Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Neutron radiography is a powerful diagnostic technique for operando studies of electrochemical devices, such as fuel cells, batteries, and electrolyzers. However, processing time-series neutron images is challenging due to high spatial/temporal resolution requirements, limited neutron flux, complex sample geometry, and low signal-to-noise ratios. Existing image processing platforms are not adequate to mitigate these issues, causing bottlenecks in data analysis and interpretation. In this work, we present our Python-based framework: neutron radiography of electrochemical devices (NeuRED). This framework integrates a robust set of image processing functions within a transparent, reproducible, and user-friendly workflow. The advantages and unique features of the framework are outlined, and demonstrations are provided for proton exchange membrane fuel cells, Li-ion batteries, and gas-liquid systems. NeuRED is a unique open-access software tool for the electrochemistry community that will contribute to the advancements of operando imaging applications in energy research.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12267630 | PMC |
http://dx.doi.org/10.1038/s41598-025-09425-w | DOI Listing |