To improve the performance of GaAs NEA photocathodes, an exponential-doping structure GaAs material has been put forward, in which from the GaAs bulk-to-surface doping concentration is distributed exponentially from high to low. We apply this exponential-doping GaAs structure to the transmission-mode GaAs photocathodes. This sample was grown on the high quality
p-type Be-doped GaAs (100) substrate by MBE. We have calculated the band-bending energy in exponential-doping GaAs emission-layer, and the total band-bending energy is 59 meV which helps to improve the photoexcited electrons movement towards surface for the thin epilayer. The integrated sensitivity of the exponential-doping GaAs photocathode samples reaches 1547uA/lm.
The stability for reflection-mode GaN photocathode has been investigated by monitoring the photocurrent and the
spectral response at room temperature. We watch that the photocurrent of the cathode decays with time in the vacuum
system, and compare the spectral response curves after activation and after degradation. The photocurrent decay
mechanism for reflection-mode NEA GaN photocathode was studied by the surface model [GaN (Mg) :Cs]:O-Cs. The
reduction of the effective dipole quantity, which is caused by harmful gases, is the key factor of the photocurrent
reduction.
By omitting local decay and phase evolution,
traditional MRI models each datum as a sample
from k-space so that reconstruction can be implemented
by FFTs. Single-shot parameter assessment by
retrieval from signal encoding (SS-PARSE) acknowledges
local decay and phase evolution, so it models
each datum as a sample from (k, t)-space rather than
k-space. Local decay and frequency vary continuously
in space. Because of this, discrete models in space
can cause artifacts in the reconstructed parameters.
Increasing the resolution of the reconstructed parameters
can more accurately capture the spatial variations,
but the resolution is limited not only by computational
complexity but also by the size of the acquired data.
For a limited data set used for reconstruction, simply
increasing the resolution may cause the reconstruction
to become an underdetermined problem. This paper
presents a solution to this problem based on cubic
convolution interpolation.
By acknowledging local decay and phase
evolution, single-shot parameter assessment by retrieval
from signal encoding (SS-PARSE) models each
datum as a sample from (k, t)-space rather than
k-space. This more accurate model promises better
performance at a price of more complicated reconstruction
computations. Normally, conjugate-gradients
is used to simultaneously estimate local image magnitude,
decay, and frequency. Each iteration of the
conjugate-gradients algorithm requires several evaluations
of the image synthesis function and one evaluation
of gradients. Because of local decay and frequency
and the non-Cartesian trajectory, fast algorithms
based on FFT cannot be effectively used to accelerate
the evaluation of the image synthesis function and gradients.
This paper presents a fast algorithm to compute
the image synthesis function and gradients by linear
combinations of FFTs. By polynomial approximation
of the exponential time function with local decay and
frequency as parameters, the image synthesis function
and gradients become linear combinations of non-
Cartesian Fourier transforms. In order to use the FFT,
one can interpolate non-Cartesian trajectories. The
quality of images reconstructed by the fast approach
presented in this paper is the same as that of the
normal conjugate-gradient method with significantly
reduced computation time.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.