Investigation of oxidation mechanism of SiC single crystal for plasma electrochemical oxidation

Yin, Xincheng; Li, Shujuan; Ma, Gaoling; Jia, Zhen Yuan; Xu, Linli

doi:10.1039/d1ra04604g

Cited by 16 publications

(10 citation statements)

References 35 publications

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“… Preoperative Preparation . All patients were intramuscularly injected with pethidine 50 mg before positioning, and appropriate body positions were taken according to the position of the nodule after three-dimensional reconstruction and the surgical approach, and the patients were instructed to keep a relatively static state and a relatively stable breathing range as much as possible [ 16 ]. CT scan is performed to display the location of the target lesion.…”

Section: Methodsmentioning

confidence: 99%

The Effect of CT Imaging Technology in the Diagnosis of Thoracic and Cardiac Surgery Diseases

et al. 2022

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In order to increase doctors’ cognition of the three-dimensional anatomical structure of cardiothoracic and cardiothoracic surgery and increase the diagnosis rate and cure rate of cardiothoracic surgery diseases, the authors propose a method of CT imaging technology for diagnosing cardiothoracic surgery diseases. Through the joint Hookwire positioning of 3D-CTBA, application in thoracoscopic segmentectomy and CT energy spectrum curve, retrospective analysis of diagnosis of intrathoracic lymph node metastasis in non-small-cell lung cancer, 3D-CTBA and CT-guided Hookwire localization, and preoperative CT-enhanced scanning were performed using two methods. The experimental results showed that the chest tube placement time, postoperative thoracic drainage volume, and postoperative hospital stay after the first operation all showed a good trend. The diagnostic sensitivity was 87.1%. The specificity was 92.6%. The correct index was 79.7%. The accuracy was 91.3%. The positive predictive value was 79.4%. And the negative predictive value was 95.7%. These data prove that CT imaging technology has high diagnostic value for thoracic and cardiac surgery diseases and can effectively help the formulation and implementation of thoracic and cardiac surgery diseases.

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Section: Methodsmentioning

confidence: 99%

The Effect of CT Imaging Technology in the Diagnosis of Thoracic and Cardiac Surgery Diseases

et al. 2022

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“…The possible reaction equations are as follows. [ 40–42 ]

\begin{array}{*{20}{c}}{{\rm{SiC}} + \;\cdot{{\rm{O}}_2} + 4\cdot{\rm{OH}} \to \;{\rm{Si}}{{\rm{O}}_2} + {\rm{C}}{{\rm{O}}_2} + 2{{\rm{H}}_2}{\rm{O}}}\end{array}

\begin{array}{*{20}{c}}{{\rm{SiC}} + 4\cdot{\rm{OH}} + 4{{\rm{h}}^ + }\; \to \;{\rm{Si}}{{\rm{O}}_2} + 4{{\rm{H}}^ + } + {\rm{C}}{{\rm{O}}_2} \uparrow }\end{array}

…”

Section: Resultsmentioning

confidence: 99%

Fabrication of Homogeneous Nanoporous Structure on 4H‐/6H‐SiC Wafer Surface via Efficient and Eco‐Friendly Electrolytic Plasma‐Assisted Chemical Etching

Zhan

Liu

et al. 2023

Small

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bio-compatibility, and high resistance to mechanical damage and chemical attack. [1,2] The combination of exceptional intrinsic properties with a high specific surface area and low dimensionality (in the case of SiC membranes) make nanoporous SiC excellent candidates for application in optoelectronic nanodevices. Many studies have reported that nanoporous structures can improve the material's optical, [3] electronic, and oxidation properties. [4,5] Various possible application scenarios for nanoporous structures have been reported in fields like microelectromechanical systems (MEMS), [6] membranes for biomedical applications, [7] chemical sensors, [8] supercapacitors, [9] and photoelectrodes. [10] In recent years, there have been extensive studies on constructing nanostructure SiC, employing robust and efficient techniques with improved controllability. However, the nanostructuring of SiC is very challenging owing to its extremely high chemical inertness and mechanical resistance. Although various fabrication methods have been developed, SiC nanofabrication techniques, which must meet the strict requirements of scalability and efficiency for industrial applications, remain very limited.The nanofabrication techniques for SiC can be broadly classified into two principal approaches, that is, top-down and bottom-up. The most explored bottom-up nanofabrication approach is a direct chemical synthesis for the growth of low-dimension SiC (i.e., 1D or 2D), such as chemical vapor deposition for the growth of SiC nanowires. [11] However, to produce nanostructure SiC from a single crystal wafer, for example, nanoporous SiC, the top-down fabrication approach by nanoscale etching is more effective and robust. Compared with the bottom-up approach, the top-down principle enables a well-ordered nanostructure with high homogeneity. Primary top-down nanofabrication methods include nanolithography using high-energy particles (i.e., photon, ion, electron), [12] dry etching, [13] and wet etching, [14] resulting in high-quality nanostructures for application in electronic devices or MEMS. The semiconductor lithography technique using UV or electron beam is mainly used for high-resolution nanostructure Nanoporous single-crystal silicon carbide (SiC) is widely used in various applications such as protein dialysis, as a catalyst support, and in photoanodes for photoelectrochemical water splitting. However, the fabrication of nano-structured SiC is challenging owing to its extreme chemical and mechanical stability. This study demonstrates a highly-efficient, open-circuit electrolytic plasma-assisted chemical etching (EPACE) method without aggressive fluorine-containing reactants. The EPACE method enables the nano-structuring of SiC via a plasma-enveloped microtool traversing over the target material in an electrolyte bath. Through process design, EPACE readily produces a uniform nanoporous layer on a 4H-SiC wafer in KOH aqueous solution, with adjustable pore diameters in the range 40-130 nm. Plasma diagnosis by optical emission spectrometr...

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“…The inputs for test set are shown in Table 4. To make the model more inclusive and convinced, Root Mean Square Error (RMSE) and R 2 29,30 are chosen as evaluation indicators and shown in equations ( 9) and (10). It can be deduced that the RMAE is 0.403 and the R 2 is 0.9915 in the test set, which indicates that the model owns high ability to map the relationship in CMP.…”

Section: Experiments Verification and Discussion Of Dnn Modelmentioning

confidence: 99%

“…6,7 During the CMP process, the procedure is so complicated that the empirical model and physical model cannot clarify the process thoroughly. [8][9][10] Due to the above reasons, how to build a model to study the relationship between parameters and surface quality quantitatively and how to optimize the parameters based on the model have always been worth-solving problems in CMP process. As a burgeoning artificial intelligence technology, machine learning methods, such as Support Vector Regression (SVR), Decision Tree (DT), Artificial Neural Network (ANN) can analyze the data quickly, by building a complex relationship between inputs and output(s) parameters.…”

Section: Introductionmentioning

confidence: 99%

Modelling and optimization of surface roughness in chemical mechanical polishing based on DNN-GA

Pan

Guo

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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The surface quality of Lithium Niobate (LiNbO3) has a significant influence on photonics and optoelectronics components. However, the prediction and optimization models of surface roughness were not accurate due to the random parameters. Hence, a prediction model of surface roughness is established based on an improved neural network, and a new method is proposed to optimize the arguments in chemical mechanical polishing (CMP) process. In the model, the structure of the neural network is optimized according to data features rather than choosing networks randomly. To improve the model accuracy, the optimal number of hidden layers is 4 and the corresponding amounts of nodes in each layer are 46, 34, 28, and 33, respectively. ReLU function is chosen as activation function. Subsequently, the relationship between surface roughness and processing parameters is built and the variation process of surface roughness is particularly considered. The accuracy and generalization ability of the model is verified by the experiments with the Mean Absolute Percentage Error (MAPE) of 6.42% and Root Mean Square Error (RMSE) of 0.403. Furthermore, the Genetic Algorithm (GA) method based on the selected model is applied to optimize processing arguments under the target surface roughness value of 0.3 nm. The accuracy of the fusion model is also validated by experiments with an error of 13.3%.

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Investigation of oxidation mechanism of SiC single crystal for plasma electrochemical oxidation

Abstract: Silicon carbide (SiC) surface modification is an essential step in chemical mechanical polishing. For high quality and high efficiency surface modification of SiC, a green and promising surface modification method named plasma electrochemical oxidation (PECO) is proposed.

Cited by 16 publications

References 35 publications

The Effect of CT Imaging Technology in the Diagnosis of Thoracic and Cardiac Surgery Diseases

The Effect of CT Imaging Technology in the Diagnosis of Thoracic and Cardiac Surgery Diseases

Fabrication of Homogeneous Nanoporous Structure on 4H‐/6H‐SiC Wafer Surface via Efficient and Eco‐Friendly Electrolytic Plasma‐Assisted Chemical Etching

Modelling and optimization of surface roughness in chemical mechanical polishing based on DNN-GA

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