The 2017–2027 National Academies' Decadal Survey, Thriving on Our Changing Planet, recommended Surface Biology and Geology (SBG) as a “Designated Targeted Observable” (DO). The SBG DO is based on the ...need for capabilities to acquire global, high spatial resolution, visible to shortwave infrared (VSWIR; 380–2500 nm; ~30 m pixel resolution) hyperspectral (imaging spectroscopy) and multispectral midwave and thermal infrared (MWIR: 3–5 μm; TIR: 8–12 μm; ~60 m pixel resolution) measurements with sub-monthly temporal revisits over terrestrial, freshwater, and coastal marine habitats. To address the various mission design needs, an SBG Algorithms Working Group of multidisciplinary researchers has been formed to review and evaluate the algorithms applicable to the SBG DO across a wide range of Earth science disciplines, including terrestrial and aquatic ecology, atmospheric science, geology, and hydrology. Here, we summarize current state-of-the-practice VSWIR and TIR algorithms that use airborne or orbital spectral imaging observations to address the SBG DO priorities identified by the Decadal Survey: (i) terrestrial vegetation physiology, functional traits, and health; (ii) inland and coastal aquatic ecosystems physiology, functional traits, and health; (iii) snow and ice accumulation, melting, and albedo; (iv) active surface composition (eruptions, landslides, evolving landscapes, hazard risks); (v) effects of changing land use on surface energy, water, momentum, and carbon fluxes; and (vi) managing agriculture, natural habitats, water use/quality, and urban development. We review existing algorithms in the following categories: snow/ice, aquatic environments, geology, and terrestrial vegetation, and summarize the community-state-of-practice in each category. This effort synthesizes the findings of more than 130 scientists.
•The 2017 Decadal Survey recommended Surface Biology and Geology mission•Visible to shortwave infrared hyperspectral and multi-band thermal data•Global high resolution measurements at sub-monthly temporal resolution•Applications in snow/ice, aquatic environment, geology, and terrestrial vegetation•We review existing relevant algorithms and community-state-of-practice
Reflectance spectra of soil can be used to estimate the concentrations of organic carbon in soil (SOC). The estimates are more or less imprecise, but spectroscopy is quicker, less laborious and ...cheaper than conventional dry combustion analysis. Are the greater economy and efficiency sufficient to justify the loss of information arising from errors in estimation? We measured soil spectra with three instruments: a bench‐top mid‐infrared (mid‐IR) (mid‐IRb) spectrometer, a portable mid‐IR (mid‐IRp) spectrometer and a portable visible–near infrared (vis–NIRp) spectrometer. We calculated a quantity E to express the cost‐effectiveness of spectroscopic estimates relative to the conventional analysis, by accounting for their inaccuracy, their cost and their capacity, namely the maximum number of samples that can be prepared and measured daily. In all, 562 samples of soil were collected from 150 locations at four depths on a farm. The samples were dried and ground to particle sizes of ≤2 and ≤0.5 mm before measurements were made by dry‐combustion analysis. The machine learning algorithm Cubist was used to derive spectroscopic models of SOC concentrations and their uncertainties. We found that the mid‐IRb on the ≤0.5 mm samples was the most accurate and expensive but nevertheless sufficiently cost‐effective (large value of E) for determining the organic C. The mid‐IRp was somewhat more accurate, but its E was smaller than vis–NIRp on corresponding samples because it required more time to record the spectra. We also found that, with the portable spectrometers, the SOC predictions made on the ≤0.5 mm samples were somewhat more accurate than those made on the ≤2 mm samples, but their E was smaller because of the additional cost of sample preparation. The vis–NIRp on the ≤2 mm samples was the most cost‐effective for estimating SOC because it is cheap, accurate and has a large capacity for measurements.
Highlights
Concentrations of soil organic carbon (SOC) were determined by standard dry combustion and estimated from reflectance spectra recorded by three instruments.
The labour required for each of the techniques and the cost, including that of the equipment, were recorded.
A quantity E, expressing the cost‐effectiveness relative to dry combustion was calculated for each spectral technique, taking into account both accuracy and cost.
Dry combustion was always more accurate than estimates from spectra for individual samples, and the technique was also more cost‐effective for small numbers of samples.
The cost‐effectiveness of the spectral techniques varied among themselves, but all were more cost‐effective than dry combustion for large numbers of samples.
Abstract The possibility of inducing new polar and/or magnetic transient states through the pumping of optical phonons towards the non-linear regime has renewed the scientific interest in ...orthoferrites. Nonetheless, to perform these studies it is fundamental to have a deep knowledge of the lattice excitations at equilibrium conditions. In this work, we present a complete characterization of the optically-active zone-center phonons in NdFeO 3 single crystals at room temperature by means of polarized Raman and infrared spectroscopies. The study is complemented with polarized infrared spectroscopy at 4 K and unpolarized Raman scattering at 10 K. The predicted polar phonons were successfully observed together with some of the crystal-field excitations. First-principles simulations further allow the eigenmode and symmetry assignments of the optical phonons. The calculated atomic motions of each mode are of significant interest, as they are common for all orthoferrites and to most of the large family of orthorhombic Pbnm perovskites.
Vibrational spectroscopy techniques, such as Fourier-transform infrared (FTIR) and Raman spectroscopy, have been successful methods for studying the interaction of light with biological materials and ...facilitating novel cell biology analysis. Spectrochemical analysis is very attractive in disease screening and diagnosis, microbiological studies and forensic and environmental investigations because of its low cost, minimal sample preparation, non-destructive nature and substantially accurate results. However, there is now an urgent need for multivariate classification protocols allowing one to analyze biologically derived spectrochemical data to obtain accurate and reliable results. Multivariate classification comprises discriminant analysis and class-modeling techniques where multiple spectral variables are analyzed in conjunction to distinguish and assign unknown samples to pre-defined groups. The requirement for such protocols is demonstrated by the fact that applications of deep-learning algorithms of complex datasets are being increasingly recognized as critical for extracting important information and visualizing it in a readily interpretable form. Hereby, we have provided a tutorial for multivariate classification analysis of vibrational spectroscopy data (FTIR, Raman and near-IR) highlighting a series of critical steps, such as preprocessing, data selection, feature extraction, classification and model validation. This is an essential aspect toward the construction of a practical spectrochemical analysis model for biological analysis in real-world applications, where fast, accurate and reliable classification models are fundamental.
Fourier‐transform infrared spectroscopy (FTIR) is the golden standard of mid‐infrared (MIR) molecular spectroscopic analysis through optically encoded vibrational signatures. Michelson‐type FTIR and ...MIR dual‐comb spectrometers allow us to simultaneously investigate multiple molecular species via the broadband and high‐resolution spectroscopic capabilities. However, these are not applicable to high‐speed measurements due to the low temporal resolution which is fundamentally limited by the signal‐to‐noise ratio (SNR). In this study, a high‐speed FTIR spectroscopy technique called phase‐controlled Fourier‐transform infrared spectroscopy (PC‐FTIR) that has the capability to measure MIR absorption spectra at a rate of above 10 kHz is developed. PC‐FTIR demonstrates the high scan rate with a high SNR for various spectral bandwidths by arbitrarily adjusting the instrumental spectral resolution. As a proof of principle demonstration, high‐speed mixing dynamics of two liquids is measured at a rate of 24 kHz. MIR spectra of gas‐phase molecules are also measured with higher spectral resolution at a rate of 12 kHz. This high‐speed MIR spectrometer could be used especially for measuring non‐repetitive fast phenomena and acquiring a large amount of spectral data within a short time.
Rapid‐scan Fourier‐transform infrared spectroscopy with a phase‐controlled delay line that allows for measuring broadband MIR spectra of gas‐ and liquid‐phase molecules at a rate of above 10 kHz is demonstrated. This technique is to be especially useful for measuring non‐repetitive fast phenomena and acquiring a large amount of spectral data within a short time.
Last decade's advances and modern aspects of near infrared spectroscopy are critically examined and reviewed. Innovative instrumentation, highlighted by portable and imaging instruments, chemometrics ...data multivariate processing, and new and valuable applications are presented and discussed. Because of these advances, this mature analytical technique is continually experiencing renewed interest. The drawbacks and misuses of the technique and its supporting mathematical tools are also addressed. The principal achievements in the field are shown in a critical manner, in order to understand why the technique has found intensive application in the most diverse and modern areas of analytical importance during the last ten years.
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•State of the art of near infrared technology.•Critical review of modern near infrared spectroscopy.•The three sustaining pillars of near infrared spectroscopy.
A methanol economy will be favored by the availability of low‐cost catalysts able to selectively oxidize methanol to formate. This selective oxidation would allow extraction of the largest part of ...the fuel energy while concurrently producing a chemical with even higher commercial value than the fuel itself. Herein, we present a highly active methanol electrooxidation catalyst based on abundant elements and with an optimized structure to simultaneously maximize interaction with the electrolyte and mobility of charge carriers. In situ infrared spectroscopy combined with nuclear magnetic resonance spectroscopy showed that branched nickel carbide particles are the first catalyst determined to have nearly 100 % electrochemical conversion of methanol to formate without generating detectable CO2 as a byproduct. Electrochemical kinetics analysis revealed the optimized reaction conditions and the electrode delivered excellent activities. This work provides a straightforward and cost‐efficient way for the conversion of organic small molecules and the first direct evidence of a selective formate reaction pathway.
Highly active Ni3C branched particles are demonstrated and their selective electrocatalytic conversion of methanol to formate is probed by using advanced in situ infrared spectroscopy combined with nuclear magnetic resonance spectroscopy.
Microplastics in agricultural soils have become the research hotspot in recent years, however, the quantitative methods based on the traditional visual inspection may have a high false detection ...rate. Here we combined the laser direct infrared (LDIR) and Fourier–transform infrared (FTIR) methods to investigate the microplastics in farmland with long–term agricultural activities. The results showed that the total abundance of microplastics reached 1.98 ± 0.41 × 105, 1.57 ± 0.28 × 105, 1.78 ± 0.27 × 105, and 3.20 ± 0.41 × 105 particles/kg soil in cotton fields with film mulching of 5, 10, 20, and >30 years, respectively. LDIR results indicated that microplastics ranging from 10 to 500 μm accounted for 96.5–99.9 % of the total microplastic amounts in the soils. Additionally, a total of 26 polymer types of microplastics were detected, among which polyethylene (PE), polypropylene (PP), polyvinyl chloride (PVC), polyamide (PA), and polytetrafluoroethylene (PTFE) were dominantly observed. For the microplastics detected by FTIR (500 μm–5 mm), PE polymer was majorly observed (88.0–98.9 %). Most microplastics were films (88.2 %), while fibers and pellets were also found. The reclaimed water from sewage treatment plants, the drip irrigation utilities, and the residual plastic film are the potential sources of microplastics in the farmland soils. By using the automated quantitative and identifiable approaches, this study suggested that the commonly used visual counting method may underestimate the microplastic contamination in agricultural soils.
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•Using 8700 LDIR and ATR-FTIR to investigate the MPs in soil is rapid and accurate.•The abundance of MPs reached 105 particles/kg soil in Xinjiang province.•Totally 26 types of MPs are detected, and the majority were PP, PVC, PE and PA.•Film mulching and irrigation are important sources of MPs in agricultural soils.
The neural mechanism for the dyadic process of teaching is poorly understood. Although theories about teaching have proposed that before any teaching takes place, the teacher will predict the ...knowledge state of the student(s) to enhance the teaching outcome, this theoretical Prediction‐Transmission hypothesis has not been tested with any neuroimaging studies. Using functional near‐infrared spectroscopy‐based hyperscanning, this study measured brain activities of the teacher–student pairs simultaneously. Results showed that better teaching outcome was associated with higher time‐lagged interpersonal neural synchronization (INS) between right temporal‐parietal junction (TPJ) of the teacher and anterior superior temporal cortex (aSTC) of the student, when the teacher's brain activity preceded that of the student. Moreover, time course analyses suggested that such INS could mark the quality of the teaching outcome at an early stage of the teaching process. These results provided key neural evidence for the Prediction‐Transmission hypothesis about teaching, and suggested that the INS plays an important role in the successful teaching.
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