Aaron Urbas

Molecular Factor Computing for Predictive Spectroscopy

PurposeThe concept of molecular factor computing (MFC)-based predictive spectroscopy was demonstrated here with quantitative analysis of ethanol-in-water mixtures in a MFC-based prototype instrument. MethodsMolecular computing of vectors for transformation matrices enabled spectra to be represented in a desired coordinate system. New coordinate systems were selected to reduce the dimensionality of the spectral hyperspace and simplify the mechanical/electrical/computational construction of a new MFC spectrometer employing transmission MFC filters. A library search algorithm was developed to calculate the chemical constituents of the MFC filters. The prototype instrument was used to collect data from 39 ethanol-in-water mixtures (range 0–14%). For each sample, four different voltage outputs from the detector (forming two factor scores) were measured by using four different MFC filters. Twenty samples were used to calibrate the instrument and build a multivariate linear regression prediction model, and the remaining samples were used to validate the predictive ability of the model.Results In engineering simulations, four MFC filters gave an adequate calibration model (r2 = 0.995, RMSEC = 0.229%, RMSECV = 0.339%, p = 0.05 by f test). This result is slightly better than a corresponding PCR calibration model based on corrected transmission spectra (r2 = 0.993, RMSEC = 0.359%, RMSECV = 0.551%, p = 0.05 by f test). The first actual MFC prototype gave an RMSECV = 0.735%.ConclusionMFC was a viable alternative to conventional spectrometry with the potential to be more simply implemented and more rapid and accurate.

In vivo applications of a molecular computing-based high-throughput NIR spectrometer

Modern hyperspectral imaging is able to collect exceptional amounts of information at astonishing speed. Reducing these data from physical fields to high-level, useful information is difficult. Integrated computational imaging (ICI) is a process in which image information is encoded as it is sensed to produce information better suited for high-speed digital processors. Both spatial and spectral features of samples can be encoded in ICI. When spectral images are simultaneously obtained and encoded at many different wavelengths, the process is called hyperspectral integrated computational imaging (HICI). Lenslet arrays and masks are ideal for encoding spatial features of an image. This process is used here to analyze motion and metabolism in freely moving rats. Complex molecular absorption filters can be used as mathematical factors in spectral encoding to create a factor-analytic optical calibration in a high-throughput spectrometer. This process is used here for remote sensing of ethanol concentrations. In this system, the molecules in the filter effectively compute the calibration function by weighting the signals received at each wavelength over a broad wavelength range. One or two molecular filters are sufficient to produce a detector voltage that is proportional to an analyte concentration in the image field. Because a single detector voltage can reveal analyte concentration, HICI is able to calculate chemical images orders of magnitude more rapidly than conventional chemometric approaches.

In situ spectroscopic cleaning validation

Although these methods have proven successful, there are several shortcomings. Drawbacks with swabbing, the most commonly used technique, include the need to sample the surface, incomplete analyte recovery from surfaces, analyte extraction requirements after swabbing. Additionally, the procedure is time consuming, resulting in lengthy downtimes for processing equipment. Rinse testing can be used as an alternative or complementary method and allows for collection from the entire surface. This method suffers from limitations as well, including more difficult method validation and analyte solubility/surface detachment issues. An additional drawback to these two methods is the fact that the quantity of analyte remaining on the surface must be estimated from the analysis of the samples drawn. An ideal validation method for cleaning procedures would be a rapid, automated, in situ, multi-component analysis of the entire surface. With this approach, errors and inadequacies associated with surface sampling procedures would be eliminated. The use of spectroscopic techniques for in situ determination of contamination on sur

Prospects for Implantable Sensors Powered by near Infrared Rechargeable Batteries

is charged and is able to automatically power the device when the photodiode array is not illuminated. The current flow backward from the battery to the photodiode array is shut off by inserting a diode between them. Of course, sunlight is not always available. One light source easily able to recharge the battery in the absence of sunlight is a NIR laser diode (e.g., a Coherent S-81–1000C-100-H at 810 nm). The photodiode array to convert light into electricity comprises eight Si PIN photodiodes (Hamamatsu, S6775) connected in series to obtain sufficient voltage to the charge the battery. The detection area for every photodiode is 5.5 × 4.8 mm. The dimensions of the complete photodiode array prototype, including the packages, are 28 × 20 × 3 mm. The battery is a composite dimensional manganese oxide (CDMO) lithium secondary battery (Sanyo, ML-2430, 100 mAh). The power conversion efficiency of the photodiode array varies with the voltage across it. The photodiode array sustains the best power conversion efficiency throughout the battery charge because the voltage across the photodiode array is regulated by the battery. Enhanced power conversion efficiency can be used to provide shorter charge time or reduced radiant power, or both. Animal studies have been conducted with the photodiode array completely implanted under the shaved abdominal skin of an anesthetised rat at 10 weeks of age. The pathlength of the rat skin over the photodiode array was 0.8 mm

Real-time broad-band measurement of cholesterol, collagen, and elastin using a novel rotary switch spectrometer

The present paper introduces an integrated sensing and processing spectroscopic system that combines Multivariate Factor Analysis (MFA) and Molecular Factor Computation (MFC) with a broad band light source, incorporating a rotary, multichannel optical device to produce real-time, spectroscopic analysis. The system is able to distinguish samples of cholesterol and collagen/elastin within a time range of 25 ms, by using near-infrared reflectance spectroscopy. The potential for the use of the device for in-vivo coronary angiography will be discussed. The system presents several key features that make it unique as a spectroscopic tool: it is compact and rugged with multilayer interference wavelength selection, and capable of operation in high vibration environments. The system is also fast, with the capacity to reduce the measurement delay even further; it is broad band, with a bandwidth limited by the optical source and the sensitivity of the photodetector used; it will allow quantitative, simultaneous, multispecies detection; and it is amenable to different optical delivery/detection schemes. Standard telecommunications-grade parts comprise the system, bridging the gap between the prototype and manufactured product; these include: optical fibers, electrically actuated optical switches, and free-space optics elements. A detailed description of the data analysis algorithm will be presented, with special emphasis on its use for multispecies detection.