This PDF file contains the front matter associated with SPIE Proceedings Volume 9106, including the Title Page, Copyright information, Table of Contents, Invited Panel Discussion, and Conference Committee listing.

Demonstrating particle matter (PM) emissions compliance with environmental regulations is required for operation of any industrial, commercial or military facility. Emission sources are initially screened based on their visible opacity via US EPA Method 9 standard. Nowadays, it is rather surprising that opacity is still visually determined by human eyes with smoke school training and semi-annual certification. Nonetheless, opacity alone doesn’t reveal particle concentration and size distribution which is crucial to determine PM values. It would be desirable to have an automated, calibratable device to make such a measurement with higher accuracy and reliability and is not available to date. We present our preliminary work on developing a compact, hand portable system capable of quantitatively determining plume optical opacity in combination with possible particle concentration and size distribution (and hence PM) measurement for standoff distances up to 150 meters. Our benchtop lidar-based system was built with a frequencydoubled Q-switched Nd:YAG laser and an optical receiver. We have demonstrated the feasibility of a remote-capable optical sensor system for real-time continuous monitoring of visible emission plumes and its effectiveness for quantitative opacity measurement. The hand-portable Remote Plume Particulate Matter (RPPM) meter being developed will be capable of determining opacity and PM load from remote PM sources will provide a regulatory compliance solution for visible emissions from sources for environmental studies, industrial and military applications.

With continuing improvements in both standoff- and point-sensing techniques, there is an ongoing need for high-quality infrared spectral databases. The Northwest Infrared Database (NWIR) contains quantitative, gas-phase infrared spectra of nearly 500 pure chemical species that can be used for a variety of applications such as atmospheric monitoring, biomass burning studies, etc. The data, recorded at 0.1 cm^-1 resolution, are pressure broadened to one atmosphere (N₂). Each spectrum is a composite composed of multiple individual measurements. Recent updates to the database include over 60 molecules that are known or suspected biomass-burning effluents. Examples from this set of measurements will be presented and experimental details will be discussed in the context of the utility of NWIR for environmental applications.

A highly-sensitive, reliable, simple and inexpensive chemical detection and identification platform is demonstrated. The sensing technique is based on localized surface plasmon enhanced Raman scattering measurements from gold-coated highly-ordered symmetric nanoporous ceramic membranes fabricated from anodic aluminum oxide. To investigate the effects of the thickness of the sputter-coated gold films on the sensitivity of sensor, and optimize the performance of the substrates, the geometry of the nanopores and the film thicknesses are varied in the range of 30 nm to 120 nm. To characterize the sensing technique and the detection limits, surface enhanced Raman scatterings of low concentrations of a standard chemical adsorbed on the gold coated substrates are collected and analyzed. The morphology of the proposed substrates is characterized by atomic force microscopy and the optical properties including transmittance, reflectance and absorbance of each substrate are also investigated.

Block MEMS/Engineering develops mid-infrared spectroscopy systems based on both Fourier transform infrared (FTIR) spectrometers and quantum cascade lasers (QCLs). Our recently developed miniaturized external-cavity QCLs are widely tunable over a spectral range of >250 cm^-1 and tuning can be accomplished at rates of <25 cm^-1 per millisecond. This enables high-speed mid-infrared spectroscopy of gases and surface contaminants for a variety of military and commercial applications. This paper provides an overview of our FTIR and QCL systems and their defense-related applications.

The use of Hyper-Spectral Imaging (HSI) as a diagnostic tool in the field of cultural heritage is of great interest presenting high potentialities. This analysis, in fact, is non-destructive, non-invasive and portable. Furthermore, the possibility to couple hyperspectral data with chemometric techniques allows getting qualitative and/or quantitative information on the nature and physical-chemical characteristics of the investigated materials. A study was carried out to explore the possibilities offered by this approach to identify pigments in paintings. More in detail, six pigments have been selected and they have been then mixed with four different binders and applied to a wood support. The resulting reference samples were acquired by HSI in the SWIR wavelength range (1000-2500 nm). Data were processed adopting a chemometric approach based on the PLS Toolbox (Eigenvector Research, Inc.) running inside Matlab® (The Mathworks, Inc.). The aim of the study was to verify, according to the information acquired in the investigated wavelength region, the correlation existing between collected spectral signatures and sample characteristics related to the different selected pigments and binders. Results were very good showing as correlations exist. New scenarios can thus be envisaged for analysis, characterization, conservation and restoration of paintings, considering that the developed approach allows to obtain, just “in one shot”, information, not only on the type of pigment, but also on the utilized binder and support.

Characterization of gas clouds are challenging situations to address due to the large and uneven distribution of these fast moving entities. Whether gas characterization is carried out for gas leaks surveys or environmental monitoring purposes, explosives and/or toxic chemicals are often involved. In such situations, airborne measurements present distinct advantages over ground based-techniques since large areas can be covered efficiently from a safe distance. In order to illustrate the potential of airborne thermal infrared hyperspectral imaging for gas cloud characterization, measurements were carried out above smokestacks and a ground-based gas release experiment. Quantitative airborne chemical images of carbon monoxide (CO) and ethylene (C₂H₄) were obtained from measurements carried out using a midwave (MWIR, 3-5 μm) and a longwave (LWIR, 8-12 μm) airborne infrared hyperspectral sensor respectively. Scattering effects were observed in the MWIR experiments on smokestacks as a result of water condensation upon rapid cool down of the hot emission gases. Airborne measurements were carried out using both mapping and targeting acquisition modes. The later provides unique time-dependent information such as the gas cloud direction and velocity.

The recovery of materials from Demolition Waste (DW) represents one of the main target of the recycling industry and the its characterization is important in order to set up efficient sorting and/or quality control systems. End-Of-Life (EOL) concrete materials identification is necessary to maximize DW conversion into useful secondary raw materials, so it is fundamental to develop strategies for the implementation of an automatic recognition system of the recovered products. In this paper, HyperSpectral Imaging (HSI) technique was applied in order to detect DW composition. Hyperspectral images were acquired by a laboratory device equipped with a HSI sensing device working in the near infrared range (1000-1700 nm): NIR Spectral Camera™, embedding an ImSpector™ N17E (SPECIM Ltd, Finland). Acquired spectral data were analyzed adopting the PLS_Toolbox (Version 7.5, Eigenvector Research, Inc.) under Matlab® environment (Version 7.11.1, The Mathworks, Inc.), applying different chemometric methods: Principal Component Analysis (PCA) for exploratory data approach and Partial Least Square- Discriminant Analysis (PLS-DA) to build classification models. Results showed that it is possible to recognize DW materials, distinguishing recycled aggregates from contaminants (e.g. bricks, gypsum, plastics, wood, foam, etc.). The developed procedure is cheap, fast and non-destructive: it could be used to make some steps of the recycling process more efficient and less expensive.

Real-time detection and identification of bio-aerosol particles are crucial for the protection against chemical and biological agents. The strong elastic light scattering properties of airborne particles provides a natural means for rapid, non-invasive aerosol characterization. Recent theoretical predictions suggested that variations in the polarization dependent angular scattering cross section could provide an efficient means of classifying different airborne particles. In particular, the polarization dependent scattering cross section of aggregate particles is expected to depend on the shape of the primary particles. In order to experimentally validate this prediction, we built a high throughput, sampling system, capable of measuring the polarization resolved angular scattering cross section of individual aerosol particles flowing through an interrogating volume with a single shot of laser pulse. We calibrated the system by comparing the polarization dependent scattering cross section of individual polystyrene spheres with that predicted by Mie theory. We then used the system to study different particles types: Polystyrene aggregates composed 500 nm spheres and Bacillus subtilis (BG, Anthrax simulant) spores composed of elongated 500 nm × 1000 nm cylinder-line particles. We found that the polarization resolved scattering cross section depends on the shape of the constituent elements of the aggregates. This work indicates that the polarization resolved scattering cross section could be used for rapid discrimination between different bio-aerosol particles.

This paper presents an experiment making use of the near-infrared spectrum for distinguishing the wines produced in two close provinces of Abruzzo region of Italy. A collection of 32 wines was considered, 18 of which were produced in the province of Chieti, while the other 14 were from the province of Teramo. A conventional dual-beam spectrophotometer was used for absorption measurements in the 1300-1900 nm spectroscopic range. Principal Component Analysis was used for explorative analysis. Score maps in the PC1-PC2 or PC2-PC3 spaces were obtained, which successfully grouped the wine samples in two distinct clusters, corresponding to Chieti and Teramo provinces, respectively. A modelling of dual-band spectroscopy was also proposed, making use of two LEDs for illumination and a PIN detector instead of the spectrometer. These data were processed using Linear Discriminant Analysis which demonstrated satisfactory classification results.

Microplasmas are receiving attention in recent conferences and current scientific literature. In our laboratory, microplasmas-on-chips proved to be particularly attractive. The 2D- and 3D-chips we developed became hybrid because they were fitted with a quartz plate (quartz was used due to its transparency to UV). Fabrication of 2D- and 3D-chips for microplasma research is described. The fabrication methods described ranged from semiconductor fabrication technology, to Computer Numerical Control (CNC) machining, to 3D-printing. These methods may prove to be useful for those contemplating in entering microplasma research but have no access to expensive semiconductor fabrication equipment.

A temperature-stable, low-power ring oscillator design with a wide tuning frequency range, for implementation in an ASIC is presented. The design uses a new arrangement of chain delay elements consisting of a current-starved inverter and a CMOS capacitor. The delay is controlled by changing the current through the delay elements. The simulation results show that the frequency of the presented oscillator is stable against ambient temperature variations, with less than 0.5% deviation in frequency when the temperature was changed from 0 to 50°C. The oscillation frequency is highly sensitive to the control voltage (sensitivity ~10 mV) with a tuning range of 203 MHz for 0.9 V increase in the input voltage, and simulated power consumption of 1.2 nW. The design and simulation results of the ring oscillator with 180 nm technology are presented and discussed. The presented design is applicable in advanced sensing systems, including biomedical, chemical, and other sensors.

Today evanescent wave based fiber optic (F/O) platforms are in favor of the use for monitoring molecular interactions since they are practical, economic and easy to operate which make them ideal turnkey systems for clinical, pharmaceutical, environmental and security applications. The side polishing is one of techniques for reshaping the geometry of the waveguide to make the F/O sensor more sensitive to surrounding refractive index (RI) in evanescent field. In this study D-type F/O sensors with a 25 mm-long interaction lengths are fabricated. In addition to that, effects of the critical parameters such as the polishing depth, the wavelength, and the temperature on the sensor response are determined for the RI in the range of 1.33 - 1.47. The developing key of these F/O sensors is reaching high strength and penetration depth of evanescent wave in varying RI of the surrounding bio-layer. Development steps of D-type F/O sensors are; fabrication of supporting elements - silicon V channels, F/O cable preparation, adhesion, lapping and polishing, fusing the FC connectors, construction of the optical system, and RI measurements. Details of these steps are explained and the general characteristics of the D-type F/O sensor are presented. Results indicate that the sensor’s responses in three different RI ranges can be improved by the polishing depth. A maximum sensitivity of around 2x10⁵ for the D-type F/O sensors is demonstrated in the RI range of 1.44-1.46.

Nanoporous anodic aluminum oxide (AAO) has been investigated as an ideal and cost-effective chemical and biosensing platform. In this paper, we report the optical properties of periodic 100 micron thick nanoporous anodic alumina membranes with uniform and high density cylindrical pores penetrating the entire thickness of the substrate, ranging in size from 18 nm to 150 nm in diameter and pore periods from 44 nm to 243 nm. The surface geometry of the top and bottom surface of each membrane is studied using atomic force microscopy. The optical properties including transmittance, reflectance, and absorbance spectra on both sides of each substrate are studied and found to be symmetrical. It is observed that, as the pore size increases, the peak resonance intensity in transmittance decreases and in absorbance increases. The effects of the pore sizes on the optical properties of the bare nanoporous membranes and the benefit of using arrays of nanohole arrays with varying hole size and periodicity as a chemical sensing platform is also discussed. To characterize the optical sensing technique, transmittance and reflectance measurements of various concentrations of a standard chemical adsorbed on the bare nanoporous substrates are investigated. The preliminary results presented here show variation in transmittance and reflectance spectra with the concentration of the chemical used or the amount of the material adsorbed on the surface of the substrate.

We discuss a robust method for optimal oil probe path planning inspired by medical imaging. Horizontal wells require three-dimensional steering made possible by the rotary steerable capabilities of the system, which allows the hole to intersect multiple target shale gas zones. Horizontal "legs" can be over a mile long; the longer the exposure length, the more oil and natural gas is drained and the faster it can flow. More oil and natural gas can be produced with fewer wells and less surface disturbance. Horizontal drilling can help producers tap oil and natural gas deposits under surface areas where a vertical well cannot be drilled, such as under developed or environmentally sensitive areas. Drilling creates well paths which have multiple twists and turns to try to hit multiple accumulations from a single well location. Our algorithm can be used to augment current state of the art methods. Our goal is to obtain a 3D path with nodes describing the optimal route to the destination. This algorithm works with BIG data and saves cost in planning for probe insertion. Our solution may be able to help increase the energy extracted vs. input energy.

In a relatively recent paper an electrochemical biosensor for water toxicity detection based on a bio-chip as a whole cell was proposed and numerically solved and analyzed. In such paper the kinetic processes in a miniaturized electrochemical biosensor system was described using the equations for specific enzymatic reaction and the diffusion equation. The numerical solution shown excellent agreement with the measured data but such numerical solution is not enough to design efficiently the corresponding bio-chip. For this reason an analytical solution is demanded. The object of the present work is to provide such analytical solution and then to give algebraic guides to design the bio-sensor. The analytical solution is obtained using computer algebra software, specifically Maple. The method of solution is the Laplace transform, with Bromwich integral and residue theorem. The final solution is given as a series of Bessel functions and the effective time for the bio-sensor is computed. It is claimed that the analytical solutions that were obtained will be very useful to predict further current variations in similar systems with different geometries, materials and biological components. Beside of this the analytical solution that we provide is very useful to investigate the relationship between different chamber parameters such as cell radius and height; and electrode radius.