Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Machine vision techniques are widely applied for object identification in daily life and industrial production, where images are captured and processed by sensors, memories, and processing units sequentially. Neuromorphic optoelectronic synapses, as a preferable option to promote the efficiency of image recognition, are hotly pursued in non-ionizing radiation range, but rarely in ionizing radiation including X-rays. Here, the study proposes an X-ray optoelectronic synapse using amorphous GaO (a-GaO) thin film. Boosted by the interfacial V defects and its slow neutralization rate, the enhanced electron tunneling process at metal/a-GaO interface produces remarkable X-ray-induced post-synaptic current, contributing to a sensitivity of 20.5, 64.3, 164.1 µC mGy cm for the 1st, 5th, and 10th excitation periods, respectively. Further, a 64 × 64 imaging sensor is constructed on a commercial amorphous Si (a-Si) thin film transistor (TFT) array. The image contrast can be apparently improved under a series of X-ray pulses due to an outstanding long-term plasticity of the single pixel, which is beneficial to the subsequent image recognition and classification based on artificial neural network. The merits of large-scale production ability and good compatibility with modern microelectronic techniques belonging to amorphous oxide semiconductors may promote the development of neuro-inspired X-ray imagers and corresponding machine vision systems.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1002/advs.202410761 | DOI Listing |
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