Continuous progress in science, technology, and clean environmental regulations for energy requires low-power chip scale devices in sensing applications. Conventional trace gas sensing in the midinfrared region is highly sensitive. However, it requires a complex optomechanical setup that may not be suitable for wide-area deployments. This paper shows the development of new waveguide materials for near and mid-infrared silicon photonics ranging from 0.7 to 10 mm. These include amorphous semiconductors like Chalcogenide Glasses (ChGs) of Germanium-Selenium-Silicon (Ge-Se-S) elements with different compositions. UV-Vis measurements show the optical energy gap between 1.6 eV with high Se concentration to 3.8 eV, where Se is replaced by S in the compositions. ATRFTIR measurements show a high transmission spectrum ranging from 4000 to 400 cm-1. We show the optical properties of such thin film materials in the broadband range of mid-infrared, suitable for fabricating waveguides and micro-resonator cavities for on-chip sensing applications.
Mid-infrared sensing in the broadband spectral region of 5 – 11 𝜇m is suitable for detecting and quantifying multiple trace species. However, the challenge in detection is precise discrimination due to the broad linewidth of molecular transitions of species like methane, nitrous oxide, and other volatile organic compounds. In addition, isotopic transitions are generally weaker, with significant overlap with the neighboring abundant molecular transitions. This paper shows broadband detection of multiple species using an external cavity laser operation in 6 to 11 𝜇m spectral region. We use a combination of Savitzy-Golay filtering and machine learning-based classification to discern weaker rotational vibrational transitions. The proposed scheme is used to denoise and discriminate molecular transition in mid-infrared absorption spectroscopy. We show that an optimized S-G framework can be used by choosing a selected frame length determined by the adaptive learning outcome with low loss. We show that an ML-based adaptive SV filter can effectively suppress mod-hop (or any other instrumental-related effects and drifts). This is achieved by appropriately training the absorption spectroscopy signals with a calibrated reference in a (gaussian or thermal) noisy environment.
Several environmental trace gas species and toxic chemicals or warfare simulants have fingerprint spectral signatures in the mid-infrared region of the spectrum. For instance, methane, nitrous oxide, and water vapor are critical greenhouse gases relevant for environmental sensing. In contrast, Sarin is one of the most lethal warfare agents that is a highly toxic synthetic chemical organophosphorus compound, which is of interest in defense and security sensing applications. Due to complex chemical structure and significant absorption and collision cross-section, the molecular linewidths of such chemicals can cover a broad range of spectral widths in the mid-infrared region. Detection of such molecules in the mid-infrared region is sensitive, which requires broadly tunable sources and appropriate spectral resolution in detection schemes. We show a rapid detection methodology of atmospheric bands of trace gases in the 7 μm to 8 μm region, which also coincides with the fingerprints region of several hazardous chemicals. Methane absorbs strongly in the wavelength range of 3 μm to 8 μm, and nitrous oxide has absorption from 5 μm to 8 μm. We use molecular rotational-vibrational transitions of carbon and nitrogen trace species to demonstrate well-resolved peaks in the spectral region of 6.88 μm to 7.6 μm for detection. The detection was performed by a continuous wave multiplexed quantum cascade laser source capable of an ultra-wide tuning range from 6.88 μm to 11.05 μm.
KEYWORDS: Absorption, Mid-IR, Methane, Sensors, Spectroscopy, Quantum cascade lasers, Chemical weapons, Signal detection, Nitrous oxide, Biological and chemical sensing
Several chemical warfare chemicals have fingerprint spectral signatures in the mid-infrared region of the spectrum. For instance, Sarin is one of the most lethal warfare agents that is a highly toxic synthetic chemical organophos phorus compound. Due to complex chemical structure and large absorption and collision cross-section, the molecular linewidths of such chemicals can cover a broad range of spectral width. Detection of such molecules in the mid-infrared region is sensitive which requires broadly tunable sources and detection methods. We show a rapid detection methodology of such chemicals using proxy methane and nitrous oxide atmospheric bands in the 7 µm to 8 µm region which also have fingerprints region of several hazardous chemicals. Methane absorbs strongly in the wavelength range of 3 µm to 8 µm, nitrous oxide has absorption from 5 µm to 8 µm. As the large wavelength range that they have covered, we use molecular rotational-vibrational transitions of CH4
Mid-infrared laser-based sensors are commonly used to detect and quantify many chemical species for environmental, industrial, defense, and security applications. Data-driven approaches, including machine learning and information theory, can be applied to photonics-based sensors to quantify drifts and improve precision. These methods are used to classify signals from rotational-vibrational absorption spectra of Nitrous oxide (N2O) in the 4.3 m region of the spectrum. The detection method utilizes the structural complexity of wavelength modulation spectroscopy signals and information encoded in the spectra. We create our basic training models by simulating temperature, pressure, density fluctuations effects, and molecular transition line broadening of a Voigt lineshape profile. Instrument (laser and detector) noise optical fringing effects can be incorporated in the models. The paper shows that signal variations due to Trace gas density fluctuations and molecular collision dynamics can be discriminated from instrument drifts. The proposed methodology can be used to accurately predict, detect, and evaluate short-term and long-term drifts in sensing systems which can be integrated with the conventional Allan variance methods. We demonstrate this methodology by high-precision sensing of rotational-vibrational transitions of Nitrous oxide and carbon monoxide using an interband cascade laser operating at a 4.3 m spectral region.
It is estimated that about 60 percent of total global methane emissions are thought to be from anthropogenic sources and about 40 percent from natural sources. Anthropogenic sources encompass a wide range of human activities, including food and energy production and waste disposal. Livestock (through fermentation processes in their digestive system that generates methane and manure management), rice cultivation, landfills, and sewage account for 55-57 percent of global anthropogenic emissions. This paper investigates methane emissions from agricultural land-use and livestock (e.g., poultry and cattle) farming practices in Delaware. Laser-based point sensing can provide a higher spatial and temporal resolution that can complement satellite observations to identify individual sources and broader geographical areas. A detailed understanding of their sources and sinks is necessary to model emissions profile accurately. This paper shows field measurements of methane using mid-IR laser-based sensors and validation with satellite data. We conducted our field deployment locally in the Delaware, Kent, and Sussex county regions focusing on high methane emitting areas. We used the TROPOspheric Monitoring Instrument (TROPOMI) methane satellite data to get a unified emissions map of methane production in Delaware by comparing our ground-based measurements with the satellite data. Furthermore, we examined the satellite data for long-term methane emissions trends to quantify 2020 average methane emissions.
KEYWORDS: Chemical weapons, Spectroscopy, Mid-IR, Biological and chemical sensing, Absorption, Sensing systems, Standards development, Doppler effect, Databases, Data modeling
We show mid-infrared detection of chemical warfare simulants using rapidly tuned and broadband mid-infrared laser spectroscopy suite of chemical species with disparate absorption cross-sections. Sarin gas is one of the most lethal chemical weapons with significant impacts at trace concentrations as low as 64 ppbv within a very short exposure time. In this research, we develop theoretical models to design a mid-infrared (8-11 μm) detection system for high-precision sensing of trace chemical-warfare agents. The models are based on absorption cross-sections and theoretical estimation of chemicals using direct-absorption spectroscopy. Due to the extremely hazardous nature of Sarin, Triethyl Phosphate (TEP), which has a very similar structure to Sarin, was chosen as a proxy chemical. TEP is a standard simulant for organophosphate nerve agents like Sarin. We use a combination of direct absorption spectroscopy and wavelength modulation spectroscopy to resolve and detect line-broadened transitions of TEP. Thus, by analyzing the regression slope of the theoretical absorption cross-section and experimental absorbance, TEP concentration can be estimated in a congested molecular spectrum. The absorption cross-section was modeled using Doppler and Voigt profiles.
techniques to measure changes of the translational diffusion times and the rotational diffusion times of two nanoprobes, Alexa488 and FITC-Ficoll, dispersed in aqueous Ficoll solutions at room temperature. Analysis of the data indicated that the lifetimes of the nanoprobes appeared to be unaltered by the Ficoll solutions. In contrast, the FCS functions of each nanoprobe, which demonstrated slowing down of diffusion due to Ficoll, were adequately fitted with the expression of a freely diffusing nanoparticle. Similarly, the FA data indicated that the rotational diffusion of both nanoprobes was slowed down. The changes of the diffusion times and the rotational times of both nanoprobes could not be accounted for, however, by the corresponding changes of the viscosity of the solutions. Instead, we applied the entropic model proposed by de-Gennes and his collaborators, and fitted each set of diffusion data with a stretched exponential [exp(- αcn)] with n being related to the quality of the solvent. We determined n-values close to the value one for both nanoprobes and for both diffusions, suggesting a theta-like behavior of the solutions. However, the -values for the translation of both nanoprobes were larger than the corresponding ones derived for their rotation, indicating dissimilar local entropic effects. Together with calculations, the present results confirmed the slowing down of the diffusion processes of the nanoprobes due to crowding and, more significantly, provided through the nanoprobes insight into entangled but flexible polymeric structures of the concentrated solutions.
We report a compact, portable, low power tunable diode laser based sensor for a fast, non-intrusive measurement of
temperature on airborne-based vehicles. The proposed sensor design avoids common problems in existing sensors such
as adiabatic compression of the ambient airstream, thermal inertia of the sensing element, and impinging cloud particles.
These effects are quite common in the conventional temperature sensors used in most aerial vehicles for ambient
temperature measurements. The molecular oxygen transitions are measured using a 765 nm wavelength range vertical
cavity surface emitting laser in the spectral region of two closely spaced oxygen transitions, centered at 13069.95 cm-1and 13068.07 cm-1 respectively, according to HITRAN database.
Another advantage of the proposed sensor design is that it can simultaneously detect additional trace gas species along
with in-situ temperature measurements. For example, in this design we detect carbon dioxide concentration using a 2000
nm wavelength laser. The two laser beams are co-aligned and coupled into a single 20 cm multipass cell. The absorption
signal (from both carbon-dioxide and oxygen) was detected simultaneously on a 2 micron photodetector. Second
harmonic (Nf, N=2) detection, using wavelength modulation spectroscopy was employed to enhance the sensitivity of
measurements. The sensor can readily be miniaturized and consumes less than 2 W of power, ideal for use of unmanned
aerial systems and other airborne platforms.
A basic wireless laser spectroscopic sensor network for monitoring of trace-gases will be presented. The prototype lowpower
sensor nodes targeting carbon dioxide are based on tunable diode laser absorption spectroscopy and operate using
a 2 μm VCSEL and a 3.5 m Herriott multi-pass cell. The sensor system, which employs real-time wireless
communications, is controlled by custom electronics and can be operated autonomously. The sensor core electronics
performs molecular concentration measurements using wavelength modulation spectroscopy with an active laser
frequency locking to the target transition. The operating sensor node consumes approximately 300 mW of electrical
power and can work autonomously for up to 100 hours when powered by a 10.5 Ah Lithium-ion polymer battery.
Environmentally controlled long term (12 hours) stability tests show sensor node detection limit of ~0.286 ppm with 1
second integration time and the ultimate minimum detectable fractional absorption of 1.5x10-6 is obtained after 3500
seconds averaging time. The sensor node performance results and preliminary tests in a basic network configuration are
discussed.
We describe a non-intrusive, open-path, fast-response compact sensor for simultaneous measurements of nitrous-oxide (N2O) and carbon-monoxide (CO) primarily designed for UAV applications. N2O is the third most important anthropogenic greenhouse gas, but the spatial and temporal distributions of N2O emissions are poorly quantified. On the other hand, CO is an important tracer to distinguish between fossil fuel and biogenic sources. We use a 4.5 micron thermoelectrically-cooled, distributed feedback, continuous wave quantum cascade laser as a mid-infrared radiation source to scan CO and N2O transitions centered at 4538.9 nm and 4539.8 nm respectively. Detection was achieved by a thermo-electrically (TE) cooled 5 micron Indium-Phosphide (InSb) infrared detector.
For the first time in this application, a compact cylindrical cell with a pattern configuration to minimize the sensor size with a pathlength of 10 meters (2.54 cm radius mirrors, 25 cm basepath). Wavelength modulation spectroscopy was employed to achieve high sensitivity detection. The detection limit of 10-5 fractional absorbance was achieved at a 10 sec. averaging time. This is equivalent to less than 1 ppbv of N2O and 2 ppbv of CO out of 320 ppbv and 200 ppbv ambient levels respectively. In summary we report a cryogen-free, consumable-free sensor that can operate with 10s W of electrical power and packaged in a small shoe-box size which is ideal for UAV or airborne applications.
We present a novel approach to quantifying and optimizing the amount of information available in radiation
patterns. The technique presented and the results obtained are applicable on a broad scale, including those
in infrared, nanophotonics and other non-intrusive sensing techniques. We investigate the amount of
information lost due to limitations of the detector system. The method, which is based on information
principles developed by Shannon, expands on the many conventional approaches to optimizing performance
of sensors. The fundamental question of how many bits of information can be extracted by any sensor is
addressed. We focus on answering this question for the measurement of the radiation pattern from an
antenna array. The effects of a finite detector size, on the structure of the radiation pattern, are presented,
and we quantify the relationship between loss of structure and loss of information. The work presented may
be extended to a wide range of applications, including remote sensing. While the information content of
antenna array radiation patterns is based on the spatial distribution of photons, the method presented is
general and may be applied to a variety of distributions, such as lineshape functions, important in
spectroscopy, where the information is contained in the frequency distribution of photons.
KEYWORDS: Modulation, Signal to noise ratio, Signal detection, Absorption, Spectroscopy, Interference (communication), Information theory, Sensors, Molecules, Amplifiers
Shannon's information theory is applied to Wavelength Modulation Spectroscopy (WMS) providing quantitative figures
of merit such as the measurement precision and a prediction of the optimal detection harmonic order to be used. The
amount of information, in bits, that can be extracted in any WMS measurement is calculated. The theory is applied to
experimental results we have obtained in WMS experiments in congested spectra with overlapping lines that have highly
disparate absorption cross-sections. A key result is that the complexity of signal structure can play a much more
important role than the conventional signal to noise ratio. We show that there are some parts (where it exhibits turning
points and zero crossings) of the structurally-rich WMS signal that play a larger role in conveying information about the
measurement than other parts of the signal. Practical applications follow immediately. We also show that, for a particular
noise limitation of the apparatus, there is a finite amount of information that can be transmitted (to the detection
equipment) by the probe laser as it samples the probed species. The apparatus is analogous to a Shannon's information
channel. Application of the theory developed to our experimental absorption measurements in the Oxygen A-band shows
why high detection harmonic orders (up to the 7th or 8th) yield the highest resolution. This is in contrast to statements in
the literature, based on conventional signal to noise ratio considerations, that the best results are to be expected with
second harmonic detection.
Wavelength Modulation Spectroscopy (WMS) has been extensively used as a tool for sensitive detection through precise
measurements of the absorption lineshape function of gaseous species. In this paper pathlength saturation in wavelength
modulation spectroscopy is studied. New effects are found when one takes advantage of demodulation at higher
harmonics of the modulation frequency. We show here that modulation spectroscopy is a much more sensitive probe of
these effects. In particular, when synchronous detection is performed at higher harmonics of the modulation frequency,
even very small pathlength saturation effects become clearly visible. The method discussed allows one to probe
lineshape profiles by observing how the signal profile varies with absorption pathlength. In particular, the signal around
line center displays effects of saturation that are characteristic of the lineshape. This method is powerful because,
ultimately, all the information about any measurement is contained in the lineshape profile. Since different lineshape
profiles exhibit different saturation behavior, higher harmonic detection provides a new method to perform sensitive
detection. We have shown effects of saturation on the central lobes of harmonic signals. We also show that there are
definite relationships between the variation of the individual side lobes as well as their relative magnitudes that yield
further information about the lineshape function.
Absorption and emission spectroscopy measurements have been extensively and effectively utilized in the probing and monitoring of gases. As in any real experimental situation, the measurement of absorption or emission profiles results in a loss of information due to practical limitations, such as a finite precision of the detector. Also, it is now accepted that there is a relationship between information loss and thermodynamics. Hence, the question "How much information, in bits, is lost when making a practical spectroscopic measurement and how much heat is generated in the process?" arises. Shannon's information theoretical concepts are used to quantify the information lost due to the finite precision in wavelength measurement, of a detector used in a spectroscopic measurement. The heat generated in such a detector is also studied. The relationship between the heat generated and information lost as a result of the finite precision of a practical detector is investigated.
Wavelength Modulation Spectroscopy (WMS) utilizes low frequency modulation of the probe, followed by synchronous detection at the modulation frequency or at one of the harmonics. WMS provides a particularly useful tool for resolving highly disparate overlapping lines, because the high-order derivative-like structure of higher harmonics results in an enhancement of features, not possible with conventional ("direct") absorption spectroscopy. An important question, not yet systematically addressed in the literature is, "Given that in any measurement seeking to resolve overlapping spectra there is always a minimum harmonic detection order, how does one determine this order?" To address this issue, a Rayleigh-like criterion is defined and used to determine when two lines are barely resolved. Shannon's information theoretical principles are then used to calculate the information obtained when overlapping spectra are barely resolved at a particular harmonic. The results obtained allow one to predict the minimal harmonic detection order that should be used to resolve overlapping lines.
An information theoretic approach to maximizing the efficacy of optical sensing devices is presented. The principles used and the results obtained are applicable on a wide range of scales, including those in nano photonics sensing and detection. A key factor which is investigated is the aspect of extraction of the maximum amount of information in any given environment. The method used, which is based on information principles developed by Shannon, augments the many conventional approaches to optimizing performance of sensors. The fundamental issue of how many bits of information can be extracted by a sensor is addressed. The radiation pattern from a radiating or receiving sensor-array provides a spatial probability density function, which carries all the information about the system. Various such arrays are treated and the significance of the structure of the radiation pattern is examined. The technique is extended to the well-known concept of the lineshape profile of radiative atomic and molecular transitions, which is a probability density function in the frequency domain. Extensions of this work have applications in nanotechnology.
A quantitative analysis of Wavelength Modulation Spectroscopy (WMS) signals at various harmonic detection orders for use in precision, non-intrusive measurements is performed. A theoretical analysis of fitting of WMS signals is developed. The detailed structures of WMS signals at various harmonic detection orders are studied and analyzed, using statistical measures. It is shown that the variance of errors increases with mesmatches in linewidth in a particular (Nth order) harmonic signal. However, this rate of increase in variance is characteristic of the harmonic detection order used, thereby demonstrating the advantage in measurements at different harmonics. It is shown that for a constant error in estimation of linewidth of a profile, the variance of errors can be higher for higher detection orders. Therefore, mismatches in fits are more prominent at some optimal detection order. The methods developed can be used to examine subtle effects such as Dicke narrowing in certain molecular spectra. These small perturbations of lineshape profile reveal details of the molecular collision kinetics, and hence yield precise measurements that are difficult to achieve by other techniques.
KEYWORDS: Modulation, Spectroscopy, Absorption, Distortion, Signal detection, Molecules, Sensors, Information theory, Frequency modulation, Thermodynamics
Modulation Spectroscopy is a sensitive, convenient, versatile and cost-effective method for monitoring gaseous species and for obtaining quantitative information about molecular collision dynamics through precise measurements of the absorption lineshape function. Even slight perturbations in the lineprofile can be measured precisely, and because these perturbations are directly linked to changes in physical conditions of the sampled target, one obtains very precise non-intrusive measurements of these parameters. Over the last few years, we have extended this technique to the regime of higher harmonic detection and demonstrated that, in many cases, one obtains a higher precision by using an optimal harmonic detection order higher than the commonly used second harmonic. Experimental and theoretical results have been presented. In this paper we use the principles of Information Theory developed by Shannon to describe the information content in modulation spectroscopic signals. A simple argument is used to show that information that may otherwise be lost because of distortion can be recovered by derivative like techniques, such as those used in low frequency modulation spectroscopy. Experimental results obtained for the resolution of overlapping lines of disparate strength are discussed.
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