TY - JOUR
T1 - Automation of mass spectrometric detection of analytes and related workflows
T2 - A review
AU - Elpa, Decibel P.
AU - Prabhu, Gurpur Rakesh D.
AU - Wu, Shu Pao
AU - Tay, Kheng Soo
AU - Urban, Pawel L.
N1 - Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2020/2/1
Y1 - 2020/2/1
N2 - The developments in mass spectrometry (MS) in the past few decades reveal the power and versatility of this technology. MS methods are utilized in routine analyses as well as research activities involving a broad range of analytes (elements and molecules) and countless matrices. However, manual MS analysis is gradually becoming a thing of the past. In this article, the available MS automation strategies are critically evaluated. Automation of analytical workflows culminating with MS detection encompasses involvement of automated operations in any of the steps related to sample handling/treatment before MS detection, sample introduction, MS data acquisition, and MS data processing. Automated MS workflows help to overcome the intrinsic limitations of MS methodology regarding reproducibility, throughput, and the expertise required to operate MS instruments. Such workflows often comprise automated off-line and on-line steps such as sampling, extraction, derivatization, and separation. The most common instrumental tools include autosamplers, multi-axis robots, flow injection systems, and lab-on-a-chip. Prototyping customized automated MS systems is a way to introduce non-standard automated features to MS workflows. The review highlights the enabling role of automated MS procedures in various sectors of academic research and industry. Examples include applications of automated MS workflows in bioscience, environmental studies, and exploration of the outer space.
AB - The developments in mass spectrometry (MS) in the past few decades reveal the power and versatility of this technology. MS methods are utilized in routine analyses as well as research activities involving a broad range of analytes (elements and molecules) and countless matrices. However, manual MS analysis is gradually becoming a thing of the past. In this article, the available MS automation strategies are critically evaluated. Automation of analytical workflows culminating with MS detection encompasses involvement of automated operations in any of the steps related to sample handling/treatment before MS detection, sample introduction, MS data acquisition, and MS data processing. Automated MS workflows help to overcome the intrinsic limitations of MS methodology regarding reproducibility, throughput, and the expertise required to operate MS instruments. Such workflows often comprise automated off-line and on-line steps such as sampling, extraction, derivatization, and separation. The most common instrumental tools include autosamplers, multi-axis robots, flow injection systems, and lab-on-a-chip. Prototyping customized automated MS systems is a way to introduce non-standard automated features to MS workflows. The review highlights the enabling role of automated MS procedures in various sectors of academic research and industry. Examples include applications of automated MS workflows in bioscience, environmental studies, and exploration of the outer space.
KW - Automation
KW - Mass spectrometry
KW - Robotics
KW - Sample preparation
KW - Sampling
UR - http://www.scopus.com/inward/record.url?scp=85073052294&partnerID=8YFLogxK
U2 - 10.1016/j.talanta.2019.120304
DO - 10.1016/j.talanta.2019.120304
M3 - Review article
C2 - 31816721
AN - SCOPUS:85073052294
SN - 0039-9140
VL - 208
JO - Talanta
JF - Talanta
M1 - 120304
ER -