Continuous Process Research Articles

Effects of Ultrasound on Reactive Crystallization and Particle Properties of an Aromatic Amine in Batch and Continuous modes

Ultrasound has shown its benefits in the manufacturing processes of many pharmaceuticals and fine chemicals. This study focused on the reactive crystallization system of an aromatic amine and explored the potential uses of ultrasound in both batch and continuous modes. In batch experiments, we studied the effects of different sonication conditions including power, duration, and starting point on final particle properties. Under ultrasound, the crystal form and crystal morphology remained well maintained. The results of particle size and size distribution suggested that ultrasound reduced the mean sizes by improving the nucleation process and breaking up large particles. Additionally, the presence of ultrasound in continuous experiments was capable of inducing nucleation and the crystal products collected had a suitable distribution. Integrating ultrasound into the beginning of the continuous crystallization process can be an alternative to the seeding technique. The increasing sonication power did not reduce the induction time substantially. This indicated that a rational sonication condition should balance the overall process efficiency and energy consumption. The findings from batch and continuous experiments indicate that ultrasound could intensify industrial crystallization of the aromatic amine. Incorporating energy-efficient ultrasound with the continuous process will potentially lead to increased production efficiency and a well-controlled product quality.

A Review on Secure Outsourcing and Privacy-Preserving Traffic Monitoring in Fog-Enabled VANETs

New possibilities for fog-based vehicle monitoring have emerged with the expansion of fog computing, but present privacy concerns provide a significant barrier that limits the extent to which vehicles can participate. Because of its potential to improve road network security and vehicle productivity, the field of Vehicle-based Ad hoc Networks (VANETs) is gaining prominence. The security problems with VANETs, such as data confidentiality and message access control are still need better solutions to provide better Quality of Service (QoS). The effectiveness of VANET networks is diminished due to their instability problem. Vehicles continually add requests to the Road Side Unit (RSU) queue whenever they want specific information. For ever-evolving networks like VANETs, better routing is a continual process. Fundamental problems arise in large-scale systems when centralized procedures are used to assign jobs to the nodes along a route. The present centralized system for computing and safety has many needs, including the protection of data storage, user authentication, access control, system availability across multiple network connections, and the provision of a real-time data flow overview. Distributed problem solving and work sharing between multiple agents can improve the system's scalability. This paper provides a brief survey on the secured outsourcing and privacy preservation-based traffic monitoring model with routing and task scheduling models in Fog-enabled VANETS. This survey presents the limitations of the traditional models that help the researchers design new solutions for secure outsourcing in VANETs.

Thinking beyond the closure assumption: Designing surveys for estimating biological truth with occupancy models

Abstract Occupancy models estimate distributions of imperfectly detected species, but violations of the closure assumption can bias results. However, researchers working with mobile animals may find it impossible to eliminate such violations. Here, we tested the hypothesis that occupancy models fit to realistic sampling data can generate unbiased occupancy estimates for an itinerant Wood Thrush (Hylocichla mustelina) population. In 2013 and 2014, we tracked movements of 41 breeding Wood Thrush males. We modelled territory shift probabilities using logistic exposure models and within‐territory movements using continuous‐time stochastic process models. We then constructed an individual‐based model, simulated (1000 iterations) spatiotemporal locations for individuals and simulated sampling these populations using 162 different point count protocols with variable spatial (sampling radius and point placement method), and temporal (survey length, between‐survey intervals and number of surveys) characteristics. We compared occupancy estimates with true values of instantaneous, daily and seasonal occupancy from the simulations. We parameterized continuous time stochastic process models based on movements within 34 unique territories and estimated a daily territory shift probability of 0.0099 (95% CI: 0.0060, 0.0152). Simulated data indicated that estimates of occupancy ranged from 0.18 (0.06, 1.00) to 0.80 (0.71, 0.89) depending on protocol characteristics. Occupancy estimates increased with increasing survey radius, survey length and between‐survey interval. Protocols using shorter surveys and between‐survey intervals were good estimators for instantaneous occupancy (low bias and mean‐squared error) but poor estimators for daily and seasonal occupancy; longer surveys and intervals generated unbiased estimators of daily occupancy but underestimated seasonal occupancy. Logistic regression models that ignored imperfect detection outperformed occupancy models for estimating instantaneous occupancy but not daily or seasonal occupancy. For mobile animals, occupancy of sampling sites changes in space and time. Consequently, the spatial and temporal aspects of a sampling protocol have strong, but predictable, effects on occupancy model parameter estimates. Our results demonstrate that how these factors interact is critical for designing surveys that produce occupancy estimates representative of the biological process of interest to a researcher.

Capacity assessment for euthanasia in dementia: A qualitative study of 60 Dutch cases.

The number of patients with dementia who are granted euthanasia or assisted suicide (EAS) increases yearly in the Netherlands. By law, patients need to be decisionally competent or have an advance directive. Assessment of decisional capacity is challenging as dementia progressively affects cognitive performance. We aimed to assess qualitatively which factors, and how, influence the judgment of decisional capacity in EAS cases with dementia. We performed a qualitative study of 60 dementia EAS case summaries published by the Dutch regional euthanasia review committees between 2012 and 2021. Included reports were evaluated using the grounded theory approach. All quotes related to decisional capacity were coded independently by two researchers and compared in an iterative process to formulate an overarching framework on the assessment of decisional capacity. We selected 20 patients who had an advance directive and were judged to be decisionally compromised, as well as a selection of 40 EAS cases judged to be decisionally competent, half of which also had an advance directive (purposive sampling). Decisional capacity was present in every case report. Predefined, external criteria were rarely described explicitly, but physicians indirectly referred to the (cognitive) criteria set by Appelbaum and Grisso. Whether the thresholds for these dimensional criteria were met was influenced by six supporting factors (level of communication, psychiatric comorbidity, personality, presence of an advance directive, consistency of the request, and, finally, the patient-physician relationship) that also directly contributed to the judgment of capacity. The involved physicians and executed investigations were the two contextual factors providing a background. Decisional capacity regarding euthanasia is a multidimensional construct, often implicitly assessed and influenced by supporting and contextual factors. The subjectivity of the final judgment poses ethical and legal issues and argues for continuous quality improvement processes.

Functional failure analysis of the graphite crystallizer used in horizontal continuous casting process of copper tube

The presence of a particular type of white powder has emerged as a significant challenge in the horizontal continuous casting process of copper. This white powder leads to the blockage of the graphite crystallizer, resulting in a functional failure that adversely affects the mold’s lifespan, increases production costs, and reduces overall efficiency. The issue has posed significant challenges for engineers due to its complex and unclear formation mechanism. This investigation employed various experimental characterization methods to analyze the composition, element distribution, phase properties, and other relevant factors of the white powder. Meanwhile, a high-temperature experiment was also designed to examine the potential reactions between copper oxide (Cu2O) and the furnace lining (3Al2O3·2SiO2). It is found that the main component of the white powder blocking the inlet hole of the graphite mold is SiO2, which is traced back to the furnace lining. Under high temperatures, oxygen reacts with liquid copper to form Cu2O. Subsequently, this Cu2O reacts with Al2O3 in the furnace lining to produce CuAlO2. Meanwhile, SiO2 becomes isolated as Al2O3 is deprived. The resultant SiO2 accumulates at the inlet hole of the graphite mold due to rapid cooling. The accumulated SiO2 in the form of white powder blocks the inlet hole of the graphite mold, leading to functional failure of the graphite mold. To address this issue, several improvement measures are proposed including drying the raw and protective material, enhancing the sealing of the furnace, and reducing the holding time.

Passive Inclination Sensor Based on a Patch Antenna with a Reconfigurable Water Load.

In order to ensure the safety and preserve the value of historical buildings, inclination is an essential parameter during the continuous structural health monitoring process. However, the wire and price of a traditional sensor limit application. This paper proposes a low-cost inclination sensor based on a patch antenna with a reconfigurable water load. Only the water directly on the antenna is considered effective. The different volume of the effective water load, which is determined by the inclination of the attached surface, will affect the effective permittivity of the dielectric plate of the patch antenna, further causing a variation in the resonant frequency. Therefore, the proposed antenna sensor can monitor the inclination of the attached surface by interrogating the resonant frequency. The working mechanism is first clarified by theoretically investigating the relationship between the dielectric properties and the inclination of the covering medium. The antenna sensor is then simulated using High-Frequency Structure Simulator ver.15 (HFSS 15), which helps to determine geometric parameters and confirm accuracy and sensitivity. An experiment has been conducted based on the design verified in the simulation. The inclination detection shows a correlation coefficient of 0.9771 with a sensitivity of 7.92 MHz/°, indicating a potential for real application.

Monitoring Myelin Lipid Composition and the Structure of Myelinated Fibers Reveals a Maturation Delay in CMT1A.

Findings accumulated over time show that neurophysiological, neuropathological, and molecular alterations are present in CMT1A and support the dysmyelinating rather than demyelinating nature of this neuropathy. Moreover, uniform slowing of nerve conduction velocity is already manifest in CMT1A children and does not improve throughout their life. This evidence and our previous studies displaying aberrant myelin composition and structure in adult CMT1A rats prompt us to hypothesize a myelin and axon developmental defect in the CMT1A peripheral nervous system. Peripheral myelination begins during the early stages of development in mammals and, during this process, chemical and structural features of myelinated fibers (MFs) evolve towards a mature phenotype; deficiencies within this self-modulating circuit can cause its blockage. Therefore, to shed light on pathophysiological mechanisms that occur during development, and to investigate the relationship among axonal, myelin, and lipidome deficiencies in CMT1A, we extensively analyzed the evolution of both myelin lipid profile and MF structure in WT and CMT1A rats. Lipidomic analysis revealed a delayed maturation of CMT1A myelin already detectable at P10 characterized by a deprivation of sphingolipid species such as hexosylceramides and long-chain sphingomyelins, whose concentration physiologically increases in WT, and an increase in lipids typical of unspecialized plasma membranes, including phosphatidylcholines and phosphatidylethanolamines. Consistently, advanced morphometric analysis on more than 130,000 MFs revealed a delay in the evolution of CMT1A axon and myelin geometric parameters, appearing concomitantly with lipid impairment. We here demonstrate that, during normal development, MFs undergo a continuous maturation process in both chemical composition and physical structure, but these processes are delayed in CMT1A.

Enhanced desalination performance of flow capacitive deionization with the addition of conductive polymer in redox couples and activated carbon

Freshwater scarcity is a critical global issue and desalination of brackish water and seawater technologies are regarded as effective solution to mitigate the increasing severity of water shortage. Flow-electrode capacitive deionization (FCDI) is an emerging electrochemical desalination technology capable of continuous deionization behavior. However, reducing energy consumption and enhancing desalination rate are now markedly needed for its advancement. Herein, we propose a FCDI system with energy consumption as low as 88.08 kJ mol−1 and a desalting rate of 1.75 μg cm−2 s−1. This is achieved by using flow electrodes containing 0.03125 wt% conductive polymer, 5 wt% activated carbon/carbon black and 80 mM/80 mM ferricyanide/ferrocyanide at a current density 3 mA cm−2 (3.36 mA current for a 1.12 cm2 active area). We further investigate the effects of polymer content, redox pair content, salt content and current densities on desalination performance. Seawater with a conductivity of 52.78 mS cm−1 was successfully desalinated to 0.50 mS cm−1 in continuous process. This research provides a promising approach to enhance FCDI system by achieving a low energy consumption and high salt removal rate, representing a significant advancement in continuous electrochemical desalination technology.

Control of an integrated first and second-generation continuous alcoholic fermentation process with cell recycling using model predictive control

This study explores controlling a first- and second-generation alcoholic fermentation process with cell recycling, modeled through algebraic differential equations (DAE) with constraints. It evaluates seven controller types: PI, PID, Model Predictive Control (MPC), Neural Network Model Predictive Control (NNMPC), Mixed Model Predictive Control (MMPC), Internal Model Control (IMC), and Linear Quadratic Regulator (LQR). Results show that, while PI and PID controllers can track setpoints, they exhibit slow responses and oscillations. In contrast, MPC controllers respond faster, with both MPC and MMPC demonstrating more robust dynamics, achieving a significant reduction in Integral of the Absolute Error (IAE) across various disturbances, notably an 87% reduction in regulatory scenarios. NNMPC outperforms PI and PID but exhibits overshoot and oscillations, and lacks robustness for servo-type problems. However, MMPC showcases comparable or superior performance to MPC, surpassing other controllers in robustness, especially the IMC and LQR in the regulatory problems. NNMPC maintains a simulation time of under 4 seconds, whereas MPC incurs a computational cost 1,000 times higher. Integrating NNMPC’s optimal increment as an initial estimate in MPC reduces computational time by up to 79.7%. These findings highlight the ANN’s effectiveness in addressing complex control challenges, especially when integrated with MPC. MMPC offers a superior balance between accuracy, robustness, and computational efficiency, serving as a promising solution for reducing computational costs in MPC-type controllers.

Improving group problem solving through awareness of members’ problem-solving preferences

PurposeMany groups in organisations are unsuccessful in problem solving. However, the principle of continuous improvement necessitates that organisations refine their employees’ problem-solving skills. In this mixed-method, field-based lab experiment, we explored the impact of a treatment to enhance the quality of group problem-solving processes.Design/methodology/approachWe focused on the structured problem-solving process in Kaizen Events by differentiating six consecutive phases. About 16 Kaizen Event groups (101 members) participated in a field-based lab experiment that used a lean simulation game to establish a group problem-solving context. Data were collected via video, surveys and group interviews. We examined if a high-quality process is strengthened through group members’ elevated awareness of problem-solving preferences. About 11 groups received a treatment of tailor-made individual feedback to increase awareness of their problem-solving preferences. Additionally, we repeated the experiment in five control groups, where member preferences were not shared.FindingsIn the treatment groups, where problem-solving preferences had been shared, we observed a clear improvement in Kaizen Event process quality and higher problem-solving self-efficacy levels. Moreover, their self-reported Kaizen Event behaviour had changed. Within the control groups, the participants also reported that their problem-solving self-efficacy had improved, but this did not have a positive impact on the quality of the objectively measured Kaizen Event process.Originality/valueBy combining insights from operations management and organisational behaviour, we demonstrate that the structured Kaizen Event problem-solving process improves when group members’ individual problem-solving preferences are shared. We thus add an individual-level variable to the extant models of Kaizen Event success factors. Our results provide fresh insights into how to improve the continuous improvement process within organisations. Kaizen Event stakeholders and their facilitators are offered guidance on how to increase one’s awareness of own and others’ problem-solving preferences in group-based problem-solving events.

How higher education teachers see their professional identity

An important dimension to understand the student learning process is the professional identity of teachers, which is conceptualized as a continuous process of construction and reconstruction. In this process, teachers define and assume their roles in a specific educational context that is characterized by tensions, adjustments, and transformations. This study focuses on understanding the professional identity of higher education teachers, a field characterized by constant evolution and demands. The personal characteristics of this identity are explored, including experiences and biographical representations, as well as its interrelationship with the institutional environment. Using a qualitative interpretive approach, six teachers recognized for their pedagogical innovation and educational commitment were interviewed. The results reveal outstanding motivation and responsibility in educational work, but also tensions between personal identity and the work context, reflected in the perception of low recognition and the importance of institutional leadership. The teachers show a critical and reflective view of their work, influenced by childhood experiences that impact their conceptions of educational justice and equity. To conclude, the common characteristics of professional identity in higher education highlight the need to integrate them into professional development. The article advocates for the design of more personalized training programs and the promotion of continuous learning among peers as key elements to strengthen this identity and improve pedagogical practice.

Optimization Study on Hardness of Cold Rolled Strip Steel Based on a Data-Driven Approach

As a key index to measure product quality and processability, the hardness of cold-rolled strip steel has an important influence on the production efficiency of iron and steel enterprises. However, due to the coupling between the process parameters at each stage of the continuous annealing process, and the setting of traditional process parameters depending on the experience of the operator, the lack of scientific and systematic optimization methods, which easily leads to the problem of high hardness fluctuation and low resource utilization. In this study, the data-driven method is used to conduct a preliminary correlation analysis to further clarify the optimal combination of process parameters for achieving the target hardness. The Pearson correlation coefficient is used to determine that carbon content, quenching furnace temperature, and strip speed significantly affect strip hardness. To further clarify the optimal combination of process parameters to achieve the target hardness, a Genetic Algorithm (GA) was tried in this study. The results show that the optimized process parameter combination can effectively improve the stability and consistency of strip hardness, and provide a scientific basis for the process parameter setting in the cold rolled strip production process, which is helpful for enterprises to improve product quality, reduce cost, and enhance market competitiveness.

Generalized Itô’s lemma and the stochastic thermodynamics of diffusion with resetting

Abstract Methods from the theory of stochastic processes are increasingly being used to extend classical thermodynamics to mesoscopic non-equilibrium systems. One characteristic feature of these systems is that averaging the stochastic entropy with respect to an ensemble of stochastic trajectories leads to a second law of thermodynamics that quantifies the degree of departure from thermodynamic equilibrium. A well known mechanism for maintaining a diffusing particle out of thermodynamic equilibrium is stochastic resetting. In its simplest form, the position of the particle instantaneously resets to a fixed position x 0 at a sequence of times generated from a Poisson process of constant rate r. Within the context of stochastic thermodynamics, instantaneous resetting to a single point is a unidirectional process that has no time-reversed equivalent. Hence, the average rate of entropy production calculated using the Gibbs–Shannon entropy cannot be related to the degree of time-reversal symmetry breaking. The problem of unidirectionality can be avoided by considering resetting to a random position or diffusion in an intermittent confining potential. In this paper we show how stochastic entropy production along sample paths of diffusion processes with resetting can be analyzed in terms of extensions of Itô’s formula for stochastic differential equations (SDEs) that include both continuous and discrete processes. First, we use the stochastic calculus of jump-diffusion processes to calculate the rate of stochastic entropy production for instantaneous resetting, and show how previous results are recovered upon averaging over sample trajectories. Second, we formulate single-particle diffusion in a switching potential as a hybrid SDE and develop a hybrid extension of Itô’s stochastic calculus to derive a general expression for the rate of stochastic entropy production. We illustrate the theory by considering overdamped Brownian motion in an intermittent harmonic potential. Finally, we calculate the average rate of entropy production for a population of non-interacting Brownian particles moving in a common switching potential. In particular, we show that the latter induces statistical correlations between the particles, which means that the total entropy is not given by the sum of the 1-particle entropies.

Study on the Continuous Whole Process Preparation of Peptizable Pseudoboehmite by High Gravity Strengthening Reaction of CO2 and Heat Transfer.

The preparation of highly peptizable pseudoboehmite faces challenges such as slow reaction rate, prolonged aging times leading to poor peptization performance, and difficulty in achieving continuous production. In this study, a novel approach was proposed involving a high gravity reactor to enhance carbonation reaction control for pseudoboehmite nucleation, a high gravity steam heating process, and a continuous aging process in pipelines. By coupling these three processes, the continuous whole process production of highly peptizable pseudoboehmite under high gravity conditions was achieved. First, the effect of high gravity reactor enhancement on the reaction and the resulting solid phase was investigated. Second, the impact of aging temperature and time on the solid phase formed at different reaction end points was studied using high gravity and steam heating of the liquid phase. Furthermore, the influence of synthesis conditions on the peptization performance of pseudoboehmite was extensively examined. Finally, the nucleation and growth mechanisms of pseudoboehmite under high gravity conditions were analyzed. It was found that increasing high gravity factor, CO2 gas flow rate, and CO2 content accelerated carbonation reaction rate, promoting pseudoboehmite crystal nucleation. Increasing aging temperature and time facilitated the growth of pseudoboehmite nuclei and improved peptization performance. The high gravity device altered the gas-liquid phase contact state of traditional kettle-type equipment, reducing the reaction time and heating time from minutes to seconds, thus achieving the continuous whole process production of pseudoboehmite with a peptization index of 100% from sodium aluminate solution by kiln flue gas.

Characterization and Inversion Method of Relative Permeability of Emulsion Flooding.

Relative permeability curves are one of the crucial factors that control the behavior of multiphase flow in petroleum reservoirs. Accurate prediction of the relative permeability curve involving emulsification and emulsion transport in emulsion flooding is vital to enhancing heavy oil recovery. In this study, a relative permeability characterization model including the emulsification mechanism and emulsion transport is developed, in which residual oil saturation and end-point permeability for water are parametrized as functions of emulsion concentration and capillary number. Based on the built characterization model, an inversion method (ensemble Kalman filter) is used to estimate the relative permeability curves of emulsion flooding. The inversion results of four sets of emulsion flooding experiments show that the errors of end points between the Johnson-Bossler-Neumann method and inversion method are less than 10%. For the continuous emulsification process in the in situ emulsion flooding tests, the inversed relative permeability curves shift between the upper and the inferior limits of the permeability. The error of residual oil saturation between the inversion and the experiment is less than 10%. In summary, this study demonstrates the feasibility of using the characterization model and inversion method to infer the relative permeability curves of emulsion flooding, which can aid in the predictions of multiphase flow in heavy oil reservoirs.

Comparative Evaluation of Methane Yield from Continuous and Batch Fermentative Processing of Selected Agrowaste

This study investigated the influence of different agrowaste compositions on methane yield in batch and continuous operational modes, highlighting the significance of substrate characteristics in determining the efficiency of methane production. It comparatively assessed the methane yield derived from continuous and batch fermentative processing of the following agrowaste; Cassava peels (A), Maize husks (B), Pig Slurry (C), and composite (D) that represents the co-digestion of the aforementioned A, B & C. Eight digesters were used in all, two anaerobic systems for each substrate, [I.e one operating in a batch mode (1) and the other in a continuous mode (2)]. The proximate properties of the substrates were determined and gas production rates were monitored over the experimental period of 45 days. Gas analysis of the generated gas revealed mainly methane and CO2, with concomitant organic compounds like; Ethanol, Methanol, Acetic Acid, Acetone, etc. Minute quantities of Phenol and Lactic Acid were mainly found in the gas generated from Cassava peels. The average percentage value of Co-digested substrates (D) yielded higher gas volume of 78.263±4.54, followed by C (74.263±4.65), B (70.240±4.38), and A (56.090±3.50). The results also revealed that the continuous fermentative process demonstrated a more stable and consistent methane production rate compared to the batch system, attributed to its steady-state operational mode and continuous substrate feed input. However, modeled graphical results showed that batch fermentation system produced higher gas yield (for all the substrates) between days 29-39 before it recorded a sharp decline curve, attributed to the reduction in substrate availability.

Evaluation of Integrated Anaerobic/Aerobic Conditions for Treating Dye-Rich Synthetic and Real Textile Wastewater Using a Soda Lake Derived Alkaliphilic Microbial Consortia

Textile industry wastewater (WW) has intense color, high chemical oxygen demand (COD), pH, and salinity, making it challenging for conventional treatment. Soda lakes, with high alkalinity and salinity, host diverse microbes capable of textile dye degradation. This study evaluated anaerobic/aerobic reactors using alkaliphilic microbial consortia from Lake Chitu, an Ethiopian soda lake, for treating synthetic and real textile WW. The experimental setup consisted of a first-stage anaerobic reactor followed by a second-stage aerobic reactor, operating continuously with a predetermined flow rate and hydraulic residence time. After evaluating synthetic WW, real textile WW was collected in two batches (rounds I and II). The treatment setup removed 99% of the dye color for synthetic WW, 98% for round I, and 96% for round II. COD removal was 87% for synthetic WW, 86% for round I, and 93.37% for round II. TKN removal reached 90% for synthetic WW, 91% for round I, and 96% for round II at a steady state. Residual COD and TKN values met the final effluent discharge standards. GC–MS and IR analyses revealed that dyes were broken down into intermediate organic compounds under anaerobic conditions and further degraded into smaller molecules under aerobic conditions. This integrated reactor approach effectively removes dyes and enhances COD and TKN removal. The study’s novelty lies in evaluating both synthetic and real textile WW using integrated reactors under alkaline conditions in a continuous process, inoculating alkaliphilic consortia, without pre-enrichment or external nutrient addition to real WW. The study provides insights into the effectiveness of alkaliphilic microbial consortia derived from soda lakes for treating textile WW using integrated reactor conditions. Reactor microbiome characterization is needed to further explore microbial diversity and community structure.

Successful Aging and Preventative Health: A Business Owner's Perspective

Successful aging can be viewed as a continuous and ongoing holistic process or as a goal-oriented approach. Both views provide sufficient exploration and definition toward development continuing through adulthood into the latter. However, the investigation of successful aging and how its definition can become affected by technological-based health innovation is an under-researched topic. Using literature and qualitative interview findings, successful aging may be considered to also incorporate the use of health-related innovation assets under the umbrella of preventative health, which contributes as an important factor toward how older individuals perceive the success of themselves and the various areas of their life as they continue to develop in late adulthood.

Highly efficient synthesis of the chiral ACE inhibitor intermediate (R)-2-hydroxy-4-phenylbutyrate ethyl ester via engineered bi-enzyme coupled systems

(R)-2-Hydroxy-4-phenylbutyric acid ethyl ester ((R)-HPBE) is an essential chiral intermediate in the synthesis of angiotensin-converting enzyme (ACE) inhibitors. Its production involves the highly selective asymmetric reduction of ethyl 2-oxo-4-phenylbutyrate (OPBE), catalyzed by carbonyl reductase (CpCR), with efficient cofactor regeneration playing a crucial role. In this study, an in-situ coenzyme regeneration system was developed by coupling carbonyl reductase (CpCR) with glucose dehydrogenase (GDH), resulting in the construction of five recombinant strains capable of NADPH regeneration. Among these, the recombinant strain E. coli BL21-pETDuet-1-GDH-L-CpCR, where CpCR is fused to the C-terminus of GDH, demonstrated the highest catalytic activity. This strain exhibited an enzyme activity of 69.78 U/mg and achieved a conversion rate of 98.3%, with an enantiomeric excess (ee) of 99.9% during the conversion of 30 mM OPBE to (R)-HPBE. High-density fermentation further enhanced enzyme yield, achieving an enzyme activity of 1960 U/mL in the fermentation broth, which is 16.2 times higher than the volumetric activity obtained from shake flask fermentation. Additionally, the implementation of a substrate feeding strategy enabled continuous processing, allowing the strain to efficiently convert a final OPBE concentration of 920 mM, producing 912 mM of (R)-HPBE. These findings highlight the system’s improved catalytic efficiency, stability, and scalability, making it highly suitable for industrial-scale biocatalytic production.

Sustainable fluoride removal with scrap aluminum: Co-producing cryolite and hydrogen

This study presents a novel continuous process for fluoride removal and re- source recovery as cryolite, using a scrap aluminum-packed column. Efficient aluminum dissolution in hydrofluoric acid (HF) generates hydrogen gas and provides cost-saving alkalinity. The process achieves high efficiency (Al/F molar ratio of 2/6) within short Empty Bed Contact Times (15 min) and at low HF concentrations (500 mg/L). Solution pH plays a crucial role, with Al/F ratios above 1 achievable at pH below 4. The exothermic reaction requires temperature control, with a strong correlation (R²=0.99) between HF concentration and heat generation. Hydrogen production matches theoretical predictions. Cryolite synthesis was confirmed at optimized pH (5–5.5) with a 1:1 bypass ratio, achieving 98 % fluoride removal. XRD and SEM- EDS analyses verified cryolite formation. This approach offers a promising solution for industrial fluoride management, resource recovery, and clean hydrogen production.