Spectral Plots Research Articles

Spectral Similarity: Full-Wavelength Range Calibration of Circular Dichroism Spectroscopy.

Circular dichroism (CD) measurements help characterize optically active molecules and higher-order biomolecular structures. The harmonization of interlaboratory CD measurements requires minimizing measurement uncertainties and determinate errors. Most CD measurements utilize a single-wavelength intensity measurement at a spectral peak to calibrate the intensities of the ultraviolet wavelength range. However, such a single-wavelength calibration is inherently less precise than using the CD instrument's spectrum over the entire measured spectral range. A more thorough and informative calibration can be achieved by remapping the spectrum into what we call a spectral similarity plot. This process allows a straightforward, quantitative evaluation of the shape congruence between two spectra over the full spectral range. While preliminary analyses suggest spectral similarity plots can be utilized with a variety of different spectrometry methods, here we illustrate the process applied to circular dichroism. Spectral similarity plots are highly sensitive to deviations due to differences in concentration, pathlength, source and detector properties, circular polarization balance, as well as wavelength nonlinearities and shifts. Deviations in these properties can be quantitated by a linear least squares fit of the remapped data. The remapping enables protocols to correct spectra toward congruence between two spectra. The spectra similarity comparison provides an objective, unambiguous test of the CD instrument quality when, for example, compared to a carefully calibrated system as shown in the examples described in the text.

Physical Characterization of Near-Earth Asteroid (52768) 1998 OR2: Evidence of Shock Darkening/Impact Melt

We conducted photometric and spectroscopic characterization of near-Earth asteroid (52768) 1998 OR2 during a close approach to Earth in 2020 April. Our photometric measurements confirm the rotation period of the asteroid to be 4.126 ± 0.179 hr, consistent with the previously published value of 4.112 ± 0.001 hr. By combining our visible spectroscopic measurements (0.45–0.93 μm) with archival MITHNEOS near-infrared spectra (0.78–2.49 μm), we classify the asteroid as an Xn-type in the Bus–DeMeo taxonomy. The combined spectrum shows two weak absorption bands: Band I at 0.926 ± 0.003 μm and Band II at 2.07 ± 0.02 μm, with band depths of 4.5% ± 0.15% and 4.0% ± 0.21%, respectively. The band area ratio is 1.13 ± 0.05. These spectral band parameters plot at the tip of the S(IV) region of the Gaffey S-asteroid subtypes plot, suggesting an affinity to ordinary chondrite meteorites. We calculated the chemistry of olivine and pyroxene using the Band I center to be 20.1 ± 2.3 mol% fayalite and 18.2 ± 1.5 mol% ferrosilite, consistent with H-chondrites. Principal component analysis of 1998 OR2's combined visible–near-IR spectrum falls on the C/X-complex side of the α-line, near the end of the shock-darkening trend, consistent with its weak absorption bands (band depth <5%). We use an areal mixing model with lab measurements of the shock-darkened H5 chondrite, Chergach, to constrain the amount of shock-darkened material on the asteroid’s surface at ∼63% dark lithology and ∼37% light lithology.

Processing of Multispectral ASTER Data to Delineate Bauxite Abundant Zones and its Geochemical Characterisation Deposited over Deccan Traps of Central India in Mainpat Plateau, Surguja District, Chhattisgarh

Abstract The current study deals with the application of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral data to delineate bauxite deposits over Mainpat plateau, Surguja district, Chhattisgarh, India. Application of specific band combinations help to delineate bauxite in the (SWIR) region (2.16-2.33 μm) and visible near infrared (VNIR) band (0.4–1.0 μm) of multispectral ASTER data. Various image processing techniques like atmospheric correction, minimum noise fraction, pixel purity index, n-dimensional visualiser, and spectral angle mapper were applied to ASTER image to delineate bauxite rich zones. The pure pixels were differentiated from the mixed pixels using pixel purity index which were further subjected to n-dimensional visualiser to identify the target end-members. The presence of bauxite was confirmed by comparing the spectral signatures of end-members with in-built spectral plots of United States Geological Survey spectral libraries and categorized as bauxite and ferruginous bauxite. Finally, the end-members were categorised as bauxite and ferruginous bauxite and mapped using spectral angle mapper. The result obtained was further compared with the lithological map provided by Geological Survey of India for accuracy. Then XRF analysis was carried out for the collected samples to confirm the presence of bauxite and ferruginous bauxite. Geochemical analysis also categorized the samples as bauxite and ferruginous bauxite that added accuracy to the results obtained from remote sensing technique. This study might be considered as a time saving eco-friendly exploitation of natural resources and finally the potential of multispectral ASTER data for mapping mineral resources.

Monitoring abnormal vibration and structural health conditions of an in-service structure from its SHM data

Vortex-induced vibration occurred recently in several important engineering structures in China. Very large mono-frequency periodic vibration was noted. This study reports on the analysis of recorded data from the structural health monitoring (SHM) system of a suspension bridge with the aim to develop some indicators that may be useful to evaluate if there is any abnormal vibration or change of health conditions of a structure in future. The power spectrum of measured acceleration responses is plotted in three-dimensions of time, frequency and power. Acceleration responses from 16 sensors on the target bridge deck in 233 days are analyzed. The evolution of different dynamic parameters in the period encompassing the occurrences of large vortex-induced vibration are reported. The changes in these parameters are identified to be closely associated with some temporary installations on the deck and temporary measures for vibration suppression. The changes in vibration power at different natural frequencies of the structure can be used to demonstrate the evolution of the unexpected event. The trend and abrupt changes of natural frequencies and modal components show the flow of vibration energy between different vibration modes. In addition to the intuitive three-dimension power spectral plot, two state vectors are also developed from the power spectrum. The identification of abnormal vibration and structural state can then be carried out automatically with the novelty detection method and a threshold. The analysis of the SHM acceleration responses of the bridge deck demonstrates the implementation procedure and the effectiveness of the proposed method.

SOLUTION OF DIFFERENTIAL EQUATIONS OF WAGON OVERSPREAD MASSES OSCILLATION

The paper gives the methodology of differential equations solution for description of bouncing, galloping and side swaying oscillations of railcar with asymmetrically located cargoes of different masses which were carried out on computer. Continuous ­vertical irregularities in the rail track and level difference (track skewness) of two rail tracks in the vertical transverse plane were taken as disturbances­, spectral density of which is shown, respectively. To obtain the spectral densities depending on the speed, the abscissa of the spectral densities plots were multiplied by the speed, and the ordinates were divided by the speed at which the oscillations of the loaded car ­were investigated at that moment. As a result, spectral ­densities of unevenness of rail ­thread and misalignment of two rail threads in vertical transverse ­plane at speeds of 50; 80; 100 and 120 km/h of four-axle car with tare weight 21 t with bogies type CNIIKhZ ­were obtained.

Continuous monitoring of the depth of the water-mud interface using distributed acoustic sensing

PurposeCurrent surveying techniques used by port authorities to estimate the nautical depth are limited in depth resolution and temporal resolution. Because of this, certain heavily occupied quay walls cannot be optimised in terms of utilisation. Therefore, a permanent continuous measuring system with a higher depth resolution is needed to optimise the occupation at these quay walls. We show how this could be achieved with distributed acoustic sensing (DAS) using fibre-optical cables.MaterialsWe analyse recordings from a dual-frequency echo-sounder source along a standard communication optical fibre coiled vertically around a PVC pipe to represent vertical seismic profiling. This PVC pipe is placed inside a transparent plastic cylindrical tank which is partly filled with water and mud. This allows us to track the water-mud interface visually. We use a Silixa iDAS v2 and a Febus A1 DAS interrogator to convert the optical fibre into a seismic sensor. We use a wave generator to select the source frequency and an amplifier to amplify the output of the wave generator to a SIMRAD 38/200 COMBI C dual-frequency echo-sounder.ResultsWe identify standing waves and use them to make accurate depth estimates of the water-mud interface inside the column we measure. Due to the high apparent velocity, the standing waves are easy to identify in the time domain. Due to the constructive interference, standing waves also show the water-mud interface in a power spectral density plot. We demonstrate that these standing waves could be used with an on-demand permanent continuous measuring system using ambient noise sources.ConclusionOur laboratory experiment showed that DAS could be used to estimate the water-mud interface. In addition, we showed the potential for on-demand monitoring in ports and waterways using DAS. Furthermore, due to the low cost of optical fibres, and the possibility of utilising ambient noise sources, DAS could be used for continuous depth monitoring purposes in ports and waterways.

Graphene-based multilayer metasurface solar absorber with parameter optimization and behavior prediction using Long Short-Term Memory model

Most of the solar absorbers are absorbing visible spectrum energy and are not focused on the ultraviolet spectrum and infrared spectrum energies. Here we propose a solar absorber that absorbs most of the energy of the available solar spectrum including visible spectrum and ultraviolet spectrum energies. The multilayer metasurface solar absorber design is analyzed and its results are compared with the single-layer metasurface solar absorber design. Both design results are also compared with AM 1.5 solar spectral irradiance plot for a wavelength range of 0.2 μm–1.5 μm. The graphene is used as a spacer to increase the absorption response of the proposed structure. The efficiency of multilayer design is high in both visible spectrum regions and ultraviolet spectrum regions compared to single-layer design. The parameter optimization for substrate thickness and resonator thickness is analyzed for improvement of absorption of the proposed design. The design results in the form of absorption, a normalized electric field. The proposed solar absorber with its high efficiency in visible and ultraviolet regions can be used in solar energy harvesting devices. The novel part of this research is predicting absorption values for assorted variations in substrate thickness, resonator thickness for forthcoming wavelengths using a Long Short-Term Memory model. The results of the experiments show that prediction may accurately anticipate absorption values, reducing simulation time and resource requirements. The visual comparison of simulated and predicted values is also presented in the paper.

High-Precision Intelligent Cancer Diagnosis Method: 2D Raman Figures Combined with Deep Learning.

Raman spectroscopy, as a label-free detection technology, has been widely used in tumor diagnosis. However, most tumor diagnosis procedures utilize multivariate statistical analysis methods for classification, which poses a major bottleneck toward achieving high accuracy. Here, we propose a concept called the two-dimensional (2D) Raman figure combined with convolutional neural network (CNN) to improve the accuracy. Two-dimensional Raman figures can be obtained from four transformation methods: spectral recurrence plot (SRP), spectral Gramian angular field (SGAF), spectral short-time Fourier transform (SSTFT), and spectral Markov transition field (SMTF). Two-dimensional CNN models all yield more than 95% accuracy, which is higher than the PCA-LDA method and the Raman-spectrum-CNN method, indicating that 2D Raman figure inputs combined with CNN may be one reason for gaining excellent performances. Among 2D-CNN models, the main difference is the conversion, where SRP is based on the structure of wavenumber series with the best performances (98.9% accuracy, 99.5% sensitivity, 98.3% specificity), followed by SGAF on the wavenumber series, SSTFT on wavenumber and intensity information, and SMTF on wavenumber position information. The inclusion of external information in the conversion may be another reason for improvement in the accuracy. The excellent capability shows huge potential for tumor diagnosis via 2D Raman figures and may be applied in other spectroscopy analytical fields.

Advancing towards Ubiquitous EEG, Correlation of In-Ear EEG with Forehead EEG.

Wearable EEG has gained popularity in recent years driven by promising uses outside of clinics and research. The ubiquitous application of continuous EEG requires unobtrusive form-factors that are easily acceptable by the end-users. In this progression, wearable EEG systems have been moving from full scalp to forehead and recently to the ear. The aim of this study is to demonstrate that emerging ear-EEG provides similar impedance and signal properties as established forehead EEG. EEG data using eyes-open and closed alpha paradigm were acquired from ten healthy subjects using generic earpieces fitted with three custom-made electrodes and a forehead electrode (at Fpx) after impedance analysis. Inter-subject variability in in-ear electrode impedance ranged from 20 kΩ to 25 kΩ at 10 Hz. Signal quality was comparable with an SNR of 6 for in-ear and 8 for forehead electrodes. Alpha attenuation was significant during the eyes-open condition in all in-ear electrodes, and it followed the structure of power spectral density plots of forehead electrodes, with the Pearson correlation coefficient of 0.92 between in-ear locations ELE (Left Ear Superior) and ERE (Right Ear Superior) and forehead locations, Fp1 and Fp2, respectively. The results indicate that in-ear EEG is an unobtrusive alternative in terms of impedance, signal properties and information content to established forehead EEG.

Circular Dichroism Spectral Similarity Plots to Extend Validation and Correction to All Measured Wavelengths.

Interlaboratory comparisons of circular dichroism (CD) spectra are useful for developing confidence in the measurements associated with optically active molecules. These measurements also help define the higher-order (secondary and tertiary) structure of biopolymers. Unfortunately, the extent of the validity of these measurements has been unclear. In this work, a method is described to extend CD validation over the entire observed wavelength range using what will be called spectral similarity plots. The method involves plotting, wavelength by wavelength, all measured spectral intensities of a sample at one concentration against the intensity values of the same material at a different concentration or pathlength. These spectral similarity plots validate the instrument in terms of spectral shape and whether the shape is shifted in intensity and/or in wavelength. This comparison tests the linearity of instrument's signal, the balance of its left and right polarizations, its wavelengths, and its spectral intensity scales. When the process is applied to materials with accepted and archived intensity values, the method can be linked to older single-wavelength and double-wavelength calibration techniques. Further, spectral similarity testing of CD spectra from samples with different concentrations run in different labs suggests that improved interlaboratory validation of CD data is possible. Since a database of archival CD measurements is available online, spectral similarity comparisons could possibly provide the ability to compare linearity, polarization balance, wavelength, and spectral intensity between all current CD instruments. If the preliminary results published here prove robust and transferable, then comparisons of full-wavelength range spectra to archived data using spectral similarity plots should become part of the standard process to validate and calibrate the performance of CD instruments.

Pre-fire aboveground biomass, estimated from LiDAR, spectral and field inventory data, as a major driver of burn severity in maritime pine (Pinus pinaster) ecosystems

The characterization of surface and canopy fuel loadings in fire-prone pine ecosystems is critical for understanding fire behavior and anticipating the most harmful ecological effects of fire. Nevertheless, the joint consideration of both overstory and understory strata in burn severity assessments is often dismissed. The aim of this work was to assess the role of total, overstory and understory pre-fire aboveground biomass (AGB), estimated by means of airborne Light Detection and Ranging (LiDAR) and Landsat data, as drivers of burn severity in a megafire occurred in a pine ecosystem dominated by Pinus pinaster Ait. in the western Mediterranean Basin. Total and overstory AGB were more accurately estimated ( R 2 equal to 0.72 and 0.68, respectively) from LiDAR and spectral data than understory AGB ( R 2 ​= ​0.26). Density and height percentile LiDAR metrics for several strata were found to be important predictors of AGB. Burn severity responded markedly and non-linearly to total ( R 2 ​= ​0.60) and overstory ( R 2 ​= ​0.53) AGB, whereas the relationship with understory AGB was weaker ( R 2 ​= ​0.21). Nevertheless, the overstory plus understory AGB contribution led to the highest ability to predict burn severity (RMSE ​= ​122.46 in dNBR scale), instead of the joint consideration as total AGB (RMSE ​= ​158.41). This study novelty evaluated the potential of pre-fire AGB, as a vegetation biophysical property derived from LiDAR, spectral and field plot inventory data, for predicting burn severity, separating the contribution of the fuel loads in the understory and overstory strata in Pinus pinaster stands. The evidenced relationships between burn severity and pre-fire AGB distribution in Pinus pinaster stands would allow the implementation of threshold criteria to support decision making in fuel treatments designed to minimize crown fire hazard.

A technical note on digitizing color mapped spectral power distribution images

AbstractData visualization is producing images that communicate data in the form of visual objects like lines, points, bars, or colored areas. Often it is necessary to extract numerical data from these images for further analysis. There are a wide variety of data digitization tools, however, only limited formats of plot images can be digitized using them. There exists many data visualization formats spread across different domains of science. Some of these formats need tailored solutions. One such format is color mapped spectral power distribution images of light sources captured by proprietary spectrometers. In this work, a methodology is discussed to digitize spectral plots of light sources. Unlike typical digitization tools which extract data based on contrast difference, color, or morphological similarities, color mapped spectral plots contain blending colors across the x‐axis, without containing any notable morphological features. In this work, image processing is applied to extract the contour representing a spectral plot. For color mapped spectral plots, the importance of appropriate binary input images for edge detection algorithms is highlighted. There are only a few edge‐detection methods give the desired results except a few. Further, the importance of repeatedly adjusting threshold values in extracting desired contours is also discussed. The estimated and measured spectral parameters are in mutual agreement with each other thereby validating the adopted approach.

Decoding self-automated and motivated finger movements using novel single-frequency filtering method – An EEG study

Electroencephalography (EEG) provides the temporal resolution required to map the neural activations for studying motor movements and control. This study aims to compare the power amplitude of electrodes covering the central and frontal regions of a 32-channel scalp EEG. The activations from a standard index finger-tapping and a game paradigm are analyzed. Twenty-five right-handed and five left-handed healthy subjects (range = 18–30 years; mean = 24.25 years; SD = 3.96 years) participated in this study. A novel single-frequency filter (SFF) bank was applied to identify the peak amplitude from the power spectral density plots. The results show that the gaming paradigm yields lower or comparable power amplitudes than the standard finger tapping. We observed that the right-hand finger tapping by the left-handed subjects shows lower between-subject dispersion in amplitude. Nonparametric Spearman correlation showed no association between game scores and power amplitude for the right-handed participants. However, for left-handers, both positive and negative associations were observed. This study demonstrates the efficacy of SFF for extracting power amplitudes with a better signal-to-noise ratio, which has implications in BCI and motor rehabilitation applications. The findings support the role of game paradigms for motor movement research and in understanding bilateral hemispheric activations in cognitive tasks.

Random telegraphic noise and 1/f noise from CNT emitters in Tuning fork-based scanning tunneling microscopy

In the present manuscript, we have investigated the fluctuations in the tunneling current (noise) from vertically aligned Carbon nanotube (CNT) emitters using home-built tuning-fork based Scanning Tunneling Microscopy/Spectroscopy (tf-STM/S). The fluctuations in the tunneling current are recorded in near field geometry (i. e. tunneling geometry, the distance between tip and CNT emitters is ∼1 nm) and in far field geometry (i.e. Fowler-Northeim tunneling (F-N), the distance between tip and CNT emitters is ≥100 nm). The recorded fluctuations in the tunneling current for near field are showing a Random Telegraphic Noise (RTN) and extrinsic 1/f type noise for various time domains. An observed fluctuation is explained with plausible mechanism of a two-level on-off trap state model. The average lifetime for the on state is τ 1 = 3.36 sec, and for the off state τ 2 = 0.89 sec. The calculated trap energy level is ΔE = 0.034 eV. The calculated slope from the power spectral density plot ∼1.9 for RTN, and ∼1.1 for extrinsic 1/f type noise. Furthermore, the extrinsic 1/f type noise is observed in the tunneling current recorded in far field geometry, where the tunneling current is generated by tunneling of electrons through a triangular barrier. The calculated slope from power spectral density plot is ≈1.0. The understanding of noise from surface interface of CNTs is important in different tunneling geometries for device applications.

Direct infusion–tandem mass spectrometry combining with data mining strategies enables rapid chemome characterization of medicinal plants: A case study of Polygala tenuifolia

Data-independent MS2 spectrum acquisition after fragmenting the precursor ion cohort with 1 Da bin, termed as MS/MSALL ®, offers an opportunity to achieve rapid chemome characterization when being coupled with direct infusion (DI). Some post-acquisition data processing strategies, such as mass defect filtering (MDF), diagnostic fragment ion filtering (DFIF), and neutral loss filtering (NLF), facilitate data extraction from massive dataset, and moreover, molecular weight (MW) imprinting allows rapid capturing those reported components. Here, DI–MS/MSALL ® was employed to acquire cubic spectral dataset, and the strategies such as MW imprinting, MDF, DFIF, and NLF, were subsequently applied to filter the structural information. The integrated pipeline was utilized for the chemome characterization of Polygala tenuifolia, a famous edible medicinal plant. To aid information filtering, an in-house chemical library was built by comprehensively collecting structural information from some available databases. A single analytical run was completed within 5 min. For MS1 spectrum processing, MW imprinting was firstly applied to capture the compounds in the chemical library, and “five-point” MDF frames were employed to pursue saponins, oligosaccharide esters, and xanthones. Regarding MS2 spectral plot, DFIF and NLF were deployed to search information-of-interest. Structural identification was accomplished by carefully correlating precursor ions and MS2 spectra, applying the well-defined mass cracking rules, and referring to literature information as well as available databases. A total of 109 compounds, mainly saponins (40 ones), oligosaccharide esters (29 ones), and xanthones (19 ones), were captured and structurally annotated. MS1 spectra were also implemented for chemome comparison between Polygala tenuifolia and several similar plants belonging to Polygala genus, resulting in the observation of significant inter- and intra-species differences. Above all, DI–MS/MSALL ® is a promising choice for high-throughput chemome profiling of, but not limited to, medicinal plants, in particular when being integrated with post-acquisition data processing strategies.

Signal quality and power spectrum analysis of remote ultra long-term subcutaneous EEG.

Ultra long-term subcutaneous electroencephalography (sqEEG) monitoring is a new modality with great potential for both health and disease, including epileptic seizure detection and forecasting. However, little is known about the long-term quality and consistency of the sqEEG signal, which is the objective of this study. The largest multicenter cohort of sqEEG was analyzed, including 14 patients with epilepsy and 12 healthy subjects, implanted with a sqEEG device (24/7 EEG™ SubQ), and recorded from 23 to 230days (median 42days), with a median data capture rate of 75% (17.9hours/day). Median power spectral density plots of each subject were examined for physiological peaks, including at diurnal and nocturnal periods. Long-term temporal trends in signal impedance and power spectral features were investigated with subject-specific linear regression models and group-level linear mixed-effects models. sqEEG spectrograms showed an approximate 1/f power distribution. Diurnal peaks in the alpha range (8-13Hz) and nocturnal peaks in the sigma range (12-16Hz) were seen in the majority of subjects. Signal impedances remained low, and frequency band powers were highly stable throughout the recording periods. The spectral characteristics of minimally invasive, ultra long-term sqEEG are similar to scalp EEG, whereas the signal is highly stationary. Our findings reinforce the suitability of this system for chronic implantation on diverse clinical applications, from seizure detection and forecasting to brain-computer interfaces.

Remote sensing of forest diversities: the effect of image resolution and spectral plot extent

ABSTRACT Detecting field diversities via remote sensing is becoming important to monitor vegetation dynamics at large scale. The characteristics of the remotely sensed image, depending on the study organism and habitat, affect the efficiency of measuring α-and β-diversities. Therefore, we examined the impact of image resolutions and spectral plot extents on the accuracy of estimating forest α-diversities and compositional variances on the active volcano Mount Usu, northern Japan. Low- (3.2 m) and high-resolution (0.8 m) IKONOS multispectral images were used to create spectral indicators from pixels covering the field plots (narrow extent) and from pixels including neighbouring area (wide extent). Six forest diversity indices were obtained for canopy and for canopy-herb layer (total diversity): species richness (S), Shannon (H’), evenness (J’), Gini-Simpson (D), and true diversity of order 1 (N 1 = expH’) and order 2 (N 2 = 1/D). Changes in species composition were assessed by dissimilarity matrices. The spectral diversity indicators were calculated from the combination of image resolutions and spectral plot extents, and then compared with field diversities. The low-resolution–narrow extent based spectral indicators showed the highest correlations with canopy and total diversities. The best spectral indicators were derived from the scores of the first axis of principal component analysis and from the near infrared band, reaching high correlations with both canopy and total field diversity indices. Of the six field diversities, J’ showed the highest correlations with single spectral indicators, and N 1, 2 showed the highest correlations with pairs of spectral indicators. The correlations between spectral and field dissimilarities were lower than the correlations between α-diversities and spectral indicators, and were unaffected by the resolution and extent. In conclusion, the best spectral indicators were obtained from the low-resolution–narrow extent combination, and the indicators estimated canopy and total field diversity indices of temperate forests equally.

Experimental Study of Rotor-Stator Contact Cycles

A rotor can contact a stator thereby inducing some very strong non-linearities that can result in a plethora of vibration phenomena. Synchronous motions, chaotic motion, backward whirl, forward whirl are some of the reported phenomena in the literature. This article presents an experimental approach based on a very flexible rotor rig designed with drill string dynamics in mind for rotordynamic experiments. A non-contact technique was used for data acquisition using a consumer-grade Go-Pro Hero 6 Black camera which captures a series of images(video) which are then post-processed using MATLAB’s image processing toolbox to understand the nature of dynamics involved. A mathematical model of the experimental rig was used for comparison with the actual experiment to assess the effectiveness of the data acquisition procedure used and validity of the model. The model is able to a good extent to reproduce the behaviour of the test rig. The fundamental phenomena exhibited by the system is analysed and discussed based on bifurcation plots, spectral intensity plots and orbit plots visualised in both rotating and stationary frame.

Dynamic modeling and stability analysis of a rotor-bearing system with bolted-disk joint

In large rotating machines, the rotor system involves multistage disks, where bolted joints are the basic form to connect the adjacent disks. Those bolted joints, subjected to unbalanced forces and moments during normal operation, influencing the rotor dynamics and giving rise to different motion states, which are of interest for investigations focusing on vibration signatures and dynamic stability. However, little research has been done on the rotor vibration characteristics considering dynamic parameters of bolted-disk joints. Thus, the bolted-disk joint element with two nodes is proposed by characterizing the mechanical relationship between the adjacent disks in this paper. Then, in terms of the proposed joint element and lumped mass modeling method, the dynamic model for the rotor system with a bolted-disk joint is established. After that, the responses of the system are solved numerically using the Newmark-β method, and bifurcation diagram, three-dimensional spectral plots, Poincare maps as well as spectral plots are used to analyze the dynamic behaviors under different tangential stiffness and transition point of bending stiffness of the bolted joint. Additionally, the influences of the bending stiffness of bolted-disk joint on system response are also examined. Finally, utilizing the rotor dynamic responses experiment performed at a bolted-joint rotor-bearing test rig with an electric tightening wrench, some of the results from the simulation study are verified. The present work provides a theoretical basis for detecting the performance of the bolted joint of the rotor-bearing system, and prevent failure caused by changes in the stiffness of the bolted joint.

Influence of size and shape on key performance metrics in spin-torque oscillators

Spin Torque Oscillators (STOs) are promising solutions in a wide variety of next generation technologies from read-head sensors in high-density magnetic recording technology to neural oscillator units for neuromorphic computing. There are several metrics that can be used to quantify the performance of an STO such as power, quality factor, frequency tunability, etc., most of which are dependent on the design of the STO device itself. Furthermore, determining the most important metric will be contingent on its desired application, meaning that it is crucial to understand how the STOs design parameters influence all aspects of its performance so that its design can be optimized to perform the desired function. In this work, we analyzed spin torque oscillations generated from 20 magnetic tunnel junctions with in-plane anisotropy and patterned into elliptical nano-pillars with a wide range of sizes and aspect ratios. For each device, we acquired 20 to 50 data sets at various bias fields and currents and used power spectral density plots to measure output power, frequency, linewidth, quality factor, and power-to-linewidth ratio for each set. We also analyzed each STOs performance in terms of the bias fields and bias currents required to maximize output power and signal quality as well as the frequency tunability with both field and current. By comparing all of these performance metrics between the 20 STOs tested, we studied the influence of device size and shape on all aspects of STO performance and used correlation coefficients to quantify relative magnitude of these effects.