Real-time optical diagnostics of graphene growth induced by pulsed chemical vapor deposition

Nanoscale ◽  
2013 ◽  
Vol 5 (14) ◽  
pp. 6507 ◽  
Author(s):  
Alexander A. Puretzky ◽  
David B. Geohegan ◽  
Sreekanth Pannala ◽  
Christopher M. Rouleau ◽  
Murari Regmi ◽  
...  
Keyword(s):  
Chemical Vapor Deposition ◽  
Real Time ◽  
Vapor Deposition ◽  
Chemical Vapor ◽  
Optical Diagnostics ◽  
Graphene Growth

Effect of Cu surface treatment in graphene growth by chemical vapor deposition

2019 ◽  
Vol 236 ◽  
pp. 403-407 ◽  
Author(s):  
Seong-Yong Cho ◽  
Minsu Kim ◽  
Min-Sik Kim ◽  
Min-Hyun Lee ◽  
Ki-Bum Kim
Keyword(s):  
Chemical Vapor Deposition ◽  
Surface Treatment ◽  
Vapor Deposition ◽  
Chemical Vapor ◽  
Graphene Growth

scholarly journals Real-time in-situ Investigation of III-V Nanowire Growth using Custom-designed Hybrid Chemical Vapor Deposition-TEM

2017 ◽  
Vol 23 (S1) ◽  
pp. 1716-1717 ◽  
Author(s):  
Kimberly Dick Thelander ◽  
L. Reine Wallenberg ◽  
Axel R. Persson ◽  
Marcus Tornberg ◽  
Daniel Jacobsson ◽  
...  
Keyword(s):  
Chemical Vapor Deposition ◽  
Real Time ◽  
Vapor Deposition ◽  
Chemical Vapor ◽  
Nanowire Growth ◽  
In Situ Investigation

Real-Time Diagnosis of Nano-Sized Contaminant Particles Generated in TiN Metal Organic Chemical Vapor Deposition

2009 ◽  
Vol 2 ◽  
pp. 035501 ◽  
Author(s):  
Jeonggil Na ◽  
Taesung Kim ◽  
Jae-Boong Choi ◽  
Ju-Young Yun ◽  
Yong-Hyeon Shin ◽  
...  
Keyword(s):  
Chemical Vapor Deposition ◽  
Real Time ◽  
Vapor Deposition ◽  
Chemical Vapor ◽  
Organic Chemical ◽  
Metal Organic ◽  
Tin Metal ◽  
Organic Chemical Vapor Deposition ◽  
Time Diagnosis

Real-Time Composition And Thickness Control Techniques In A Metalorganic Chemical Vapor Deposition Process

1995 ◽  
Vol 406 ◽  
Author(s):  
M. S. Gaffneyt ◽  
C. M. Reavesl ◽  
A. L Holmes ◽  
R. S. Smith ◽  
S. P. DenBaars
Keyword(s):  
Chemical Vapor Deposition ◽  
Real Time ◽  
Vapor Deposition ◽  
Metalorganic Chemical Vapor Deposition ◽  
Chemical Vapor ◽  
Normal Operation ◽  
Growth Monitoring ◽  
X Ray Diffraction ◽  
X Ray ◽  
Metalorganic Chemical

AbstractMetalorganic chemical vapor deposition (MOCVD) is a process used to manufacture electronic and optoelectronic devices that has traditionally lacked real-time growth monitoring and control. We have developed control strategies that incorporate monitors as real-time control sensors to improve MOCVD growth. An analog control system with an ultrasonic concentration monitor was used to reject bubbler concentration disturbances which exist under normal operation, during the growth of a four-period GaInAs/InP superlattice. Using X-ray diffraction, it was determined that the normally occurring concentration variations led to a wider GaInAs peak in the uncompensated growths as compared to the compensated growths, indicating that closed loop control improved GaInAs composition regulation. In further analysis of the X-ray diffraction curves, superlattice peaks were used as a measure of high crystalline quality. The compensated curve clearly displayed eight orders of satellite peaks, whereas the uncompensated curve shows little evidence of satellite peaks.

Intelligent Process Control of Silicon Nitride Chemical Vapor Deposition

1994 ◽  
Vol 363 ◽  
Author(s):  
Paul S. Bowen ◽  
Steve K. Phelps ◽  
Harry I. Ringermacher ◽  
Richard D. Veltri
Keyword(s):  
Chemical Vapor Deposition ◽  
High Temperature ◽  
Silicon Nitride ◽  
Process Control ◽  
Real Time ◽  
Vapor Deposition ◽  
Process Model ◽  
Chemical Vapor ◽  
Laser Ultrasonics ◽  
Hierarchical Architecture

AbstractThe chemical vapor deposition of silicon nitride can be used to protect advanced materials and composites from high temperature, corrosive, and oxidative environments. Desired coating characteristics, such as uniformity and morphology, cannot be measured in-situ by traditional sensors due to the adverse conditions within the high-temperature reactor. A control strategy has been developed which utilizes a process model and an advanced laser-based sensor to measure the deposition rate of the silicon nitride coating in real-time. The control system is based on a three level hierarchical architecture which functionally separates the process control into PID, supervisory and advanced sensor-based control. Optimal setpoint schedules for the supervisory level are derived from a quasi-fuzzy logic inverse mapping of the process model. An advanced sensor utilizing laser ultrasonics provides real-time coating thickness estimates. Model bias is characterized for each reactor and is correlated on-line with the sensor's deposit thickness estimate. Deviations from model predictions may result in parametric changes to the process model. New setpoint schedules are then created as input to the supervisory control level by regenerating the inverse map of the updated process model.

Effects of Process Parameters on Graphene Growth Via Low-Pressure Chemical Vapor Deposition

2020 ◽  
Vol 8 (3) ◽  
Author(s):  
Byoungdo Lee ◽  
Weishen Chu ◽  
Wei Li
Keyword(s):  
Grain Size ◽  
Chemical Vapor Deposition ◽  
Process Parameters ◽  
Vapor Deposition ◽  
Chemical Vapor ◽  
High Growth ◽  
Low Pressure ◽  
Large Set ◽  
Graphene Growth ◽  
Pressure Chemical

Abstract Graphene has attracted enormous research interest due to its extraordinary material properties. Process control to achieve high-quality graphene is indispensable for graphene-based applications. This research investigates the effects of process parameters on graphene quality in a low-pressure chemical vapor deposition (LPCVD) graphene growth process. A fractional factorial design of experiment is conducted to provide understanding on not only the main effect of process parameters, but also the interaction effect among them. Graphene quality including the number of layers and grain size is analyzed. To achieve monolayer graphene with large grain size, a condition with low CH4–H2 ratio, short growth time, high growth pressure, high growth temperature, and slow cooling rate is recommended. This study considers a large set of process parameters with their interaction effects and provides guidelines to optimize graphene growth via LPCVD focusing on the number of graphene layers and the grain size.

The growth modes of graphene in the initial stage of a chemical vapor-deposition process

RSC Advances ◽  
2016 ◽  
Vol 6 (94) ◽  
pp. 91157-91162 ◽  
Author(s):  
Zhaoming Fu ◽  
Yipeng An
Keyword(s):  
Chemical Vapor Deposition ◽  
Vapor Deposition ◽  
Chemical Vapor ◽  
Deposition Process ◽  
Chemical Vapor Deposition Process ◽  
Graphene Growth ◽  
Carbon Chains ◽  
Growth Modes ◽  
Initial Stage ◽  
Vapor Deposition Process

The different growth modes of carbon chains and carbon islands in the initial stage of graphene growth.

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