtails are employed to cover the absorption lines of CH4 and H2S at 1653.73 nm and 1578.13 nm, respectively. Wavelength modulation spectroscopy with 1 f normalized 2 f detection (WMS-2f/1 f) method is used for gas measurement to eliminate the change of return light intensity caused by different distances and different non cooperative targets. Kalman filter is developed as a post-processing method to reduce the output fluctuations during standoff gas measurement. The performance of the sensor is assessed, including signal noise ratio under different standoff distances and hard targets, measurement precision, time-response and the detection limit. The reported sensor allows for real-time non-contact standoff detection of CH4 and H2S, with great potential for its application in oil and gas industries.

Photomechanical detection of bioaerosol fluorescence free-from solar background

Detection of biological molecules in aerosol via fluorescence signature is well established. However, standoff detection of weak target fluorescence deeply submerged in the ambient bright solar background is challenging with conventional approaches (using photo-multiplier tubes, avalanche photodiodes or ICCD) due to saturation effects and overlapping spectral signatures. Here, we demonstrate a Quartz tuning fork (QTF) enhanced photomechanical detection of fluorescence spectra from bio-aerosols free from broadband solar light. The detection is based on resonant excitation of QTF at 32.78 kHz by on–off modulated laser-induced fluorescence from aerosol while the stray solar background is essentially suppressed by the QTF. A remote detection of fluorescence spectra of Bacillus Globbigi and Riboflavin aerosols was demonstrated at 5 m standoff distance using two near-UV excitation wavelengths with good signal-to-noise ratio. The fluorescence signal increases linearly with excitation power, concentration and quality factor of the QTF. Besides being low-cost and reliable, the detection range of the presented approach can be extended to large standoff distance free-from ambient sunlight noise.

Analysis of the Feasibility of UAS-Based EMI Sensing for Underground Utilities Detection and Mapping

This paper investigates the feasibility of using a linear current sensing (LCS) technique integrated on an unmanned aerial system (UAS) for detecting and mapping underground infrastructure rapidly and cost-effectively. The LCS technique is based on data from a wide band of electromagnetic induction frequencies (50 kHz to 2 MHz) using a vector magnetic field gradiometer. This technique takes advantage of a slowly decaying secondary magnetic field in order to achieve greater standoff detection distance (1R2 vs. 1R6 for compact metallic targets during EMI sensing, where R is the distance from a target to the sensor). These secondary magnetic fields are produced by the excite current on long conductors, allowing detection at a distance of 10 meters or more. The system operates between tens of kHz to a few MHz and uses either an active EMI source or existing EM fields to excite this linear current on a long metallic subsurface target. Once excited, these linear currents produce a secondary magnetic field that is detected with an above ground triaxial magnetic field gradiometer. By moving and tracking its geolocation, the system outputs rich datasets sufficient to support high-fidelity forward and inverse EMI models for estimating the depth and orientation of deep underground long linear metallic infrastructure. The system’s hardware and its integration to a UAS system are outlined, along with the formulation of LCS theory, and numerical and experimental data are presented. The results illustrate that the LCS technique offers large standoff detection, is adaptable to UAS, and could be used effectively for detecting deep underground infrastructure such as wires and pipes.

Time domain analysis of photon scattering and Huygens-Fresnel back projection.

Stand-off detection and characterization of scattering media such as fog and aerosols is an important task in environmental monitoring and related applications. We present, for the first time, a stand-off characterization of sprayed water fog in the time domain. Using a time correlated single photon counting, we measure transient signatures of photons reflected off a target within the fog volume. We can distinguish ballistic from scattered photon. By application of a forward propagation model, we reconstruct the scattered photon paths and determine the fog's mean scattering length μscat. in a range of 1.55 m to 1.86m. Moreover, in a second analysis, we project the recorded transients back to reconstruct the scene using virtual Huygens-Fresnel wavefronts. While in medium-density fog some contribution of ballistic remain in the signatures, we could demonstrate that in high-density fog, all recorded photons are at least scattered a single time. This work may path the way to novel characterization tools of and enhanced imaging in scattering media.

Wavelength modulation‐based active laser heterodyne spectroscopy for standoff gas detection

AbstractThe wavelength modulation‐active laser heterodyne spectroscopy (WM‐ALHS), which introduces wavelength modulation technique into active laser heterodyne spectroscopy, is reported to enhance the gas standoff detection capability of weak return optical power. The ALHS gas standoff detection system is developed using a 1.65 μm butterfly packaged distributed feedback laser with tail fiber and an all‐fiber structure, which successfully detects methane concentrations at a distance of 35 cm using an aluminum plate as the reflective surface. Allan variance analysis shows that the system has good stability, and the detection limit at 29.2 s integration time is 0.84 ppm m. Standoff detection experiments with direct absorption‐active laser heterodyne spectroscopy (DA‐ALHS) and wavelength modulation spectroscopy (WMS) are carried out on the basis of the WM‐ALHS system and the detection limits of 4.49 and 1.64 ppm m were achieved within integration times of 18.6 and 29 s for DA‐ALHS and WMS, respectively. The superiority of the WM‐ALHS method compared to these two spectral detection methods is demonstrated. Furthermore, the feasibility of applying WM‐ALHS to gas standoff detection has been verified, laying the foundation for the development of this spectroscopic technology.

The physical mechanism of alpha-particle-air interaction and analysis of long-range secondary particles yield

The α-particle detection has a pivotal role in radiation measurement. Standoff α-particle detection has advantages such as high efficiency and safety compared with the traditional method. However, the low yield of the characteristic signal significantly limits the broad application of this technique. To efficiently perform standoff detection of α-particle, the physical mechanism of α-particle interaction with air, the various secondary effects generated, and the yields are systematically analyzed in this paper. The results show that in addition to the radioluminescence, which is the focus of most current studies, the characteristic X-rays also meet the requirements as a characteristic signal for standoff detection. The processes of induced generation of these two secondary particles in the air are studied, the yields of characteristic X-rays of nitrogen and oxygen atoms and the yields of radioluminescence photons in the near-ultraviolet (UVA/UVB) and deep-ultraviolet (UVC) bands are given, respectively. The interference brought by the presence of β-particles and γ-particles to the α-detection when the radiation field is more complex is also quantitatively analyzed.

Characterization of fentanyl HCl powder prior to and after systematic degradation.

Fentanyl HCl is of particular interest in forensic cases but there is a notable gap in literature regarding its analysis. This study utilized a multi-method approach to characterize fentanyl HCl powder, both fresh and following a forced degradation process. Using sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) and direct injection gas chromatography-mass spectrometry (GC-MS), five compounds were identified in fresh fentanyl HCl powder. The identified compounds were: N-phenylpropanamide, 1-phenethyl-4-propionyloxypiperidine (1-P-4-POP), 4-anilino-N-phenethylpiperidine (4-ANPP), acetylfentanyl, and fentanyl; all identified compounds but acetylfentanyl and fentanyl decreased in quantity as the sample was degraded. Fresh headspace samples analyzed with solid phase microextraction (SPME)-GC-MS identified four compounds in common with the powder analyses: N-phenylpropanamide,1-P-4-POP, 4-ANPP, and fentanyl. Acetylfentanyl was not present in the headspace samples, although two additional compounds were: N-phenylacetamide and N-phenethyl-4-piperidinone (NPP). Where direct analysis of degraded fentanyl HCl showed decreased quantities of the identified compounds, headspace samples of the degraded fentanyl HCl resulted in higher quantities, implying that the degradation process drove those compounds to volatilize. Notably, fentanyl was identified in the headspace, implying that this could be an appropriate target for standoff detection. Finally, thermogravimetric analysis (TGA) and differential scanning calorimetry (DCS) confirmed that the forced degradation process had little permanent effect on the powder.

Standoff Detection System Using Raman Spectroscopy in the Deep-Ultraviolet Wavelength Region for the Detection of Hazardous Gas.

This study developed a standoff detection system for Raman spectra in the deep-ultraviolet region to facilitate remote detection of various hazardous materials. Although Raman spectroscopy can distinguish various materials, the measurement of Raman spectra through standoff detection is challenging because of the low scattering cross-section of Raman scattering. The resonance Raman scattering effect in the deep-ultraviolet wavelength region is promising in terms of enhancing the spectral intensity of Raman scattering. A catoptric light receiver system was developed to effectively collect deep-ultraviolet light via a change in the distance from the primary to secondary mirror of the telescope. The experimental results for the standoff detection indicate that the system enables the measurement of the Raman spectrum of SO2 gas, which was locally present 20 m from the system with a wavelength resolution of 0.15 nm. The gas used in this remote measurement has a relatively simple molecular structure among chemical, biological, radiological, nuclear, and explosive gases. However, the high wavelength resolution of Raman spectroscopy will enable measurement of substances with complex molecular structures, such as bacteria and explosives, without losing the detailed structure of their spectra.

Experimental study on standoff detection of explosives traces using Laser Raman spectroscopy: challenges and possible solution

Experimental study on standoff detection of explosives traces using Laser Raman spectroscopy: challenges and possible solution

Specific Bacterial Pathogen Phytosensing Is Enabled by a Synthetic Promoter-Transcription Factor System in Potato.

Phytosensors are genetically engineered plant-based sensors that feature synthetic promoters fused to reporter genes to sense and report the presence of specific biotic and abiotic stressors on plants. However, when induced reporter gene output is below detectable limits, owing to relatively weak promoters, the phytosensor may not function as intended. Here, we show modifications to the system to amplify reporter gene signal by using a synthetic transcription factor gene driven by a plant pathogen-inducible synthetic promoter. The output signal was unambiguous green fluorescence when plants were infected by pathogenic bacteria. We produced and characterized a phytosensor with improved sensing to specific bacterial pathogens with targeted detection using spectral wavelengths specific to a fluorescence reporter at 3 m standoff detection. Previous attempts to create phytosensors revealed limitations in using innate plant promoters with low-inducible activity since they are not sufficient to produce a strong detectable fluorescence signal for standoff detection. To address this, we designed a pathogen-specific phytosensor using a synthetic promoter-transcription factor system: the S-Box cis-regulatory element which has low-inducible activity as a synthetic 4xS-Box promoter, and the Q-system transcription factor as an amplifier of reporter gene expression. This promoter-transcription factor system resulted in 6-fold amplification of the fluorescence after infection with a potato pathogen, which was detectable as early as 24 h post-bacterial infection. This novel bacterial pathogen-specific phytosensor potato plant demonstrates that the Q-system may be leveraged as a powerful orthogonal tool to amplify a relatively weak synthetic inducible promoter, enabling standoff detection of a previously undetectable fluorescence signal. Pathogen-specific phytosensors would be an important asset for real-time early detection of plant pathogens prior to the display of disease symptoms on crop plants.

Standoff Detection and Identification of Liquid Chemicals on a Reflective Substrate Using a Wavelength-Tunable Quantum Cascade Laser.

Standoff chemical detection and identification techniques are necessary for ensuring safe exposure to dangerous substances. Molecular fingerprints of unknown chemicals can be measured using wavelength-tunable quantum cascade lasers operating in long-wavelength infrared. In this work, we present a method that can identify liquid chemicals on a reflective substrate via diffuse reflection spectra measurement from 50 cm away and multiple nonlinear regression analysis. Experimental measurements and numerical analyses were conducted for different chemical surface densities and angles of light incidence using diethyl phthalate (DEP) and dimethyl methylphosphonate (DMMP). Candidate substances can be classified using a deep learning model to reduce analysis time.

Laser-induced breakdown spectroscopy combined with a convolutional neural network: A promising methodology for geochemical sample identification in Tianwen-1 Mars mission

As an in-situ and stand-off detection technique, laser-induced breakdown spectroscopy (LIBS) can perform efficient geochemical sample identification and classification with chemometrics, and therefore LIBS has played a shining role in planetary exploration missions. Unlike in laboratory experiments, the LIBS sampling distance in field detection for planetary exploration naturally varies. The considerable spectral differences caused by the varying distance can be a critical challenge for chemometrics model training and testing. In this research, we address this issue by focusing on the construction of a chemometrics model with powerful learning ability rather than the conventional spectral data processing for distance correction. Specifically, we have investigated the performance of a designed deep convolutional neural network (CNN) on datasets consisting of multi-distance spectra. More than 18,000 LIBS spectra were collected by a duplicate model of the MarSCoDe instrument for China's Tianwen-1 Mars mission, at eight different distances ranging from 2.0 m to 5.0 m. These spectra were acquired from 39 geochemical standard samples, which were classified by the deep CNN. The competence of the CNN is compared with that of four alternative chemometrics, i. e. back-propagation neural network, support vector machine, linear discriminant analysis, and logistic regression. The CNN can surpass the other four algorithms in terms of overall prediction accuracy. In addition, we have inspected the dependence of the CNN performance on the distance number involved in the training set and the data properties of the testing set. Furthermore, it has been revealed that the CNN model can behave even better if an extremely simple distance correction procedure is supplemented. Our results show that CNN is an extraordinary chemometrics for material classification on multi-distance spectra datasets, implying that CNN-LIBS is a promising methodology for geochemical sample identification/classification in Tianwen-1 mission and other future planetary exploration missions, and in even more field detection scenarios with varying sampling distance.

Raman spectroscopic and advanced signal processing analyses for real time standoff detection and identification of explosives

Laser Raman spectroscopy is a powerful instrument commonly used for detection of bulk and trace amounts of explosives. The work carried out in this paper is divided into two phases; the first phase is to propose a real time standoff explosive detection and identification system based on Raman spectroscopy that can be deployed in static checkpoints. The measurement is performed for samples placed in contact and at distances up to 1 m in ambient light conditions. The second phase is to propose a novel sophisticated signal processing and pattern recognition techniques for accurate identification and classification of the investigated materials.

Standoff and Point Detection of Thin Polymer Layers Using Microcantilever Photothermal Spectroscopy

Standoff detection based on optical spectroscopy is an attractive method for identifying materials at a distance with very high molecular selectivity. Standoff spectroscopy can be exploited in demanding practical applications such as sorting plastics for recycling. Here, we demonstrate selective and sensitive standoff detection of polymer films using bi-material cantilever-based photothermal spectroscopy. We demonstrate that the selectivity of the technique is sufficient to discriminate various polymers. We also demonstrate in situ, point detection of thin layers of polymers deposited on bi-material cantilevers using photothermal spectroscopy. Comparison of the standoff spectra with those obtained by point detection, FTIR, and FTIR-ATR show relative broadening of peaks. Exposure of polymers to UV radiation (365 nm) reveal that the spectral peaks do not change with exposure time, but results in peak broadening with an overall increase in the background cantilever response. The sensitivity of the technique can be further improved by optimizing the thermal sensitivity of the bi-material cantilever and by increasing the number of photons impinging on the cantilever.

Introduction of quorum sensing elements into bacterial bioreporter circuits enhances explosives' detection capabilities.

A possible solution for the standoff detection of buried landmines is based on the use of microbial bioreporters, genetically engineered to emit a remotely detectable optical signal in response to trace amounts of explosives’ signature chemicals, mostly 2,4‐dinitrotoluene (DNT). Previously developed DNT sensor strains were based on the fusion of a DNT‐inducible gene promoter to a reporting element, either a fluorescent protein gene or a bacterial bioluminescence gene cassette. In the present study, a different approach was used: the DNT‐inducible promoter activates, in Escherichia coli, the quorum‐sensing luxI and luxR genes of Aliivibrio fischeri. N‐Acyl homoserine lactone (AHL), synthesized by LuxI, combines with LuxR and activates the bioluminescence reporter genes. The resulting bioreporter displayed a dose‐dependent luminescent signal in the presence of DNT. Performance of the sensor strain was further enhanced by manipulation of the sensing element (combining the E. coli DNT‐inducible azoR and yqjF gene promoters), by replacing the luminescence gene cassette of Photorhabdus luminescens luxCDABE with A. fischeri luxCDABEG, and by introducing two mutations, eutE and ygdD, into the host strain. DNT detection sensitivity of the final bioreporter was over 340‐fold higher than the original construct.

High-Sensitivity Gas Detection with Air-Lasing-Assisted Coherent Raman Spectroscopy

Remote or standoff detection of greenhouse gases, air pollutants, and biological agents with innovative ultrafast laser technology attracts growing interests in recent years. Hybrid femtosecond/picosecond coherent Raman spectroscopy is considered as one of the most versatile techniques due to its great advantages in terms of detection sensitivity and chemical specificity. However, the simultaneous requirement for the femtosecond pump and the picosecond probe increases the complexity of optical system. Herein, we demonstrate that air lasing naturally created inside a filament can serve as an ideal light source to probe Raman coherence excited by the femtosecond pump, producing coherent Raman signal with molecular vibrational signatures. The combination of pulse self-compression effect and air lasing action during filamentation improves Raman excitation efficiency and greatly simplifies the experimental setup. The air-lasing-assisted Raman spectroscopy was applied to quantitatively detect greenhouse gases mixed in air, and it was found that the minimum detectable concentrations of CO 2 and SF 6 can reach 0.1% and 0.03%, respectively. The ingenious designs, especially the optimization of pump-seed delay and the choice of perpendicular polarization, ensure a high detection sensitivity and signal stability. Moreover, it is demonstrated that this method can be used for simultaneously measuring CO 2 and SF 6 gases and distinguishing 12 CO 2 and 13 CO 2 . The developed scheme provides a new route for high-sensitivity standoff detection and combustion diagnosis.

Stand-Off Detection of Ethanol Gas at Simulated Turbulence Channel Using a 1.7μm/1.5μm Dual-Band Switched Tm-Doped Fiber Laser Based on Differential Optical Absorption Spectroscopy

Stand-Off Detection of Ethanol Gas at Simulated Turbulence Channel Using a 1.7μm/1.5μm Dual-Band Switched Tm-Doped Fiber Laser Based on Differential Optical Absorption Spectroscopy

Standoff Detection of Backscattered Light Based on Tunable Diode Laser Absorption Spectroscopy

Standoff Detection of Backscattered Light Based on Tunable Diode Laser Absorption Spectroscopy