Vibrational Spectra Research Articles

Iron borophosphate glasses: Merging optical transparency, structural integrity, and radiation shielding efficacy for sustainable uses

The research work explored the influence of iron doping on the optical behavior, structural characteristics, and radiation shielding capabilities of soda lime borophosphate glass system of composition xFe2O3-(42.5-x)B2O3-26CaO-28.7Na2O-2.8P2O5 (x up to 8 mol%). The glass samples doped with varying iron concentrations were synthesized via the conventional melt-quenching method. A comprehensive characterization approach was employed, integrating X-ray diffraction (XRD) analysis to probe the structural aspects, Fourier transform infrared (FTIR) spectroscopy to examine the molecular vibrations and bonding, and UV–visible spectroscopic techniques to investigate the optical properties. Furthermore, the study evaluated the potential of these iron-doped glasses as effective radiation shielding materials by assessing their attenuation performance against various radiation types. The influence of iron oxide (Fe2O3) addition on the borophosphate network, coordination environment, and optical absorption was examined. The radiation shielding characteristics, such as mass attenuation coefficient, half-value layer, mean free path, and other parameters, were assessed using Phy-x freeware program calculations. The results revealed the formation of an amorphous glass structure and the incorporation of iron ions into the borophosphate network. The addition of Fe2O3 influenced the borate superstructural units, the conversion of BO3 to BO4 units, and the optical absorption bands. The glasses exhibited promising radiation shielding properties combined with increasing Fe2O3 content.

Microsphere lens array embedded microfluidic chip for SERS detection with simultaneous enhancement of sensitivity and stability

Surface enhanced Raman spectroscopy (SERS) utilizes the fingerprint features of molecular vibrations to identify and detect substances. However, in traditional single focus excitation scenarios, its signal collection efficiency of the objective is restricted. Furthermore, the uneven distribution of samples on the SERS substrate would result in poor signal stability, while the excitation power is limited to avoid sample damage. SERS detection system always requires precise adjustment of focal length and spot size, making it difficult for point-of-care testing applications. Here, we proposed a SERS microfluidic chip with barium titanate microspheres array (BTMA) embedded using vacuum self-assembled hot-pressing method for SERS detection with simultaneous enhancement of sensitivity and stability. Due to photonic nano-jets and directional antenna effects, high index microspheres are perfect micro-lens for effective light focusing and signal collecting. The BTMA can not only disperse excitation beam into an array of focal points covering the target uniformly with very low signal fluctuation, but enlarge the power threshold for higher signal intensity. We conducted a proof-of-principle experiment on chip for the detection of bacteria with immuno-magnetic tags and immuno-SERS tags. Together with magnetic and ultrasonic operations, the target bacteria in the flow were evenly congregated on the focal plane of BTMA. It demonstrated a limit of detection of 5 cells/mL, excellent signal reproducibility (error∼4.84%), and excellent position tolerance of 500 μm in X–Y plane (error∼5.375%). It can be seen that BTMA-SERS microfluidic chip can effectively solve the contradiction between sensitivity and stability in SERS detection.

Polyamidoxime‐Coated Coconut Haustorium Derived Magnetic Biochar Adsorbent with Photothermal Conversion for Highly Efficient Uranium Recovery from Nuclear Wastewater

AbstractEfficient removal of uranium from uranium‐containing nuclear wastewater is of great significance for utilizing uranium resources and protecting the environment from uranium hazards. In this paper, a polyamidoxime‐coated coconut haustorium derived magnetic biochar (CHMBC‐PAO) composite adsorbent with excellent adsorption performance, magnetism, recyclability, and photothermal conversion properties in complex environments is prepared through a simple soak‐gelation coating method for efficient removal of uranium from nuclear wastewater. The coconut haustorium biochar, carbonized by a sponge‐like organ inside the sprouted coconut, can provide rich functional groups and electronegative surface, which are conducive to the loading of functional materials and the adsorption of uranyl, respectively. The CHMBC‐PAO presents 2.4 emu g−1 saturation magnetization, making it can be efficiently recovered through magnetic recovery. It can convert absorbed light into thermal energy through molecular thermal vibration and non‐radiative relaxation process of excitons. Enhanced by the photothermal effect, CHMBC‐PAO shows an extra high uranium adsorption capacity of 310.30 mg g−1 in acidic nuclear wastewater within a short period of time, surpassing the adsorption capacity of most reported uranium removal materials. Meanwhile, the CHMBC‐PAO also presented excellent ion selectivity and reusability. Therefore, CHMBC‐PAO composite adsorbent can be considered as a potential candidate for treating radioactive nuclear wastewater.

Pressure-induced phase transition in nanostructured cation-deficient Zn0.34Fe2.53☐0.13O4 ferrite

The crystal structure and vibrational spectra of cation-deficient nanostructured zinс ferrite Zn0.34Fe2.53☐0.13O4 (where ☐ denotes the cation vacancies) have been studied using X-ray diffraction and Raman spectroscopy methods in the pressure range of 0–34 GPa. Our results indicate a phase transition from the initial cubic phase with space group Fd3‾m to a high-pressure phase with orthorhombic symmetry of Bbmm at pressures above 18 GPa. This phase transition is accompanied by changes in lattice parameters, unit cell volume, interatomic bond lengths, and vibration mode frequencies.

Picking up Good Vibrations through Quartic Force Fields and Vibrational Perturbation Theory.

Quartic force fields (QFFs) define sparse potential energy surfaces (compared to semiglobal surfaces) that are the cheapest and easiest means of computing anharmonic vibrational frequencies, especially when utilized with second-order vibrational perturbation theory (VPT2). However, flat and shallow potential surfaces are exceedingly difficult for QFFs to treat through a combination of numerical noise in the often numerically computed derivatives and in competing energy factors in the composite energies often utilized to provide high-level spectroscopic predictions. While some of these issues can be alleviated with analytic derivatives, hybrid QFFs, and intelligent choices in coordinate systems, the best practice is for predicting good molecular vibrations via QFFs is to understand what they cannot do, and this manuscript documents such cases where QFFs may fail.

Optical nuclear electric resonance in LiNa: selective addressing of nuclear spins through pulsed lasers

Optical nuclear electric resonance (ONER), a recently proposed protocol for nuclear spin manipulation in atomic systems via short laser pulses with MHz repetition rate, exploits the coupling between the nuclear quadrupole moment of a suitable atom and the periodic modulations of the electric field gradient generated by an optically stimulated electronic excitation. In this theory paper, we extend the scope of ONER from atomic to molecular systems and show that molecular vibrations do not interfere with our protocol. Exploring the diatomic molecule LiNa as a first benchmark system, our investigation showcases the robustness with respect to molecular vibration, and the ability to address and manipulate each of the two nuclear spins independently, simply by adjusting the repetition rate of a pulsed laser. Our findings suggest that it might be possible to shift complicated spin manipulation tasks required for quantum computing into the time domain by pulse-duration encoded laser signals.

Spectroscopy of substrate thermal vibrational modes using an optomechanical sensor

We used an optomechanical sensor to record the vibrational spectrum of its own fused silica substrate. The coupling of the substrate modes was greatly enhanced by covering the sensor with an appropriately sized ethylene glycol droplet, and in that case even thermally populated modes could be clearly detected. We observed a rich spectrum of high-quality flexural modes for frequencies less than ∼ 10 MHz, in good agreement with analytical theory and finite element simulations. We also observed signatures of acoustic waves resonantly confined by the droplet, over the entire ∼ 0–40 MHz range of the experiment. This work could inform efforts to increase the quality factor of mechanical resonators, and the use of substrate phonon modes as information channels.

Long-wavelength emission room-temperature phosphorescent carbon dots activated by an ortho-carboxyl substitution strategy and employed for achieving tunable LED

While room temperature phosphorescence (RTP) associated with carbon dots (CDs) has been widely achieved, obtaining long-wavelength emission RTP, especially while mitigating the quenching effect of water or dissolved oxygen, remains a challenging yet desirable goal. We synthesized three types of phosphorescent CDs with varying luminescent properties by using three precursors with carboxyls positioned differently. The formation process of these CDs resulted in a well-ordered and compact structure, effectively inhibiting molecular vibrations and reducing non-radiative transitions. Consequently, it successfully prevented the quenching effect of dissolved oxygen on the RTP of CDs in an aqueous environment. Significantly, PA-AIBN synthesized with phthalic acid, rather than iso-phthalic acid and terephthalic acid, exhibited long-wavelength emission RTP, with the phosphorescent emission center reaching as far as 640 nm. To be specific, the ortho-substituted carboxyls played a critical role in boosting the formation of intramolecular hydrogen bonds. Simultaneously, an increase in the doping levels of both nitrogen (N) and phosphorus (P) in PA-AIBN facilitated the long-wavelength emission RTP. The increased sp2 conjugated carbon core of PA-AIBN narrowed the optical band gap, contributing to the long-wavelength emission. Taken together, these factors cooperatively promoted the long-wavelength emission of RTP. Importantly, the PA-AIBN synthesized in this study exhibited a broad half-peak width and long-wavelength emission. It was successfully used in the preparation of white-light-emitting diodes without the need for commercial phosphor powder, demonstrating its enormous potential for practical lighting devices.

Highly-Polarized Solar-Blind Ultraviolet Organic Photodetectors.

Developing high-performance polarization-sensitive ultraviolet photodetectors is crucial for their application in military remote sensing, detection, bio-inspired navigation, and machine vision. However, the significant absorption in the visible light range severely limits the application of polarization-sensitive ultraviolet photodetectors, such as high-quality anti-interference imaging. Here, based on a wide-bandgap organic semiconductor single crystal (trans-1,2-bis(5-phenyldithieno[2,3-b:3',2'-d]thiophen-2-yl)ethene, BPTTE), high-performance polarization-sensitive solar-blind ultraviolet photodetectors with a dichroic ratio close to 4.26 are demonstrated. The strong anisotropy of 2D grown BPTTE single crystals in molecular vibration and optical absorption is characterized by various techniques. Under voltage modulation, stable and efficient detection of polarized light is demonstrated, attributed to the intrinsic anisotropy of transition dipole moment in the bc crystal plane, rather than other factors. Finally, high-contrast polarimetric imaging and anti-interference imaging are successfully demonstrated based on BPTTE single crystal photodetectors, highlighting the potential of organic semiconductors for polarization-sensitive solar-blind ultraviolet photodetectors.

Hydrostatic pressure effect on excited state properties of room temperature phosphorescence molecules: A QM/MM study

Stimulus-responsive organic room temperature phosphorescence (RTP) materials exhibit variations in their luminescent characteristics (lifetime and efficiency) upon exposure to external stimuli, including force, heat, light and acid-base conditions, the development of stimulus-responsive RTP molecules becomes imperative. However, the inner responsive mechanism is unclear, theoretical investigations to reveal the relationship among hydrostatic pressures, molecular structures and photophysical properties are highly desired. Herein, taking the Se-containing RTP molecule (SeAN) as a model, based on the dispersion corrected density functional theory (DFT-D), the combined quantum mechanics and molecular dynamics (QM/MM) method and thermal vibration correlation function (TVCF) theory, the influences of hydrostatic pressure on molecular structures, transition properties as well as lifetimes and efficiencies of RTP molecule are theoretically studied. Results show that extended lifetime and enhanced efficiency are observed at 2 Gpa compared with molecule at normal pressure, and this is related with the small reorganization energy and large oscillator strength. Moreover, due to the small energy gap (0.34 eV) and remarkable spin-orbit coupling (SOC) constant (8.56 cm-1) between first singlet excited state and triplet state, fast intersystem crossing (ISC) process is determined for molecule at 6 Gpa. Furthermore, the intermolecular interactions are visualized using independent gradient model based on Hirshfeld partition (IGMH) and the changes of molecular packing modes, SOC values, lifetimes and efficiencies with pressures are detected. These results reveal the relationship between molecular structures and RTP properties. Our work provides theoretical insights into the hydrostatic pressure response mechanism and could promote the development new efficient stimulus-responsive molecules.

Sub-100-fs energy transfer in coenzyme NADH is a coherent process assisted by a charge-transfer state

Excitation energy transfer (EET) is a key photoinduced process in biological chromophoric assemblies. Here we investigate the factors which can drive EET into efficient ultrafast sub-ps regimes. We demonstrate how a coherent transport of electronic population could facilitate this in water solvated NADH coenzyme and uncover the role of an intermediate dark charge-transfer state. High temporal resolution ultrafast optical spectroscopy gives a 54±11 fs time constant for the EET process. Nonadiabatic quantum dynamical simulations computed through the time-evolution of multidimensional wavepackets suggest that the population transfer is mediated by photoexcited molecular vibrations due to strong coupling between the electronic states. The polar aqueous solvent environment leads to the active participation of a dark charge transfer state, accelerating the vibronically coherent EET process in favorably stacked conformers and solvent cavities. Our work demonstrates how the interplay of structural and environmental factors leads to diverse pathways for the EET process in flexible heterodimers and provides general insights relevant for coherent EET processes in stacked multichromophoric aggregates like DNA strands.

Влияние динамических характеристик процесса резания на шероховатость поверхности детали при токарной обработке

Introduction. The formation of the surface of a part when processing it on a metal-cutting machine is based on properly selected cutting modes. Complex methods of ensuring the specified quality of the part surface also take into account the tool geometry, its condition, and include corrections for tool deviation from the trajectory set by the CNC system under the influence of kinematic disturbances and spindle wavering. Subject. The paper analyzes the relationship between cutting modes and dynamic characteristics of the turning process, and its mapping into surface roughness. The aim of the work is to evaluate the influence of technological cutting modes taking into account the vibration activity of the tool on the roughness of the machined surface by means of simulation modeling. Method and methodology. Mathematical simulation of the dynamics of the cutting process is given, on the basis of which a digital simulation model is built. A methodology of using the simulation model for determining optimal cutting modes and predicting surface roughness taking into account tool vibrations is proposed. By means of experiments and analysis of the frequency characteristics of tool vibrations, the created model is validated, parameters of the cutting forces model subsystem and dynamic tool subsystem are specified, and geometrical topologies of the part surface are constructed. The calculated cutting forces are compared with experimental forces, and similar patterns and levels of characteristics are observed. An assessment of the optimality of the selected cutting modes is proposed based on the analysis of the tool vibration spectrum relative to the workpiece and the results of the numerical model simulation. Results and Discussion. A comparison of the results of digital modeling of the geometrical surface of the workpiece and the real surface obtained during the field experiment is given. It is shown that the roughness of the real surface obtained by machining with constant cutting modes varies relative to the surface roughness of the simulation model within the limits of not more than 0.066 µm.

Neuro-Fuzzy Framework for Fault Prediction in Electrical Machines via Vibration Analysis

The advent of Industry 4.0 has ushered in a new era of technological advancements, particularly in integrating information technology with physical devices. This convergence has given rise to smart devices and the Internet of Things (IoT), revolutionizing industrial processes. However, despite the push towards predictive maintenance, there still is a significant gap in fault prediction algorithms for electrical machines. This paper proposes a signal spectrum-based machine learning approach for fault prediction, specifically focusing on bearing faults. This study compares the effectiveness of traditional neural network algorithms with a novel approach integrating fuzzy logic. Through extensive experimentation and analysis of vibration spectra from various mechanical faults in bearings, it is demonstrated that the fuzzy-neuro network model outperforms traditional neural networks, achieving a validation accuracy of 99.40% compared to 94.34%. Incorporating fuzzy logic within the neural network framework offers advantages in handling complex fault combinations, showing promise for applications requiring higher accuracy in fault detection. While initial results are encouraging, further validation with more complex fault scenarios and additional fuzzy layers is recommended to fully explore the potential of fuzzy-neuro networks in fault prediction for electrical machines.

First Principle Study on Structural, Electronic, Magnetic, and Optical Properties of Co-Doped Middle Size Silver Clusters.

The structural, electronic, magnetic, and optical properties of Co-doped 10-20-atom silver clusters are investigated by GGA/PBE via the density functional theory. The Ag-Co clusters form core-shell structures with a Co atom in the center. Co atom doping modulates electronic properties like energy gap, molecular softness, global hardness, electronegativity, and electrophilicity index. For the optical spectra of the Ag-Co clusters, the energy of their spectra overall exhibits little change with increasing numbers of atoms; the strongest peaks are roughly distributed at 3.5 eV, and the intensity of their spectra overall is strengthened. Raman and vibrational spectra reflect structural changes with Co atom addition. The addition of the Co atom alters magnetic moments of specific Ag-Co clusters, while others remain unchanged.

VIBRATIONAL AND X-RAY MEASUREMENTS OF La2Ti2O7 UNDER HIGH PRESSURE CONDITION

The present study focuses on investigating the impact of high-pressure conditions on the crystal structure and vibration spectra of the perovskite-like layered compound La2Ti2O7. To this end, X-ray diffraction and Raman spectroscopy techniques were employed to observe the behavior of the compound under pressure levels up to 30 GPa. The neutron diffraction at ambient pressure confirms that the structure of La2Ti2O7 is monoclinic P21. The results indicate that when the pressure attains 17.3 GPa, the original monoclinic phase of P21 symmetry undergoes a phase transition to the monoclinic phase of P2 symmetry. The observed pressure-induced phase transitions in La2Ti2O7 are associated with anomalous changes in both the unit cell parameters and the vibrational modes. Additionally, the study obtained the baric dependences of lattice parameters, unit cell volume and vibration frequencies, which were used to calculate the bulk modules for the initial and pressure-induced phases of La2Ti2O7.

Effect of Cage Occupancies on Molecular Vibrations of Methane in Structure H Clathrate Hydrate: Ab Initio Molecular Dynamics Simulation.

The structure H (sH) of methane hydrate, which has a distinctive structure with large (LL) cages capable of encapsulating multiple methane molecules, has been suggested as a methane reservoir in large icy bodies such as Titan, making it important in planetary science. This high-pressure phase, which exists in the GPa range, lends itself to the study of methane states and dynamics using powerful experimental techniques such as IR and Raman spectroscopy. However, the interpretation of the vibrational spectra of methane in the sH structure has been challenging because of the spectral complexities. The signals attributed to the methane molecules in the LL cage, as well as those of the other two cage types, overlap in the spectra. In this study, we investigated the microscopic origins of the shape of the C-H stretching vibration spectrum of methane in the LL cage using ab initio molecular dynamics (AIMD) simulations. For a single methane molecule in the LL cage, the ν3 band of the C-H stretching mode was observed at a higher frequency typical of isolated molecules in vacuum due to the large size of the LL cage. As the number of methane molecules in the LL cage increased beyond one, a tendency to blue-shift with increasing methane occupancy was observed, consistent with a loose-cage-tight-cage model. By characterizing the time correlation function of methane stretching vibrations based on the solvation number of methane and water molecules proximal to methane within the LL cage, we showed that the complicated spectral line shape observed in cases of higher methane occupancy in the LL cage resulted from the wider variation of the solvation shell states. Analysis of the solvation structures of the AIMD trajectories provided interpretations of the experimental spectral line shape, demonstrating the complementary nature of AIMD to the experiment and its effectiveness in analysis.

VSCF/VCI theory based on the Podolsky Hamiltonian.

While the vibrational spectra of semi-rigid molecules can be computed on approaches relying on the Watson Hamiltonian, floppy molecules or molecular clusters are better described by Hamiltonians, which are capable of dealing with any curvilinear coordinates. It is the kinetic energy operator (KEO) of these Hamiltonians, which render the correlated calculations relying on them rather costly. Novel implementation of vibrational self-consistent field theory and vibrational configuration interaction theory on the basis of the Podolsky Hamiltonian are reported, in which the inverse of the metric tensor, i.e., the G matrix, is represented by an n-mode expansion expressed in terms of polynomials. An analysis of the importance of the individual terms of the KEO with respect to the truncation orders of the n-mode expansion is provided. Benchmark calculations have been performed for the cis-HOPO and methanimine, H2CNH, molecules and are compared to experimental data and to calculations based on the Watson Hamiltonian and the internal coordinate path Hamiltonian.

Accelerating Molecular Vibrational Spectra Simulations with a Physically Informed Deep Learning Model.

In recent years, machine learning (ML) surrogate models have emerged as an indispensable tool to accelerate simulations of physical and chemical processes. However, there is still a lack of ML models that can accurately predict molecular vibrational spectra. Here, we present a highly efficient multitask ML surrogate model termed Vibrational Spectra Neural Network (VSpecNN), to accurately calculate infrared (IR) and Raman spectra based on dipole moments and polarizabilities obtained on-the-fly via ML-enhanced molecular dynamics simulations. The methodology is applied to pyrazine, a prototypical polyatomic chromophore. The VSpecNN-predicted energies are well within the chemical accuracy (1 kcal/mol), and the errors for VSpecNN-predicted forces are only half of those obtained from a popular high-performance ML model. Compared to the ab initio reference, the VSpecNN-predicted frequencies of IR and Raman spectra differ only by less than 5.87 cm-1, and the intensities of IR spectra and the depolarization ratios of Raman spectra are well reproduced. The VSpecNN model developed in this work highlights the importance of constructing highly accurate neural network potentials for predicting molecular vibrational spectra.

Coherent molecular vibrational dynamics studied by a 10-fs laser pulse in comparison for selective and nonselective excitation

Various selective excitation methods for molecular vibrations have been developed based on the characteristics of the applied lasers. In the present work, we coherently and selectively excited molecular vibrations up to 3000 cm−1 by irradiation with a sub-10-fs laser pulse. The spectral shaping of this laser pulse enabled us to selectively excite only the target vibrational frequency range (of the model compounds acetonitrile and benzene). Furthermore, the coherent molecular vibrational dynamics were compared between selective and nonselective excitation. The coherence of the molecular vibration persisted until 2–3 ps after photoexcitation, with the lifetime of this coherence being independent of whether the coherent molecular vibration was selective or nonselective excitation.

Synthesis of isoprene from 1-butanol and from diethyl ether in the presence of 3d-metal oxides nano-clusters acting as catalysts

The conformational equilibria of 1-butanol (1-BuOH) and diethyl ether (DEE) molecules were investigated in gas and liquid phases. The geometry of the molecules of all stable isomers of 1-BuOH and DEE was fully optimised and the thermochemical quantities’ values (ΔH, ΔG and ΔS) were computed in the temperature range from close to 0 K to 1000 K at the Density Functional Theory (DFT) level. DEE shows two rotamers (namely, Tt and Tg), whereas five different rotamers were identified for 1-BuOH (namely, Tt, Tg, Gt, Gg and Gg’) with different stability, due to the presence of intramolecular interactions. Electrostatic properties of 1-BuOH, ethanol (EtOH), and DEE were also evaluated. Calculated vibration spectra of 1-BuOH and DEE were compared with the experimental FT-IR and Raman spectra recorded in neat phase and diluted in cyclohexane (CHX). The experimental vibrational spectra found the best match with the sum of calculated spectra using the Boltzmann coefficients based on the thermal stability of each conformer. The frequency shift observed for some peaks as a function of the concentration of 1-BuOH in CHX reveals the impact of hydrogen bonds between 1-BuOH molecules, in particular in the case of conformer Gg’. In contrast, very weak interactions among molecules of DEE were spectroscopically detected. The transformation reactions of {1-BuOH+EtOH} and {DEE+EtOH} mixtures at different temperatures were studied using the method of quantum mechanical calculations. The mechanism of isoprene formation from these mixtures was determined taking into account the chemisorption of 1-BuOH and DEE onto metal oxide nano-clusters M4O4 (M = Sc to Zn) and its effect on the vibrations of BuOH and DEE at the interface for M = Zn, Cu and Ti using Raman microscopic spectroscopy.