Velocity auto-correlation and hot-electron diffusion constant in GaAs and InP

1982 ◽  
Vol 28 (3) ◽  
pp. 195-204 ◽  
Author(s):  
M. Deb Roy ◽  
B. R. Nag
Keyword(s):  
Diffusion Constant ◽  
Hot Electron ◽  
Electron Diffusion ◽  
Auto Correlation

Hot electron diffusion in fine line semiconductor devices

1982 ◽  
Vol 25 (10) ◽  
pp. 1017-1021 ◽  
Author(s):  
W.T. Jones ◽  
K. Hess ◽  
G.J. Iafrate
Keyword(s):  
Semiconductor Devices ◽  
Hot Electron ◽  
Electron Diffusion ◽  
Fine Line

scholarly journals Tracking ultrafast hot-electron diffusion in space and time by ultrafast thermomodulation microscopy

2019 ◽  
Vol 5 (5) ◽  
pp. eaav8965 ◽  
Author(s):  
A. Block ◽  
M. Liebel ◽  
R. Yu ◽  
M. Spector ◽  
Y. Sivan ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Nonequilibrium Dynamics ◽  
Hot Electron ◽  
Temperature Model ◽  
Three Dimensional Model ◽  
Electron Diffusion ◽  
Diffusion Dynamics ◽  
Electron Phonon Coupling ◽  
20 Nm ◽  
Two Temperature

The ultrafast response of metals to light is governed by intriguing nonequilibrium dynamics involving the interplay of excited electrons and phonons. The coupling between them leads to nonlinear diffusion behavior on ultrashort time scales. Here, we use scanning ultrafast thermomodulation microscopy to image the spatiotemporal hot-electron diffusion in thin gold films. By tracking local transient reflectivity with 20-nm spatial precision and 0.25-ps temporal resolution, we reveal two distinct diffusion regimes: an initial rapid diffusion during the first few picoseconds, followed by about 100-fold slower diffusion at longer times. We find a slower initial diffusion than previously predicted for purely electronic diffusion. We develop a comprehensive three-dimensional model based on a two-temperature model and evaluation of the thermo-optical response, taking into account the delaying effect of electron-phonon coupling. Our simulations describe well the observed diffusion dynamics and let us identify the two diffusion regimes as hot-electron and phonon-limited thermal diffusion, respectively.

Hot electron diffusion

1974 ◽  
Vol 48 (1) ◽  
pp. 5-6 ◽  
Author(s):  
B.R. Nag
Keyword(s):  
Hot Electron ◽  
Electron Diffusion

scholarly journals Proximity effect and hot-electron diffusion in Ag/Al/sub 2/O/sub 3//Al tunnel junctions

1997 ◽  
Vol 7 (2) ◽  
pp. 3379-3382 ◽  
Author(s):  
H. Netel ◽  
J. Jochum ◽  
S.E. Labov ◽  
C.A. Mears ◽  
M. Frank ◽  
...  
Keyword(s):  
Proximity Effect ◽  
Tunnel Junctions ◽  
Hot Electron ◽  
Electron Diffusion

Hot electron diffusion in CdTe

1983 ◽  
Vol 30 (3) ◽  
pp. 189-193 ◽  
Author(s):  
M. Deb Roy ◽  
B. R. Nag
Keyword(s):  
Hot Electron ◽  
Electron Diffusion

Calculation of the hot electron diffusion rate for GaAs

1969 ◽  
Vol 29 (10) ◽  
pp. 578-579 ◽  
Author(s):  
W. Fawcett ◽  
H.D. Rees
Keyword(s):  
Diffusion Rate ◽  
Hot Electron ◽  
Electron Diffusion

Hot electron diffusion in CdTe

1975 ◽  
Vol 17 (11) ◽  
pp. 1443-1445 ◽  
Author(s):  
C. Canali ◽  
F. Catellani ◽  
C. Jacoboni ◽  
R. Minder ◽  
G. Ottaviani ◽  
...  
Keyword(s):  
Hot Electron ◽  
Electron Diffusion

Introduction to spin-polarized ballistic hot electron injection and detection in silicon

2011 ◽  
Vol 369 (1951) ◽  
pp. 3554-3574 ◽  
Author(s):  
Ian Appelbaum
Keyword(s):  
Ohmic Contacts ◽  
Spin Injection ◽  
Spin Valve ◽  
Diffusion Constant ◽  
Spin Current ◽  
Mean Free Path ◽  
Quantitative Model ◽  
Hot Electron ◽  
Ferromagnetic Thin Films ◽  
Spin Lifetime

Ballistic hot electron transport overcomes the well-known problems of conductivity and spin lifetime mismatch that plague spin injection attempts in semiconductors using ferromagnetic ohmic contacts. Through the spin dependence of the mean free path in ferromagnetic thin films, it also provides a means for spin detection after transport. Experimental results using these techniques (consisting of spin precession and spin-valve measurements) with silicon-based devices reveals the exceptionally long spin lifetime and high spin coherence induced by drift-dominated transport in the semiconductor. An appropriate quantitative model that accurately simulates the device characteristics for both undoped and doped spin transport channels is described; it can be used to recover the transit-time distribution from precession measurements and determine the spin current velocity, diffusion constant and spin lifetime, constituting a spin ‘Haynes–Shockley’ experiment without time-of-flight techniques. A perspective on the future of these methods is offered as a summary.

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