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: 3122
Function: getPubMedXML
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
We present a fast, nondestructive, and quantitative approach to characterize the morphology of capillary silica-based monolithic columns by reconstruction from confocal laser scanning microscopy images. The method comprises column pretreatment, image acquisition, image processing, and statistical analysis of the image data. The received morphological data are chord length distributions for the bulk macropore space and skeleton of the silica monolith. The morphological information is shown to be comparable to that derived from transmission electron microscopy, but far easier to access. The approach is generally applicable to silica-based capillary columns, monolithic or particulate. It allows the rapid acquisition of hundreds of longitudinal and cross-sectional images in a single session, resolving a multitude of morphological details in the column.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1021/ac100909t | DOI Listing |
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