Rapid Identification of Areas of Interest in Thin Film Materials Libraries by Combining Electrical, Optical, X-ray Diffraction, and Mechanical High-Throughput Measurements: A Case Study for the System Ni–Al

2014 ◽  
Vol 16 (12) ◽  
pp. 686-694 ◽  
Author(s):  
S. Thienhaus ◽  
D. Naujoks ◽  
J. Pfetzing-Micklich ◽  
D. König ◽  
A. Ludwig
2016 ◽  
pp. 45-54 ◽  
Author(s):  
LD Connor ◽  
PM Mignanelli ◽  
S Guérin ◽  
JP Soulié ◽  
C Mormiche ◽  
...  

2010 ◽  
Vol 82 (11) ◽  
pp. 4564-4569 ◽  
Author(s):  
Scilla Roncallo ◽  
Omeed Karimi ◽  
Keith D. Rogers ◽  
John M. Gregoire ◽  
David W. Lane ◽  
...  

2003 ◽  
Vol 775 ◽  
Author(s):  
Donghai Wang ◽  
David T. Johnson ◽  
Byron F. McCaughey ◽  
J. Eric Hampsey ◽  
Jibao He ◽  
...  

AbstractPalladium nanowires have been electrodeposited into mesoporous silica thin film templates. Palladium continually grows and fills silica mesopores starting from a bottom conductive substrate, providing a ready and efficient route to fabricate a macroscopic palladium nanowire thin films for potentially use in fuel cells, electrodes, sensors, and other applications. X-ray diffraction (XRD) and transmission electron microscopy (TEM) indicate it is possible to create different nanowire morphology such as bundles and swirling mesostructure based on the template pore structure.


2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Lars Banko ◽  
Phillip M. Maffettone ◽  
Dennis Naujoks ◽  
Daniel Olds ◽  
Alfred Ludwig

AbstractWe apply variational autoencoders (VAE) to X-ray diffraction (XRD) data analysis on both simulated and experimental thin-film data. We show that crystal structure representations learned by a VAE reveal latent information, such as the structural similarity of textured diffraction patterns. While other artificial intelligence (AI) agents are effective at classifying XRD data into known phases, a similarly conditioned VAE is uniquely effective at knowing what it doesn’t know: it can rapidly identify data outside the distribution it was trained on, such as novel phases and mixtures. These capabilities demonstrate that a VAE is a valuable AI agent for aiding materials discovery and understanding XRD measurements both ‘on-the-fly’ and during post hoc analysis.


1988 ◽  
Vol 119 ◽  
Author(s):  
Hung-Yu Liu ◽  
Peng-Heng Chang ◽  
Jim Bohlman ◽  
Hun-Lian Tsai

AbstractThe interaction of Al and W in the Si/SiO2/W-Ti/Al thin film system is studied quantitatively by glancing angle x-ray diffraction. The formation of Al-W compounds due to annealing is monitored by the variation of the integrated intensity from a few x-ray diffraction peaks of the corresponding compounds. The annealing was conducted at 400°C, 450°C and 500°C from 1 hour to 300 hours. The kinetics of compound formation is determined using x-ray diffraction data and verified by TEM observations. We will also show the correlation of the compound formation to the change of the electrical properties of these films.


1990 ◽  
Vol 7 (7) ◽  
pp. 308-311
Author(s):  
Li Chaorong ◽  
Mai Zhenhong ◽  
Cui Shufan ◽  
Zhou Junming ◽  
Yutian Wang

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