Real-time Reaction Monitoring Research Articles

Real-Time Monitoring of Electrochemical Reactions in All-Solid-State Lithium Batteries by Simultaneous Grazing-Incidence Small-Angle/Wide-Angle X-Ray Scattering

Polyethylene oxide (PEO)-based composite electrolytes (PCEs) are considered as the promising candidates for next generation lithium metal batteries due to its high safety, easy fabrication and good electrochemical stability. However, the material suffers from low conductivity and high crystallinity of the ethylene oxide (EO) chain, which inhibits its commercialization. Therefore, it is crucial to understand the electrochemcial process as well as Li+ transfer pathway within PEO-based batteries. Using operando grazing-incidence small-angle and wide-angle X-ray scattering (GISAXS and GIWAXS) in Li||Cu cell framework, we find that the electrochemical reaction within the PCE is highly correlated with the evolution of the buried morphology and crystalline structure evolution of the PCE. This two irreversible reactions, PEO-Li+ reduction and TFSI- decomposition, cause changes in both the crystalline structure and morphology of the PCE. In addition, the reversible Li plating/stripping process alters the inner morphology, especially the PEO-LiTFSI domain radius, rather than causing crystalline structure changes. This work provides a new path to monitor a working battery in real time, thereby enabling detailed understanding of electrochemically-induced changes of the microscopic morphology and crystalline structure of PCE, which is essential for developing high transferable and interface stable PCE-based lithium metal batteries. Figure 1

Tandem Solid-Solution Post-Synthetic Modification of Porous Molecular Crystals for In-situ Generation of Fluorophores.

Conventional synthetic methods of organic luminescent molecules often involve labor-intensive solution-phase organic synthesis, which violate the principles of atom-economic transformation. Post-synthetic modification (PSM) offers a promising alternative, allowing direct transformation from one fluorophore to another. Although PSM is commonly implemented in extended frameworks, its application in porous molecular crystals remains challenging. Herein, we focus on utilizing porous molecular crystals, specifically tetraphenylethylene-cored frameworks, as versatile platforms for tandem PSM reactions to customize organic fluorophores. The tailored skeleton design ensures both the formation of porous structures and the occurrence of tandem solid-solution reactions while maintaining the solid state of reactants and products in each step. The inherent non-covalent bonding nature of the frameworks facilitates processing and characterization, offering unparalleled advantages for porous networks. The accompanying solid-state fluorescence transition from green to blue and then to green (or yellow) enables real-time monitoring of tandem reactions and provides intuitive mechanistic insights. This phenomenon is exploited for the facile construction of a dynamic information encryption system using fluorescent quick response codes.

Efficient derivatization-free monitoring of glycosyltransferase reactions via flow injection analysis-mass spectrometry for rapid sugar analytics

The widespread application of enzymes in industrial chemical synthesis requires efficient process control to maintain high yields and purity. Flow injection analysis-electrospray ionization-mass spectrometry (FIA-ESI–MS) offers a promising solution for real-time monitoring of these enzymatic processes, particularly when handling challenging compounds like sugars and glycans, which are difficult to quickly analyze using liquid chromatography-mass spectrometry due to their physical properties or the requirement for a derivatization step beforehand. This study compares the performance of FIA-MS with traditional hydrophilic interaction liquid chromatography (HILIC)-ultra high-performance liquid chromatography (UHPLC)-mass spectrometry (MS) setups for the monitoring of the enzymatic synthesis of N-acetyllactosamine (LacNAc) using beta-1,4-galactosyltransferase. Our results show that FIA-MS, without prior chromatographic separation or derivatization, can quickly generate accurate mass spectrometric data within minutes, contrasting with the lengthy separations required by LC–MS methods. The rapid data acquisition of FIA-MS enables effective real-time monitoring and adjustment of the enzymatic reactions. Furthermore, by eliminating the derivatization step, this method offers the possibility of being directly coupled to a continuously operated reactor, thus providing a rapid on-line methodology for glycan synthesis as well.Graphical

Real-Time Monitoring of Hydrolysis Reactions of Pyrophosphates with Dissolution Dynamic Nuclear Polarization.

Dissolution dynamic nuclear polarization (d-DNP) has enabled applications such as the real-time monitoring of chemical reactions. Such applications are mainly for 13C and 15N spins with long spin-lattice relaxation times in the molecules of interest. However, the only applications for phosphorus using d-DNP are pH imaging and nucleation during crystallization due to the short relaxation times. Here we show that it is possible to observe enzyme reactions using d-DNP with phosphorus. Hyperpolarized 31P spins in pyrophosphate were obtained using bullet-DNP, which requires less dilution of highly polarized solid samples. Real-time monitoring of the hydrolysis reaction of pyrophosphate by inorganic pyrophosphatase from baker's yeast at physiological pH and was successfully achieved and the reaction rate was determined. This is an important reaction for a wide range of applications related to medicine, agriculture, and quantum life science.

Broadband backscattering by Atlantic herring (Clupea harengus L.) differs when measured from a research vessel vs. a silent uncrewed surface vehicle

Abstract Broadband frequency-modulated signals are believed to improve acoustic spectral-based target classification. Efficient use of uncrewed surface vehicles (USV) for fisheries science applications, with no possibility for biological sampling, is believed to be facilitated by use of broadband signals with methods for target classification. If the broadband frequency response used to train automated target classifiers are obtained from conventional research vessels (RVs), due to potential vessel avoidance, the swimming angle distribution may be different than for USVs. This may have consequences for target classification if the model is trained with RV data. The aim of this study was to assess whether the frequency response differs between platforms due to avoidance. Broadband acoustic data were collected with a conventional RV and a small USV. The broadband frequency response of Norwegian spring spawning herring obtained with the USV and RV was found to be significantly different for shallow herring layers in the 200 kHz band. This indicates that broadband frequency response has potential as a tool for real-time monitoring of behaviour reactions to vessels and to provide insight into fish behaviour in general. When using broadband frequency response for target classification, the potential platform-dependent broadband frequency response should be considered.

Coupling Exponential to Linear Amplification for Endpoint Quantitative Analysis.

Exponential DNA amplification techniques are fundamental in ultrasensitive molecular diagnostics. These systems offer a wide dynamic range, but the quantification requires real-time monitoring of the amplification reaction. Linear amplification schemes, despite their limited sensitivity, can achieve quantitative measurement from a single end-point readout, suitable for low-cost, point-of-care, or massive testing. Reconciling the sensitivity of exponential amplification with the simplicity of end-point readout would thus break through a major design dilemma and open a route to a new generation of massively scalable quantitative bioassays. Here a hybrid nucleic acid-based circuit design is introduced to compute a logarithmic function, therefore providing a wide dynamic range based on a single end-point measurement. CELIA (Coupling Exponential amplification reaction to LInear Amplification) exploits a versatile biochemical circuit architecture to couple a tunable linear amplification stage - optionally embedding an inverter function - downstream of an exponential module in a one-pot format. Applied to the detection of microRNAs, CELIA provides a limit of detection in the femtomolar range and a dynamic range of six decades. This isothermal approach bypasses thermocyclers without compromising sensitivity, thereby opening the way to applications in various diagnostic assays, and providing a simplified, cost-efficient, and high throughput solution for quantitative nucleic acid analysis.

Real-Time Biosynthetic Reaction Monitoring Informs the Mechanism of Action of Antibiotics.

The rapid spread of drug-resistant pathogens and the declining discovery of new antibiotics have created a global health crisis and heightened interest in the search for novel antibiotics. Beyond their discovery, elucidating mechanisms of action has necessitated new approaches, especially for antibiotics that interact with lipidic substrates and membrane proteins. Here, we develop a methodology for real-time reaction monitoring of the activities of two bacterial membrane phosphatases, UppP and PgpB. We then show how we can inhibit their activities using existing and newly discovered antibiotics such as bacitracin and teixobactin. Additionally, we found that the UppP dimer is stabilized by phosphatidylethanolamine, which, unexpectedly, enhanced the speed of substrate processing. Overall, our results demonstrate the potential of native mass spectrometry for real-time biosynthetic reaction monitoring of membrane enzymes, as well as their in situ inhibition and cofactor binding, to inform the mode of action of emerging antibiotics.

Oxidation Analysis of l-Cysteine with a Chiral Sensor Based on Quantum Weak Measurement.

l-Cysteine, distinguished by its possession of reactive sulfhydryl groups within its molecular structure, plays a significant role in both biological systems and the pharmaceutical industry. It stands not only as a natural component integral to the constitution of glutathione but also as the principal precursor for the synthesis of l-cystine through an oxidation reaction. This study endeavors to introduce a novel approach to l-cysteine analysis, capitalizing on its optical activity, whereby an optical rotation detection system grounded in the principles of quantum weak measurement is proffered. The optical rotation angle corresponding to the concentration of chiral solutions can be accurately ascertained through spectral analysis. In practical implementation, a chiral sensing system, boasting a sensitivity of 372 nm/rad, was meticulously constructed, leveraging the concept of weak value amplification. Then, the real-time monitoring of chemical reactions involving l-cysteine and dimethyl sulfoxide was performed. Under the specific experimental conditions outlined in this investigation, it was observed that the oxidation process culminated within approximately 12 h. The application of weak measurement-based chiral sensors holds immense potential, providing robust technical support for real-time monitoring in fields such as chiral analysis and the synthesis of chiral pharmaceutical compounds.

Development and evaluation of a rapid visual loop-mediated isothermal amplification assay for the tcdA gene in Clostridioides difficile detection.

The tcdA gene codes for an important toxin produced by Clostridioides difficile (C. difficile), but there is currently no simple and cost-effective method of detecting it. This article establishes and validates a rapid and visual loop-mediated isothermal amplification (LAMP) assay for the detection of the tcdA gene. Three sets of primers were designed and optimized to amplify the tcdA gene in C. difficile using a LAMP assay. To evaluate the specificity of the LAMP assay, C. difficile VPI10463 was used as a positive control, while 26 pathogenic bacterial strains lacking the tcdA gene and distilled water were utilized as negative controls. For sensitivity analysis, the LAMP assay was compared to PCR using ten-fold serial dilutions of DNA from C. difficile VPI10463, ranging from 207 ng/µl to 0.000207 pg/µl. The tcdA gene of C.difficile was detected in 164 stool specimens using both LAMP and polymerase chain reaction (PCR). Positive and negative results were distinguished using real-time monitoring of turbidity and chromogenic reaction. At a temperature of 66 °C, the target DNA was successfully amplified with a set of primers designated, and visualized within 60 min. Under the same conditions, the target DNA was not amplified with the tcdA12 primers for 26 pathogenic bacterial strains that do not carry the tcdA gene. The detection limit of LAMP was 20.700 pg/µl, which was 10 times more sensitive than that of conventional PCR. The detection rate of tcdA in 164 stool specimens using the LAMP method was 17% (28/164), significantly higher than the 10% (16/164) detection rate of the PCR method (X2 = 47, p < 0.01). LAMP method is an effective technique for the rapid and visual detection of the tcdA gene of C. difficile, and shows potential advantages over PCR in terms of speed, simplicity, and sensitivity. The tcdA-LAMP assay is particularly suitable for medical diagnostic environments with limited resources and is a promising diagnostic strategy for the screening and detection of C. difficile infection in populations at high risk.

Neurofinance: Exploratory Analysis Stock Trader's Decision-Making Process by Real-Time Monitoring of Emotional Reactions

Human emotions can be associated with decision-making, and emotions can generate behaviors. Due to the fact that it could be biased and exhaustively complex to examine how human beings make choices, it is necessary to consider relevant groups of study, such as stock traders and non-traders in finance. This work aims to analyze the connection between emotions and the decision-making process of investors and non-investors submitted to the same set of stimuli to understand how emotional arousal might dictate the decision process. Neuroscience monitoring tools such as Real-Time Facial Expression Analysis (AFFDEX), Eye-Tracking, and Galvanic Skin Response (GSR) were adopted to monitor the related experiments of this paper and its accompanying analysis process. Thirty-seven participants attended the study, 24 were classified as stock traders, and 13 were non-traders; the mean age for the groups was 35 and 25, respectively. The designed experiment initially disclosed a thought-provoking result between the two groups under the certainty and risk-seeking prospect theory; there were more risk-takers among non-investors at 75%, while investors were inclined toward certainty at 79.17%. The implication could be that the non-investing individuals were less complex in thought and therefore pursued higher returns besides a high probability of losing the game. In addition, the automatic emotion classification system indicates that when non-investors confronted a stock trending chart beyond their acquaintance or knowledge, they were psychologically exposed to fear, anger, sadness, and surprise. On the contrary, investors were detected with disgust, joy, contempt, engagement, sadness, and surprise, where sadness and surprise overlapped in both parties. Under time pressure conditions, 54.05% of investors or non-investors tend to make decisions after the peak(s) of emotional arousal. Variations were found in the deciding points of the slopes: 2.70% were decided right after the peak(s), 37.84% waited until the emotions turned stable, and 13.51% were determined as the emotional indicators started to slide downwards. Several combinations of emotional responses were associated with decisions. For example, negative emotions could induce passive decision-making, in this case, to sell the stock; nevertheless, it was also examined that as the slope slipped downwards to a particular horizontal point, the individuals became more optimistic and selected the "BUY" option. Future works may consider expanding the study to larger sample size, different demographic groups, and other biometrics for further analysis and conclusions.

Native top-down mass spectrometry for monitoring the rapid chymotrypsin catalyzed hydrolysis reaction

Enzymes play crucial roles in life sciences, pharmaceuticals and industries as biological catalysts that speed up biochemical reactions in living organisms. New catalytic reactions are continuously developed by enzymatic engineering to meet industrial needs, which thereby drives the development of analytical approaches for real-time reaction monitoring to reveal catalytic processes. Here, taking the hydrolase— chymotrypsin as a model system, we proposed a convenient method for monitoring catalytic processes through native top-down mass spectrometry (native TDMS). The chymotrypsin sample heterogeneity was first explored. By altering sample introduction modes and pHs, covalent and noncovalent enzymatic complexes, substrates and products can be monitored during the catalysis and further confirmed by tandem MS. Our results demonstrated that native TDMS based catalysis monitoring has distinctive strength on real-time inspection and continuous observation, making it a promising tool for characterizing more biocatalysts.

Construction of an OCP-ATR-FTIR Spectroscopy Device to In Situ Monitor the Interfacial Reaction of Contaminants: Competitive Adsorption of Cr(VI) and Oxalate on Hematite.

The comprehensive understanding of contaminant interfacial behavior strongly depends on the in situ characterization technique, which is still a great challenge. In this study, we constructed a device integrated with open-circuit potentialand attenuated total reflectance Fourier transform infrared (OCP-ATR-FTIR) spectroscopy to simultaneously monitor the electrochemical and infrared spectral information on the interfacial reaction for the process analysis, taking the competitive adsorption of hexavalent chromium (Cr(VI)) and oxalate on hematite nanocubes (HNC) as an example. The synchronous OCP and infrared results revealed that Cr(VI) interacted with HNC via bidentate binuclear inner-sphere coordination, accompanied by electron transfer from HNC to Cr(VI), while oxalate was adsorbed on HNC through bidentate mononuclear side-on inner-sphere coordination with electron transfer from HNC to oxalate, and also outer-sphere coordination with negative charge accumulation. When oxalate was added to HNC with preadsorbed Cr(VI), oxalate would occupy the inner-sphere adsorption sites and thus cause the detaching of preadsorbed Cr(VI) from HNC. This study provides a promising in situ characterization technique for real-time interfacial reaction monitoring and also sheds light on the competitive adsorption mechanism of oxalate and Cr(VI) on the mineral surface.

Visualizing Chain Growth of Polytelluoxane via Polymerization Induced Emission.

Visualizing polymer chain growth is always a hot topic for tailoring structure-function properties in polymer chemistry. However, current characterization methods are limited in their ability to differentiate the degree of polymerization in real-time without isolating the samples from the reaction vessel, let alone to detect insoluble polymers. Herein, a reliable relationship is established between polymer chain growth and fluorescence properties through polymerization induced emission. (TPE-C2)2 -Te is used to realize in situ oxidative polymerization, leading to the aggregation of fluorophores. The relationship between polymerization degree of growing polytelluoxane (PTeO) and fluorescence intensity is constructed, enabling real-time monitoring of the polymerization reaction. More importantly, this novel method can be further applied to the observation of the polymerization process for growing insoluble polymer via surface polymerization. Therefore, the development of visualization technology will open a new avenue for visualizing polymer chain growth in real-time, regardless of polymer solubility.

Construction of continuous flow catalytic reactor-HPLC system with ultrahigh catalytic activity using 2D nanoflower MOF-derived Cu2O/Cu/PDA/CF catalyst

Currently, metal-organic frameworks (MOFs) derived materials have been widely concerned for the reduction of 4-nitrophenol (4-NP). However, complex recovery of powder catalysts and low utilization ratio of active sites make their application challenging. Herein, a novel Cu2O/Cu/PDA/CF catalyst has been developed for the rapid reduction of 4-NP to 4-aminophenol (4-AP). The catalyst was constructed by compositing a two-dimensional nanoflower MOF-derived nanoporous Cu2O/Cu network on a polydopamine (PDA)-modified porous copper foam by a mild and controllable in-situ reduction synthesis. Notably, an enhanced catalytic performance of Cu2O/Cu/PDA/CF was obtained for 4-NP reduction with a rate constant (k) of 0.8001 min−1, outperforming Cu/PDA/CF-X (X = 400, 500 and 600 ℃ pyrolysis temperature) catalysts (2.3–6.4 folds), and even many reported catalysts (2.3–46.5 folds). The ultrafast degradation of 4-NP was completed in 70 s. Moreover, an ingenious online continuous flow catalytic reactor (CFCR)-high performance liquid chromatography (HPLC) system was constructed for automatic and real-time monitoring of the reduction reaction. System stability experiments over 300 min revealed a surprisingly high reaction k value of 76.68 min−1 at low NaBH4 usage, significant increasing by 2–3 orders of magnitude compared with Cu2O/Cu/PDA/CF batch catalysis, due to the high aspect ratio of 2D nanoflower MOF and convection-accelerated mass transfer. This work offers new insights for the rational design of catalytic reactor and its potential application in wastewater treatment.

High-Performance Recognition, Cell-Imaging, and Efficient Removal of Carbon Monoxide toward a Palladium-Mediated Fluorescent Sensing Platform.

Novel high-performance fluorescent approaches have always significant demand for room-temperature detection of carbon monoxide (CO), which is highly toxic even at low concentration levels and is not easy to recognize due to its colorless and odorless nature. In this paper, we constructed a palladium-mediated fluorescence turn-on sensing platform (TPANN-Pd) for the recognition of CO at room temperature, revealing simultaneously quick response speed (<30 s), excellent selectivity, superior sensitivity, and low detection limit (∼160 nM for CORM-3, ∼1.7 ppb for CO vapor). Moreover, rapid detection and efficient removal (24%) from the air by naked-eye vision has been successfully realized based on TPANN-Pd supramolecular gels. Furthermore, the developed sensing platform was elucidated with low cytotoxicity and high cellular uptake, and it was successfully applied to CO imaging in living cells, providing real-time monitoring of potential CO-involved reactions in biological systems.

Experimental Advances in the Real-Time Recording of Cross-Linking Alginate In Situ Gelation: A Review.

Alginate-based hydrogels are promising smart materials widely employed in the food, bioengineering, and energy sectors. The development and optimization of their production require a thorough knowledge of gelation. In recent years, advanced experimental procedures have been developed for real-time cross-linking alginate reaction monitoring. Novel methods, such as customized rheometric setups, enable the recording of mechanical properties and morphological changes during hydrogel formation. These innovative techniques provide important insights into the gelation stages, the reaction rate, the diffusion of cross-linker to polymer chains, and the homogeneity of the gelling structures. Based on real-time experimental data, kinetic models are developed to enhance comprehension of the reaction mechanism and, eventually, to predict the gelation progress. The aim is to enable better control of the characterization of both the complex gelation and the propagated structures. This review aspires to present a comprehensive overview and evaluation of the breakthrough innovations of the real-time in situ recording of cross-linking alginate hydrogels and bead formation. A detailed analysis of the pioneering experimental developments provides a deep comprehension of the alginate gelation, including the parameters controlling the reaction.

Automation, analytics and artificial intelligence for chemical synthesis

Automation and real-time reaction monitoring have enabled data-rich experimentation, which is critically important in navigating the complexities of chemical synthesis. Linking real-time analysis with machine learning and artificial intelligence tools provides the opportunity to accelerate the identification of optimal reaction conditions and facilitate error-free autonomous synthesis. This Comment provides a viewpoint underscoring the growing significance of data-rich experiments and interdisciplinary approaches in driving future progress in synthetic chemistry.

Chirality-induced spin selectivity enables real-time monitoring of a chemical reaction

Chirality-induced spin selectivity enables real-time monitoring of a chemical reaction

Real-Time Monitoring of Reactions by Headspace Sampling under Ambient Mass Spectrometric Conditions

The helium-plasma (HePI) ionization mass spectrometry method was used to track the formation of reaction products and consumption of reactants by continually monitoring the vapors in the reaction headspace in real time. Two examples of the application procedure are presented here: a nucleophilic acyl substitution reaction and a 1,4-nucleophilic addition process. For the purposes of the work, a specially constructed helium-plasma ionization (HePI) source was mounted on a single-quadrupole benchtop mass spectrometer. However, any electrospray source is easily convertible to an ambient HePI source. This setup has the potential to be used in the teaching of organic and analytical chemistry laboratories, as well as for demonstrations. Because the procedure requires only the headspace of the reaction vessel to be sampled by an easily prepared Venturi suction device (pump), the experiments can be quickly set up and adapted for any available mass spectrometer equipped with an electrospray source. For sampling, students can be shown how to prepare their own Venturi pumps and conduct reactions at different temperatures.

An adaptive soft-sensor for advanced real-time monitoring of an antibody-drug conjugation reaction.

In the production of antibody-drug conjugates (ADCs), the conjugation reaction is a central step defining the final product composition and, hence, directly affecting product safety and efficacy. To enable real-time monitoring, spectroscopic sensors in combination with multivariate regression models have gained popularity in recent years. The extended Kalman filter (EKF) can be used as so-called soft-sensor to fuse sensor predictions with long-horizon forecasts by process models. This enables the dynamic update of the current state and provides increased robustness against experimental noise or model errors. Due to the uncertainty associated with sensor and process models in biopharmaceutical applications, the deployment of such soft-sensors is challenging. In this study, we demonstrate the combination of an uncertainty-aware sensor model with a kinetic reaction model using an EKF to monitor a site-directed ADC conjugation reaction. As the sensor model, a Gaussian process regression model is presented to realize a time-variant determination of the sensor uncertainty. The EKF fuses the time-discrete predictions of the amount of conjugated drug from the sensor model with the time-continuous predictions from the kinetic model. While the ADC species are not distinguishable by on-line recorded UV/Vis spectra, the developed soft-sensor is able to dynamically update all relevant reaction species. It could be shown that the use of time-variant process and sensor noise computation approaches improved the performance of the EKF and achieved a reduction of the prediction error of up to 23% compared with the kinetic model. The developed framework proved to enhance robustness against noisy sensor measurements or wrong model initialization and was successfully transferred from batch to fed-batch mode. In future, this framework could be implemented for model-based process control and be adopted for other ADC conjugation reaction types.