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: 1075
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3195
Function: GetPubMedArticleOutput_2016
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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Ultrahigh-resolution mass spectrometry (UHRMS), whether hyphenated or not, has emerged as a powerful analytical technique for the molecular characterization of formulated lubricants. These lubricants, particularly motor vehicle/engine oils, are complex mixtures composed of base oils and various additives. However, the resulting data from UHRMS are highly complex due to the intricate nature of these samples, making it challenging to identify the molecular structures of lubricant additives. Kendrick mass defect (KMD) analysis, which utilizes plots of Kendrick nominal mass (KNM) as a function of KMD, is a widely used method for visualizing and interpreting complex MS data. This review highlights the principles of KMD, its advantages in the analysis of complex mixtures, and its potential applications in the structural identification of additives in low-viscosity engine oils (LVEOs). Additionally, we discuss recent progress, current challenges, and future prospects for KMD analysis in this field, providing a critical evaluation of its role in advancing lubricant characterization. By outlining future directions, this review aims to guide researchers in leveraging KMD analysis to advance the characterization and development of next-generation lubricants.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12290622 | PMC |
http://dx.doi.org/10.1021/acsomega.5c03129 | DOI Listing |