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Raman spectroscopy is typically envisioned as an in situ analysis technique. Raman spectra measured remotely (10s of meters) from a planetary lander can be calibrated to spectral radiance and the Raman scattering efficiency can be determined.
Monolayer transition metal dichalcogenides (TMDs) are a key class of two-dimensional (2D) materials with broad technological potential. Their Janus counterparts exhibit unique properties due to broken out-of-plane symmetry and further enrich the functionalities of TMDs. However, experimental synthesis and identification of Janus TMDs remain challenging. It is thus highly desirable to have a rapid, simple, and in situ characterization technique to monitor, in real time, the conversion process from the parent to Janus structure. Raman spectroscopy stands out for such a task as it is a powerful, nondestructive, and very commonly used tool to characterize 2D materials both in situ and ex situ. To realize the full potential of Raman spectroscopy on rapid characterization of Janus TMDs, we present a computational “Raman digital twin” library for various monolayer Janus TMDs in both 2H and Td phases. We focus on group-6 TMDs: MoS 2 , WS 2 , MoSe 2 , WSe 2 , MoTe 2 , WTe 2 and their Janus variants: MoSSe, MoSTe, MoSeTe, WSSe, WSTe, and WSeTe. Using first-principles density functional theory (DFT), we calculate their vibrational properties and predict distinct Raman fingerprints. These phonon and Raman signatures reflect each material’s structural symmetry and atomic composition, enabling clear identification via Raman spectroscopy. Our theoretical work supports experimental efforts by providing benchmarks for material identification, structural analysis, and quality control. In conclusion, the computational library expedites the discovery and development of Janus 2D materials, facilitating tighter integration between theoretical predictions and experimental validation.
The Raman Code automates the analysis of laser-Raman-spectroscopy data for diagnosis of combustion at high pressure. On the basis of the theory of molecular spectroscopy, the software calculates the rovibrational and pure rotational Raman spectra of H2, O2, N2, and H2O in hydrogen/air flames at given temperatures and pressures. Given a set of Raman spectral data from measurements on a given flame and results from the aforementioned calculations, the software calculates the thermodynamic temperature and number densities of the aforementioned species. The software accounts for collisional spectral-line-broadening effects at pressures up to 60 bar (6 MPa). The line-broadening effects increase with pressure and thereby complicate the analysis. The software also corrects for spectral interference ("cross-talk") among the various chemical species. In the absence of such correction, the cross-talk is a significant source of error in temperatures and number densities. This is the first known comprehensive computer code that, when used in conjunction with a spectral calibration database, can process Raman-scattering spectral data from high-pressure hydrogen/air flames to obtain temperatures accurate to within 10 K and chemical-species number densities accurate to within 2 percent.
How can we use our current wealth of terrestrial data, encompassing biogenic and abiogenic systems, to determine the distinguishing properties of life? SCOBI (Statistical Classification of Biosignature Information) uses machine learning techniques to algorithmically identify combinations of measurements that are “indicative of life”. A set of ~1000 observations, comprising elemental abundance, isotopic fractionation, VNIR reflectance, and (in progress) Raman spectra, have been assembled from existing literature and databases. The observations cover systems classified as “indicative alive” (e.g., cells, vegetation), “indicative non-alive” (e.g., fossils, teeth), “mixed indicative” (e.g., soil, pond water), or “non-indicative” (e.g., rocks, meteorites). VNIR data was preprocessed by linear interpolation from 400-2100 nm and smoothed with a Savitzky-Golay filter. To limit the amount of Earth-biochemistry-specific (non-agnostic) information included, the first five spectral features extracted were number of peaks, number of troughs, mean reflectance, mean peak width, and broadest peak width. To help further emphasize agnostic biosignatures, Earth-specific features such as chlorophylls have been manually flagged so that feature importance with and without them can be compared. Classifiers including k-nearest neighbors (KNN), Gaussian Naïve Bayes (GNB), logistic regression (LR), random forest (RF), and support vector machine (SVM) were implemented, as was a combination voting classifier. Performance metrics included false positive rates, false negative rates, and AUC with 50-50 test/train splits (Monte Carlo simulations). Key takeaways from this stage, prior to the inclusion of Raman spectra, are (1) the overall success rate of 0.933 AUC was most heavily influenced by the elemental abundance data; and (2) VNIR reflectance had the lowest classification performance with 0.52 AUC (58% of objects correctly classified). The next steps are to complete integration of Raman spectral data and to improve the approach to pre-processing and feature extraction for both types of spectral data, such as automated baseline removal, whole spectrum matching, and dimensionality reduction.
Aerosols and their interactions and influence on clouds are among the main sources of uncertainties in radiative direct and indirect forcing (IPCC 2013). Continuous height-resolved measurements of cloud and aerosol optical properties are needed to reduce these uncertainties. Here we describe the Raman Lidar Profiles – Feature detection and Extinction (RLPROF-FEX) Value-Added Product (VAP) derived using Raman lidar data at multiple U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility sites. RLPROF-FEX provides estimates of extinction, backscatter, and depolarization using the algorithm described by Thorsen et al. 2015 and Thorsen and Fu 2015. This document provides a description of the FEX algorithm, its input and output data, and related details about the Raman lidar (RL) system.
La-Rh system study by powder X ray diffraction, metallographic and differential thermal analysis, constructing equilibrium diagram and determining crystal structure data
Raman spectroscopic data allow one to distinguish nickel electrode active mass, alpha and beta phase materials. Discharges active mass is not isostructural with beta-Ni(OH)2. This is contrary to the generally accepted model for the discharged beta phase of active mass. It is concluded that charged active mass displays a disordered and nonstoichiometric, nonclose packed structure of the R3 bar m, NiOOH structure type. Raman spectral data and x ray diffraction data are analyzed and shown to be consistent with this structural model.
Raman spectroscopic data allow one to distinguish nickel electrode active mass, alpha and beta phase materials. Discharges active mass is not isostructural with beta-Ni(OH)2. This is contrary to the generally accepted model for the discharged beta phase of active mass. It is concluded that charged active mass displays a disordered and nonstoichiometric, nonclose packed structure of the R3 bar m, NiOOH structure type. Raman spectral data and X ray diffraction data are analyzed and shown to be consistent with this structural model.
Aerosols are particles of different composition and origin and influence the formation of clouds which are important in atmospheric radiative balance. At the present there is high uncertainty on the effect of aerosols on climate and this is mainly due to the fact that aerosol presence in the atmosphere can be highly variable in space and time. Monitoring of the aerosols in the atmosphere is necessary to better understanding many of these uncertainties. A lidar (an instrument that uses light to detect the extent of atmospheric aerosol loading) can be particularly useful to monitor aerosols in the atmosphere since it is capable to record the scattered intensity as a function of altitude from molecules and aerosols. One lidar method (the Raman lidar) makes use of the different wavelength changes that occur when light interacts with the varying chemistry and structure of atmospheric aerosols. One quantity that is indicative of aerosol presence is the aerosol extinction which quantifies the amount of attenuation (removal of photons), due to scattering, that light undergoes when propagating in the atmosphere. It can be directly measured with a Raman lidar using the wavelength dependence of the received signal. In order to calculate aerosol extinction from Raman scattering data it is necessary to evaluate the rate of change (derivative) of a Raman signal with respect to altitude. Since derivatives are defined for continuous functions, they cannot be performed directly on the experimental data which are not continuous. The most popular technique to find the functional behavior of experimental data is the least-square fit. This procedure allows finding a polynomial function which better approximate the experimental data. The typical approach in the lidar community is to make an a priori assumption about the functional behavior of the data in order to calculate the derivative. It has been shown in previous work that the use of the chi-square technique to determine the most likely functional behavior of the data prior to actually calculating the derivative eliminates the need for making a priori assumptions. We note that the a priori choice of a model itself can lead to larger uncertainties as compared to the method that is validated here. In this manuscript, the chi-square technique that determines the most likely functional behavior is validated through numerical simulation and by application to a large body of Raman lidar measurements. In general, we show that the chi-square approach to evaluate aerosol extinction yields lower extinction uncertainty than the traditional technique. We also use the technique to study the feasibility of developing a general characterization of the extinction uncertainty that could permit the uncertainty in Raman lidar aerosol extinction measurements to be estimated accurately without the use of the chi-square technique.
Solid glyoxal Raman spectrum data, showing operativity of mutual exclusion principle by IR comparison to Raman bands
A dedicated analysis method is presented to extract the Raman spectrum of an interphase layer thinner than the laser spot size. We focused on spatial correlations between the contrast of optical micrographs and Raman hyperspectral data to predict the constituents of the mixed spectra measured near the interphase. By employing a mapping step size of 0.1 μm, the Raman spectrum of approximately 0.3-μm-thick carbon interphase in a SiC fiber-reinforced SiC matrix composite was extracted from data acquired with a theoretical spot size of about 0.7 μm. Notably, conventional chemometrics procedures were unable to isolate the interphase signal, instead producing a spectrum representing a mixture of interphase and matrix. This study used another composite with approximately 0.9-μm-thick interphase to validate the analysis method, enabling direct measurement of the interphase spectrum. The proposed Raman analysis method has advantages in specimen volume and turnaround time compared to traditional characterization methods, such as transmission electron microscopy. In conclusion, this study also evaluates the applicability of the analysis method to different composite materials and identifies key requirements of the measurements, including the ratio of interphase thickness to spot size and the homogeneity of the surrounding matrix.
Data supporting manuscript submitted to PNAS: Video-Rate Raman-based Metabolic Imaging by Airy Light-Sheet Illumination and Photon-Sparse Detection. The data set includes: [1] raw data and [2] related images used in the analyses described within the manuscript.
Raman lidar water vapor and aerosol extinction profiles acquired during the daytime over the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in northern Oklahoma (36.606 N, 97.50 W, 315 m) are evaluated using profiles measured by in situ and remote sensing instruments deployed during the May 2003 Aerosol Intensive Operations Period (IOP). The automated algorithms used to derive these profiles from the Raman lidar data were first modified to reduce the adverse effects associated with a general loss of sensitivity of the Raman lidar since early 2002. The Raman lidar water vapor measurements, which are calibrated to match precipitable water vapor (PWV) derived from coincident microwave radiometer (MWR) measurements were, on average, 5-10% (0.3-0.6 g/m(exp 3) higher than the other measurements. Some of this difference is due to out-of-date line parameters that were subsequently updated in the MWR PWV retrievals. The Raman lidar aerosol extinction measurements were, on average, about 0.03 km(exp -1) higher than aerosol measurements derived from airborne Sun photometer measurements of aerosol optical thickness and in situ measurements of aerosol scattering and absorption. This bias, which was about 50% of the mean aerosol extinction measured during this IOP, decreased to about 10% when aerosol extinction comparisons were restricted to aerosol extinction values larger than 0.15 km(exp -1). The lidar measurements of the aerosol extinction/backscatter ratio and airborne Sun photometer measurements of the aerosol optical thickness were used along with in situ measurements of the aerosol size distribution to retrieve estimates of the aerosol single scattering albedo (omega(sub o)) and the effective complex refractive index. Retrieved values of omega(sub o) ranged from (0.91-0.98) and were in generally good agreement with omega(sub o) derived from airborne in situ measurements of scattering and absorption. Elevated aerosol layers located between about 2.6 and 3.6 km were observed by the Raman lidar on May 25 and May 27. The airborne measurements and lidar retrievals indicated that these layers, which were likely smoke produced by Siberian forest fires, were primarily composed of relatively large particles (r(sub eff) approximately 0.23 micrometers), and that the layers were relatively nonabsorbing (omega(sub o) approximately 0.96-0.98). Preliminary results show that major modifications that were made to the Raman lidar system during 2004 have dramatically improved the sensitivity in the aerosol and water vapor channels and reduced random errors in the aerosol scattering ratio and water vapor retrievals by an order of magnitude.
Lithium isotopic ratios have wide ranging applications as chemical signatures, including improved understanding of geochemical processes and battery development. Measurement of isotope ratios using optical spectroscopies would provide an alternative to traditional mass spectrometric methods, which are expensive and often limited to a chemical laboratory. In this work, Raman spectra of 7 Li 2 CO 3 , 6 Li 2 CO 3 , 7 LiOH*H 2 O and 6 LiOH*H 2 O have been measured to determine the effect of lithium isotope substitution on the Raman molecular vibrations. Thirteen peaks were observed in the spectrum of lithium carbonate, with discernable isotopic shifts occurring in eleven of the thirteen vibrations, two of which have not been previously reported in the literature. The spectrum of lithium hydroxide monohydrate contained nine peaks, with discernable isotopic shifts occurring in eight of the nine vibrations, four of which have not been previously reported in the literature. The Raman spectral data reported here for lithium carbonate and lithium hydroxide monohydrate are in agreement with the previously reported works in the literature, in which the Raman active modes of these molecules were first identified and assigned. However, due to the stability and resolution of the detection system used in this work, isotopic shifts with a magnitude less than one wavenumber have been identified. Principal Component Regression was used to evaluate the sensitivity to isotopic content of small Raman peak shifts in Li 2 CO 3 and indicates differences greater than 2 atom-% could be reliably determined. These measurements add to the body of work on lithium isotope Raman spectroscopy for these two compounds and increases the number of Raman bands which could be used for lithium isotope content analysis.
Despite several theoretically proposed two-dimensional (2D) diamond structures, experimental efforts to obtain such structures are in initial stage. Recent high-pressure experiments provided significant advancements in the field, however, expected properties of a 2D-like diamond such as sp 3 content, transparency and hardness, have not been observed together in a compressed graphene system. Here, we compress few-layer graphene samples on SiO 2 /Si substrate in water and provide experimental evidence for the formation of a quenchable hard, transparent, sp 3 -containing 2D phase. Our Raman spectroscopy data indicates phase transition and a surprisingly similar critical pressure for two-, five-layer graphene and graphite in the 4e6 GPa range, as evidenced by changes in several Raman features, combined with a lack of evidence of significant pressure gradients or local non-hydrostatic stress components of the pressure medium up to ≈ 8 GPa. The new phase is transparent and hard, as evidenced from indentation marks on the SiO 2 substrate, a material considerably harder than graphene systems. Furthermore, we report the lowest critical pressure (≈ 4 GPa) in graphite, which we attribute to the role of water in facilitating the phase transition. Overall, theoretical calculations and experimental data indicate a novel, surface to- bulk phase transition mechanism that gives hint of diamondene formation.
The crystal chemistry of americium-containing extended structures was investigated, and several classes of americium-containing solid-state oxide materials were obtained in single-crystal form via high-temperature flux crystal growth. This enabled the structural characterization of rare examples of ternary, quaternary, and penternary americium-containing silicates K 3 Am (Si 2 O 7 ) and Cs 6 Am 2 Si 21 O 48 , phosphates Na 3 Am (PO 4 ) 2 and K 3 Am (PO 4 ) 2 , borates Ba 3 Am 2 (BO 3 ) 4 and AmBO 3 , borate halides Ca 5 Am(BO 3 ) 4 Cl, molybdates Li 0.5 Am 0.5 MoO 4 , and fluorides CsAm 2 F 7 . Using these crystallographic data, the ionic radii of Am 3+ with coordination numbers of six (0.975 Å), seven (1.052 Å), and nine (1.162 Å) were established. A maximum entropy method (MEM) analysis was performed on the single-crystal X-ray diffraction data that were collected for K 3 Nd(PO 4 ) 2 /K 3 Am(PO 4 ) 2 , K 3 NdSi 2 O 7 /K 3 AmSi 2 O 7 , and NdBO 3 /AmBO 3 , to qualitatively compare the ionicities of the Nd–O and Am–O bonds. In conclusion, Raman spectroscopy data were collected on single crystals of K 3 Am(PO 4 ) 2 and compared to the calculated Raman spectrum of K 3 Am(PO 4 ) 2 obtained from DFT calculations.
We introduce a stimulated Raman scattering (SRS) methodology designed for rapid, real-time, and in situ monitoring of RO membrane scaling adapted for bench-scale desalination flow cells. The methodology can provide new insights into membrane scaling dynamics by offering time-resolved reflection imaging of inorganic crystal growth, coupled with chemical identification from Raman spectral data. These capabilities allow for direct local measurement of the membrane surface area covered by different scalants as well as an approximation of the scalant volume using three-dimensional, integrated Raman intensity. The 2D and 3D SRS results obtained from CaSO 4 scaling experiments are compared to and are in reasonable agreement with those provided by confocal microscopy. The real-time physical and chemical characterization capabilities presented here could be extended to study combinations of inorganic, organic, and biological fouling. Overall, the SRS methodology represents an advancement in real-time sensing of membrane fouling that offers the potential for improved operation, lower cost, and more resilient RO membrane systems for sustainable water management.
The intent of this paper and its companion paper is to pull together the essential information required for the traditional Raman lidar data analysis to be performed. As a part of this, complications such as the temperature dependence of the water vapor signal is evaluated through numerical simulation. A new form of the lidar equation is presented that accounts for the temperature dependence of Raman scattering. Also the calculation of atmospheric transmission is examined carefully. Several photon correction techniques are considered as is the influence of multiple scattering on the measurement of aerosol extinction using the Raman lidar technique.