Calibration Transfer of Partial Least Squares Regression Models between Desktop Nuclear Magnetic Resonance Spectrometers

校准 分光计 偏最小二乘回归 化学 标准化 分析化学(期刊) 计算物理学 光学 统计 计算机科学 数学 色谱法 物理 操作系统
作者
Diego Galvan,Evandro Bona,Dionísio Borsato,Ernesto Danieli,Mário Henrique Montazzolli Killner
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:92 (19): 12809-12816 被引量:35
标识
DOI:10.1021/acs.analchem.0c00902
摘要

Low-field proton nuclear magnetic resonance (LF-1H NMR) devices based on permanent magnets are a promising analytical tool to be extensively applied to the process analytical chemistry scenario. To enhance its analytical applicability in samples where the spectral resolution is compromised, multivariate regression methods are required. However, building a robust calibration model, such as partial least squares (PLS) regression, is a laborious task because (1) the number of measurements required during the calibration process is large and (2) the procedure must be repeated when the instrument is changed or after a certain period due to the long-term stability of the instrument. Thus, the present work describes the application of calibration transfer methodologies (direct standardization (DS), piece-wise direct standardization (PDS), and double-window piece-wise direct standardization (DWPDS)) on LF-1H NMR to exempt the necessity of a recalibration procedure when moving from the original spectrometer to a second one with the same, lower, or higher magnetic field. These calibration transfer methodologies were tested with PLS models built on a 60 MHz (for the proton Larmor frequency) spectrometer to predict the specific gravity (SG), distillation temperature (T50%), and final boiling point (FBP) of commercial gasoline. The results showed that the DWPDS method applying only 2 to 7 transference samples enables the transference of all PLS models built on the primary instrument (60 MHz) to other (43, 60, and 80 MHz) different instruments, reaching the same RMSEP values as the primary instrument: 1.2 kg/m3 for SG, 5.1 °C for FBP, and 1.1 °C for T50%.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
酷酷安南完成签到,获得积分20
刚刚
谦让雁风发布了新的文献求助30
刚刚
有点儿发布了新的文献求助10
刚刚
xin_qin_Wei完成签到,获得积分10
刚刚
在水一方应助舒克采纳,获得10
1秒前
老马发布了新的文献求助10
1秒前
木司发布了新的文献求助10
1秒前
DeepSeek忠实信徒完成签到,获得积分10
2秒前
LCJ发布了新的文献求助10
2秒前
所所应助oh777采纳,获得10
2秒前
完美世界应助zz采纳,获得10
3秒前
LL发布了新的文献求助10
3秒前
张小波完成签到,获得积分10
3秒前
4秒前
4秒前
英俊的铭应助einspringen采纳,获得10
4秒前
糊涂的剑发布了新的文献求助10
5秒前
5秒前
dent强完成签到,获得积分10
5秒前
5秒前
6秒前
Marina发布了新的文献求助10
6秒前
小鱼儿发布了新的文献求助10
6秒前
xiaozhang完成签到,获得积分10
6秒前
留胡子的代天完成签到,获得积分10
7秒前
科研通AI6.4应助饶小漫采纳,获得10
7秒前
整齐的饼干完成签到,获得积分10
7秒前
8秒前
小白完成签到,获得积分10
8秒前
pdx3完成签到,获得积分10
9秒前
zhouzhouzhou发布了新的文献求助30
9秒前
9秒前
ding应助有点儿采纳,获得10
9秒前
louyu完成签到 ,获得积分0
9秒前
顺利的飞荷完成签到,获得积分0
9秒前
刘同学发布了新的文献求助10
10秒前
10秒前
10秒前
10秒前
einspringen发布了新的文献求助10
11秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
A Case Study on Hotels as Noncongregate Emergency Living Accommodations for Returning Citizens 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7764446
求助须知:如何正确求助?哪些是违规求助? 9308652
关于积分的说明 20307206
捐赠科研通 7349118
什么是DOI,文献DOI怎么找? 3314390
关于科研通互助平台的介绍 2463914
邀请新用户注册赠送积分活动 2328561