We present the development of an eye-safe, invisible, stand-off technique designed for the detection of target chemicals (such as explosives) in a single “snapshot” frame. Broadband Fabry-Perot quantum cascade lasers (FP-QCLs) in the wavelength range of 7 to 12 microns, are directed to a target to interrogate its spectral features. The “backscatter” return signals from target chemicals are spectrally discriminated by an LWIR spatial heterodyne spectrometer (SHS). The SHS offers high throughput and full spectral coverage in each single frame from an IR imaging array. This presentation will cover the performance and optimization of FP-QCLs for this broadband spectroscopic application. We will also discuss the operation and processing of SHS images to extract spectral information. Finally, we will present results of measurements using specific analytes to demonstrate the application of the method to stand-off detection of targets such as explosives and other chemical threats.
We are using active infrared (IR) spectroscopic imaging to detect trace explosives on surfaces at proximal distances up to a few meters. The technology comprises an IR quantum cascade laser (QCL) for illumination and an IR focal plane array (FPA) sensor to collect signal backscattered from surfaces of interest. By sweeping the wavelength of the QCL while collecting image frames with the FPA, we generate an active hyperspectral image (HSI) cube. The HSI cube contains both spatial and spectral information, where the spectrum of a pixel, or region of interest within the image, can be extracted and compared against a known threat library. These cubes are fed into a convolutional neural network (CNN) trained on purely synthetic data to identify chemicals in the field of view. The CNN identifies chemicals by their IR signature and identifies their location within the image.
In this work, we are developing a custom-built broadband laser source in the Mid-LWIR range by combining several high power FP-QCLs for a single snap shot application. To minimize temperature variation or reduce the thermal load while the FP-QCL emits at high currents, the FP-QCL was operated in pulsed mode with varying diode temperatures and applied currents. The spectral outputs in pulsed mode were temporally resolved using a step scan FTIR spectrometer. FP mode peaks typically broaden by driving higher currents. FP mode hopping, emerging, and disappearing were observed during the laser pulse length (3000 ns) at different applied current values. The ideal spectral characteristics for a single snap shot application are discussed, with respect to a broad spectral bandwidth, a flat-top power profile, and high spectral power density.
We are developing a cart-based mobile system for the detection of trace explosives on surfaces by active infrared (IR) backscatter hyperspectral imaging (HSI). We refer to this technology as Infrared Backscatter Imaging Spectroscopy (IBIS). A wavelength tunable multi-chip infrared quantum cascade laser (QCL) is used to interrogate a surface while an MCT focal plane array (FPA) collects backscattered images. The QCL tunes across the full wavelength range from 6 – 11 μm. Full 128 X 128 pixel frames from the FPA are collected at up to 1610 frames per second and comprise a hyperspectral image (HSI) cube. The HSI cube is processed and the extracted spectral information is fed into an algorithm to detect and identify traces of explosives. The algorithm utilizes a convolutional neural network (CNN) and has been pre-trained on synthetic diffuse reflectance spectra. In this manuscript, we present backscatter data and hyperspectral image mapping from a car panel substrate deposited with traces of the explosive RDX. We have used a mask to restrict the RDX analyte deposition to small 4 mm diameter areas. The results presented here were measured at 1 meter standoff.
The use of rapid scanning quantum cascade lasers in the detection of trace amounts of explosive materials is presented. This technique, infrared backscatter imaging spectroscopy (IBIS), utilizes an array of quick tuning infrared quantum cascade lasers (QCLs) to illuminate targets with mid-IR light, 6 – 11 μm in wavelength, to perform measurements in less than one second. The backscattered signal from targets is collected with a liquid nitrogen cooled MCT focal plane array. This information is stored in a hyperspectral image cube which is then run through a detection algorithm which has been trained on synthetic reflectance spectra of analytes of interest. We discuss the experimental parameters used with the QCLs and the focal plane array to generate and collect the infrared backscatter signal. The performance of the fast scanning QCL is presented in detail along with the experimental protocol used to collect high quality data from targets at proximal standoff distance. Camera frames are collected as the laser wavelength is swept and then are binned and assigned discrete wavelength steps. Spectra are extracted from the binned frames on a pixel by pixel basis. When run at full frame imaging, this results in over 16,000 individual spectra.
The results from infrared backscatter imaging spectroscopy on a mobile platform for stand-off detection of trace amounts of explosive materials on relevant substrates are presented. This technique utilizes an array of tunable infrared quantum cascade lasers to illuminate targets. The spectral range of the QCL system spans from 6 - 11 μm, which enables excitation of a wide variety of absorption bands present in analytes of interest. Targets are prepared by sieving particles through a 20 μm mesh onto substrates to simulate relevant qualities (particle size, fill factor, and mass loading) expected of real world targets. The backscatter signal from targets is collected with an IR focal plane array. This information is stored in a hyperspectral image cube to allow for post processing in a detection algorithm. We demonstrate the selectivity and sensitivity of the discussed technique down to the nanogram level for RDX and PETN on glass. Spectra are generated by extracting the signal from small regions of interest to simulate targets with miniscule coverage areas. Preliminary comparison of backscatter data with simulated data from a model that incorporates particle size, mass loading, and substrate response show good agreement. Confusant agents, such as sand, are introduced to the targets loaded with analyte to illustrate the selectivity of this technique. The results of these studies are presented, along with future improvements to the technique.
We are developing a cart-mounted platform for chemical threat detection and identification based on active LWIR imaging spectroscopy. Infrared backscatter imaging spectroscopy (IBIS) leverages IR quantum cascade lasers, tuned through signature absorption bands (6 - 11 μm) in the analytes while illuminating a surface area of interest. An IR focal plane array captures the time-dependent backscattering surface response. The image stream forms a hyperspectral image cube composed of spatial, spectral and temporal dimensions as feature vectors for detection and identification. Our current emphasis is on rapid screening. This manuscript also describes methods for simulating IBIS data and for training detection algorithms based on convolutional neural networks (CNN). We have previously demonstrated standoff trace detection at several meters indoors and in field tests, while operating the lasers below the eye-safe intensity limit (100 mW/cm2). Sensitivity to explosive traces as small as a single grain (~1 ng) has been demonstrated. Analytes tested include RDX, PETN, TNT, ammonium nitrate, caffeine and perchlorates on relevant glass, plastic, metal, and painted substrates.
We pursue the development of an eye-safe stand-off technique suitable for the detection of trace explosives. As the active illumination sources, tunable quantum cascade lasers (QCLs) are employed in Mid-LWIR (long-wave infrared) in the range of 6 to 11 μm, which contains many spectral features from analytes of interest. Any fluctuation of the laser beam direction and/or beam profile is amplified at the sample position, which would lead to diminished performance of the detection technique, both in sensitivity and selectivity. Several beam stabilization approaches were conducted to overcome this challenge: 1) Using a KBr/diamond pellet as a diffuser in combination with a multimode fiber 2) Feedback stabilization of quantum cascade laser beam steering. The purpose of the first method is to make a temporally and spatially incoherent laser beam source through the multimode fiber and KBr/diamond pellet. The second approach is to stabilize the beam position by using an active feedback loop. We have demonstrated that beam wander and speckle noise were successfully suppressed by these approaches. Independently, we have developed a custom-built broadband laser source in the Mid-LWIR range consisting of several high power Fabry Perot (FP)-QCLs. The FP-QCLs were operated in both CW and pulsed modes at different diode temperatures, and the emission spectra were collected by a FTIR. For our future work, the output beams will be collimated to spectrally combine multi-QCLs and aligned toward the same target. Also, a spatial heterodyne spectrometer (SHS) will be applied to discriminate spectral and spatial information from a single snapshot.
KEYWORDS: Perovskite, Solar cells, Near field scanning optical microscopy, Lead, Microscopy, Atomic force microscopy, Photovoltaics, Scanning electron microscopy, Crystals, Silver
Photocurrent generation of methylammonium lead iodide (CH3NH3PbI3) hybrid perovskite solar cells is observed at the nanoscale using near-field scanning photocurrent microscopy (NSPM). We examine how the spatial map of photocurrent at individual grains or grain boundaries is affected either by sample post-annealing temperature or by extended light illumination. For NSPM measurements, we use a tapered fiber with an output opening of 200 nm in the Cr/Au cladded metal coating attached to a tuning fork-based atomic force microscopy (AFM) probe. Increased photocurrent is observed at grain boundaries of perovskite solar cells annealed at moderate temperature (100 °C); however, the opposite spatial pattern (i.e., increased photocurrent generation at grain interiors) is observed in samples annealed at higher temperature (130 °C). Combining NSPM results with other macro-/microscale characterization techniques including electron microscopy, x-ray diffraction, and other electrical property measurements, we suggest that such spatial patterns are caused by material inhomogeneity, dynamics of lead iodide segregation, and defect passivation. Finally, we discuss the degradation mechanism of perovskite solar cells under extended light illumination, which is related to further segregation of lead iodide.
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