Enhancing Sensitivity in the Hyphenation of High-Performance Liquid Chromatography to Benchtop Nuclear Magnetic Resonance Spectroscopy at Isocratic and Onflow Conditions

The onflow hyphenation of high-performance liquid chromatography (HPLC) in adsorption mode with a benchtop 1H nuclear magnetic resonance (NMR) spectrometer is described for the first time. Protonated solvents and isocratic conditions are used. The sensitivity was increased by choosing suitable NMR acquisition parameter as well as optimizing injection parameters and postacquisition data processing methods. With optimized conditions, the limit of detection (LOD) and the limit of quantification (LOQ) were LOD = 0.010 g L-1 and LOQ = 0.031 g L-1 for the methoxy 1H of methyl paraben at 4.07 ppm, LOD = 0.038 g L-1 and LOQ = 0.134 g L-1 for the aromatic 1H of pentyl paraben between 7.00 and 8.50 ppm. These are expressed in injection concentration and are comparable to existing HPLC hyphenation with high-field NMR spectrometers. The analysis of a 2 g L-1 paraben mixture, far below the legal limits for usage in cosmetics, illustrates the applicability of the method. Taking advantage of the spectral resolution, chromatographically overlapping peaks are resolved using analyte-specific NMR elution traces. A methodology is detailed to facilitate the transfer of the optimized method to other (analyte) systems.

High Performance Liquid chromatography - Fourier Transform Infrared Spectroscopy Coupling: A Comprehensive Review

This review presents a critical examination of the interface for coupling high performance liquid chromatography (HPLC) with Fourier transform infrared spectrometry (FTIR) since 2010. This coupling offers a robust analytical approach characterized by exceptional chemical specificity and the capacity to analyze complex multi-component mixtures qualitatively and quantitatively with high sensitivity, particularly in low limit of detection ranges. This coupling enables the identification of individual components of a mixture by IR after their separation by HPLC, although challenges arise from the potential distortion of infrared spectra by mobile phase components. Addressing this issue necessitates the implementation of suitable interfaces, such as flow cells or off-line indirect measurement methods like hot inert gas streams or ultrasonic nebulizers. The key parameters influencing the coupling of HPLC-FTIR include the solvent elimination methods, mode of FTIR technique, and IR background for accurate analyte identification. Moreover, the composition of the mobile phase and the utilization of buffer solutions in the HPLC mobile phase profoundly impact analyte identification by FTIR.

Fourier transformation liquid chromatography: increasing sensitivity by a factor of 50

To turn liquid chromatography into a Fourier transformation technique a continuous sinusoidal sample concentration profile is developed, which increases the sensitivity. The analytes can be characterized by evaluating the phase angle and magnitude.

Deep Learning for Reconstructing Low-Quality FTIR and Raman Spectra─A Case Study in Microplastic Analyses

Herein we report on a deep-learning method for the removal of instrumental noise and unwanted spectral artifacts in Fourier transform infrared (FTIR) or Raman spectra, especially in automated applications in which a large number of spectra have to be acquired within limited time. Automated batch workflows allowing only a few seconds per measurement, without the possibility of manually optimizing measurement parameters, often result in challenging and heterogeneous datasets. A prominent example of this problem is the automated spectroscopic measurement of particles in environmental samples regarding their content of microplastic (MP) particles. Effective spectral identification is hampered by low signal-to-noise ratios and baseline artifacts as, again, spectral post-processing and analysis must be performed in automated measurements, without adjusting specific parameters for each spectrum. We demonstrate the application of a simple autoencoding neural net for reconstruction of complex spectral distortions, such as high levels of noise, baseline bending, interferences, or distorted bands. Once trained on appropriate data, the network is able to remove all unwanted artifacts in a single pass without the need for tuning spectra-specific parameters and with high computational efficiency. Thus, it offers great potential for monitoring applications with a large number of spectra and limited analysis time with availability of representative data from already completed experiments.

Strengths and limitations of size exclusion chromatography for investigating single chain folding – current status and future perspectives

Synthetic approaches for Single-Chain Nanoparticles (SCNPs) developed rapidly during the last decade, opening a multitude of avenues for the design of functional macromolecular chains able to collapse into defined nanoparticles. However, the analytical evaluation of the SCNP formation process still requires critical improvements.

On-line SEC-MR-NMR hyphenation: optimization of sensitivity and selectivity on a 62 MHz benchtop NMR spectrometer

The development of sophisticated synthetic routes for polymeric materials and more complex formulation used in current polymers require more advanced analytical techniques. A direct correlation between molar mass distribution and chemical composition is provided.

Medium Resolution 1 H-NMR at 62 MHz as a New Chemically Sensitive Online Detector for Size-Exclusion Chromatography (SEC-NMR)

A state-of-the-art, medium-resolution ¹ H-NMR spectrometer (62 MHz) is used as a chemically sensitive online detector for size-exclusion chromatography of polymers such as polymethylmethacrylate (PMMA) and polystyrene (PS). The method uses protonated eluents and works at typical chromatographic conditions with trace amounts of analytes (<0.5 g L^-1 after separation). Strong solvent suppression, e.g., by a factor of 500, is achieved by means of T₁ -filtering and mathematical subtraction methods. Substantial improvements are made with respect to previous work in terms of the sensitivity (signal-to-noise ratio up to 130:1, PMMA OCH₃ ) and selectivity (peak width, full width half maximum (FWHM) 4 Hz on-flow). Typical homopolymers and a blend are investigated to deformulate their composition along the dimensions of molecular weight and NMR chemical shift. These results validate this new hyphenated chromatography method, which can greatly facilitate analysis and is much more effective than previously published results.

Online Detection of Functional Groups in SEC via Quantum Cascade Laser IR Spectroscopy

The development of coupled techniques based on chemically sensitive detectors, such as FTIR or NMR spectrometers, for size exclusion chromatography (SEC) provides sophisticated methods for determining the molecular-weight-dependent chemical composition in polymers. However, the detection of rare functionalities such as end groups or branching points presents a challenge, especially for online coupled SEC detection, which is based on low-concentration chromatography. To address this issue, for the first time, an external cavity quantum cascade laser (EC-QCL) infrared spectrometer is coupled to an SEC. The system is evaluated using polystyrene/poly(methyl methacrylate) (PS/PMMA) blends. The current limit of detection for the carbonyl (PMMA) stretch vibration at 1730 cm^-1 with this technique is 3.5 µg PMMA on a semipreparative column (typical load of 2.5 mg polymer in total). That equals 0.15 mol% of PMMA in the PS/PMMA blend and corresponds to one carbonyl group per 70 kg mol^-1 polymer.

On the feasibility of determining polymer chemical heterogeneity by SEC with continuous off-line Raman detection

Examined here is the feasibility of employing Raman spectroscopy as a detection method in size-exclusion chromatography (SEC) and related macromolecular separations, for the purposes of determining the chemical heterogeneity of copolymers.