Highly sensitive and selective laser-based BTEX sensor for occupational and environmental monitoring.

A mid-infrared laser-based sensor is designed and demonstrated for trace detection of benzene, toluene, ethylbenzene, and xylene isomers at ambient conditions. The sensor is based on a distributed feedback inter-band cascade laser emitting near 3.29 µm and an off-axis cavity-enhanced absorption spectroscopy configuration with an optical gain of 2800. Wavelength tuning and a deep neural network (DNN) model were employed to enable simultaneous and selective BTEX measurements. The sensor performance was demonstrated by measuring BTEX mole fractions in various mixtures. At an integration time of 10 s, minimum detection limits of 11.4, 9.7, 9.1, 10, 15.6, and 12.9 ppb were achieved for benzene, toluene, ethylbenzene, m-xylene, o-xylene, and p-xylene, respectively. The sensor can be used to detect tiny BTEX leaks in petrochemical facilities and to monitor air quality in residential and industrial areas for workplace pollution.

Fast rate dual-comb spectrometer in the water-transparent 7.5-11.5†µm region.

We introduce a dual-comb spectrometer based on erbium fiber oscillators at 250 MHz that operates in the 7.5-11.5 µm spectral range over optical bandwidths up to 9 THz with a multi-kHz acquisition rate. Over an observation bandwidth of 0.8 THz, the signal-to-noise ratio per spectral point reaches 168 Hz0.5 at an acquisition rate of 26 kHz, which allows the investigation of transient processes in the gas phase at high temporal resolution. The system also represents an attractive solution for multi-species atmospheric gas detection in open paths due to the water transparency of the spectral window, the use of thermo-electrically cooled detectors, and the out-of-loop phase correction of the interferograms.

Skeletal CH3OH/NOx Kinetic Model for Simulating Spark-Ignition and Turbulent Jet Ignition Engines.

Methanol is a promising renewable fuel for achieving a better engine combustion efficiency and lower exhaust emissions. Under exhaust gas recirculation conditions, trace amounts of nitrogen oxides have been shown to participate in fuel oxidation and impact the ignition characteristics significantly. Despite numerous studies that analyzed the methanol/NOx interaction, no reliable skeletal kinetic mechanism is available for computational fluid dynamics (CFD) modeling. This work focuses on developing a skeletal CH3OH/NOx kinetic model consisting of 25 species and 55 irreversible and 27 reversible reactions, used for full-cycle engine combustion simulations. New experiments of methanol with the presence of 200 ppmv NO/NO2 were conducted in a rapid compression machine (RCM) at engine-relevant conditions (20-30 bar, 850-950 K). Experimental results indicate notable enhancement effects of the presence of NO/NO2 on methanol ignition under the conditions tested, which highlights the importance of including the CH3OH/NOx interactions in predicting combustion performance. The proposed skeletal mechanism was validated against the literature and new methanol and methanol/NOx experiments over a wide range of operating conditions. Furthermore, the skeletal mechanism was applied in three-dimensional (3D) CFD full-cycle simulations of spark-ignition (SI) and turbulent jet ignition (TJI) engine combustion using methanol. Simulation results demonstrate good agreement with experimental measurements of pressure traces and engine metrics, proving that the proposed skeletal mechanism is suitable and sufficient for CFD simulations.

Mixtures Recomposition by Neural Nets: A Multidisciplinary Overview.

Artificial Neural Networks (ANNs) are transforming how we understand chemical mixtures, providing an expressive view of the chemical space and multiscale processes. Their hybridization with physical knowledge can bridge the gap between predictivity and understanding of the underlying processes. This overview explores recent progress in ANNs, particularly their potential in the 'recomposition' of chemical mixtures. Graph-based representations reveal patterns among mixture components, and deep learning models excel in capturing complexity and symmetries when compared to traditional Quantitative Structure-Property Relationship models. Key components, such as Hamiltonian networks and convolution operations, play a central role in representing multiscale mixtures. The integration of ANNs with Chemical Reaction Networks and Physics-Informed Neural Networks for inverse chemical kinetic problems is also examined. The combination of sensors with ANNs shows promise in optical and biomimetic applications. A common ground is identified in the context of statistical physics, where ANN-based methods iteratively adapt their models by blending their initial states with training data. The concept of mixture recomposition unveils a reciprocal inspiration between ANNs and reactive mixtures, highlighting learning behaviors influenced by the training environment.

Shock Tube/Laser Absorption Measurements of the High-Temperature Spectra and Decomposition of Propyl Ethers.

This work presents measurements of temperature-dependent absorption spectra and thermal decomposition rates of propyl ethers, specifically di-n-propyl ether (DnPE) and diisopropyl ether (DiPE), which are two renewable fuel candidates. We employed a broadband rapid-tuning MIRcat-QT laser, operating in the scan/fixed-wavelength mode in combination with a shock tube. Spectral measurements were performed over the wavelength range of 8.4-11 µm (909.1-1190.5 cm-1), covering the strongest infrared absorption bands of the studied ethers, at temperatures of 559-853 K and pressure near 1 bar. These high-temperature spectra help in selecting the optimum wavelength for sensitive and selective measurements of the target ethers. Based on the criteria of high sensitivity, minimum interference, and insensitivity to temperature and pressure variations, we selected a wavelength of 1121.82 cm-1 for high-temperature diagnostics of DnPE and DiPE. Absorption cross sections at the selected wavelength of 1121.82 cm-1 were measured over 550-1500 K, and pressures ranging from 0.3-1.4 bar. This diagnostic was then applied to study the high-temperature pyrolysis of these ethers by measuring their time histories behind the reflected shock waves. Our experimentally measured overall decomposition rate coefficients for DnPE and DiPE are given as (unit of s-1) kDnPE = 1.25 × 1027 × T-3.483 × exp(-37620 K/T) and kDiPE = 5.26 × 1023 × T-2.857 × exp(-32360 K/T).

High-resolution molecular fingerprinting in the 11.6-15†µm range by a quasi-CW difference-frequency-generation laser source.

We report an approach for high-resolution spectroscopy using a widely tunable laser emitting in the molecular fingerprint region. The laser is based on difference-frequency generation (DFG) in a nonlinear orientation-patterned GaAs crystal. The signal laser, a CO2 gas laser, is operated in a kHz-pulsed mode while the pump laser, an external-cavity quantum cascade laser, is finely mode-hop-free tuned. The idler radiation covers a spectral range of ∼11.6-15 µm with a laser linewidth of ∼ 2.3 MHz. We showcase the versatility and the potential for molecular fingerprinting of the developed DFG laser source by resolving the absorption features of a mixture of several species in the long-wavelength mid-infrared. Furthermore, exploiting the wide tunability and resolution of the spectrometer, we resolve the broadband absorption spectrum of ethylene (C2H4) over ∼13-14.2 µm and quantify the self-broadening coefficients of some selected spectral lines.

Laser-based sensing in the long-wavelength mid-infrared: chemical kinetics and environmental monitoring applications.

We present chemical kinetics and environmental monitoring applications in the long-wavelength mid-infrared (LW-MIR) region using a new diagnostic that exploits a widely tunable light source emitting in the LW-MIR. The custom-designed laser source is based on a difference-frequency generation (DFG) process in a nonlinear orientation-patterned GaAs crystal. The pump laser, an external-cavity quantum cascade laser, is tuned in a continuous-wave (cw) mode, while the signal laser, a C O 2 gas laser, is operated in a pulsed mode with a kilohertz repetition rate. The idler wavelength can be tuned between 11.58 (863.56c m -1) and 15.00 µm (666.67c m -1) in a quasi-cw manner. We discuss the unique prospective applications offered by probing the LW-MIR region for chemical kinetics and environment-monitoring applications. We showcase the potential of the DFG laser source by some representative applications.

A selective laser-based sensor for fugitive methane emissions.

A mid-infrared laser-based sensor is reported for the quantification of fugitive methane emissions. The sensor is based on a distributed feedback inter-band cascade laser operating near 3.3 µm. Wavelength tuning with cepstral analysis is employed to isolate methane absorbance from (1) fluctuations in the baseline laser intensity, and (2) interfering species. Cepstral analysis creates a modified form of the time-domain molecular free-induction-decay (m-FID) signal to temporally separate optical and molecular responses. The developed sensor is insensitive to baseline laser intensity imperfections and spectral interference from other species. Accurate measurements of methane in the presence of a representative interfering species, benzene, are performed by careful selection of the scan index (ratio of laser tuning range to spectral linewidth) and initial and final time of m-FID signal fitting. The minimum detection limit of the sensor is ~ 110 ppm which can be enhanced with an optical cavity. The proposed sensing strategy can be utilized to measure methane leaks in harsh environments and in the presence of interfering species in environment-monitoring applications.

Free convective trickling over a porous medium of fractional nanofluid with MHD and heat source/sink.

Nanofluids are considered as smart fluids that can improve heat and mass transfer and have numerous applications in industry and engineering fields such as electronics, manufacturing, and biomedicine. For this reason, blood-based nanofluids with carbon nanotubes (CNTs) as nanoparticles in the presence of a magnetic field are discussed. The nanofluid traverses the porous medium. The nanofluids move on a vertical plate that can be moved. The free convection heat transfer mode is considered when the heat source and heat fluxes are constant. Convective flows are often used in engineering processes, especially in heat removal, such as geothermal and petroleum extraction, building construction, and so on. Heat transfer is used in chemical processing, power generation, automobile manufacturing, air conditioning, refrigeration, and computer technology, among others. Heat transfer fluids such as water, methanol, air and glycerine are used as heat exchange media because these fluids have low thermal conductivity compared to other metals. We have studied the effects of MHD on the heat and velocity of nanofluids keeping efficiency in mind. Laplace transform is used to solve the mathematical model. The velocity and temperature profiles of MHD flow with free convection of nanofluids were described using Nusselt number and skin friction coefficient. An accurate solution is obtained for both the velocity and temperature profiles. The graph shows the effects of the different parameters on the velocity and temperature profiles. The temperature profile improved with increasing estimates of the fraction parameter and the volume friction parameter. The velocity of the nanofluid is also a de-escalating function with the increasing values of the magnetic parameter and the porosity parameter. The thickness of the thermal boundary layer decreases with increasing values of the fractional parameter.

Deep neural networks for simultaneous BTEX sensing at high temperatures.

In the study of chemical reactions, it is desirable to have a diagnostic strategy that can detect multiple species simultaneously with high sensitivity, selectivity, and fast time response. Laser-based selective detection of benzene, toluene, ethylbenzene, and xylenes (BTEX) has been challenging due to the similarly broad absorbance spectra of these species. Here, a mid-infrared laser sensor is presented for selective and simultaneous BTEX detection in high-temperature shock tube experiments using deep neural networks (DNN). A shock tube was coupled with a non-intrusive mid-infrared laser source, scanned over 3038.6-3039.8 cm-1, and an off-axis cavity enhanced absorption spectroscopy (OA-CEAS) setup of ∼ 100 gain to enable trace detection. Absorption cross-sections of BTEX species were measured at temperatures of 1000-1250 K and pressures near 1 atm. A DNN model with five hidden layers of 256, 128, 64, 32, and 16 nodes was implemented to split the composite measured spectra into the contributing spectra of each species. Several BTEX mixtures with varying mole fractions (0-600 ppm) of each species were prepared manometrically and shock-heated to 1000-1250 K and 1 atm, and the composite measured absorbance were split into contributions from each BTEX species using the developed DNN model, and thus make selective determinations of BTEX species. Predicted and manometric mole fractions were in good agreement with an absolute relative error of ∼ 11%. We obtained a minimum detection limit of 0.73-1.38 ppm of the target species at 1180 K. To the best of our knowledge, this work reports the first successful implementation of multispecies detection with a single narrow wavelength-tuning laser in a shock tube with laser absorption spectroscopy.

Transfer Learning Approach to Multitarget Temperature-Dependent Reaction Rate Prediction.

Accurate prediction of temperature-dependent reaction rate constants of organic compounds is of great importance to both atmospheric chemistry and combustion science. Extensive work has been done on developing automated mechanism generation systems but the lack of quality reaction rate data remains a huge bottleneck in the application of highly detailed mechanisms. Machine learning prediction models have been recently adopted to alleviate the data gap in thermochemistry and have great potential to do the same for kinetic data with the recent release of quality reaction rate data compilations. The ultimate goal is to formulate easily accessible, general-purpose, temperature-dependent, and multitarget models for the prediction of reaction rates. To that end, we propose a model that depends on the well-known Morgan fingerprints as well as learned representations transferred from the QM9 data set. We propose the use of an Arrhenius-based loss where predictions of the three modified-Arrhenius parameters (A, n, and B = Ea/R) are given instead of the direct prediction of reaction rate constants. Our model is >35% more accurate compared to a baseline model of feed forward network (FFN) on Morgan fingerprints.

Laser-based selective BTEX sensing using deep neural networks.

A mid-infrared absorption-based laser sensor is developed for selective and simultaneous benzene, toluene, ethylbenzene, and xylenes (BTEX) measurements under ambient conditions. The sensor is based on a distributed feedback inter-band cascade laser emitting near 3.3 µm. Wavelength tuning and deep neural networks were employed to differentiate the broadband absorbance of BTEX species. The sensor was validated with gas mixtures and real-time measurements were demonstrated at a temporal resolution of 1 s. Minimum detection limits for BTEX in air are 8, 20, 5, and 46 ppm, respectively. This sensor can be utilized to monitor BTEX emissions in the petrochemical, rubber, and paint industries to avoid hazardous health effects.

Closed-form solution of oscillating Maxwell nano-fluid with heat and mass transfer.

The primary goal of this article is to analyze the oscillating behavior of Maxwell Nano-fluid with regard to heat and mass transfer. Due to high thermal conductivity of engine oil is taken as a base fluid and graphene Nano-particles are introduced in it. Coupled partial differential equations are used to model the governing equations. To evaluate the given differential equations, certain dimensionless factors and Laplace transformations are used. The analytical solution is obtained for temperature, concentration and velocity. The temperature and concentration gradient are also finds to analyze the rate of heat and mass transfer. As a special case, the solution for Newtonian fluid is discussed. Finally, the behaviors of various physical factors are studied graphically for both sine and cosine oscillation and give physical meanings to the parameters.

The effect of hydrogen bonding on the reactivity of OH radicals with prenol and isoprenol: a shock tube and multi-structural torsional variational transition state theory study.

The presence of two functional groups (OH and double bond) in C5 methyl-substituted enols (i.e., isopentenols), such as 3-methyl-2-buten-1-ol (prenol) and 3-methyl-3-buten-1-ol (isoprenol), makes them excellent biofuel candidates as fuel additives. As OH radicals are abundant in both combustion and atmospheric environments, OH-initiated oxidation of these isopentenols over wide ranges of temperatures and pressures needs to be investigated. In alkenes, OH addition to the double bond is prominent at low temperatures (i.e., below ∼700 K), and H-atom abstraction dominates at higher temperatures. However, we find that the OH-initiated oxidation of prenol and isoprenol displays a larger role for OH addition at higher temperatures. In this work, the reaction kinetics of prenol and isoprenol with OH radicals was investigated over the temperature range of 900-1290 K and pressure of 1-5 atm by utilizing a shock tube and OH laser diagnostic. To rationalize these chemical systems, variational transition state theory calculations with multi-structural torsional anharmonicity and small curvature tunneling corrections were run using a potential energy surface characterized at the UCCSD(T)/jun-cc-pVQZ//M06-2X/6-311++G(2df,2pd) level of theory. A good agreement was observed between the experiment and theory, with both predicting a non-Arrhenius behavior and negligible pressure effects. OH additions to the double bond of prenol and isoprenol were found to be important, with at least 50% contribution to the total rate constants even at temperatures as high as 700 and 2000 K, respectively. This behavior was attributed to the stabilizing effect induced by hydrogen bonding between the reacting OH radical and the OH functional group of isopentenols at the saddle points. These stabilizing intermolecular interactions help mitigate the entropic effects that hinder association reactions as temperature increases, thus extending the prominent role of addition pathways to high temperatures. The site-specific rate constants were also found to be slower than their analogous reactions of OH + n-alkenes.

Reaction kinetics of 1,4-cyclohexadienes with OH radicals: an experimental and theoretical study.

This work presents the OH-initiated oxidation kinetics of 1,4-cyclochexadiene (1,4-CHD). The temperature dependence of the reaction was investigated by utilizing a laser flash photolysis flow reactor and laser-induced fluorescence (LPFR/LIF) technique over the temperature range of 295-438 K and a pressure of ∼50 torr. The kinetics of the reaction was followed by measuring the LIF signal of OH radicals near 308 nm. The reaction of OH radicals with 1,4-CHD exhibited a clear negative temperature dependence. To discern the role of various channels, ab initio and RRKM-based ME calculations (RRKM-ME) were performed over temperatures of 200-2000 K and pressures of 0.76-7600 torr. The computed energy profile revealed that the reaction proceeds via the formation of a pre-reaction van der Waals complex at the entrance channel. The complex was found to be more stable than that usually seen in other alkenes + OH reactions. Both the addition channel and the abstraction reaction of allylic hydrogen were found to have negative energy barriers. Interestingly, the abstraction reaction exhibited a negative temperature dependence at low temperatures and contributed significantly (∼37%) to the total rate coefficients even under atmospheric conditions. At T ≥ 900 K, the reaction was found to proceed exclusively (>95%) via the abstraction channel. Due to the competing channels, the reaction of OH radicals with 1,4-CHD displays complicated kinetic behaviours, reflecting the salient features of the energy profile. The role of competing channels was fully characterized by our kinetic model. The calculated rate coefficients showed excellent agreement with the available experimental data.

The kinetics of the reactions of Br atoms with the xylenes: an experimental and theoretical study.

This work reports the temperature dependence of the rate coefficients for the reactions of atomic bromine with the xylenes that are determined experimentally and theoretically. The experiments were carried out in a Pyrex chamber equipped with fluorescent lamps to measure the rate coefficients at temperatures from 295 K to 346 K. Experiments were made at several concentrations of oxygen to assess its potential kinetic role under atmospheric conditions and to validate comparison of our rate coefficients with those obtained by others using air as the diluent. Br2 was used to generate Br atoms photolytically. The relative rate method was used to obtain the rate coefficients for the reactions of Br atoms with the xylenes. The reactions of Br with both toluene and diethyl ether (DEE) were used as reference reactions where the loss of the organic reactants was measured by gas chromatography. The rate coefficient for the reaction of Br with diethyl ether was also measured in the same way over the same temperature range with toluene as the reference reactant. The rate coefficients were independent of the concentration of O2. The experimentally determined temperature dependence of the rate coefficients of these reactions can be given in the units cm3 molecule-1 s-1 by: o-xylene + Br, log10(k) = (-10.03 ± 0.35) - (921 ± 110)/T; m-xylene + Br, log10(k) = (-10.78 ± 0.09) - (787 ± 92/T); p-xylene + Br, log10(k) = (-9.98 ± 0.39) - (956 ± 121)/T; diethyl ether + Br, log10(k) = (-7.69 ± 0.55) - (1700 ± 180)/T). This leads to the following rate coefficients, in the units of cm3 molecule-1 s-1, based on our experimental measurements: o-xylene + Br, k(298 K) = 7.53 × 10-14; m-xylene + Br, k(298 K) = 3.77 × 10-14; p-xylene + Br, k(298 K) = 6.43 × 10-14; diethyl ether + Br, k(298 K) = 4.02 × 10-14. Various ab initio methods including G3, G4, CCSD(T)/cc-pV(D,T)Z//MP2/aug-cc-pVDZ and CCSD(T)/cc-pV(D,T)Z//B3LYP/cc-pVTZ levels of theory were employed to gain detailed information about the kinetics as well as the thermochemical quantities. Among the ab initio methods, the G4 method performed remarkably well in describing the kinetics and thermochemistry of the xylenes + Br reaction system. Our theoretical calculations revealed that the reaction of Br atoms with the xylenes proceeds via a complex forming mechanism in an overall endothermic reaction. The rate determining step is the intramolecular rearrangement of the pre-reactive complex leading to the post-reactive complex. After lowering the relative energy of the corresponding transition state by less than 1.5 kJ mol-1 for this step in the reaction of each of the xylenes with Br, the calculated rate coefficients are in very good agreement with the experimental data.

Comparative study of heat and mass transfer of generalized MHD Oldroyd-B bio-nano fluid in a permeable medium with ramped conditions.

This article aims to investigate the heat and mass transfer of MHD Oldroyd-B fluid with ramped conditions. The Oldroyd-B fluid is taken as a base fluid (Blood) with a suspension of gold nano-particles, to make the solution of non-Newtonian bio-magnetic nanofluid. The surface medium is taken porous. The well-known equation of Oldroyd-B nano-fluid of integer order derivative has been generalized to a non-integer order derivative. Three different types of definitions of fractional differential operators, like Caputo, Caputo-Fabrizio, Atangana-Baleanu (will be called later as [Formula: see text]) are used to develop the resulting fractional nano-fluid model. The solution for temperature, concentration, and velocity profiles is obtained via Laplace transform and for inverse two different numerical algorithms like Zakian's, Stehfest's are utilized. The solutions are also shown in tabular form. To see the physical meaning of various parameters like thermal Grashof number, Radiation factor, mass Grashof number, Schmidt number, Prandtl number etc. are explained graphically and theoretically. The velocity and temperature of nanofluid decrease with increasing the value of gold nanoparticles, while increase with increasing the value of both thermal Grashof number and mass Grashof number. The Prandtl number shows opposite behavior for both temperature and velocity field. It will decelerate both the profile. Also, a comparative analysis is also presented between ours and the existing findings.

Inception of Carbonaceous Nanostructures via Hydrogen-Abstraction Phenylacetylene-Addition Mechanism.

Sufficient experimental evidence has suggested that polycyclic aromatic hydrocarbons are the building blocks of carbonaceous nanostructures in combustion and circumstellar envelops of carbon-rich stars, but their fundamental formation mechanisms remain elusive. By exploring the reaction kinetics of phenylacetylene with 1-naphthyl/4-phenanthryl radicals, we provide compelling theoretical and experimental evidence for a novel and self-consistent hydrogen-abstraction phenylacetylene-addition (HAPaA) mechanism. HAPaA operates efficiently at both low and high temperatures, leading to the formation, expansion, and nucleation of peri-condensed aromatic hydrocarbons (PCAHs), which are otherwise difficult to synthesis via traditional hydrogen-abstraction acetylene/vinylacetylene-addition pathways. The HAPaA mechanism can be generalized to other α-alkynyl PCAHs and thus provides an alternative covalent bond bridge for PCAH combination via an acetylene linker. The proposed HAPaA mechanism may contribute toward a comprehensive understanding of soot formation, carbonaceous nanomaterials synthesis, and the origin and evolution of carbon in our galaxy.

Continuous Butadiyne Addition to Propargyl: A Radical-Efficient Pathway for Polycyclic Aromatic Hydrocarbons.

Polycyclic aromatic hydrocarbons (PAHs) play a crucial role in soot inception, interstellar evolution, and nanomaterial synthesis. Although several mechanisms, such as hydrogen-abstraction acetylene/vinylacetylene addition, have previously been proposed, PAH formation and growth are not yet fully understood. We propose an alternate PAH growth mechanism wherein propargyl radical reacts with butadiyne to form larger radicals containing newly fused aromatic rings. Butadiyne is an important intermediate in hydrocarbon oxidation and carbon rich stars, while propargyl is one of the most important resonantly stabilized radicals that persists for long times. Our proposed mechanism is validated by quantum chemical calculations, elementary reaction experiments, laminar flame analysis, and kinetic modeling. Our findings challenge the conventional wisdom that radical site regeneration, being central to PAH growth, requires sequential hydrogen elimination and/or abstraction. In our proposed mechanism, PAH growth does not depend on abundant free radical consumption, and could, therefore, help explain carbonaceous nanoparticle coalescence in radical-deficient reaction environments.