Somphonsane, Ratchanok

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In-situ current annealing of graphene-metal contacts
(2018-12-19)
Ramamoorthy, Harihara
;
Somphonsane, Ratchanok
We study the effect of current-induced annealing on contact resistance between graphene and metal contacts, demonstrating that this technique may be used as an effective in-situ annealing procedure to improve the graphene-metal contact resistance which has long been an issue in the characterization of graphene-based devices. By studying as many as 30 devices with varying sample sizes and geometry, we are able to reduce the overall resistance systematically to around 400 Ω⋅μm, which is competitive with the best values obtained in the literature to treat this problem. We also demonstrate the effectiveness of current annealing in desorbing contaminants from the surface of the graphene layer, simultaneously shifting the charge-neutrality point to zero back-gate voltage, thus allowing the tuning of carrier density on both the electron and hole sides of the Dirac spectrum.
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The optimized time of 18F-THK5351 PET/CT in normal Thai population
(2018-01-01)
Thonglim, Pachara
;
Sungkarat, Witaya
;
Chotipanich, Chanisa
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Somphonsane, Ratchanok
;
Phoemphoonthanyakit, Suwaphit
In this paper, we investigated 18F-THK5351 PET/CT image of normal Thai population for the optimized time of radioactive tracer PET/CT. Twenty-five volunteers without neurological or psychiatric illnesses and all of them have no abnormalities detected on neurologic examination. All subject were underdiagnosed on 18F-THK5351 PET/CT and 3.0 Tesla MR imaging. THK5351 PET/CT were operated on the co-registered MRI comprised for drawing an ROI. The DICOM file was converted to.img file,.hdr file and then merge with each other for obtaining an fmridata.mat. Position of ROI and fmridata.mat were used to plot graph showing the relationship between quantitative uptake with the frame of image. The optimized time of 18F-THK5351 PET/CT in normal Thai population is 50 to 70 minutes.
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Versatile Recognition of Graphene Layers from Optical Images Under Controlled Illumination Through Green-Channel Correlation Method
(2024-06-23)
Sahriar, Miah Abdullah
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Abed, Mohd Rakibul Hasan
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Somphonsane, Ratchanok
;
Jang, Houk
;
Nam, Chang Yong
The proposed method for identifying the number of exfoliated graphene layers on an oxide substrate from optical images is both simple and versatile. It involves using a limited number of input images for training, paired with a larger set of well-published Github images for testing and prediction. This study has employed a linear regression-based method in executing its thresholding process. This method leverages the red, green, and blue color channels of image pixels and establishes a correlation between the green channel of the background and the green channel of various graphene layers. The method is positioned as an alternative to both deep learning-based graphene recognition and traditional microscopic analysis. Notably, the proposed methodology performs well under conditions where the influence of surrounding light on the graphene-on-oxide sample is minimal. It enables the rapid identification of various graphene layers, showcasing its feasibility for non-destructive identification. The study also addresses the functionality of the methodology under nonhomogeneous lighting conditions, demonstrating successful predictions of graphene layers even in lower-quality images compared to those typically published in literature. In summary, the proposed methodology offers a quick, inexpensive, and effective means of non-destructively identifying graphene layers from optical images. Its versatility and performance under varying conditions make it a promising approach for practical applications in graphene research. Additionally, and critically: the methods highlighted in this research can be utilized across a multitude of disciplines (from bioengineering to electrical, materials, nanoengineering, etc.) for one of the most fundamental areas of experimental research in STEM at the undergraduate level: accurately identifying multiple systems from optical images. A broad, relevant, and timely curriculum can be built around data analytics and application to solving STEM problems - including components such as data mining, cleaning, wrangling, and analysis, and critically, tying in these processes in solving real experimental challenges in a laboratory setting.
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The investigation of corrosion behavior of electrodeposited Co-Fe alloys surface with phase and 3D reconstruction of image using TIE and TPE
(2018-01-01)
Srisuwan, Thanthanat
;
Somphonsane, Ratchanok
;
Sutthiruangwong, Sutha
;
Buranasiri, Prathan
In this research, phase retrieval using transport of intensity equation (TIE) and transport of phase equation (TPE) have been used for determine the surface of corrosion behavior of electrodeposited Co-Fe alloys, an important component in hard disk drive. Without interferometer as used in digital holography technique, by using TIE and TPE, our observing setup is simple and compact. The experimental results show the capability of TIE and TPE for observing the pitting corrosion. The pitting corrosion of Co-Fe image results have also shown. The dynamic process of microstructure surface system would be conducted and may be applied to hard disk drive industry in the future.

Somphonsane, Ratchanok

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