Applied Spectroscopy最新文献

Passive infrared (IR) systems enable rapid detection of chemical vapors but are limited by size, weight, cost, and power. Previously, the authors reported a novel passive sensor that utilizes multiple IR filter/detector combinations to discriminate between different chemical vapors based on their unique IR absorption spectra in the same manner the human eye uses to generate colors. This approach enables a very small, compact, and low-power sensor system with the capability to discriminate between chemical vapors of interest and background chemicals. All previous work showed the capability of this sensor system in discriminating chemical vapors against a hot blackbody in a laboratory environment. Now the authors demonstrate the ability of this sensor system to discriminate between the chemical vapor agent simulant dimethyl methylphosphonate and ethanol against the cold sky in an outdoor environment.

Noninvasive detection of surface-enhanced Raman spectroscopy (SERS) signals from deep within tissue represents a common challenge in many biological and clinical applications including disease diagnosis and therapy monitoring. Such signals are typically weak and not readily discernible from often much larger Raman and fluorescence background signals (e.g., from surrounding tissue). Consequently, suboptimal sensitivity in the detection of SERS signals is often achieved in these situations. Similar issues can arise in SERS measurements in other diffusely scattering samples and complex matrices. Here, we propose a novel concept, active SERS, for the efficient retrieval of SERS signals from deep within complex matrices such as biological tissues that mitigates these issues. It relies on applying an external perturbation to the sample to alter the SERS signal from nanoparticles (NPs) deep inside the matrix. A measurement with and without, or before and after, such perturbation then can provide powerful contrasting data enabling an effective elimination of the matrix signals to reveal more clearly the desired SERS signal without the interfering background and associated artifacts. The concept is demonstrated using ultrasound (US) as an external source of perturbation and SERS NPs inserted deep within a heterogeneous tissue phantom mimicking a cluster of NPs accumulated within a small target lesion. The overall SERS signal intensity induced by the applied US perturbation decreased by ∼21% and the SERS signal contrast was considerably improved by eliminating subtraction artifacts present in a conventional measurement performed at a neighboring spatial location in a heterogeneous tissue sample. Although the technique was demonstrated with SERS gold NPs with a standard Raman label, it is envisaged that active SERS NPs (both the nanoscale metal geometry and Raman label) could be specifically designed to deliver an augmented response to the external stimulus to further enhance the achievable SERS signal contrast and yield even greater improvement in detection sensitivity. The method was demonstrated using transmission Raman spectroscopy; however, it is also applicable to other Raman implementations including spatially offset Raman spectroscopy and conventional Raman spectroscopy performed both at depth and at surfaces of complex matrices.

The enhancement of Raman signals using photonic crystal structures has been the subject of numerous experimental and theoretical studies, leading to a variety of issues and inconsistencies. This paper presents a comprehensive experimental investigation into the impact of alignment between the laser excitation wavelength and the specific position of the photonic band gap on signal enhancement in Raman spectroscopy. By employing one-dimensional (1D) porous silicon photonic crystals, a systematic analysis across a large number of spectra was conducted. The study focused on examining the signal enhancement of both the Raman ∼520 cm^-1 silicon band, representing the constituent material of photonic crystal, and the most prominent Raman bands of crystal violet, used as a probe molecule. The probe molecules were both infiltrated into and adsorbed on top of the photonic crystal structure. The obtained experimental results for the contribution of 1D photonic crystals to Raman signal enhancement are much smaller compared to most predictions. The Raman signal of silicon and the signal from the probe molecule are enhanced ≤2.5 times when the laser excitation aligns with the edge of the photonic band gap, strictly defined as the position at the very bottom of the reflectance peak. The results have been discussed within the context of theoretical explanations.

Nondispersive ultraviolet visible gas analyzer designs were evaluated for monitoring molybdenum-containing chloride and oxychloride precursor delivery during microelectronics vapor deposition processes. The performances of three analyzer designs, which differed only in the bandpass filter employed for wavelength selection, were compared for measuring the partial pressure of molybdenum pentachloride, molybdenum oxytetrachloride (MoOCl₄), and molybdenum dioxydichloride (MoO₂Cl₂). The analyzer's optical response with a 369 nm center wavelength filter for molybdenum pentachloride was determined by measuring the molybdenum pentachloride absorbance as a function of vapor molar density. The calibrated analyzer was transferred to a process line on a deposition chamber and used to measure the molybdenum pentachloride partial pressure during delivery in a flowing carrier gas. The molybdenum pentachloride minimum detectable density was determined to be 1 × 10^-4 mol m^-3 (0.35 Pa for a cell temperature of 145 °C), for data collected at 1 kHz and referenced to a 0.2 s duration background. The analyzer optical response for molybdenum pentachloride with the two other filters and the response for MoOCl₄ and MoO₂Cl₂ with all three filters were simulated with a simple model. These data were used to evaluate the sensitivity and selectivity of analyzers incorporating the different filters to some likely combinations of analytes and interferents.

The perceived color of human skin is the result of the interaction of environmental lighting with the skin. Only by resorting to human skin spectral reflectance, it is possible to obtain physical outcomes of this interaction. The purpose of this work was to provide a cured and validated database of hyperspectral images of human faces, useful for several applications, such as psychophysics-based research, object recognition, and material modeling. The hyperspectral imaging data from 29 human faces with different skin tones and sexes, under constant lighting and controlled movements, were described and characterized. Each hyperspectral image, which comprised spectral reflectance of the whole face from 400 to 720 nm in 10 nm steps at each pixel, was analyzed between and within nine facial positions located at different areas of the face. Simultaneously, spectral measurements at the same nine facial positions using conventional local point and/or contact devices were used to ascertain the data. It was found that the spectral reflectance profile changed between skin tones, subjects, and facial locations. Important local variations of the spectral reflectance profile showed that extra care is needed when considering average values from conventional devices at the same area of measurement.

We present an attenuated total reflection (ATR) correction scheme capable of rectifying ATR spectra while considering the polarization state for arbitrary angles of incidence, provided that this angle exceeds the critical angle for the entire ATR spectrum. Due to its reliance on the weak absorption approximation, it cannot achieve perfect correction of the ATR spectra. However, comprehending its functionality may offer valuable insights into the concept behind the weak absorption approximation. Depending on the specific polarization state of an instrument accessory combination, this correction scheme may outperform the proprietary advanced ATR correction authored by ThermoFisher while being as user-friendly, but in contrast to the latter completely transparent with regard to its functionality.

This article provides a detailed discussion of the evidence available to date on the application of laser-induced breakdown spectroscopy (LIBS) and supervised classification methods for the individual reassignment of commingled bone remains. Specialized bone chemistry studies have demonstrated the suitability of bone elemental composition as a distinct individual identifier. Given the widely documented ability of the LIBS technique to provide elemental emission spectra that are considered elemental fingerprints of the samples analyzed, the analytical potential of this technique has been assessed for the investigation of the contexts of commingled bone remains for their individual reassignment. The LIBS bone analysis consists of the direct ablation of micrometric portions of bone samples, either on their surface or within their internal structure. To produce reliable, accurate, and robust bone classifications, however, the available evidence suggests that LIBS spectral information must be processed by appropriate methods. When comparing the performance of seven different supervised classification methods using spectrochemical LIBS data for individual reassociation, those employing artificial intelligence-based algorithms produce analytically conclusive results, concretely individual reassociations with 100% accuracy, sensitivity, and robustness. Compared to LIBS, other techniques used for the purpose of interest exhibit limited performance in terms of robustness, sensitivity, and accuracy, as well as variations in these results depending on the type of bones used in the classification. The available literature supports the suitability of the LIBS technique for reliable individual reassociation of bone remains in a fast, simple, and cost-effective manner without the need for complicated sample processing.

Time-resolved, rapid-scan Fourier transform infrared (FT-IR) difference spectra have been recorded upon illumination on photosynthetic reaction centers (RCs) from Rhodobacter sphaeroides under fixed hydration conditions (relative humidity = 76%). Two different illumination schemes were adopted. Whereas the use of a laser flash (duration: 7 ns) made it possible to follow the kinetics of recombination of the light-induced state P⁺Q_A^- to the neutral state PQ_A, the use of a 20.5 s continuous light from a lamp made it possible to follow both the build-up of a steady-state P⁺Q_A^- population and its decay to PQ_A. Comparison between P⁺Q_A^-/PQ_A FT-IR difference spectra obtained under (or 650 ms after) continuous illumination and obtained after one laser flash show small but meaningful differences, reflecting structural changes in the light-adapted state produced by the 20.5 s period of illumination. These differences are strikingly similar to those observed when comparing FT-IR difference spectra reflecting charge separation in photosystem II in light-adapted states and non-light-adapted states (c.f. Sipka et al., "Light-Adapted Charge-Separated State of Photosystem II: Structural and Functional Dynamics of the Closed Reaction Center". Plant Cell. 2021. 33(4): 1286-1302). Two-dimensional correlation spectroscopy analysis revealed that in all the observed series of time-resolved FT-IR difference spectra (under illumination, after illumination, and after a laser flash), marker bands at 1749, 1716, and 1668 cm^-1 all evolve synchronously, demonstrating that electron transfer reactions and protein backbone response (at least the one reflected by the 1668 cm^-1 band) are strongly correlated. Conversely, for spectra under and after continuous illumination, many asynchronicities are observed for (still unassigned) bands throughout the whole 1740-1200 cm^-1 region, reflecting a more complicated molecular scenario in the RC upon build-up of the light-adapted state and during its relaxation to the resting neutral state.

Impeding linear calibration models from accurately predicting target sample analyte amounts are the target sample-wise deviations in measurement profiles (e.g., spectra) relative to calibration samples. Target sample measurement shifts are due to uncontrollable factors, compositely termed matrix effects, such as temperature, instrument drift, and sample composition divergences relative to analyte and other species amounts altering inter and intramolecular interactions. One approach to circumvent the matrix effect matching problem is to use local modeling where a library with thousands of samples and respective reference analyte values is mined for unique calibration sets matched to each target sample, including analyte amounts between calibration and target samples. Current local modeling methods suffer because it is wrongly assumed similar measurements between calibration and target samples translate to a complete locally matched calibration set. Measurements can be similar, but the underlying matrix effects (and analyte amount) can be drastically different. The presented procedure named local adaptive fusion regression (LAFR) solves this matrix effect matching problem with crucial local modeling paradigm shifts. Expertise with LAFR is unnecessary because input hyperparameters are self-optimized. The capabilities of LAFR to form highly dense localized linear calibration sets matched to target samples spectrally and analyte amounts are verified using a well-studied nonlinear benchmark near-infrared (NIR) meat dataset, a NIR sugarcane dataset covering four major process steps with multiple subgroups within, and a NIR soil database of 98 910 samples spanning the contiguous USA. While LAFR is tested on NIR datasets, it is applicable to other measurement systems affected by matrix effects in a broad sense.