Applied Spectroscopy最新文献

In the first paper in this series, we proposed the use of a set of colored LEGO blocks as "standard" samples for the evaluation of fluorescence avoidance and mitigation schemes in Raman spectroscopy, as well as for use to evaluate the instruments' performance on dark samples. In the second paper we described the spectra obtained on the same blocks from ten different handheld Raman instruments. We found that the combination of a series of colored blocks (white, yellow, red, and blue), and successively darker tone blocks (white, gray, and black) do challenge these instruments and shed light on the ways that their manufacturers have optimized these instruments in specific areas and for different purposes. In this paper we extend the work using an advanced Raman data collection technique: A fast-repetition-rate, short-pulse, laser with a single-photon avalanche photodiode (SPAD) array detector capable of providing a time-sequence output, commonly known as a "time-gating" or "time-resolved" approach. The results are evaluated and compared to those in the first two papers. In addition, X-ray fluorescence (XRF) spectra were also collected to confirm identifications of some of the blocks' inorganic pigments, which were detected via their Raman spectra.

Optical identification of liquid droplets, aerosols, or thin films is critical for many applications. While reference spectra are sometimes available for such measurements, they are not always applicable to the observed spectrum or the given sample morphology. Reference spectra for many forms can be modeled, however, if the n/k vectors (real and imaginary refractive indices) are available. In previous work we have reported protocols to determine the n/k vectors for dozens of liquids, primarily in the mid-infrared (MIR) spectral range from 7500 to 400 cm^-1. In this work we extend the spectral range into the near-infrared (NIR) region, demonstrating a method to measure and merge the data sets to create composite n/k data ranging from 10 000 to 400 cm^-1 (1.0 to 25 µm) with absorbance fidelity spanning over four orders of magnitude, and vastly improved signal-to-noise in the NIR. The precision of the composite data is evaluated for three different liquids, focusing primarily on the steps for converting the raw absorbance spectra to k values. The variability in both MIR and NIR data as well as in the final n/k vectors is also investigated for several liquids. For typical liquids, the overall variability (reported as 2σ) in the final n and k-vectors is determined to be ∼0.4% and 3%, respectively. Finally, the derived n/k data are used to calculate absorbance spectra for aerosol droplets, showing marginal variability due to the typical measurement errors in the final n/k vectors.

In this paper, a lanthanide complex-based fluorescent sensor Tb(4-MBA) was developed for the selective recognition of diabetic ketoacidosis (DKA) and the diabetes biomarker β-hydroxybutyric (β-Hb). β-Hb significantly enhanced the fluorescence emission of the Tb(4-MBA) complex at 539  nm. Based on the analysis of the surface electrostatic potential distribution and time-resolved spectra, we speculate that in the reaction system of β-Hb with Tb(4-MBA), β-Hb and Tb(4-MBA) may form a complex through hydrogen bonding interactions, which brings β-Hb closer to Tb³⁺ and thus reduces the non-radiative energy loss of the solvent molecules to Tb³⁺ and significantly enhances the Tb(4-MBA) fluorescence intensity. The linear range of Tb(4-MBA) for β-Hb was 2-55 μM, and the limit of detection (LOD) was 50.6 nM. This sensor has high sensitivity and selectivity and shows great potential in the field of screening and diagnosis of diabetes mellitus and DKA.

Tropical mosquitoes transmit diseases like malaria, yellow fever, and Zika. Classifying mosquitoes by species, sex, age, and gravidity offers vital insights for assessing transmission risk and effective mitigations. Photonic monitoring for mosquito classification can be used in distributed sensors or lidars on longer ranges. However, a reflectance model and its parameters are lacking in the current literature. This study investigates mosquitoes of different species, sexes, age groups, and gravidity states, and reports metric pathlengths of wing chitin, body melanin, and water. We use hyperspectral push-broom imaging and laser multiplexing with a rotation stage to measure near-infrared spectra from different angles and develop simple models for spectral reflectance, including wing thickness and equivalent absorption path lengths for melanin and water. We demonstrate wing thickness of 174 (±1) nm - the thinnest wings reported to our knowledge. Water and melanin pathlengths are determined with ∼10 µm precision, and spectral models achieve adjusted R² values exceeding 95%. While mosquito aspect angle impacts the optical cross-section, it alters shortwave infrared spectra minimally (∼2%). These results demonstrate the potential for remote retrieval of micro- and nanoscopic mosquito features using spectral sensors and lidars irrespective of insect body orientation. Improved specificity of vector monitoring can be foreseen.

The waxy gene of maize is a high value breeding target, but it is time consuming to separate waxy and wild-type kernels. A common method involves staining the endosperm with iodine. Near-infrared reflectance (NIR) spectroscopy has been used in several species including maize with success. A custom-built single kernel NIR spectroscopy instrument was used to scan 2880 individual kernels from 60 samples with a diversity of pedigrees, with both waxy, wild type, and heterozygous kernels represented. Chemical analysis was performed to classify the kernels with the waxy or wild type phenotypes. Linear discriminant analysis (LDA) was conducted to develop a prediction equation for single kernel NIR spectroscopy. The discriminant results showed that there was an 88% accuracy in predicting waxy kernels as waxy, and a 96% accuracy in predicting wild type kernels as wild type. A receiver operating characteristic (ROC) curve was determined to allow threshold adjustment to meet desired true positive or false negative rates. Thus, the prediction equation can be used in breeding programs to select for waxy kernels in an efficient and effective manner using a single kernel NIR instrument. This approach will benefit breeders of waxy corn by providing a rapid, automated non-destructive method for identification of waxy kernels in segregating breeding populations.

Polymer films with a thickness in the two-digit micrometer range are coated with nanometer-thin oxide layers in roll-to-roll coating systems. The coating improves the properties of the film, such as gas or water permeation. Maintaining a sufficiently large coating thickness is crucial to ensure its barrier function; thus, inline quality control of the thickness is indispensable. For this purpose, we have developed a sensing principle that addresses specific absorption bands of the coating via a reflection measurement in the infrared spectral range. However, for thin and weakly absorbing polymer substrates, light is reflected not only by the coating and the surface of the polymer. Partly it is also transmitted and reflected by the backside of the film, leading to interference effects that significantly affect the measurement signal. As industrial films vary in thickness by several percent and their exact values are unknown, determining the thickness of an oxide coating is hindered. In this paper, we demonstrate an approach for measuring coating thickness on such varying polymer films by averaging the interferences obtained at multiple angles of incidence. Calculations and measurements on industrial film samples indicate the effectiveness of our approach. It produces results with $\pm 2$ nm precision and $\pm 5$ nm accuracy for a thickness in the range of 5-100 nm. Furthermore, we discuss a possible implementation of this approach in an inline measurement system by fulfilling its requirements, for example, versatility and compactness.

This paper presents a novel analytical technique for evaluating fluorescence lifetimes excited by a nanosecond pulsed laser using a linearized rate equation approach that accounts for the incident pulse temporal distribution, an equivalent instrument response function, and non-exponential fluorescence decay which limits the application of traditional fluorescence lifetime techniques in stand-off applications. The approach is applied to model the fluorescence of a variety of pharmaceutical powders and phosphorescing samples exhibiting non-exponential decay and compared to results obtained with the maximum entropy method. Fluorescence lifetimes are found to be 3-5  ns, typical for organic fluorescent powders, and phosphorescence lifetimes were on the order of hundreds of nanoseconds. The approach also shows potential for determining the composition of mixed samples and can be readily extended to model increasingly complex scenarios with additional fluorescing or phosphorescing components.

In-line monitoring of continuous crystallization processes can provide real-time information about the polymorph composition, potentially providing a superior understanding and control of the crystallization kinetics throughout the process. Here, we present a case study using in-line Raman spectroscopy as a process analytical technology (PAT) tool to enable fast, in-situ, non-destructive, and quantitative measurement of complex polymorphic transitions during flow-induced continuous crystallization of a model compound, which has two main polymorphs only showing subtle differences in the fingerprint regions of their Raman spectra. Second derivative Raman spectra were used for qualitative monitoring of polymorph changes, and a Gaussian curve fitting method was developed and utilized for quantitative determinations of polymorph compositions in continuous crystallizations under an array of process conditions. This study illustrates the complex and dynamic nature of polymorph transitions during continuous crystallization under various process conditions as well as the ability of in-line Raman spectroscopy to monitor the process qualitatively and quantitatively in order to have greater understanding of the process design space and to avoid conditions that lead to undesired polymorphs in the crystallization process.

Classical quantitative chemometrics based on absorbance spectra has been routinely performed for approximately 40 years. Since absorbance is a function of the absorption index, it is natural to extend chemometric methods to the refractive index function. This function, related to the absorption index via the Kramers--Kronig relations, is derived from corrections applied to absorbance spectra to ensure compliance with wave optics principles. In this note, we demonstrate that, at least in the quasi-thermodynamically ideal binary system of benzene and toluene, classical quantitative chemometrics performs better when based on refractive index spectra than when based on absorption index spectra. The primary reason for this difference is that the refractive index at a given wavenumber integrates all changes resulting from absorptions at higher wavenumbers. This property is particularly advantageous in non-absorbing regions, where absorption index spectra provide no information about the system's composition.