Raman Characterization Research Articles

Surface Fluorination of Nuclear Graphite Exposed to Molten 2LiF-BeF2 (FLiBe) Salt and Its Cover Gas at 700 °C.

This study demonstrates that the reaction of Li2BeF4 (FLiBe) with graphite both in the liquid phase and the gas phase of the molten salt leads to the formation of covalent and semi-ionic carbon-fluorine bonds at the graphite surface and is accompanied by surface microstructural changes, removal of C-O groups, and deposition of metallic beryllium, based on XPS, Raman, and glow discharge mass spectroscopy characterization. At 700 °C, the observed surface density of C-F is higher after 240 h than after 12 h of exposure to molten FLiBe salt; the kinetics of covalent C-F formation is slower than that of semi-ionic C-F formation, and the relative amount of semi-ionic C-F content increases with depth. The graphite sample exposed to the cover gas exhibits less surface fluorination than the salt-exposed sample, with predominantly semi-ionic C-F. Based on these observations and the observed LiF/BeF2 ratio by surface XPS, the hypotheses that fluorination of the salt-exposed graphite occurs via a gas-phase mechanism or that it requires salt intrusion are refuted; future studies are warranted on the transport of C-F semi-ionic and covalent species in graphite at high temperatures.

Optical, Structural, and Synchrotron X-ray Absorption Studies for GaN Thin Films Grown on Si by Molecular Beam Epitaxy.

GaN on Si plays an important role in the integration and promotion of GaN-based wide-gap materials with Si-based integrated circuits (IC) technology. A series of GaN film materials were grown on Si (111) substrate using a unique plasma assistant molecular beam epitaxy (PA-MBE) technology and investigated using multiple characterization techniques of Nomarski microscopy (NM), high-resolution X-ray diffraction (HR-XRD), variable angular spectroscopic ellipsometry (VASE), Raman scattering, photoluminescence (PL), and synchrotron radiation (SR) near-edge X-ray absorption fine structure (NEXAFS) spectroscopy. NM confirmed crack-free wurtzite (w-) GaN thin films in a large range of 180-1500 nm. XRD identified the w- single crystalline structure for these GaN films with the orientation along the c-axis in the normal growth direction. An optimized 700 °C growth temperature, plus other corresponding parameters, was obtained for the PA-MBE growth of GaN on Si, exhibiting strong PL emission, narrow/strong Raman phonon modes, XRD w-GaN peaks, and high crystalline perfection. VASE studies identified this set of MBE-grown GaN/Si as having very low Urbach energy of about 18 meV. UV (325 nm)-excited Raman spectra of GaN/Si samples exhibited the GaN E2(low) and E2(high) phonon modes clearly without Raman features from the Si substrate, overcoming the difficulties from visible (532 nm) Raman measurements with strong Si Raman features overwhelming the GaN signals. The combined UV excitation Raman-PL spectra revealed multiple LO phonons spread over the GaN fundamental band edge emission PL band due to the outgoing resonance effect. Calculation of the UV Raman spectra determined the carrier concentrations with excellent values. Angular-dependent NEXAFS on Ga K-edge revealed the significant anisotropy of the conduction band of w-GaN and identified the NEXAFS resonances corresponding to different final states in the hexagonal GaN films on Si. Comparative GaN material properties are investigated in depth.

Vanadium pentoxide nanowires preparation via kinetic control of vanadium oxytrichloride catalytic oxidation with APCVD

Vanadium pentoxide nanowires were successfully fabricated using vanadium oxytrichloride oxidation with copper oxide nanoparticles serving as catalysts via atmospheric pressure chemical vapor deposition. Kinetic parameters such as temperature and flow velocity were proved to play important roles in the morphologic control of as-deposited product. Vanadium pentoxide nanowires with an average length of ∼10 μm and a diameter of 50–100 nm, were obtained under the optimum conditions. A root growth mechanism of nanowires was proposed that precursor was readily captured by catalyst nanoparticles at the beginning of deposition, forming nucleation sites. Subsequently, the anisotropic growth of vanadium pentoxide is primarily governed by energy minimization under the reaction rate limited conditions. The presence of oxygen vacancies in the nanowires was confirmed by Raman, XPS and photoluminescence characterization, indicating promising applications in functional materials manufacture. The novel route for preparing vanadium pentoxide nanowires provides an alternative pathway for transitioning traditional vanadium industry towards advanced functional materials development.

The influence of debromination and TR on the microstructure and properties of CMSMs

One unique challenging in achieving advanced carbon molecular sieve membranes (CMSMs) is tailoring their gas separation properties from the precursor. To clarify this, we designed two homo-polyimides with a bromine (PI-Br) and a hydroxyl (PI-OH) groups in the ortho position of imide group, and carbonized them into CMSMs at 550 °C (PI-Br-550 and PI-OH-550). There are debromination (510 °C) and carbonization occurred for PI-Br-550 whereas the PI-OH underwent thermally rearrangement (TR, 450 °C) and then pyrolysis to CMSM. After carbonization, both CMSMs showed excellent gas separation properties, with their CO2/CH4 separation performance surpassed the latest 2019 pure-gas and 2018 mixed-gas trade-off curves, additionally, the PI-Br-550 demonstrated a relatively smaller CO2 permeability (12462 vs 14,253 Barrer), lower PCO2 increment ratio (199 vs 1480), and less CO2/CH4 dropping ratio (69.7 to 45.5 vs 87.5 to 36.1) than the PI-OH-550 from their precursors. Their XPS, Raman, and WXRD characterization results indicated that debromination boosts the gas separation performance of CMSM by creating more ultra-micropore “plate” (pyrrolic-N of 36.0 % vs 19.0 %) and smaller d-spacing (3.89 vs 4.15 Å) than the TR precursor, which boosts the permeability of CMSM is due to the high stability of PBO intermediates that retarded the decomposition of the polymer main chian and caused some big pores. The above results provided a good route to get highly efficient CMSM by molecular designing of their precursors.

Identification of hypermucoviscous Klebsiella pneumoniae K1, K2, K54 and K57 capsular serotypes by Raman spectroscopy

Antimicrobial resistance poses a significant challenge in modern medicine, affecting public health. Klebsiella pneumoniae infections compound this issue due to their broad range of infections and the emergence of multiple antibiotic resistance mechanisms. Efficient detection of its capsular serotypes is crucial for immediate patient treatment, epidemiological tracking and outbreak containment. Current methods have limitations that can delay interventions and increase the risk of morbidity and mortality. Raman spectroscopy is a promising alternative to identify capsular serotypes in hypermucoviscous K. pneumoniae isolates. It provides rapid and in situ measurements with minimal sample preparation. Moreover, its combination with machine learning tools demonstrates high accuracy and reproducibility. This study analyzed the viability of combining Raman spectroscopy with one-dimensional convolutional neural networks (1-D CNN) to classify four capsular serotypes of hypermucoviscous K. pneumoniae: K1, K2, K54 and K57. Our approach involved identifying the most relevant Raman features for classification to prevent overfitting in the training models. Simplifying the dataset to essential information maintains accuracy and reduces computational costs and training time. Capsular serotypes were classified with 96 % accuracy using less than 30 Raman features out of 2400 contained in each spectrum. To validate our methodology, we expanded the dataset to include both hypermucoviscous and non-mucoid isolates and distinguished between them. This resulted in an accuracy rate of 94 %. The results obtained have significant potential for practical healthcare applications, especially for enabling the prompt prescription of the appropriate antibiotic treatment against infections.

Accurate and rapid molecular subgrouping of high-grade glioma via deep learning-assisted label-free fiber-optic Raman spectroscopy.

Molecular genetics is highly related with prognosis of high-grade glioma. Accordingly, the latest WHO guideline recommends that molecular subgroups of the genes, including IDH, 1p/19q, MGMT, TERT, EGFR, Chromosome 7/10, CDKN2A/B, need to be detected to better classify glioma and guide surgery and treatment. Unfortunately, there is no preoperative or intraoperative technology available for accurate and comprehensive molecular subgrouping of glioma. Here, we develop a deep learning-assisted fiber-optic Raman diagnostic platform for accurate and rapid molecular subgrouping of high-grade glioma. Specifically, a total of 2,354 fingerprint Raman spectra was obtained from 743 tissue sites (astrocytoma: 151; oligodendroglioma: 150; glioblastoma (GBM): 442) of 44 high-grade glioma patients. The convolutional neural networks (ResNet) model was then established and optimized for molecular subgrouping. The mean area under receiver operating characteristic curves (AUC) for identifying the molecular subgroups of high-grade glioma reached 0.904, with mean sensitivity of 83.3%, mean specificity of 85.0%, mean accuracy of 83.3%, and mean time expense of 10.6 s. The diagnosis performance using ResNet model was shown to be superior to PCA-SVM and UMAP models, suggesting that high dimensional information from Raman spectra would be helpful. In addition, for the molecular subgroups of GBM, the mean AUC reached 0.932, with mean sensitivity of 87.8%, mean specificity of 83.6%, and mean accuracy of 84.1%. Furthermore, according to saliency maps, the specific Raman features corresponding to tumor-associated biomolecules (e.g. nucleic acid, tyrosine, tryptophan, cholesteryl ester, fatty acid, and collagen) were found to contribute to the accurate molecular subgrouping. Collectively, this study opens up new opportunities for accurate and rapid molecular subgrouping of high-grade glioma, which would assist optimal surgical resection and instant post-operative decision-making.

Coherent Vibrations Promote Charge-Transfer across a Graphene-Based Interface.

Discerning the impact of the coherent motion of the nuclei on the timing and efficiency of charge transfer at the donor-acceptor interface is essential for designing performance-enhanced optoelectronic devices. Here, we employ an experimental approach using photocurrent detection in coherent multidimensional spectroscopy to excite a donor aromatic macrocycle and collect the charge transferred to a 2D acceptor layer. For this purpose, we prepared a cobalt phthalocyanine-graphene (CoPc-Gr) interface. Unlike blends, the well-ordered architecture achieved through the physical separation of the two layers allows us to unambiguously collect the electrical signal from graphene alone and associate it with a microscopic understanding of the whole process. The CoPc-Gr interface exhibits an ultrafast electron-transfer signal, stemming from an interlayer mechanism. Remarkably, the signal presents an oscillating time evolution modulated by coherent vibrations originating from the laser-excited CoPc states. By performing Fourier analysis on the beatings and correlating it with the Raman features, along with a comprehensive first-principles characterization of the vibrational coupling in the CoPc excited states, we successfully identify both the orbitals and molecular vibrations that promote the charge transfer at the interface.

Effect of process parameters on microstructure and Raman characteristics of magnesium doped ZnO thin films

MgxZn1-xO thin films were prepared on glass substrates by radio frequency magnetron sputtering under different sputtering processes. The surface morphology, microstructure, and Raman characteristics of the films were studied using scanning electron microscopy (SEM), X-ray diffraction (XRD), and Raman Spectrometer. The results show that an increase in the O/Ar ratio decreases the surface smoothness of the thin film and worsens the particle uniformity. The particles of undoped Magnesium doped Zinc Oxide (ZnO) films are small and uniform, and the uniformity of the particles in the films becomes worse after doping. Moreover, there are multiple diffraction peaks in the magnesium doped Zinc Oxide films, presenting a polycrystalline state, but the diffraction peak positions do not significantly change with the concentration and intensity of magnesium doped. The Raman characteristic peak undergoes a blue shift with the increase of magnesium doping concentration, and the peak position shifts from 573 cm−1 to 607 cm−1.

Ionic Liquid‐Induced Product Switching in CO2 Electroreduction on Copper Reaction Interface

AbstractThe electrochemical reduction of CO2 (CO2RR) mainly occurs at the three‐phase interface, and the properties of an interface can directly affect the CO2RR pathway. Cu‐based materials can produce considerable amounts of alcohols and hydrocarbons, but it is hard to precisely regulate the reaction interface and obtain specific target products. Herein, the properties of the Cu surface through a facile strategy of ionic liquid modification are successfully adjusted. According to theoretical calculations and in situ Raman and FTIR spectra characterizations, it is revealed that the introduction of ionic liquids (e.g., [Bmim][PF6]) can control the energy barriers and distribution density of key intermediates on Cu interface, thus totally change the reaction pathway of CO2 electroreduction. Consequently, the dominant products from the Cu catalyst will be dramatically switched between C2H4 with a 71.1% Faraday efficiency (FE) and CH4 with a 67.2% FE. It is rarely seen in previous reports that the CO2RR products can be fundamentally changed through simple interface modifications. This work offers a straightforward approach to tune the interfacial properties and understand the mechanisms in various electrocatalytic reactions.

Optimizing the electromagnetic wave absorption properties of core-shell Fe/FeN/Fe3C@GN nanoparticles by low-temperature NH3 plasma

Surface modification via low-temperature plasma has an extensive application prospect in different engineering fields due to its comprehensive merits in facilitating the introduction of functional groups and creating more heterogeneous interfaces. Herein, a simple high-temperature plasma method is developed to get novel multiple-phase nanocomposites of core-shell Fe/FeN/Fe3C@GN nanoparticles with bifunctional characteristics of microwave absorption (MA) and anti-corrosion. And then, we further investigate the MA properties of Fe/FeN/Fe3C@GN nanoparticles after low-temperature NH3 plasma etching. It is found that surface modification of Fe/FeN/Fe3C@GN nanoparticles can generate remarkable changes in specific surface areas, Raman features and MA properties of these nanocomposites. The Fe/FeN/Fe3C@GN nanoparticles after NH3 plasma etching possess excellent MA properties with an optimal reflection loss (RL) of −51.0 dB at an ultra-thin thickness of 1.9 mm with a low filling content of 30 wt% and the corresponding effective absorption bandwidth (EAB < −10 dB) up to 4.7 GHz (13.3–18.0 GHz). The fascinating MA properties of etched Fe/FeN/Fe3C@GN nanoparticles may be attributed to the cooperative effect of several points: (i) The NH3 plasma etch introduces a large number of polar functional groups, which can be regarded as the polarization center to produce more polarization loss; (ii) The appropriate dielectric loss and impedance matching achieve a good balance, and the abundant heterogeneous interface significantly enhances the polarization relaxation loss; (iii) The existence of hetero-nanostructure further improves the multiple reflections and scattering of the propagating microwaves. In addition, this work provides a new strategy for the design and fabrication of core-shell MA materials.

Electron Manipulation and Surface Reconstruction of Bimetallic Iron-Nickel Phosphide Nanotubes for Enhanced Alkaline Water Electrolysis.

Developing high-efficiency and stable bifunctional electrocatalysts for water splitting remains a great challenge. Herein, NiMoO4 nanowires as sacrificial templates to synthesize Mo-doped NiFe Prussian blue analogs are employed, which can be easily phosphorized to Mo-doped Fe2xNi2(1-x)P nanotubes (Mo-FeNiP NTs). This synthesis method enables the controlled etching of NiMoO4 nanowires that results in a unique hollow nanotube architecture. As a bifunctional catalyst, the Mo-FeNiP NTs present lower overpotential and Tafel slope of 151.3 (232.6) mV at 100 mA cm-2 and 76.2 (64.7) mV dec-1 for HER (OER), respectively. Additionally, it only requires an ultralow cell voltage of 1.47 V to achieve 10 mA cm-2 for overall water splitting and can steadily operate for 200 h at 100 mA cm-2. First-principles calculations demonstrate that Mo doping can effectively adjust the electron redistribution of the Ni hollow sites to optimize the hydrogen adsorption-free energy for HER. Besides, in situ Raman characterization reveals the dissolving of doped Mo can promote a rapid surface reconstruction on Mo-FeNiP NTs to dynamically stable (Fe)Ni-oxyhydroxide layers, serving as the actual active species for OER. The work proposes a rational approach addressed by electron manipulation and surface reconstruction of bimetallic phosphides to regulate both the HER and OER activity.

Boosting sunlight driven photocatalytic and catalytic performance of ZnFe2O4-ZnO nanohybrids by loading Ag nanoparticles

We report facile fabrication of magnetically separable Ag@ZnFe2O4-ZnO plasmonic hybrid nanostructures by a simple wet chemical route combined with cost-effective photodeposition. The successful formation of Ag@ZnFe2O4-ZnO hybrid nanostructures was confirmed using XRD, Raman, FESEM, TEM, HRTEM and SAED characterizations. The catalytic and photocatalytic capabilities of the synthesized magnetic Ag@ZnFe2O4-ZnO plasmonic hybrid nanostructures were evaluated with regard to 4-NP to 4-AP reduction in dark and photodecomposition of major anionic and cationic pollutants (MB, MG, MO, RhB) and emerging pollutant levofloxacin antibiotic under sunlight illumination, respectively. Results showed that Ag@ZnFe2O4-ZnO hybrid nanostructures exhibit excellent catalytic as well as photocatalytic response and reduced 98.1 % of 4-NP in only 6 min and decolorized 92.9, 93, 43.4 and 73.3 % of MB, MG, MO and RhB within only 18 min and 90.5 % of levofloxacin in 40 min of sun light irradiation, respectively. Further, the synthesized nanohybrids possess high stability and can be magnetically recovered due to its good magnetic response. In addition, the trapping experiments indicated that the main active compounds for the photodegradation of dyes are OH radicals. We demonstrate that the prepared Ag@ZnFe2O4-ZnO plasmonic hybrid nanostructures have potential application towards decomposition of organic pollutants and other emerging pollutants in wastewater for environmental remediation.

Lattice dynamics in the FeSi-based family of superconductors

The lattice dynamics of the superconducting materials LaFeSiH and LaFeSiO1-δ as well as their intermetallic precursor LaFeSi are investigated by polarized Raman spectroscopy and first-principles calculations, together with X-ray and advanced electron diffraction techniques for their structural analysis. We find that the Fe-dominated Raman-active modes reflect the chemical peculiarities of these silicides compared to their pnictide counterparts, with enhanced structural couplings between the FeSi layer and the spacer that can be related to the ionic vs. covalent character of the latter. In addition, we find signatures of enhanced electron-phonon coupling for some of the Raman-active modes. Beyond that, our study reveals intriguing Fe-based Raman features as well as structural subtleties in LaFeSiH suggesting that this superconductor may formally be non-centrosymmetric.

RGO@TiO2-x Schottky heterojunction for enhanced bidirectional catalysis in polysulfide conversion

The shuttling and sluggish conversion kinetics of lithium polysulfides (LiPSs) lead to poor cycling performance and low energy efficiency in lithium-sulfur batteries (LSBs). In this work, a hierarchically structured nanocomposite, synthesized through a surfactant-directed hydrothermal growth following dopamine-protected pyrolysis, serves as a bidirectional catalyst for LSBs. This nanocomposite comprises N-doped reduced graphene oxide (rGO) nanosheets anchored with uniformly distributed TiO2-x nanoparticles via interfacial N-Ti and C-Ti bonding, resulting in the formation of abundant 2D/0D Schottky heterojunctions (rGO/TiO2-x). Density functional theory (DFT) calculations and in situ Raman characterizations demonstrate that rGO/TiO2-x effectively inhibits the shuttling of LiPSs with enhanced redox kinetics, achieving high utilization of the sulfur cathode and improving the overall reversibility. A high areal capacity is attained at a high sulfur loading and a low electrolyte/sulfur ratio. The initial specific capacity reaches 1010 mA h g−1 at a current density of 0.2C (1C = 1675 mA g−1), and a retention of 86.4 % is attained over 100 cycles. A light-emitting diode (LED) screen using two LSBs with rGO/TiO2-x demonstrates their high potential for practical applications.

Estimating Modal Mineralogy using Raman Spectroscopy: Multivariate Analysis Models and Raman Cross-Section Proxies

Abstract Raman spectroscopy is a powerful technique in the context of planetary exploration because it provides mineral identification, chemistry, and abundance information. For Raman spectrometers with large spot sizes, multiple mineral phases can be investigated via the collection of a single Raman spectrum. There is a lack of methodology for quantifying mineral species in mixtures due to independent signal strengths of different materials in Raman spectra. Two techniques are presented in this work for the quantification of common rock-forming minerals: partial least squares multivariate analysis and a novel approach called Raman cross-section proxies (numerical metrics associated with specific Raman features). This paper targets 20 mineral species relevant to the mineralogy of the planet Mars. Mineral end-member samples and 187 binary mineral-mineral mixtures (mixture of two distinct minerals) are used for multivariate modeling. Eighteen diamond-mineral mixtures are used to derive Raman cross-section proxies. Mineral abundance proportions are predicted for the binary mineral-mineral mixtures with known mineralogical content to evaluate the efficacy of the two quantitative methods. Technique performance is mineral-dependent. The root-mean-square error for unseen predictions (RMSE-P) using Raman cross-section proxies ranges from ±3.2-17.0 volume%. For the multivariate models, the cross-validated root-mean-square error (RMSE-CV) ranges from ±8.8 to 26.2 volume%. Although these error estimates are not directly comparable, they provide the most accurate error estimate currently available. Different scenarios may favor the use of one or the other of the two quantitative methods. This work provides fundamental groundwork that can be applied to common rock-forming minerals on terrestrial planets including Mars. Quantification of mineral abundances aids in answering critical geologic questions related to ancient primary and altered rocks as well as planetary processes and conditions.

Nitrogen-Doped Porous Carbon Derived from Covalent Triazine Framework for Catalytic Oxidation of Benzyl Alcohol.

The catalytic oxidation of alcohols is an important transformation in the chemical industry. Carbon materials with a large surface area and N doping show great promise as metal-free catalysts for the reaction. In this study, a rich N-containing covalent triazine framework polymerized by cyanuric chloride and p-phenylenediamine was used to synthesize N-doped porous carbon with the assistance of a pore-forming agent-NaCl. First, the mass ratio of the polymer/NaCl was optimized to 1:9. Then, the influence of the pyrolysis temperatures (700-1000 °C) on the materials was studied in detail. It was found that the carbon materials were gradually exfoliated by molten salt at high temperatures. XRD and Raman characterizations showed them with a certain graphitization. The optimal doped carbon CNN-1-9-900 achieved the highest surface area of 199.03 m2g-1 with the largest pore volume of 0.29 cm3g-1. Furthermore, it had a high N content of 9.9 at% with the highest relative proportion of pyridinic/graphitic N. Due to the synergistic effect between the surface area and pyridinic/graphitic N, CNN-1-9-900 showed the best performance for benzyl alcohol oxidation with TBHP at moderate conditions, and the process also worked for its derivatives.

Integration of just-in-time learning with variational autoencoder for cell culture process monitoring based on Raman spectroscopy.

Protein production in the biopharmaceutical industry necessitates the utilization of multiple analytical techniques and control methodologies to ensure both safety and consistency. To facilitate real-time monitoring and control of cell culture processes, Raman spectroscopy has emerged as a versatile analytical technology. This technique, categorized as a Process Analytical Technology, employs chemometric models to establish correlations between Raman signals and key variables of interest. One notable approach for achieving real-time monitoring is through the application of just-in-time learning (JITL), an industrial soft sensor modeling technique that utilizes Raman signals to estimate process variables promptly. The conventional Raman-based JITL method relies on the K-nearest neighbor (KNN) algorithm with Euclidean distance as the similarity measure. However, it falls short of addressing the impact of data uncertainties. To rectify this limitation, this study endeavors to integrate JITL with a variational autoencoder (VAE). This integration aims to extract dominant Raman features in a nonlinear fashion, which are expressed as multivariate Gaussian distributions. Three experimental runs using different cell lines were chosen to compare the performance of the proposed algorithm with commonly utilized methods in the literature. The findings indicate that the VAE-JITL approach consistently outperforms partial least squares, convolutional neural network, and JITL with KNN similarity measure in accurately predicting key process variables.

Graphene quality evaluation by Van der Pauw-Hall Method

Evaluating graphene quality is crucial for both industrial applications and academic research. Traditional methods like Optical Microscope, Raman Spectroscope, Scanning and Transmission Electron Microscope, while common, face challenges in convience and providing electrical performance. To address these limitations, a cost-effective and rapid method was introduced for assessing macroscopic quality of graphene. This technique involves fine-tuning carrier concentration over 1013 cm-2 by controlling hydrochloric acid (HCl) doping time. Utilizing the Van der Pauw-Hall system, it tracks carrier concentration changes of graphene, allowing for mobility measurement under consistent carrier conditions. This facilitates a direct comparison of different graphene samples. The method shows reproducibility in evaluating HCl-doped graphene, which is consistent with the Raman characterizations. This advancement in graphene evaluation, focusing on mobility comparison at identical carrier concentrations, sets the stage for standardized assessments in the graphene industry.

Raman Characterization of Plastics: A DFT Study of Polystyrene.

Plastic materials are ubiquitous and raise concerns about their impact on health and the environment. To address these concerns, it is crucial to characterize the structural, size, and textural properties of plastics throughout their lifecycle from production to degradation. Raman spectroscopy appears as a valuable tool for this purpose, offering speed, robustness, and sensitivity to nanoscale and amorphous particles. In order to be properly used for plastics, the Raman response of reference materials needs to be carefully assessed, with the literature on such assessments being scarce. This study addresses this gap by using theoretical calculations to generate ab initio spectra for polystyrene, a reference material. The aim is to explain the origins of the spectral peaks and their consistency across various compositions and structures using linear ordered polymeric and finite amorphous models. The CRYSTAL package is employed to obtain full Raman spectra based on a careful benchmark of computational settings. While some peaks are present across all spectra and can serve for calibration, others exhibit structure-dependent behavior, enabling polymer identification. We conclude that Raman spectroscopy is a well-suited technique for plastics characterization provided that a careful analysis of signal origin is conducted to fully interpret the spectra and deploy applications.

Facile Synthesis of Iron Carbide via Pyrolysis of Ferrous Fumarate for Catalytic CO2 Hydrogenation to Lower Olefins.

Hydrogenation of CO2 to olefin catalyzed by iron-based catalysts is a sustainable and important way to achieve carbon neutrality. In this study, iron-based catalysts were facilely prepared by direct pyrolysis of ferric fumarate (FF), which are applied to CO2 hydrogenation to olefin reaction to explore the effects of pyrolysis temperature and atmosphere on catalytic performance of the catalysts. Among them, NaFe-Air-400 catalyst exhibits the highest catalytic activity with 33.7 %, and light olefin selectivity reaches as high as 47.1 %. The catalytic performance of pyrolytic catalysts is better than that the impregnated NaFe catalyst on activated carbon (NaFe/AC). A series of XRD, Raman and SEM characterization results show a suitable pyrolysis temperature would promote the balance between amorphous carbon and graphene, which can affect the formation of FexCy phase, leading the distinctive activity and olefin selectivity. Hence, the presented one-step pyrolysis methodology would provide a facile and quick synthesis of highly-active iron-based catalyst design for CO2 conversion.