Highly Sensitive Raman Spectroscopy with Low Laser Power for Fast In-Line Reaction and Multiphase Flow Monitoring

Raman Spectroscopy of Glass Beads in Ammonium Nitrate Solution and Compensation of Signal Losses

In the present study, the influence of disperse systems on Raman scattering was investigated. How an increasing particle concentration weakens the quantitative signal of the Raman spectrum is shown. Furthermore, the change in the position of the optimal measurement point in the fluid was considered in detail. Additional transmission measurements can be used to derive a simple and robust correction method that allows the actual concentration of the continuous phase to be determined with a standard deviation of 2.6%.

Raman spectrum model transfer method based on Cycle-GAN

The disparity in hardware quality among various models of Raman spectrometers gives rise to variations in the acquired Raman spectral data, even when the same substance is collected under identical external conditions. Conventionally, models constructed using data obtained from a particular instrument exhibit issues such as limited applicability or poor performance when deployed to different instruments. Currently, numerous model transfer algorithms grounded in chemometrics have been developed, all aiming to establish a mapping relationship capable of transforming spectral data from the source domain to the target domain. With the advancement of deep learning techniques, the utilization of deep learning enables the effective resolution of nonlinear mapping relationships between two spectral vectors. In the field of image translation, the Cycle-Consistent Adversarial Networks, Cycle-GAN, has already achieved mutual transformation between two distinct style images. However, due to images being multidimensional matrix data, unlike one-dimensional spectral data vectors, we have constructed a deep learning network based on Cycle-GAN for vector-to-vector transformation. This network allows the direct conversion of spectral data from the source domain to the target domain, without requiring parameter adjustments or other operations. Compared with traditional chemometric methods, our method is more intelligent and efficient. Finally, the cosine similarity between the source domain data and the transformed target domain data exceeds 99%.

Advantages of optical fibers for facile and enhanced detection in droplet microfluidics

Droplet microfluidics offers a unique opportunity for ultrahigh-throughput experimentation with minimal sample consumption and thus has obtained increasing attention, particularly for biological applications. Detection and measurements of analytes or biomarkers in tiny droplets are essential for proper analysis of biological and chemical assays like single-cell studies, cytometry, nucleic acid detection, protein quantification, environmental monitoring, drug discovery, and point-of-care diagnostics. Current detection setups widely use microscopes as a central device and other free-space optical components. However, microscopic setups are bulky, complicated, not flexible, and expensive. Furthermore, they require precise optical alignments, specialized optical and technical knowledge, and cumbersome maintenance. The establishment of efficient, simple, and cheap detection methods is one of the bottlenecks for adopting microfluidic strategies for diverse bioanalytical applications and widespread laboratory use. Together with great advances in optofluidic components, the integration of optical fibers as a light guiding medium into microfluidic chips has recently revolutionized analytical possibilities. Optical fibers embedded in a microfluidic platform provide a simpler, more flexible, lower-cost, and sensitive setup for the detection of several parameters from biological and chemical samples and enable widespread, hands-on application much beyond thriving point-of-care developments. In this review, we examine recent developments in droplet microfluidic systems using optical fiber as a light guiding medium, primarily focusing on different optical detection methods such as fluorescence, absorbance, light scattering, and Raman scattering and the potential applications in biochemistry and biotechnology that are and will be arising from this.

Advances in droplet microfluidics for SERS and Raman analysis

Raman spectroscopy can realize qualitative and quantitative characterization, and surface-enhanced Raman spectroscopy (SERS) can further enhance its detection sensitivity. In combination with droplet microfluidics, some significant but insurmountable limitations of SERS and Raman spectroscopy can be overcome to some extent, thus improving their detection capability and extending their application. During the past decade, these systems have constantly developed and demonstrated a great potential in more applications, but there is no new review systematically summarizing the droplet microfluidics-based Raman and SERS analysis system since the first related review was published in 2011. Thus, there is a great need for a new review to summarize the advances. In this review, we focus on droplet microfluidics-based Raman and SERS analysis, and summarize two mainstream research directions on this topic up to now. The one is SERS or Raman detection in the moving droplet microreactors, including analysis of molecules, single cells and chemical reaction processes. The other one is SERS active microparticle fabrication via microfluidic droplet templates covering polymer matrix and photonic crystal microparticles. We also comment on the advantages, disadvantage and correlation resolution of droplet microfluidics for SERS or Raman. Finally, we summarize these systems and illustrate our perspectives for future research directions in this field.

Sampling and Analysis in Flow: The Keys to Smarter, More Controllable, and Sustainable Fine-Chemical Manufacturing

Process analytical technology (PAT) is a system designed to help chemists better understand and control manufacturing processes. PAT systems operate through the combination of analytical devices, reactor control elements, and mathematical models to ensure the quality of the final product through a quality by design (QbD) approach. The expansion of continuous manufacturing in the pharmaceutical and fine-chemical industry requires the development of PAT tools suitable for continuous operation in the environment of flow reactors. This requires innovative approaches to sampling and analysis from flowing media to maintain the integrity of the reactor content and the analyte of interest. The following Review discusses examples of PAT tools implemented in flow chemistry for the preparation of small organic molecules, and applications of self-optimization tools.

Directed Evolution: Methodologies and Applications

Directed evolution aims to expedite the natural evolution process of biological molecules and systems in a test tube through iterative rounds of gene diversifications and library screening/selection. It has become one of the most powerful and widespread tools for engineering improved or novel functions in proteins, metabolic pathways, and even whole genomes. This review describes the commonly used gene diversification strategies, screening/selection methods, and recently developed continuous evolution strategies for directed evolution. Moreover, we highlight some representative applications of directed evolution in engineering nucleic acids, proteins, pathways, genetic circuits, viruses, and whole cells. Finally, we discuss the challenges and future perspectives in directed evolution.

Challenges in transfer of gas-liquid reactions from batch to continuous operation: dimensional analysis and simulations for aerobic oxidation

The transfer of gas-liquid reactions from conventional batch processes into continuous operation using milli and micro reactors is claimed as an important step towards process intensification. Importantly, this transfer step should be realized in an early phase of process development, already, in order to minimize research efforts towards the undesired operation strategy. The main challenge of this approach, therefore, arises from lack of knowledge in the early stage of process development and the resulting system with high degrees of freedom. This contribution presents an approach to tackle this challenge by means of mathematical modelling and simulation for the aerobic oxidation of 9,10-dihydroanthracene (DHA) catalyzed by polyoxometalates (POMs) being used as example for gas-liquid reactions. The reaction was chosen as it provides sufficient complexity, since it consists of three consecutive oxidation steps of DHA and a parallel catalytic redox-cycle according to a Mars-van-Krevelen mechanism. It also provides the challenge of unknown reaction kinetics, which have been estimated in this contribution. The dimensionless balance equations for reactor modeling are derived and parametrized based on early stage experimental results obtained in batch operation mode. The discrimination between batch and continuous operation was performed by means of characteristic dimensionless numbers using the identical mathematical model for comparability reasons. The model was used to perform sensitivity studies with emphasis on the interplay between mass transfer characteristics and reaction kinetics for both the batch and continuous operation mode. The simulation results show that the performance of both operation modes mainly depend on the oxidation state of the POM catalyst, which is caused by the differences in oxygen availability. Therefore, results obtained in batch operation mode are prone to be masked by mass transfer issues, which affects catalyst and reactor development at the same time and may thus cause maldevelopments. With respect to process development it can thus be concluded that the transfer from batch to continuous operation together with mathematical modeling is important in an early phase, already, in order to detect limitations misleading the development. Finally, even simple models with roughly estimated parameters from preliminary experiments are shown to be sufficient in the early phase and can systematically be improved, in the subsequent phases.

Graphical abstract

Very Selective Detection of Low Physiopathological Glucose Levels by Spontaneous Raman Spectroscopy with Univariate Data Analysis

After decades of research on non-invasive glucose monitoring, invasive devices based on finger blood sampling are still the predominant reference for diabetic patients for accurately measuring blood glucose levels. Meanwhile, research continues improving point-of-care technology toward the development of painless and more accurate devices. Raman spectroscopy is well-known as a potentially valuable and painless approach for measuring glucose levels. However, previous Raman studies deal with glucose concentrations that are still order of magnitudes away with respect to human tissues’ physiological concentrations, or they propose enhancement methodologies either invasive or much complex to assure sufficient sensitivity in the physiological range. Instead, this study proposes an alternative non-enhanced Raman spectroscopy approach sensitive to glucose concentrations from 1 to 5 mmol/l, which correspond to the lowest physiopathological glucose level in human blood. Our findings suggest a very selective detection of glucose with respect to other typical metabolites, usually interfering with Raman spectroscopy’s glucose detection. We validate the proposed univariate sensing methodology on glucose solutions mixed with lactate and urea, the two most common molecules found in human serum with concentrations similar to glucose and similar features in the Raman spectra. Our findings clearly illustrate that reliable detection of glucose by Raman spectroscopy is feasible by exploiting the shifted peak at 1125 ± 10 cm–1 within physiopathological ranges.

Molecule Sensitive Optical Imaging and Monitoring Techniques-A Review of Applications in Micro-Process Engineering

This paper provides an overview of how molecule-sensitive, spatially-resolved technologies can be applied for monitoring and measuring in microchannels. The principles of elastic light scattering, fluorescence, near-infrared, mid-infrared, and Raman imaging, as well as combination techniques, are briefly presented, and their advantages and disadvantages are explained. With optical methods, images can be acquired both scanning and simultaneously as a complete image. Scanning technologies require more acquisition time, and fast moving processes are not easily observable. On the other hand, molecular selectivity is very high, especially in Raman and mid-infrared (MIR) scanning. For near-infrared (NIR) images, the entire measuring range can be simultaneously recorded with indium gallium arsenide (InGaAs) cameras. However, in this wavelength range, water is the dominant molecule, so it is sometimes necessary to use complex learning algorithms that increase the preparation effort before the actual measurement. These technologies excite molecular vibrations in a variety of ways, making these methods suitable for specific products. Besides measurements of the fluid composition, technologies for particle detection are of additional importance. With scattered light techniques and evaluation according to the Mie theory, particles in the range of 0.2–1 µm can be detected, and fast growth processes can be observed. Local multispectral measurements can also be carried out with fiber optic-coupled systems through small probe heads of approximately 1 mm diameter.

SERS monitoring of the Fenton degradation reaction based on microfluidic droplets and alginate microparticles

Surface-enhanced Raman scattering (SERS) spectroscopy as a powerful tool has been used to explore different catalysis degradation reactions, whereas some drawbacks caused by ferric ions still exist in the current SERS monitoring of the Fenton reaction process. In this work, microfluidic droplet- and alginate microparticle-based methods were, respectively, applied to realize SERS monitoring of the Fenton degradation process in a relatively stable environment, which benefited from reduction of the loss of ferrous ions and the aggregation of the SERS substrate. As expected, the spectroscopic evidence at the molecular level directly revealed the degradation mechanism of rhodamine dyes, showing that the chemical bonds between xanthene and carboxybenzene broke continuously during the reaction. Afterward, the degradation mechanism determined by SERS was verified via mass spectrometry detection, which confirmed the validity of the SERS-based method. More broadly, the microfluidic droplet- and microparticle-based methods are potentially applicable for SERS monitoring of more Fenton degradation reactions.

Comparison of Raman and Mid-Infrared Spectroscopy for Real-Time Monitoring of Yeast Fermentations: A Proof-of-Concept for Multi-Channel Photometric Sensors

Raman and mid-infrared (MIR) spectroscopy are useful tools for the specific detection of molecules, since both methods are based on the excitation of fundamental vibration modes. In this study, Raman and MIR spectroscopy were applied simultaneously during aerobic yeast fermentations of Saccharomyces cerevisiae. Based on the recorded Raman intensities and MIR absorption spectra, respectively, temporal concentration courses of glucose, ethanol, and biomass were determined. The chemometric methods used to evaluate the analyte concentrations were partial least squares (PLS) regression and multiple linear regression (MLR). In view of potential photometric sensors, MLR models based on two (2D) and four (4D) analyte-specific optical channels were developed. All chemometric models were tested to predict glucose concentrations between 0 and 30 g L−1, ethanol concentrations between 0 and 10 g L−1, and biomass concentrations up to 15 g L−1 in real time during diauxic growth. Root-mean-squared errors of prediction (RMSEP) of 0.68 g L−1, 0.48 g L−1, and 0.37 g L−1 for glucose, ethanol, and biomass were achieved using the MIR setup combined with a PLS model. In the case of Raman spectroscopy, the corresponding RMSEP values were 0.92 g L−1, 0.39 g L−1, and 0.29 g L−1. Nevertheless, the simple 4D MLR models could reach the performance of the more complex PLS evaluation. Consequently, the replacement of spectrometer setups by four-channel sensors were discussed. Moreover, the advantages and disadvantages of Raman and MIR setups are demonstrated with regard to process implementation.

Continuous flow chemistry: where are we now? Recent applications, challenges and limitations

A general outlook of the changing face of chemical synthesis is provided in this article through recent applications of continuous flow processing in both industry and academia. The benefits, major challenges and limitations associated with the use of this mode of processing are also given due attention as an attempt to put into perspective the current position of continuous flow processing, either as an alternative or potential combinatory technology for batch processing.

Non-contact Raman spectroscopy for in-line monitoring of glucose and ethanol during yeast fermentations

The monitoring of microbiological processes using Raman spectroscopy has gained in importance over the past few years. Commercial Raman spectroscopic equipment consists of a laser, spectrometer, and fiberoptic immersion probe in direct contact with the fermentation medium. To avoid possible sterilization problems and biofilm formation on the probe tip, a large-aperture Raman probe was developed. The design of the probe enables non-contact in-line measurements through glass vessels or inspection glasses of bioreactors and chemical reactors. The practical applicability of the probe was tested during yeast fermentations by monitoring the consumption of substrate glucose and the formation of ethanol as the product. Multiple linear regression models were applied to evaluate the Raman spectra. Reference values were determined by high-performance liquid chromatography. The relative errors of prediction for glucose and ethanol were 5 and 3%, respectively. The presented Raman probe allows simple adaption to a wide range of processes in the chemical, pharmaceutical, and biotechnological industries.