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At least 163 records · Page 9

Cavity molecular dynamics simulations of vibrational polariton-enhanced molecular nonlinear absorption

We report recent experiments have observed that the chemical and photophysical properties of molecules can be modified inside an optical Fabry– Pérot microcavity under collective vibrational strong coupling (VSC) conditions, and such modification is currently not well understood by theory. In an effort to understand the origin of such cavity-induced phenomena, some recent studies have focused on the effect of the cavity environment on the nonlinear optical response of the molecular subsystem. Here, we use a recently proposed protocol for classical cavity molecular dynamics simulations to numerically investigate the linear and the nonlinear response of liquid carbon dioxide under such VSC conditions following an optical pulse excitation. We find that applying a strong pulse of excitation to the lower hybrid light–matter state, i.e., the lower polariton (LP), can lead to an overall molecular nonlinear absorption that is enhanced by up to two orders of magnitude relative to the excitation outside the cavity. This polariton-enhanced multiphoton absorption also causes an ultrashort LP lifetime (0.2 ps) under strong illumination. Unlike usual polariton relaxation processes—whereby polaritonic energy transfers directly to the manifold of singly excited vibrational dark states—under the present mechanism, the LP transfers energy directly to the manifold of higher vibrationally excited dark states; these highly excited dark states subsequently relax to the manifold of singly excited states with a lifetime of tens of ps. Because the present mechanism is generic in nature, we expect these numerical predictions to be experimentally observed in different molecular systems and in cavities with different volumes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Polariton relaxation under vibrational strong coupling: Comparing cavity molecular dynamics simulations against Fermi’s golden rule rate

Under vibrational strong coupling (VSC), the formation of molecular polaritons may significantly modify the photo-induced or thermal properties of molecules. In an effort to understand these intriguing modifications, both experimental and theoretical studies have focused on the ultrafast dynamics of vibrational polaritons. Here, following our recent work [Li et al., J. Chem. Phys. 154, 094124 (2021)], we systematically study the mechanism of polariton relaxation for liquid CO 2 under a weak external pumping. Classical cavity molecular dynamics (CavMD) simulations confirm that polariton relaxation results from the combined effects of (i) cavity loss through the photonic component and (ii) dephasing of the bright-mode component to vibrational dark modes as mediated by intermolecular interactions. The latter polaritonic dephasing rate is proportional to the product of the weight of the bright mode in the polariton wave function and the spectral overlap between the polariton and dark modes. Both these factors are sensitive to parameters such as the Rabi splitting and cavity mode detuning. Compared to a Fermi’s golden rule calculation based on a tight-binding harmonic model, CavMD yields a similar parameter dependence for the upper polariton relaxation lifetime but sometimes a modest disagreement for the lower polariton. We suggest that this disagreement results from polariton-enhanced molecular nonlinear absorption due to molecular anharmonicity, which is not included in our analytical model. Finally, we also summarize recent progress on probing nonreactive VSC dynamics with CavMD.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Vibration-Damping Properties of 3D-Printed Auxetic Structures

Two-photon polymerization is a recently developed technique that is used to print millimeter-size cellular structures with micrometer resolution. The two-photon polymerization process discussed in this paper is used to build structures to stabilize direct-drive targets that are imploded at cryogenic temperatures. These targets are supported by a very thin stalk (10 to 18 µm diameter) that can be broken (or dislodged) by vibrations that occur when the target is transported or when the cryogenic shroud is removed. And any vibration at the moment of implosion affects how precisely the target is aligned to the focus of the laser beams. Finally, this study investigates the mechanical properties of different millimeter-sized cellular auxetic structures (~0.2 g/cm 3 ) at room and cryogenic temperatures (20°C and −140°C) and how well the most promising structure dampens vibrations at room temperature.

auxetic structures↗

Fiber-Optic Silicon Fabry-Perot Interferometric Bolometer: The Influence of Mechanical Vibration and Magnetic Field

Plasma radiation plays an important role in the operation and control of magnetic confinement fusion and is typically measured by bolometers. Here, we study the influence of mechanical vibration and magnetic field, which are typically present in magnetic confinement fusion devices, on the performance of a fiber-optic bolometer (FOB) based on silicon Fabry-Perot interferometer (FPI) demodulated by a scanning diode laser. It is found that both the vibration and magnetic field could cause large noise due to the birefringence of the silicon FPI. To mitigate the birefringence effects, we demonstrated two effective methods: polarization maintaining FOB and polarization scrambling. We show that two methods can be effective in mitigating the effect caused by the sensor birefringence: (1) replacing the regular single-mode fiber in the FOB system with polarization-maintaining fiber and (2) using a polarization scrambler after the laser source. For both methods, no significant increase in the noise was observed in the vibration and magnetic field tests. Finally, our research highlights the importance of the polarization management for the FOB systems toward their practical applications in magnetic-confinement fusion systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Vibration Analysis - Presented to the MMWG Predictive Maintenance User’s Group [Slides]

Vibration Analysis monitors the condition of rotating equipment by focusing on the mechanical vibration the equipment transmits. For very little investment (a few thousands) you can protect millions of dollars of assets. Vibration Analysis is used to monitor fans, pumps, motors, compressors, chillers, and fixed structures. It is used to detect bearing problems, belt problems, bent shaft, misalignment, oil whirl, resonance, cavitation, recirculation, gear problems, mechanical looseness, sheave problems, unbalance, and some electrical problems including broken rotor bars and loose stators.

42 ENGINEERING↗

Spatially Resolved Near Field Spectroscopy of Vibrational Polaritons at the Small N Limit

Vibrational polaritons, which have been primarily studied in Fabry–Pérot cavities with a large number of molecules (N ~ 10 6 –10 10 ) coupled to the resonator mode, exhibit various experimentally observed effects on chemical reactions. However, the exact mechanism is elusively understood from the theoretical side, as the large number of molecules involved in an experimental strong coupling condition cannot be represented completely in simulations. This discrepancy between theory and experiment arises from computational descriptions of polariton systems typically being limited to only a few molecules, thus failing to represent the experimental conditions adequately. To address this mismatch, we used surface phonon polariton (SPhP) resonators as an alternative platform for vibrational strong coupling. SPhPs exhibit strong electromagnetic confinement on the surface and thus allow for coupling to a small number of molecules. As a result, this platform can enhance nonlinearity and slow down relaxation to the dark modes. In this study, we fabricated a pillar-shaped quartz resonator and then coated it with a thin layer of cobalt phthalocyanine (CoPc). By employing scattering-type scanning near-field optical microscopy (s-SNOM), we spatially investigated the dependency of vibrational strong coupling on the spatially varying electromagnetic field strength and demonstrated strong coupling with 38,000 molecules only–reaching to the small N limit. Through s-SNOM analysis, we found that strong coupling was observed primarily on the edge of the quartz pillar and the apex of the s-SNOM tip, where the maximum field enhancement occurs. In contrast, a weak resonance signal and lack of coupling were observed closer to the center of the pillar. This work demonstrates the importance of spatially resolved polariton systems in nanophotonic platforms and lays a foundation to explore polariton chemistry and chemical dynamics at the small N limit–one step closer to reconcile with high-level quantum calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Structural Characterisation and DFT-Aided Interpretation of Vibrational Spectra for Cyclo(l-Cys-d-Cys) Cyclic Dipeptide in a Solid State

Cyclic dipeptides with two intramolecular peptide bonds forming a six-membered 2,5-diketopiperazine ring are gaining significant attention due to their biological and chemical properties. Small changes in the local geometry of such molecules (from cis to trans) can lead to significant structural differences. This work presents the results of a study of cyclo(l-Cys-d-Cys), a dipeptide comprising two cysteine molecules in opposite chiral configurations, with the functional groups situated at both sides of the diketopiperazine ring. X-ray diffraction (XRD) experiment revealed that the molecule crystallises in the $P$-1 space group, which includes the centre of inversion. The IR and Raman vibrational spectra of the molecule were acquired and interpreted in terms of the potential energy distribution (PED) according to the results of density functional theory (DFT) calculations. The DFT-assisted analysis of energy frameworks for the hydrogen bond network within molecular crystals was performed to support the interpretation of X-ray structural data. The optimisation of the computational model based on three-molecule geometry sections from the crystallographic structure, selected to appropriately reflect the intermolecular interactions responsible for the formation of 1D molecular tapes in cyclo(l-Cys-d-Cys) crystal, allowed for better correspondence between theoretical and experimental vibrational spectra. This work can be considered the first complete structural characterisation of cyclo(l-Cys-d-Cys), complemented via vibrational spectroscopy results with full band assignment aided with the use of the DFT method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Vibration Fixture Design and Testing for Rigid - Y Cable Mount on MMRTG F4

INL is responsible for the fueling and testing of Radioisotope Thermoelectric Generators for NASA space missions. For the upcoming NASA mission "DRAGONFLY," INL is tasked with fueling and testing the Multi-Mission Radioisotope Thermoelectric Generator F4 (MMRTG F4). This involves conducting various tests, such as vibration testing and mass properties testing. For these tests, an interface is required between the MMRTG and the testing equipment, provided by cables mounted on a legacy bracket. Due to design changes in the cooling lines, a new cable – the Rigid Y cable – is to be used. The test described in this poster was to verify if the Rigid Y cable would survive the vibration tests. The results will determine the procedure for conducting the vibration tests on the MMRTG F4.

42 - ENGINEERING↗

Observation of Extraordinary Vibration Scatterings Induced by Strong Anharmonicity in Lead‐Free Halide Double Perovskites

Abstract Lead‐free halide double perovskites provide a promising solution for the long‐standing issues of lead‐containing halide perovskites, i.e., the toxicity of Pb and the low stability under ambient conditions and high‐intensity illumination. Their light‐to‐electricity or thermal‐to‐electricity conversion is strongly determined by the dynamics of the corresponding lattice vibrations. Here, the measurement of lattice dynamics is presented in a prototypical lead‐free halide double perovskite(Cs 2 NaInCl 6 ). The quantitative measurements and first‐principles calculations show that the scatterings among lattice vibrations at room temperature are at the timescale of ≈1 ps, which stems from the extraordinarily strong anharmonicity in Cs 2 NaInCl 6 . Further the degree of anharmonicity of each type of atom is quantitatively characterized in the Cs 2 NaInCl 6 single crystal, which stems from the interatomic forces, and demonstrate that this strong anharmonicity is synergistically contributed by the bond hierarchy, the tilting of the NaCl 6 and InCl 6 octahedral units, and the rattling of Cs + ions. Consequently, the crystalline Cs 2 NaInCl 6 possesses an ultralow thermal conductivity of ≈0.43 W mK −1 at room temperature, and a weak temperature dependence ofT −0.41 . These findings uncovered the underlying mechanisms behind the dynamics of lattice vibrations in double perovskites, which can largely benefit the design of optoelectronics and thermoelectrics based on halide double perovskites.

Chemistry↗

Shedding Light on the Vibrational Signatures in Halogen‐Bonded Graphitic Carbon Nitride Building Blocks

Abstract The relative contributions of halogen and hydrogen bonding to the interaction between graphitic carbon nitride monomers and halogen bond (XB) donors containing C−X and C≡C bonds were evaluated using computational vibrational spectroscopy. Conventional probes into select vibrational stretching frequencies can often lead to disconnected results. To elucidate this behavior, local mode analyses were performed on the XB donors and complexes identified previously at the M06‐2X/aVDZ‐PP level of theory. Due to coupling between low and high energy C−X vibrations, the C≡C stretch is deemed a better candidate when analyzing XB complex properties or detecting XB formation. The local force constants support this conclusion, as the C≡C values correlate much better with the σ ‐hole magnitude than their C−X counterparts. The intermolecular local stretching force constants were also assessed, and it was found that attractive forces other than halogen bonding play a supporting role in complex formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of XC functionals and dispersion corrections on the DFT‐computed structural and vibrational properties of SrCl 2 –NaCl and ZrF 4 –LiF

Density functional theory (DFT) calculations were performed to examine the impact of exchange–correlation (XC) functionals and van der Waals corrections (specifically the D3 method) on the structural and vibrational properties of the SrCl 2 –NaCl and ZrF 4 –LiF salt systems. Multiple XC functionals, including the local density approximation (LDA), the generalized gradient approximation using the Perdew–Burke–Ernzerhof (PBE) model, and its modified form suitable for solids (PBEsol), the dispersion-corrected PBE-D3 and PBEsol-D3, were considered. Of these functionals, LDA was found to exhibit the highest degree of error, while PBEsol and PBE-D3 displayed the least error. Underestimated lattice parameters compared with experimental values were observed to result in higher force constants, leading to an overprediction of vibrational frequencies. Conversely, an overestimation of lattice parameters was associated with lower vibrational frequencies. The methodology presented in this study yielded results that are in good agreement with experiment, irrespective of the method (finite differences vs. density functional perturbation theory) employed for calculating infrared and Raman spectra. It was further demonstrated that for alkali halides with weak Raman scattering, utilizing a supercell constructed from primitive cells better predicts Raman features than does the use of conventional cells.

Raman↗

Chatter detection in simulated machining data: a simple refined approach to vibration data

Vibration monitoring is a critical aspect of assessing the health and performance of machinery and industrial processes. This study explores the application of machine learning techniques, specifically the Random Forest (RF) classification model, to predict and classify chatter—a detrimental self-excited vibration phenomenon—during machining operations. While sophisticated methods have been employed to address chatter, this research investigates the efficacy of a novel approach to an RF model. The study leverages simulated vibration data, bypassing resource-intensive real-world data collection, to develop a versatile chatter detection model applicable across diverse machining configurations. The feature extraction process combines time-series features and Fast Fourier Transform (FFT) data features, streamlining the model while addressing challenges posed by feature selection. By focusing on the RF model’s simplicity and efficiency, this research advances chatter detection techniques, offering a practical tool with improved generalizability, computational efficiency, and ease of interpretation. The study demonstrates that innovation can reside in simplicity, opening avenues for wider applicability and accelerated progress in the machining industry.

42 ENGINEERING↗

Phase diagram of magnetic shape memory alloy Ni 50 Mn $50–x$ In $x$ , 0 < $x$ , 25 from first principles, via spin cluster expansion and phonon vibrational entropies

The metamagnetic shape memory Heusler alloy Ni 50 Mn $50–x$ In $x$ exhibits a rich phase diagram featuring competing magnetic states, coupled magnetic–structural phase transitions, and strong compositional sensitivity. Existing first-principles approaches struggletocapturetheintertwinedchemical, magnetic, andvibrationaleffectsinthesealloys, necessitating a more integrated modeling framework. We develop a spin cluster expansion (spin-CE) framework augmented by a quasi-harmonic phonon model to capture both configurational (chemical and magnetic) and vibrational contributions to the free energy of Ni 50 Mn $50–x$ In $x$ over the full compositional range 0 ≤ x ≤25. The spin-CE includes both chemical clusters and composition-dependent Ising spin interactions, with parameters fit to a first-principles density functional theory (DFT) dataset. Using this approach, we predict the complete magnetostructural phase diagram and transformation temperatures of Ni 50 Mn $50–x$ In $x$ across the composition space. We find that vibrational entropy alone is insufficient to reproduce the martensitic transformation in the magnetic shape memory alloy regime, highlighting the essential role of magnetism. Incorporating both magnetic and vibrational contributions allows us to reproduce all experimentally known phases, including the disappearance of the stable martensite phase at a critical In concentration and the Curie temperature of the austenite phase. The method also captures the transition with increasing In in martensite from antiferromagnetic to ferromagnetic order and predicts re-entrant ferromagnetism, though the latter occurs at higher In content than reported experimentally. We discuss possible sources of this discrepancy and highlight the broader applicability of the method to other magnetostructurally complex materials, where it may offer mechanistic insight and predictive design capabilities.

Cluster expansion↗

Vibrationally resolved ionization cross sections for the ground state and electronically excited states of the hydrogen molecule and its isotopomeres

An existing set of vibrationally resolved ionization cross section for the ground state and the first excited states of the hydrogen molecule, based on the Gryzinski method, is extended by cross sections for the isotopomeres of H{sub 2} (i.e. D{sub 2}, T{sub 2}, HD, HT, and DT), both for non-dissociative and dissociative ionizations. The comparison of cross sections for non-dissociative ionization of H{sub 2} with results obtained by the Molecular Convergent Close-Coupling method gives a very good agreement. The compiled tables give non-dissociative and dissociative cross sections for the ground state and the five energetically lowest electronically excited states of H{sub 2} and its isotopomeres, in each case for the first 9 vibrational levels. Data for all vibrational levels of the excited states is available online.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Angle-resolved polarized Raman study of layered b-As x P x-1 alloys: Identification of As-P vibrational modes

In this study, the polarization-resolved Raman spectra of b-As x P x-1 flakes with varying arsenic concentration (x = 0, 0.4, and 0.8) are systematically investigated. A clear polarization dependence is observed in the Raman intensity of all the P-P, As-P, and As-As modes and confirmed by the first-principles calculations. The observed angle-dependence can be related to the structure of the Raman tensors of each peak. In particular, the Raman intensities corresponding to As-P vibration modes are studied in detail. The out of plane As-P mode ($A$$^{1}_{g}$) is clearly identified, but the butterfly-shaped behavior observed in the polar plot around 350 cm -1 is interpreted as the combination of the two in-plane vibrations, one along the armchair and the other along the zigzag direction. This work allows unambiguous assignment of the $A$$^{1}_{g}$, B 2g , and $A$$^{2}_{g}$ modes of the As-P vibrational modes and the importance of the consideration of the superposition of the in-plane B 2g and $A$$^{2}_{g}$ modes. Such study can be utilized to further characterize the anisotropic structural properties and analyze the local distribution of the As and P in b-As x P x-1 alloys which will play key roles in electronic and optical properties. Furthermore, this methodology can be further extended to alloyed two-dimensional material systems with in-plane anisotropy in general.

2D materials↗

Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

42 ENGINEERING↗

Reprint of: Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

47 OTHER INSTRUMENTATION↗

Classification and regression models of audio and vibration signals for machine state monitoring in precision machining systems

Here we present a data-driven method for monitoring machine status in manufacturing processes. Audio and vibration data from precision machining are used for inference in two operating scenarios: (a) variable machine health states (anomaly detection); and (b) settings of machine operation (state estimation). Audio and vibration signals are first processed through Fast Fourier Transform and Principal Component Analysis to extract transformed and informative features. These features are then used in the training of classification and regression models for machine state monitoring. Specifically, three classifiers (K-nearest neighbors, convolutional neural networks and support vector machines) and two regressors (support vector regression and neural network regression) were explored, in terms of their accuracy in machine state prediction. It is shown that the audio and vibration signals are sufficiently rich in information about the machine that 100% state classification accuracy could be accomplished. Data fusion was also explored, showing overall superior accuracy of data-driven regression models.

42 ENGINEERING↗