Controlling semiconductor nanoparticle size distributions with tailored ultrashort pulses

2006 ◽  
Vol 17 (16) ◽  
pp. 4065-4071 ◽  
Author(s):  
R Hergenröder ◽  
M Miclea ◽  
V Hommes
2012 ◽  
Vol 226 ◽  
pp. 189-198 ◽  
Author(s):  
Vinod Kanniah ◽  
Peng Wu ◽  
Natalia Mandzy ◽  
Eric A. Grulke

2020 ◽  
Vol 370 ◽  
pp. 116-128 ◽  
Author(s):  
Pedro Bianchi Neto ◽  
Florian Meierhofer ◽  
Henry França Meier ◽  
Udo Fritsching ◽  
Dirceu Noriler

2010 ◽  
Vol 96 (22) ◽  
pp. 222506 ◽  
Author(s):  
R. S. DiPietro ◽  
H. G. Johnson ◽  
S. P. Bennett ◽  
T. J. Nummy ◽  
L. H. Lewis ◽  
...  

2020 ◽  
Author(s):  
Niamh Mac Fhionnlaoich ◽  
Stefan Guldin

Nanoparticle size impacts properties vital to applications ranging from drug delivery to diagnostics and catalysis. As such, evaluating nanoparticle size dispersity is of fundamental importance. Conventional approaches, such as standard deviation, usually require the nanoparticle population to follow a known distribution and are illequipped to deal with highly poly- or heterodisperse populations. Herein, we propose the use of information entropy as an alternative and assumption-free method for describing nanoparticle size distributions. This approach works equally well for mono-, poly- and heterodisperse populations and provides an unbiased route to evaluation and optimisation of nanoparticle synthesis. We provide an intuitive tool for analysis with a user-friendly macro and provide guidelines for interpretation with respect to known standards.


2015 ◽  
Vol 49 (10) ◽  
pp. 1009-1018 ◽  
Author(s):  
Chih-Liang Chien ◽  
Chi-Yu Tien ◽  
Chun-Nan Liu ◽  
Huajun Ye ◽  
Wei Huang ◽  
...  

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