Single Infrared Spectrum Enables Simultaneous Identification of (Bio)Chemical Nature and Particle Size of Microorganisms and Synthetic Microplastic Beads.

Populations of nearly identical chemical and biological microparticles include the synthetic microbeads used in cosmetic, biomedical, agri-food, and pharmaceutical industries as well as the class of living microorganisms such as yeast, pollen, and biological cells. Herein, we identify simultaneously the size and chemical nature of spherical microparticle populations with diameters larger than 1 µm. Our analysis relies on the extraction of both physical and chemical signatures from the same optical spectrum recorded using attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy. These signatures are the spectral resonances caused by the microparticles, which depend on their size and the absorption peaks revealing their chemical nature. We validate the method first on separated and mixed groups of spherical microplastic particles of two different diameters, where the method is used to calculate the diameter of the microspherical particles. Then, we apply the method to correctly identify and measure the diameter of Saccharomyces cerevisiae yeast cells. Theoretical simulations to help in understanding the effect of size distribution and dispersion support our results.

Polarized light diffuse reflectance FT-NIR MEMS spectrometer enabling the detection of powder samples through a thin plastic layer.

Polarized scattered light Fourier transform infrared (FTIR) spectroscopy is used for measuring the absorbance of highly scattering materials overcoming the multiple scattering effect. It has been reported for in vivo for biomedical applications and in-field for agricultural and for environmental monitoring. In this paper, we report a polarized light microelectromechanical system (MEMS)-based FTIR in the extended near infrared (NIR) that utilizes a bistate polarizer in a diffuse reflectance measurement setup. The spectrometer is capable of distinguishing between single backscattering from the uppermost layer and multiple scattering from the deep layers. The spectrometer has a spectral resolution of 64c m -1 (about 16 nm at a wavelength of 1550 nm) and operates in the spectral range of 4347c m -1 to 7692c m -1 (1300 nm to 2300 nm). The technique implies de-embedding of the MEMS spectrometer polarization response by normalizing its effect; this is applied on three different samples: milk powder, sugar, and flour in plastic bags. The technique is examined on different scattering size particles. The scattering particles diameter's range is expected to vary from 10 µm to 400 µm. The absorbance spectra of the samples are extracted and compared to the direct diffuse reflectance measurements of the samples, showing good agreement. By using the proposed technique, the calculated error for the flour was decreased from 43.2% to 2.9% at 1935 nm wavelength. The wavelength error dependence is also reduced.

Potential of a Miniature Spectral Analyzer for District-Scale Monitoring of Multiple Gaseous Air Pollutants.

Gas sensors that can measure multiple pollutants simultaneously are highly desirable for on-site air pollution monitoring at various scales, both indoor and outdoor. Herein, we introduce a low-cost multi-parameter gas analyzer capable of monitoring multiple gaseous pollutants simultaneously, thus allowing for true analytical measurement. It is a spectral sensor consisting of a Fourier-transform infrared (FTIR) gas analyzer based on a mid-infrared (MIR) spectrometer. The sensor is as small as 7 × 5 × 2.5 cm3. It was deployed in an open-path configuration within a district-scale climatic chamber (Sense City, Marne-la-Vallée, France) with a volume of 20 × 20 × 8 m3. The setup included a transmitter and a receiver separated by 38 m to enable representative measurements of the entire district domain. We used a car inside the climatic chamber, turning the engine on and off to create time sequences of a pollution source. The results showed that carbon dioxide (CO2) and water vapor (H2O) were accurately monitored using the spectral sensor, with agreement with the reference analyzers used to record the pollution levels near the car exhaust. Furthermore, the lower detection limits of CO, NO2 and NO were assessed, demonstrating the capability of the sensor to detect these pollutants. Additionally, a preliminary evaluation of the potential of the spectral sensor to screen multiple volatile organic compounds (VOCs) was conducted at the laboratory scale. Overall, the results demonstrated the potential of the proposed multi-parameter spectral gas sensor in on-site gaseous pollution monitoring.

Complex Kernel-based spectrum reconstruction algorithm for cascaded Fabry-Perot interferometric spectrometer.

A method to calculate the spectrum of the light incident on a cascaded Fabry-Perot interferometric spectrometer from the detector signal versus the scanning mirror position is presented. The method is based on modifying the Fabry-Perot integral equation to reduce possible spectrum reconstruction errors that arise due to inaccurate determination of the optical path difference reference position and the dependence on the dispersion of the cavity material. A transformation algorithm that employs the suggested kernel modification is derived and tested. The presented algorithm is then compared to the conventional kernel, showing spectral error reductions by larger than 20 dB.

Continuous Monitoring of Air Purification: A Study on Volatile Organic Compounds in a Gas Cell.

Air pollution is one of the major environmental issues that humanity is facing. Considering Indoor Air Quality (IAQ), Volatile Organic Compounds (VOCs) are among the most harmful gases that need to be detected, but also need to be eliminated using air purification technologies. In this work, we tackle both problems simultaneously by introducing an experimental setup enabling continuous measurement of the VOCs by online absorption spectroscopy using a MEMS-based Fourier Transform infrared (FTIR) spectrometer, while those VOCs are continuously eliminated by continuous adsorption and photocatalysis, using zinc oxide nanowires (ZnO-NWs). The proposed setup enabled a preliminary study of the mechanisms involved in the purification process of acetone and toluene, taken as two different VOCs, also typical of those that can be found in tobacco smoke. Our experiments revealed very different behaviors for those two gases. An elimination ratio of 63% in 3 h was achieved for toluene, while it was only 14% for acetone under same conditions. Adsorption to the nanowires appears as the dominant mechanism for the acetone, while photocatalysis is dominant in case of the toluene.

Nanowire Length, Density, and Crystalline Quality Retrieved from a Single Optical Spectrum.

We propose spectral domain attenuated reflectometry (SDAR) for fast characterization of nanomaterial growth. The method is demonstrated here for zinc oxide (ZnO) nanowires (NWs) which are grown vertically in random forest fashion showing that it is not limited to well-ordered NWs. We show how SDAR can provide, on the basis of a single measured spectrum, simultaneous information on nanowire length, nanowire density (through nanowire/air filling ratio), and crystalline quality (through band gap). The robustness of the proposed method is assessed first through comparison with information obtained from SEM and XRD taken as reference. In SDAR, the process for fast extraction of NW thickness and filling ratio values  makes use of the interference pattern contrast and the spectral periodicity in the reflection response which involve a best fit of the measured spectra with simple theoretical modeling based on the effective medium approach, achieved with a mean square error down to 0.1%. The results also suggest the existence of either 2 or 3 layers of different effective refractive index, hence providing insight on possible growth mechanisms.

Autoregressive superresolution microelectromechanical systems Fourier transform spectrometer.

In this work, the application of the superresolution autoregressive (AR) model to enhance the resolution of the microelectromechanical systems (MEMS) Fourier transform infrared spectrometer (FTIR) spectrometer is studied theoretically and experimentally. The effect of the number of spectral lines, the spacing between the lines, the resolution of the MEMS FTIR spectrometer and the signal-to-noise ratio (SNR) on the prediction accuracy is addressed for different targeted prediction resolutions. The effect of the SNR on applying the AR model is studied. Then, the AR model is applied to experimental data obtained using the MEMS FTIR for the different cases of single spectral line, xenon lamp lines and gas cells containing different gas mixtures. It is found that enhancement up to 4× can obtained in the case of the single line, while an enhancement of about 2-2.5× can be obtained in the case of multilines without having false spectral lines.

On-Channel Integrated Optofluidic Pressure Sensor with Optically Boosted Sensitivity.

A novel optofluidic sensor that measures the local pressure of the fluid inside a microfluidic channel is presented. It can be integrated directly on-channel and requires no additional layers in fabrication. The detection can be accomplished at a single wavelength; and thereby, only a single laser diode and a single photodetector are required. This renders the sensor to be compact, cheap and easy to fabricate. Basically, the sensor consisted of a Fabry⁻Pérot microresonator enclosing the fluidic channel. A novel structure of the Fabry⁻Pérot was employed to achieve high-quality factor, that was essential to facilitate the single wavelength detection. The enhanced performance was attributed to the curved mirrors and cylindrical lenses used to avoid light diffraction loss. The presented sensor was fabricated and tested with deionized water liquid and shown to exhibit a sensitivity up to 12.46 dBm/bar, and a detection limit of 8.2 mbar. Numerical simulations are also presented to evaluate the mechanical⁻fluidic performance of the device.

Optical modeling of black silicon using an effective medium/multi-layer approach.

In this work, black silicon (BSi) structures including nanocones and nanowires are modeled using effective medium theory (EMT), where each structure is assumed to be a multilayer structure of varying effective index, and its optical scattering in the infrared range is studied in terms of its total reflectance, transmittance and absorptance using the transfer matrix method (TMM). The different mechanisms of the intrinsic absorption of silicon are taken into account, which translates into proper modeling of its complex refraction index, depending on several parameters including the doping level. The model validity is studied by comparing the results with the rigorous coupled wave analysis and is found to be in good agreement. The effect of the aspect ratio, the spacing between the structure features and the structure disordered nature are all considered. Moreover, the results of the proposed model are compared with reflectance measurements of a fabricated BSi sample, in addition to other measurements reported in the literature for Silicon Nanowires (SiNWs). The TMM along with EMT proves to be a convenient method for modeling BSi due to its simple implementation and computational speed.

Transmission-enabled fiber Fabry-Perot cavity based on a deeply etched slotted micromirror.

In this work, we report the analysis, fabrication, and characterization of an optical cavity built using a Bragg-coated fiber (BCF) mirror and a metal-coated microelectromechanical systems (MEMS) slotted micromirror, where the latter allows transmission output from the cavity. Theoretical modeling, using Fourier optics analysis for the cavity response based on tracing the propagation of light back and forth between the mirrors, is presented. Detailed simulation analysis is carried out for the spectral response of the cavity under different design conditions. MEMS chips of the slotted micromirror are fabricated using deep reactive ion etching of a silicon-on-insulator substrate with different device-etching depths of 150 µm and 80 µm with aluminum and gold metal coating, respectively. The cavity is characterized as an optical filter using a BCF with reflectivity that is larger than 95% in a 300 nm range across the E-band and the L-band. Versatile filter characteristics were obtained for different values of the MEMS micromirror slit width and cavity length. A free spectral range (FSR) of about 33 nm and a quality factor of about 196 were obtained for a 5.5 µm width aluminum slit, while an FSR of about 148 nm and a quality factor of about 148 were obtained for a 1.5 µm width gold slit. The presented structure opens the door for wide spectral response transmission-type MEMS filters.

In-plane coupled Fabry-Perot micro-cavities based on Si-air Bragg mirrors: a theoretical and practical study.

In-plane Fabry-Perot cavities based on deeply etched Bragg mirrors are used in many microphotonic applications including sensing, telecom, and swept laser devices. A main limitation to their performance is the small free spectral range (FSR) and low finesse. The FSR limits the dynamic range or the wavelength tuning range, while the linewidth limits the resolution. In this work, we propose coupled Fabry-Perot micro-cavities that greatly enhance the FSR, besides reducing the linewidth, which lead to higher finesse and better performance. The proposed structure is modeled and etched on Si substrate to a depth of 150 µm using the deep reactive ion etching technology. Optical measurements indicate an enhanced FSR of more than 140 nm and a quality factor of 3152 using coupled cavities as compared to only 9 nm FSR for a single cavity of the same length. The over-etching and surface roughness, being the main effective fabrication tolerances, are modeled and extracted from the measurements.

Transformation algorithm and analysis of the Fourier transform spectrometer based on cascaded Fabry-Perot interferometers.

The Fourier transform spectrometer based on cascaded Fabry-Perot interferometers is analyzed, where one of the interferometers has a fixed length, while the other is scanning. We propose a method to reconstruct the spectrum correctly based on solving the integral equation of the overall response of the cascaded interferometers. The method is tested for different design parameters and noise conditions. Low reconstruction error below -80 dB is found to be achievable.

Analysis of dual coupler nested coupled cavities.

Coupled ring resonators are now forming the basic building blocks in several optical systems serving different applications. In many of these applications, a small full width at half maximum is required, along with a large free spectral range. In this work, a configuration of passive coupled cavities constituting dual coupler nested cavities is proposed. A theoretical study of the configuration is presented allowing us to obtain analytical expressions of its different spectral characteristics. The transfer function of the configuration is also used to generate design curves while comparing these results with analytical expressions. Finally, the configuration is compared with other coupled cavity configurations.

A disposable optofluidic micro-transmission cell with tailorable length for Fourier-transform infrared spectroscopy of biological fluids.

Mid-infrared Fourier-transform infrared (FT-IR) spectroscopy of liquid biological samples is limited by the high absorption of water in this spectral range, which makes conventional transmission cuvettes unsuitable as their centimeter-scale length is already too big. The most common alternative relies on the use of attenuated total reflection (ATR) accessories, which provide a small interaction path length for light along the interface between the analyte and the expensive ATR crystals. In this work, we address this issue by proposing a disposable and low-cost micro-transmission cell. Its construction relies on a simple technique, which consists of dispersing plastic spherical microparticles in a liquid sample before dispensing it between two pieces of silicon assembled one onto the other and acting as windows for the cell. Consequently, the microparticles act as a spacer of very precise height in-between the two silicon windows. This technique allows easy construction of infrared absorption cells with near-optimum optical interaction path length just by selecting the most appropriate particle size. The concept is demonstrated by measuring the concentration of glucose in aqueous solutions using microspheres of diameter 20 µm then 40 µm and analyzing the corresponding glucose absorption peaks in the wavenumber range 950-1200 cm-1. The performance is compared to that of standard ATR spectroscopy of the same samples. This resulted in a root-mean-square error of cross-validation (RMSECV) of 58.8 mg dl-1 as obtained for transmission measurements by partial least squares (PLS) regression, which is comparable to the RMSECV of 53 mg dl-1 for single-reflection diamond ATR measurements.

Advancing near-infrared spectroscopy: A synergistic approach through Bayesian optimization and model stacking.

Fourier transform near-infrared (FT-NIR) spectroscopy is a versatile and non-destructive analytical tool widely utilized in industries such as food, pharmaceuticals, and agriculture. While traditional FT-NIR instruments pose limitations in terms of cost and complexity, the advent of portable and affordable systems like NeoSpectra Scanners has broadened accessibility. Partial Least Squares Regression (PLSR) stands as an industry-standard method in Chemometrics for analyzing chemical compositions. This work addresses optimizing PLSR models in FT-NIR spectroscopy, focusing on enhancing accuracy and adaptability in material analysis. Unlike traditional PLSR models which often rely on grid searching a limited number of parameters, such as latent variables, the presented approach effectively expands the parameter space. A novel framework combining Bayesian search and stacking techniques is introduced to enable more customization while ensuring time and performance efficiency, along with automation in model development. Bayesian search efficiently explores hyperparameters space, enabling faster convergence to optimal model settings without exhaustive exploration. The proposed stacked model leverages learned knowledge from the top-performing PLSR models optimized through Bayesian methods, amalgamating a unified and potent body of knowledge. Bayesian-stacked models are compared with PLSR models that use grid search for a limited parameter set. Findings show a marked improvement in model performance: a 51.5% reduction in Root Mean Square Error (RMSE) for the training dataset and a 26.1% reduction for the testing dataset, alongside a 10.9% increase in the correlation coefficient square (R2) for the training dataset and a 10.4% increase for the testing dataset. Notably, Bayesian search reduces the model optimization time by approximately 90% compared with the grid search. Furthermore, when addressing instrumental variations, the models demonstrate an additional improvement, evident in the average reduction of 24.1% in the mean range of prediction. Overall, results demonstrate that the presented approach not only increases the prediction accuracy but also offers a more efficient, automated and robust solution for diverse spectroscopic applications.

Integrated wide-angle scanner based on translating a curved mirror of acylindrical shape.

A wide angle microscanning architecture is presented in which the angular deflection is achieved by displacing the principle axis of a curved silicon micromirror of acylindrical shape, with respect to the incident beam optical axis. The micromirror curvature is designed to overcome the possible deformation of the scanned beam spot size during scanning. In the presented architecture, the optical axis of the beam lays in-plane with respect to the substrate opening the door for a completely integrated and self-aligned miniaturized scanner. A micro-optical bench scanning device, based on translating a 200 µm focal length micromirror by an electrostatic comb-drive actuator, is implemented on a silicon chip. The microelectromechanical system has a resonance frequency of 329 Hz and a quality factor of 22. A single-mode optical fiber is used as the optical source and inserted into a micromachined groove fabricated and lithographically aligned with the microbench. Optical deflection angles up to 110 degrees are demonstrated.

Allan Variance Characterization of Compact Fourier Transform Infrared Spectrometers.

Handheld Fourier transform infrared (FT-IR) spectrometers are very promising candidates for several applications where accurate real-time material detection and quantification are needed. Due to their compact size, their mode of operation which does not allow for long warm-up time, and changing environmental conditions, these spectrometers suffer from short-term noise and long-term instabilities which affect their performance. In this work, the effect of long-term multiplicative instabilities on the signal-to-noise ratio (S/N), measured using the 100% line-method, is studied. An expression for the variance, in this case, is deduced. The Allan variance technique is used to identify and quantify the presence of the different types of noises. The methodology is applied to a commercial NeoSpectra scanner module from Si-Ware Systems, Inc.

Detection of Sub-20 µm Microplastic Particles by Attenuated Total Reflection Fourier Transform Infrared Spectroscopy and Comparison with Raman Spectroscopy.

Microplastics are particulate water contaminants that are raising concerns regarding their environmental and health impacts. Optical spectroscopy is the gold standard for their detection; however, it has severe limitations such as tens of hours of analysis time and spatial resolution of more than 10 µm, when targeting the production of a 2D map of the microparticle population. In this work, through a single spectrum acquisition, we aim at quickly getting information about the whole population of identical particles, their chemical nature, and their size in a range below 20 µm. To this end, we built a compact setup enabling both attenuated total reflection Fourier transform infrared (ATR-FTIR) and Raman spectroscopy measurement on the same sample for comparison purposes. We used monodisperse polystyrene and poly(methyl methacrylate) microplastic spheres of sizes ranging between 6 and 20 µm, also measured collectively using a bench-top FTIR spectrometer in ATR mode. The ATR-FTIR technique appears to be more sensitive for the smallest particles of 6 µm, while the opposite trend is observed using Raman spectroscopy. We use theoretical modeling to simulate and explain the ripples observed in the measured spectra at the shortest wavelength (higher wavenumber) region, which appears as an indicator of the microparticle dimension. The latter finding opens new perspectives for ATR-FTIR for the identification and classification of populations of nearly identical micro-scale bodies, such as bacteria and other micro-organisms, where the same measured spectrum embeds dual information about the chemical nature and the size.

Substrate Signal Inhibition in Raman Analysis of Microplastic Particles.

In Raman analysis, the substrate material serves very often for signal enhancement, especially when metallic surfaces are involved; however, in other cases, the substrate has an opposite effect as it is the source of a parasitic signal preventing the observation of the sample material of interest. This is particularly true with the advent of microfluidic devices involving either silicon or polymer surfaces. On the other hand, in a vast majority of Raman experiments, the analysis is made on a horizontal support holding the sample of interest. In our paper, we report that a simple tilting of the supporting substrate, in this case, silicon, can drastically decrease and eventually inhibit the Raman signal of the substrate material, leading to an easier observation of the target analyte of the sample, in this case, microplastic particles. This effect is very pronounced especially when looking for tiny particles. Explanation of this trend is provided thanks to a supporting experiment and further numerical simulations that suggest that the lensing effect of the particles plays an important role. These findings may be useful for Raman analysis of other microscale particles having curved shapes, including biological cells.

Spatiotemporal dynamics of nanowire growth in a microfluidic reactor.

Co-integration of nanomaterials into microdevices poses several technological challenges and presents numerous scientific opportunities that have been addressed in this paper by integrating zinc oxide nanowires (ZnO-NWs) into a microfluidic chamber. In addition to the applications of these combined materials, this work focuses on the study of the growth dynamics and uniformity of nanomaterials in a tiny microfluidic reactor environment. A unique experimental platform was built through the integration of a noninvasive optical characterization technique with the microfluidic reactor. This platform allowed the unprecedented demonstration of time-resolved and spatially resolved monitoring of the in situ growth of NWs, in which the chemicals were continuously fed into the microfluidic reactor. The platform was also used to assess the uniformity of NWs grown quickly in a 10-mm-wide microchamber, which was intentionally chosen to be 20 times wider than those used in previous attempts because it can accommodate applications requiring a large surface of interaction while still taking advantage of submillimeter height. Further observations included the effects of varying the flow rate on the NW diameter and length in addition to a synergetic effect of continuous renewal of the growth solution and the confined environment of the chemical reaction.