Gaussian Fitting Research Articles

Investigation of Individual Pulse Emission Behaviors from Pulsar J1741–0840

We have carried out a detailed study of individual pulse emission from the pulsar J1741−0840 (B1738−08) observed using the Parkes and Effelsberg radio telescopes at the L band. The pulsar exhibits four emission components, which are not well resolved by employing multicomponent Gaussian fitting. The radio emission originates at a height of approximately 1000 km, with the viewing geometry characterized by inclination and impact angles roughly estimated at 81° and 3°, respectively. Fluctuation spectral analysis of single pulse behavior reveals two prominent periodicities, around 32 and five rotation periods. The longer periodic modulation feature is linked to nulling behavior across the entire emission window, with an updated nulling fraction of 23% ± 2% derived from pulse energy distribution via Gaussian mixture modeling. In addition to quasiperiodic nulling, the pulsar also exhibits the presence of subpulse drifting in the trailing component, with the shorter periodic feature in the fluctuation spectra related to the phenomenon of subpulse drifting, and the longitudinal separation estimated to be about 5°. Both periodic modulations show significant temporal evolution with time-dependent fluctuation power. The implications of understanding the radio emission mechanisms are discussed.

Analysis of Atomic Structure Using Spectroscopy: An Emission and Absorption Line Spectrum Study

This research study investigates the emission and absorption spectra of hydrogen, helium, and sodium using modern spectroscopic techniques to gain deeper insights into their atomic structures and electronic transitions. By utilizing high-resolution spectrometry and a Gaussian fitting algorithm, the study systematically compares both emission and absorption spectra under controlled laboratory conditions. The experimental setup included repeated trials to ensure data reliability, with spectral lines captured in terms of peak wavelength, intensity, and full width at half maximum (FWHM). Key findings reveal distinct energy level transitions for each element, with sodium displaying minimal shift between its emission and absorption peaks, indicating efficient electronic transitions. Hydrogen's and helium’s spectra provided further validation of well-established theoretical models, including the Balmer series for hydrogen. This research contributes to filling a literature gap by offering a simultaneous comparison of emission and absorption spectra for the same elements, enhancing the understanding of atomic interactions. The results hold broader implications for various fields, including astrophysics, chemical analysis, and environmental monitoring, where accurate spectral analysis is critical. The study underscores the importance of high-resolution spectroscopy in scientific and industrial applications and paves the way for future advancements in spectroscopic techniques

Nonlinear convolutional sparse filtering with Gaussian fitting for rolling bearings compound fault diagnosis

The operational precision, stability, and lifespan of servo motors are directly influenced by the healthy operation of rolling bearings. Early diagnosis of bearing faults holds significant importance in enhancing the reliability of servo motors and preventing substantial economic losses and personal injuries. However, strong noise interference in industrial environments poses challenges to bearing fault diagnosis. Additionally, the difficulty in detecting single faults in bearings often leads to the occurrence of compound faults. To achieve compound fault diagnosis under intense noise interference in industrial environments, this paper proposes the nonlinear convolutional sparse filtering (NCSF). First, generalized sigmoid and Z-score normalization are utilized to amplify fault features and reduce the influence of irrelevant interference. Subsequently, multidimensional filters are learned based on a nonlinear objective function to achieve the separation of compound faults. Then, the Gaussian function is utilized to fit the trained filters, reducing the impact of low-frequency noise. Finally, the filtered signals are envelope demodulated to analyze fault types. The capability of NCSF to distinguish compound faults amid noise interference is confirmed by both experimental and simulation results. The proposed NCSF is an effective method to realize compound fault diagnosis under strong noise interference.

Low current driven blue-violet light-emitting diodes based on p-GaN/i-Ga2O3/n-Ga2O3:Si structure

This paper reports a low current driven LED with p-GaN/i-Ga2O3/n-Ga2O3:Si structure prepared by radio frequency (RF) magnetron sputtering, the driving current of the device is only 0.02 mA. Compared with the reported drive current of the LEDs, the reduction is 100 or even 1000 times. Through the study of its electrical properties, it was found that it had excellent rectification characteristics at different ambient temperatures and the turn-on voltage was about 1.8 V. In addition, the leakage current was as low as 4.30 × 10-8 mA. Through the electroluminescence test, it was found that the device had the function of emitting in the ultraviolet (363 nm) and visible (425 nm) region, which realized the blue-violet luminescence at room temperature. Furthermore, the device had excellent high temperature color stability and ultra-low color temperature of 1924 K. The color coordinate of the device at room temperature was (0.1905,0.0955). A detailed study was conducted on the electroluminescence mechanism of the device through its band structure, and the causes of the luminescence were analyzed through the Gaussian fitting of the EL spectrum.

Proof-of-Concept Validation of Noninvasive Detection of Cortical Spreading Depolarization with High Resolution Direct Current-Electroencephalography.

Cortical spreading depolarization (SD) is increasingly recognized as a major contributor to secondary brain injury. Monitoring SDs could be used to institute and guide SD-based therapeutics if noninvasive detection methods were available. Our primary objective is to use a high density array of electrodes to compare scalp direct current (DC)-shifts to SDs detected by gold standard electrocorticography (ECoG) to establish proof-of-concept validation that scalp DC-potentials can potentially provide noninvasive SD detection. Our secondary objective is to assess usability and artifact tolerance. An 83×58 mm thermoplastic elastomer array with 29 embedded 6-mm diameter Ag/AgCl 1-mcm spaced electrodes, the CerebroPatch™ Proof-of-Concept Prototype, was adhesively placed on the forehead with an intervening electrode gel interface to record DC-electroencephalography in normal volunteers and severe acute brain injury patients in the neuro-intensive care unit some with and some without invasive subdural ECoG electrodes. The scalp and ECoG voltages were collected by a Moberg® Advanced ICU Amplifier. Artifacts were visually identified and usability issues were recorded. SD was scored on ECoG using standard criteria of DC shift with associated suppression of high frequency activity with propagation across the electrode. A six parameter Gaussian plus quadratic baseline model was used to produce time-course ECoG and scalp electrode channel plots and heat-map movies of scalp voltages. The similarity of the noninvasive scalp and invasive ECoG DC-shift time-courses was compared via the Gaussian fit parameters and confirmed if the Coefficient-of-Determination exceeded 0.80. Usability and artifact issues obscured most scalp Prototype device data except for 38 of the 140 ECoG-coded SDs over a period of 11 days in one sub-arachnoid hemorrhage patient. 26 of these DC-shifts were in readable, artifact free portions of scalp recordings and 24 had an acceptable, >0.80 Coefficient-of-Determination (0.98 [0.02], median [IQR]) between invasive ECoG and noninvasive Prototype device DC-shifts. These data suggest that these scalp DC-shifts (peak -457 ± 69 µV [mean ± StD], full-width-half maximum 70.9 ± 5.92 sec, area 18.7 ± 2.76 cm 2 ) depicted in the heat-map movies represent noninvasively detected SDs. These results suggest that noninvasive SD detection is possible using scalp DC-potential signals with a high spatial resolution EEG array. Efforts to limit artifact and improve usability in DC-EEG detection are needed in order to improve the reliability of this approach and enable multi-modal monitoring for secondary brain injury.

Calibration of the JAGB method for the Magellanic Clouds and Milky Way from Gaia DR3, considering the role of oxygen-rich AGB stars

The JAGB method is a new way of measuring distances in the Universe with the use of asymptotic giant branch (AGB) that are situated in a selected region in a J versus J − Ks colour–magnitude diagram (CMD), and relying on the fact that the absolute J magnitude is (almost) constant. It is implicitly assumed in the method that the selected stars are carbon-rich AGB stars (carbon stars). However, as the sample selected to determine MJ is purely colour based, there can also be contamination by oxygen-rich AGB stars in principle. As the ratio of carbon-rich to oxygen-rich stars is known to depend on metallicity and initial mass, the star formation history and age–metallicity relation in a galaxy should influence the value of MJ . The aim of this paper is to look at mixed samples of oxygen-rich and carbon-rich stars for the Large Magellanic Cloud (LMC), Small Magellanic Cloud (SMC), and Milky way (MW) using the Gaia catalogue of long-period variables (LPVs) as a basis. The advantage of this catalogue is that it contains a classification of O- and C-stars based on the analysis of Gaia Rp spectra. The LPV catalogue is correlated with data from the Two Micron All Sky Survey (2MASS) and samples in the LMC, SMC, and the MW are retrieved. Following methods proposed in the literature, we report the mean and median magnitudes of the selected sample using different colour and magnitude cuts and the results of fitting Gaussian and Lorentzian profiles to the luminosity function (LF). For the SMC and LMC, we confirm previous results in the literature. The LFs of the SMC and LMC JAGB stars are clearly different, yet it can be argued that the mean magnitude inside a selection box agrees at the 0.021 mag level. The results of our analysis of the MW sample are less straightforward. The contamination by O-rich stars is substantial for a classical lower limit of (J − Ks)0 = 1.3, and becomes less than 10% only for (J − Ks)0 = 1.5. The sample of AGB stars is smaller than for the MCs for two reasons. Nearby AGB stars (with potentially the best determined parallax) tend to be absent as they saturate in the 2MASS catalogue, and the parallax errors of AGB stars tend to be larger compared to non-AGB stars. Several approaches have been taken to improve the situation but finally the JAGB LF for the MW contains about 130 stars, and the fit of Gaussian and Lorentzian profiles is essentially meaningless. The mean and median magnitudes are fainter than for the MC samples by about 0.4 mag which is not predicted by theory. We do not confirm the claim in the literature that the absolute calibration of the JAGB method is independent of metallicity up to solar metallicity. A reliable calibration of the JAGB method at (near) solar metallicity should await further Gaia data releases, or should be carried out in another environment.

Hydrothermal synthesis and optical luminescence center attribution in samarium-doped zirconia nanocrystals

Sm[Formula: see text] -doped ZrO2 (SDZ) nanocrystals were prepared via a hydrothermal route without subsequent calcination. These samples underwent a series of characterizations, including X-ray diffraction (XRD), scanning electron microscopy (SEM), ultraviolet–visible (UV–Vis) spectroscopy, and photoluminescence (PL) spectral. The results showed pure cubic ZrO2 nanocrystals, with a crystallite size of 8.4 nm, were achieved by doping 8 mol% Sm[Formula: see text]. It was observed that the concentration of Sm[Formula: see text] had a significant impact on the crystallite structure of the samples, which exhibited an array of spherical shape and irregular aggregates. The inclusion of PL emission bands, spanning from the ultraviolet to blue-green range, highlighted three distinct bands. These were analyzed using Gaussian fittings and were attributed to three different types of defects, referred to as the F, F1, and F2 centers, respectively.

Long-Distance Measurements Using a Chromatic Confocal Sensor

In this work, we demonstrate the use of a chromatic confocal sensor for long-distance measurements. The sensor increases the working distance of state-of-the-art confocal sensors by a factor of 10, reaching a working distance of 620 mm. The chromatic aberration exhibited by a lens was utilized to establish the working range. The chromatic dispersion of the optics led to images of the different wavelength components at different longitudinal points along the optical axis. The sensor employs a robust algorithm to measure relative displacements of the sample’s motion. The calibration process simplifies data analysis and improves the accuracy of displacement measurements in experimental setups. To facilitate the design process, a simulator was developed specifically for this purpose. The calibration data obtained in both the experimental and the simulated data show that the simulator was able to predict the sensitivity with an error of 5%. We also describe the effect on the sensitivity of oversampling the spectrum. In addition, the superiority of low-pass filtering over Gaussian fitting over the detected spectrum is shown.

A hybrid variational level set model based on double Gaussian distribution fitting energy for image segmentation and bias correction

AbstractThe variational level set model has been widely used in image segmentation. However, its performance is significantly hindered by bias fields and noise within the images. To address these limitations, we introduce a novel hybrid variational level set model based on dual Gaussian distribution fitting (DGDF) energy in this paper. The DGDF energy integrates both local and global Gaussian distributions. The local energy is derived from the original image, while the global energy employs the corrected image, enabling effective segmentation of images with intensity inhomogeneity. Furthermore, the model demonstrates low sensitivity to weighting parameters and robust performance for noisy images. We develop an alternating iteration algorithm that combines variational methods with gradient descent to efficiently solve the proposed model. Experimental results validate the effectiveness of the model and the algorithm. In addition, the proposed model shows competitiveness on test images and three datasets compared to several state‐of‐the‐art models, including other variational level set models and deep learning‐based techniques.

Beam quality measurement and image analysis of RF optical emission system

With the development of radio-over-fiber (ROF), beam quality is also an important parameter in evaluating ROF systems. Therefore, this paper selects the low-frequency to very high frequency (VHF) direct modulated optical emission system to verify its feasibility and excellent performance. It then analyzes the beam quality and image processing. In this paper, MATLAB is selected for the theoretical simulation, then CMOS is used to collect light spots, RayCiV2.5 is used to Gaussian fit the light field intensity distribution, and finally the ideal and actual light spot parameters are compared. Due to the influence of noise, this paper also preprocessed the image by brightness adjustment, filtering, edge fitting, etc. It proposed a fast two-sided filtering algorithm, which obtained a high peak signal-to-noise ratio (PSNR) and strong applicability. The results show that the edge-mode rejection ratio is as high as 33.6 dB, the beam quality is good, and it can be well applied in ROF. The M2 factor is 2.75, the optical field intensity Gaussian fit is 99.8 %, and the signal-to-noise ratio (SNR) is as high as 54.7 dB. Moreover, the image is robust after fast bilateral filtering.

Identifying Subcomponents of Mean Pulse Profiles of PSR B1822–09 with Single Pulses

Using observational data obtained with the Five-hundred-meter Aperture Spherical radio Telescope, we succeeded in identifying subcomponents of different pulse profile components of PSR B1822−09 by the phase-to-phase cross correlations between intensity sequences of single pulses. The determined number of the subcomponents and edges of the subcomponents are consistent with the results of Gaussian fitting on the mean pulse profiles of PSR B1822−09. According to the results, the main pulse (MP) in both the radio burst mode (B mode) and the radio-quiet mode (Q mode), the precursor (PC), and the interpulse (IP) of PSR B1822−09 are all composed of three subcomponents. The correlation coefficients between intensity sequences at different pulse phases reveal a positive correlation between the subcomponent C8 of the MP and C3 of the IP in the Q mode, and a positive correlation between C5 of the PC and C2 of the IP during the switching process from the B mode to the Q mode. These complex correlations present a challenge for the existing scenarios that describe relations between different pulse profile components. We proposed a hypothesis that different subcomponents correspond to different subpatches on the pulsar surface, and emissions from a subpatch reveal responses of the subpatch to some variations like the voltage in the magnetosphere. Therefore, correlations between different subcomponents depend on the responses of the subpatches to the variations.

Comparison of On-Sky Wavelength Calibration Methods for Integral Field Spectrograph

With advancements in technology, scientists are delving deeper in their explorations of the universe. Integral field spectrograph (IFS) play a significant role in investigating the physical properties of supermassive black holes at the centers of galaxies, the nuclei of galaxies, and the star formation processes within galaxies, including under extreme conditions such as those present in galaxy mergers, ultra-low-metallicity galaxies, and star-forming galaxies with strong feedback. IFS transform the spatial field into a linear field using an image slicer and obtain the spectra of targets in each spatial resolution element through a grating. Through scientific processing, two-dimensional images for each target band can be obtained. IFS use concave gratings as dispersion systems to decompose the polychromatic light emitted by celestial bodies into monochromatic light, arranged linearly according to wavelength. In this experiment, the working environment of a star was simulated in the laboratory to facilitate the wavelength calibration of the space integral field spectrometer. Tools necessary for the calibration process were also explored. A mercury–argon lamp was employed as the light source to extract characteristic information from each pixel in the detector, facilitating the wavelength calibration of the spatial IFS. The optimal peak-finding method was selected by contrasting the center of weight, polynomial fitting, and Gaussian fitting methods. Ultimately, employing the 4FFT-LMG algorithm to fit Gaussian curves enabled the determination of the spectral peak positions, yielding wavelength calibration coefficients for a spatial IFS within the range of 360 nm to 600 nm. The correlation of the fitting results between the detector pixel positions and corresponding wavelengths was >99.99%. The calibration accuracy during wavelength calibration was 0.0067 nm, reaching a very high level.

Overlapping microbubble localization based on multiscale statistical features for ultrasound super-resolution imaging

Ultrasound localization microscopy enables visualization of the microvasculature through the localization and tracking of isolated microbubbles (MBs). Currently, improving the precision for localizing overlapping MBs at high concentration to decrease the acquisition time remains a challenge. This study introduces multiscale statistical feature localization (MSFL) to address this challenge. First, the overlapping MBs are separated by local energy and blobness filters constructed from the Hessian matrix of texture features and its eigenvalues. Then, multiscale and orientation kernels are modeled to adapt to the appearance of various MBs; their amplitude and gradient convolution response results jointly determine the credibility of the MBs. Finally, precise MB localization is obtained by the weighted average of the local maxima of the response maps at each scale to achieve super-resolution (SR) imaging. The proposed method is evaluated using simulation and in-vivo datasets. Simulation results demonstrate that MSFL can adapt to asymmetric Gaussian distributions and improve overlapping MB localization, with a 9.28 % improvement in localization precision and a 5 % greater Jaccard index compared to the Gaussian fitting method. Additionally, the strong robustness of MSFL under noise interference maintains its ability to locate more MBs, and reconstruct the same saturation vessels with 36 % acquisition time reduction compared to Radial symmetry method. For SR images, MSFL can draw smoother interlaced vessels when more overlapping MBs are present, and quickly reconstructs more saturated in vivo microvasculature with a resolution is 10.5 μm(λ/10). These results validate the advantages of MSFL in achieving precise SR imaging with a short acquisition time.

Characterization and Dataset Compilation of Torque–Angle Curve Behavior for M2/M3 Screws

This research explores the torque–angle behavior of M2/M3 screws in automotive applications, focusing on ensuring component reliability and manufacturing precision within the recommended assembly specification limits. M2/M3 screws, often used in tight spaces, are susceptible to issues like stripped threads and inconsistent torque, which can compromise safety and performance. The study’s primary objective is to develop a comprehensive dataset of torque–angle measurements for these screws, facilitating the analysis of key parameters such as torque-to-seat, torque-to-fail, and process windows. By applying Gaussian curve fitting and Gaussian process regression, the research models and simulates torque behavior to understand torque dynamics in small fasteners and remarks on the potential of statistical methods in torque analysis, offering insights for improving manufacturing practices. As a result, it can be concluded that the proposed stochastics methodologies offer the benefit of fail-to-seat ratio improvement, allow inference, reduce the sample size needed in incoming test studies, and minimize the number of destructive test samples needed.

A yellow-green-emitting phosphor K3LaSi2O7:Eu2+ with superior thermal stability for solid-state lighting

Yellow-green-emitting phosphors with good thermal stability when excited by ultraviolet (UV) light are relatively less common compared to blue and red phosphors. In this study, a serial of K3LaSi2O7:xEu2+ (KLSO: xEu2+) phosphors with hexagonal structure (P63/mcm space group) were successfully synthesized. Under 360 nm excitation, KLSO: xEu2+ exhibits yellow-green luminescence peaked at 540 nm. Additionally, sharp emission peaks at 592 and 614 nm are observed when excited at 390 nm, indicating a small amount of Eu3+ ions still exist. The Eu2+ ions are found to occupy both La3+ and K+ sites in the KLSO host, resulting in two luminescent centers at 535 and 592 nm based on Gaussian fitting of the emission spectrum. The optimal Eu2+-doping concentration is verified at KLSO:0.05Eu2+. The thermal stability tests indicate that its luminescence intensity at 150 °C maintains 90.01 % of that at room-temperature. Meanwhile, the component substitution of Na+ ions for K+ ones is beneficial for the enhancement of luminescence, achieving a quantum efficiency of 40.62 %. Finally, this phosphor is applied to white LED, which shows a correlated color temperature (CCT) of 4164 K, a color rendering index (CRI) of 86.6, and CIE color coordinate of (0.3604,0.3174). It indicates that K3LaSi2O7:xEu2+ is a promising candidate for solid-state lighting.

Damage detection in composite and plastic thin-wall beams by operational modal analysis: An experimental assessment

The detection and localization of different damage features in thin-wall beam composite and plastic beams using Operational Modal Analysis (OMA) has been demonstrated experimentally. The detection of small damage features using modal analysis techniques is an emerging field, with few experimental OMA-based assessments having been reported so far. The proposed method is based on OMA combined with Stochastic Subspace Identification (SSI) and the enhancement of damage features by Continuous Wavelet Transforms (CWT). A composite thin-wall beam (CTWB) structure in two measurement configurations and a PVC tube in a free-free configuration have been tested. Damage features detected include extra masses attached to the beam, with a range from 9.5 % to 14.0 % of the beam mass, and small cracks perpendicular to the beam axis with lengths of about 4 % of the perimeter of the cross section. Calibration curves relating the strength of the damage signal with the weight of the attached masses have been constructed. Two simultaneous cracks or two masses could be detected as well. The quantification and localization of damage feature along the beam was possible through the use of Gaussian fit surface applied to damage maps obtained with the CWT technique. The width of the Gaussian fit curve was of the order of the distance between accelerometers, but the accuracy, estimated to be around 3 % of the beam length, was found to have sub-grid resolution. The proposed method was shown to work reliably with a relatively coarse measurement grid, potentially allowing for cost-effective Structural Health Monitoring (SHM) approaches.

An Investigation on the Thermal Degradation Kinetics of Wood-Polymer Composites Used in Interior Automobile Panels via Non-Isothermal Thermogravimetry

Wood plastic composites (WPCs) offer a promising alternative for various automotive components, combining the benefits of wood and polymers such as lightness, strength, and sustainability. However, determining decomposition kinetics is challenging due to the intricate composition of WPCs. Therefore, this research work focused to analyze the relationship between the thermal degradation of WPCs, the degradation atmosphere, and the kinetics. The kinetic parameters were evaluated by Coats and Redfern method based on a set of TGA experiments under variable atmospheres (inert and oxidative) using 10 ℃/min heating rate. Thermograms demonstrated significant differences in the thermal properties of WPC when subjected to oxidative and inert atmospheres, despite two conditions having the same number of thermal degradation zones. It has been suggested that the process of thermal decomposition of WPC contains three weight loss segments under inert and oxidative atmosphere according to the Gaussian multi-peak fitting function. The Coats-Redfern method showed multi-step chemical kinetics and more accurately characterizes the decomposition behavior of WPC, attributing to its multi-compositional properties. Proposed reaction schemes had regression coefficients higher than 0.9809 to obtain reaction order, activation energy and pre-exponential factor.

A Preliminary Comparative Study on the Centering Algorithms for Cassini-ISS NAC Images

Obtaining high precision is an important consideration for astrometric studies using images from the Narrow Angle Camera (NAC) of the Cassini Imaging Science Subsystem (ISS). Selecting the best centering algorithm is key to enhancing astrometric accuracy. In this study, we compared the accuracy of five centering algorithms: Gaussian fitting, the modified moments method, and three point-spread function (PSF) fitting methods (effective PSF (ePSF), PSFEx, and extended PSF (xPSF) from the Cassini Imaging Central Laboratory for Operations (CICLOPS)). We assessed these algorithms using 70 ISS NAC star field images taken with CL1 and CL2 filters across different stellar magnitudes. The ePSF method consistently demonstrated the highest accuracy, achieving precision below 0.03 pixels for stars of magnitude 8–9. Compared to the previously considered best, the modified moments method, the ePSF method improved overall accuracy by about 10% and 21% in the sample and line directions, respectively. Surprisingly, the xPSF model provided by CICLOPS had lower precision than the ePSF. Conversely, the ePSF exhibits an improvement in measurement precision of 23% and 17% in the sample and line directions, respectively, over the xPSF. This discrepancy might be attributed to the xPSF focusing on photometry rather than astrometry. These findings highlight the necessity of constructing PSF models specifically tailored for astrometric purposes in NAC images and provide guidance for enhancing astrometric measurements using these ISS NAC images.

A shifted ratio spectrum strategy for effective subtraction of fluorescence interference in Raman spectra.

Raman spectroscopy is an important technique for analyzing the chemical composition of samples in many fields. A severe challenge often encountered in Raman measurements is the presence of a concurrent fluorescence background, especially in biological samples. In order to obtain accurate Raman spectra, the fluorescence background must be subtracted from the original Raman spectra. We proposed a shifted ratio spectrum method to subtract the strong fluorescence background from the original Raman spectrum. First, the original Raman spectrum is divided into multiple regions according to the spectral shape of the shifted ratio spectra, and then, Gaussian fitting is performed in each region. The fitting results are stitched together in order to obtain the complete fluorescence background. Finally, this fluorescence background is subtracted from the original spectrum to obtain a pure Raman spectrum. This method can accurately subtract the fluorescence background of Rhodamine 6G (R6G)/ethanol solution and serum. This highlights the great potential of this method for applications in both biological and non-biological samples.

Shape-controlled growth of beta-gallium oxide nanowires and experimental investigation on the origination of electrons

Diameter-controlled growth of monoclinic gallium oxide nanowires was performed by chemical vapor deposition technique. Prior to growth, a thin layer of Au films was fabricated, SEM images indicated that Au could converge nanoparticles to govern the growth of β-Ga2O3 nanowires. The SEM images revealed both diameter and length of β-Ga2O3 nanowires strongly depended on the growth temperature. Nanowires grown at 1100 °C temperature have the minimum diameters and uniform lengths, compared with those grown at 900 °C and 1000 °C. The reasons are that a combination and a competition of vapor-liquid-solid (VLS) and vapor-solid (VS) mechanism occur in the growth process. High temperature would provide enough energy to make Ga and O atoms grow along one-dimensional axial orientation following the VLS mechanism. However, low temperature confines atoms at the nanowires interface and enhance sidewalls coalescence following the VS mechanism. X-ray diffraction (XRD) patterns and refinement indicated that the grown samples were of high crystallinity and had intrinsic oxygen vacancies. Photoluminescence spectra were examined and then followed by Gaussian fitting. Through analysis, the emission peaks were considered to originate from intrinsic oxygen vacancies and Ga-O vacancy pairs, consisting with the XRD refinement results. β-Ga2O3 nanowires was coated on the interdigitated electrode, the response to the ultraviolet light and oxygen was studied.