Continuous Production Research Articles

NON-ANALYTICAL DESIGN OF THE PI CONTROLLER OPTIMAL PARAMETERS FOR A CONTINUOUS LINE

The multiple motor drives are complex and coupled MIMO nonlinear systems. Due to the complexity of their mathematical models the development of effective control systems is quite complicated task. This paper presents the design of optimal control based on the quadratic optimality criterion for the central section of the continuous production line using soft computer methods when fuzzy model of the controlled system has been used. In this case, the proposed method demonstrates non-analytical design of the optimal parameters of PI controller with emphasis on minimal knowledge on the controlled system. The realized experimental measurements on a continuous line laboratory model confirmed the effectiveness and the good dynamic properties of the optimal continuous line controller and also its applicability to others MIMO nonlinear dynamic systems.

Surface state modulation of carbon dots for efficient generation of hydrogen peroxide

Electrocatalytic dual electron oxygen reduction to hydrogen peroxide (2e ORR) is considered a special and sustainable method for on-site continuous production of hydrogen peroxide. Oxygen doped carbon based materials have demonstrated their superiority in the generation of H2O2. However, there is still a lack of direct experimental evidence to determine the true active site on complex carbon surfaces. In this work, we introduce only carboxyl functional groups on the surface of carbon dots by a mild and simple synthesis method to study the specific COOH functional groups on the generation of H2O2. The H2O2 selectivity was correlated with the contents of COOH functional groups. In alkaline environments, the citric acid modified CDs (CA-OCDs) own excellent catalytic ability for 2e ORR, showing a maximum starting potential of 0.829 V (vs. RHE) and a high selectivity of 89.7% over a wide potential range of 0.2-0.7 V (vs. RHE). In actual H2O2 production, the Faraday efficiency (FE) of CA-OCDs can be up to 97%, and the yield achieves 838 mmol gcatalyst-1 h-1. This work provides an effective and simple strategy for designing efficient carbon-based catalysts for sustainable H2O2 electrosynthesis.

Biological fermentation pilot-scale systems and evaluation for commercial viability towards sustainable biohydrogen production

Featuring high caloric value, clean-burning, and renewability, hydrogen is a fuel believed to be able to change energy structure worldwide. Biohydrogen production technologies effectively utilize waste biomass resources and produce high-purity hydrogen. Improvements have been made in the biohydrogen production process in recent years. However, there is a lack of operational data and sustainability analysis from pilot plants to provide a reference for commercial operations. In this report, based on spectrum coupling, thermal effect, and multiphase flow properties of hydrogen production, continuous pilot-scale biohydrogen production systems (dark and photo-fermentation) are established as a research subject. Then, pilot-scale hydrogen production systems are assessed in terms of sustainability. The system being evaluated, consumes 171,530 MJ of energy and emits 9.37 t of CO2 eq when producing 1 t H2, and has a payback period of 6.86 years. Our analysis also suggests future pathways towards effective biohydrogen production technology development and real-world implementation.

A deep learning framework for quality control process in the motor oil industry

Given the advancements in the modern world, using Multivariate-Multistage Quality Control (MVMSQC) patterns in continuous production industries is deemed crucial and essential. This study examines the importance and necessity of Multivariate-Multistage Quality Control in manufacturing industries, focusing on motor oil production. Motor oil quality significantly influences engine performance. Thus, the primary objective of this research is to enhance accuracy in detecting faults in quality variables, utilizing deep learning algorithms for visual quality control of data, a facet often overlooked in classical statistical methods and reducing process control time. Combining deep learning algorithms such as Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN) for controlling numerical variables, and Residual Networks (ResNet) and Dense Convolutional Networks (DenseNet) for controlling image variables have been employed. Additionally, the Honey Bee Mating Optimization Algorithm (GBC) has been utilized to tune the parameters of the LSTM-CNN and ResNet-DenseNet deep learning algorithms. Combining heuristic algorithms and deep learning algorithms enhances the performance of the final models in quality control processes. A case study in the motor oil production industry is examined to demonstrate the real-world application of the proposed model. The proposed LSTM-CNN hybrid algorithm outperforms individual CNN and LSTM algorithms in fault detection, improving performance by 15% and 8%, respectively. Furthermore, in visual components, the proposed ResNet-DenseNet hybrid algorithm has shown higher accuracy than ResNet and DenseNet algorithms, improving performance by 10% and 15%, respectively. This research significantly contributes to developing Multivariate-Multistage Quality Control in manufacturing industries by employing deep learning methods. The primary aim is to identify faults in quality components and utilize deep learning algorithms for visual quality control of data, a facet often overlooked in classical statistical methods. The research significantly advances multivariate-multistage quality control in manufacturing industries by leveraging deep learning methods. It addresses detecting complex nonlinear patterns in large-scale data with high flexibility and minimal time.

Hierarchical multiphase heterointerfaces Ni2P–CoP/MoO2 catalyst for efficient and stable hydrogen evolution reaction over the entire pH range

The development of pH-versatile, high-performing, and durable catalysts for hydrogen evolution reaction (HER) is crucial to satisfy the complex environment of water electrolysis industry. Herein, we present the synthesis of a hierarchical multiphase heterointerfaces Ni2P–CoP/MoO2 nanocatalyst with exceptionally high HER activity in the entire pH range through a facile three-step process involved hydrothermal, electrodeposition, and in situ phosphating treatment. Experiments and characterization revealed the strong electronic interactions among the phases of Ni2P, CoP, and MoO2, which endowed the Ni2P–CoP/MoO2 with high hydrogen evolution activity in different pH ranges. Meanwhile, the layered structure of our as-prepared catalyst makes the massive exposure of active sites. As a result, the Ni2P–CoP/MoO2 catalyst shows remarkable performance, requiring mere overpotentials of 33, 41, and 23 mV to drive 10 mA cm−2 in 1 M KOH, 1 M phosphate buffer solution, 0.5 M H2SO4, respectively. Moreover, the catalyst exhibits excellent stability in the chronopotentialmetry test under different pH electrolyte. Impressively, the Ni2P–CoP/MoO2 catalyst coupled with Ni–Fe LDH to form an overall water splitting system only require 1.50 V to drive 10 mA cm−2. Furthermore, this system actuated by wind and solar energy can stably undergo a continuous production of hydrogen and oxygen.

NMR in Battery Anode Slurries with a V-Shaped Sensor

Inline analytics in industrial processes reduce operating costs and production rejection. Dedicated sensors enable inline process monitoring and control tailored to the application of interest. Nuclear Magnetic Resonance is a well-known analytical technique but needs adapting for low-cost, reliable and robust process monitoring. A V-shaped low-field NMR sensor was developed for inline process monitoring and allows non-destructive and non-invasive measurements of materials, for example in a pipe. In this paper, the industrial application is specifically devoted to the quality control of anode slurries in battery production. The characterization of anode slurries was performed with the sensor to determine chemical composition and detect gas inclusions. Additionally, flow properties play an important role in continuous production processes. Therefore, the in- and outflow effects were investigated with the V-shaped NMR sensor as a basis for the future determination of slurry flow fields.

Optimization of Matrix Components for Improved Catalytic Activities of Cellulase Immobilized on Biochar-Chitosan Beads

Bioethanol is a renewable energy that is gaining popularity globally. It’s biochemical production requires the use of enzyme, especially cellulase. Cellulase is an enzyme that catalyzes the degradation of cellulose and related polysaccharides which finds applications in food, textiles, detergents, biofuels etc. However, the worldwide use of cellulase is limited by its relatively high production costs and low biological activity. This study was design to locally produce biochar-chitosan beads at optimized conditions to immobilize cellulase for improved thermal and storage stability as well as ensure reusability of the enzyme so as to improve biological activity and avoid the continuous production of free cellulase thereby reducing the production cost. Biochar was produced by pyrolyzing sugarcane bagasse in a local airtight chamber for 1 hour. Beads were formed from different ratios of biochar and chitosan in varying concentrations of calcium chloride solution as generated by design expert software version 13. The beads were dried in an oven at 50 0C for 24 hours and functionalized in 25% glutaraldehyde (GDA). The beads were loaded with enzyme (10.06 µmole/min/mL) at room temperature (27 ± 3 oC). Enzyme activity, thermal stability, storage stability and reusability tests were carried out according to standard procedures. The half-life and activation energy were also evaluated. The result showed that the optimum activity of the loaded enzyme (2.63 µmole/min/mL) was obtained when 2.46 g of porous biochar was mixed with 2.48 g chitosan in 5 % Calcium chloride aqueous solution. The immobilized enzyme was able to maintain thermal stability between 30 oC and 70 oC while the activity for free enzyme started declining after 50 oC. Also, the activation energy for immobilized cellulase enzyme (23.17 KJ/mol) was lower than the activation energy (55.146 KJ/mol) for free cellulase. The half-life, when stored at ambient Temperature (27 ± 3 oC), for free enzyme was 0.4 days while the half-life for immobilized enzyme was 3.59 days. Therefore, cellulase immobilized on support locally produced at optimal conditions had improved catalytic properties when compared to the free enzyme. Hence, more indigenous materials and practices may be employed for a cost effective and cheaper industrial processes.

Facile synthesis of dense SiBCN coatings with excellent compactness, smoothness, and high-temperature inertness on defective graphite surfaces

SiBCN ceramics possess extreme high-temperature stability among engineering ceramics; however, their application is constrained by the difficulty in achieving large continuous products at low cost. This work exhibits the possibility of fabricating SiBCN continuous coatings on graphite substrates to improve their surface integrity, hardness, and inertness. The ceramic coatings were fabricated simply by spin coating, curing, and pyrolysis. The key innovations are the synthesis of the precursor, polyborosilazane (PBSZ), that derives continuous ceramic films after pyrolysis, and the finding that the xylene solution of PBSZ can achieve a very good spinning performance on various surfaces, especially the low-quality graphite surfaces with holes. The fabricated SiBCN coatings, characterized to be networks of Si–C, Si–N, C–C, and B–N bonds, possessed smooth and hard surfaces with roughness below 9 nm and a hardness of 7.3 GPa. The coating thickness can be well controlled in the range of 1.4 – 2.1 μm as the latter is linearly dependent on the concentration of PBSZ in the solution. Detailed observations of surface morphologies and physisorption experiments reveal that the coating surfaces are crack-free and highly dense, rendering a significant reduction in specific surface areas when a defective graphite face is coated.

Socio-environmental Opportunities for Organic Material Management in California's Sustainability Transition.

Contemporary resource management is doubly burdened by high rates of organic material disposal in landfills, generating potent greenhouse gases (GHG), and globally degraded soils, which threaten future food security. Expansion of composting can provide a resilient alternative, by avoiding landfill GHG emissions, returning valuable nutrients to the soil to ensure continued agricultural production, and sequestering carbon while supporting local communities. Recognizing this opportunity, California has set ambitious organics diversion targets in the Short-Lived Climate Pollutant Law (SB1383) which will require significant increases (5 to 8 million tonnes per year) in organic material processing capacity. This paper develops a spatial optimization model to consider how to handle this flow of additional material while achieving myriad social and ecological benefits through compost production. We consider community-based and on-farm facilities alongside centralized, large-scale infrastructure to explore decentralized and diversified alternative futures of composting infrastructure in the state of California. We find using a diversity of facilities would provide opportunity for cost savings while achieving significant emissions reductions of approximately 3.4 ± 1 MMT CO2e and demonstrate that it is possible to incorporate community protection into compost infrastructure planning while meeting economic and environmental objectives.

Influence of the Parameters of an Agricultural Biogas Plant on the Amount of Power Generated

Energy from biogas is widely available, inexpensive, and often contributes to waste management, making it one of the most promising renewable energy sources. The main factors influencing this process’ efficiency include the substrates’ chemical composition, temperature, and digester load. This paper presents the possibilities offered by a biogas plant built at a farm specialising in dairy cows. The dependence of the power generated in the micro biogas plant on its technical parameters was analysed in detail. Studies carried out by the authors in an agricultural microgas plant (with an electrical output of 40 kW) have shown that they are designed to maintain continuous energy production, despite changing process parameters such as digester mass level, biogas height, temperature or slurry flow into the digester. However, from the point of view of the amount of electricity generated, changes would have to be made to the design of the biogas plant. Firstly, a more powerful generator would have to be installed to cover the electricity requirements of the equipment installed in the biogas plant so that power close to the rated capacity of the biogas plant is still sent to the grid. Secondly, replacing the two existing agitators of the digestion mass (9 kW each) with more agitators of lower power (e.g., four agitators of 4.5 kW each) would be necessary. These should be programmed so that one of the agitators operates at any given time (the operating time of a given agitator should depend on the composition of the digestate).

Optimization of Renewable Energy Hydrogen Production Systems Using Volatility Improved Multi-Objective Particle Swarm Algorithm

Optimizing the energy structure to effectively enhance the integration level of renewable energy is an important pathway for achieving dual carbon goals. This study utilizes an improved multi-objective particle swarm optimization algorithm based on load fluctuation rates to optimize the architecture and unit capacity of hydrogen production systems. It investigates the optimal configuration methods for the architectural model of new energy hydrogen production systems in Xining City, Qinghai Province, as well as the internal storage battery, ALK hydrogen production equipment, and PEM hydrogen production equipment, aiming at various scenarios of power sources such as wind, solar, wind–solar complementary, and wind–solar–storage complementary, as well as intermittent hydrogen production scenarios such as hydrogen stations, hydrogen metallurgy, and continuous hydrogen production scenarios such as hydrogen methanol production. The results indicate that the fluctuation of hydrogen load scenarios has a significant impact on the installed capacity and initial investment of the system. Compared with the single-channel photovoltaic hydrogen production scheme, the dual-channel hydrogen production scheme still reduces equipment capacity by 6.04% and initial investment by 6.16% in the chemical hydrogen scenario with the least load fluctuation.

Production of β-cyclodextrin by immobilized CGTase in packed bed bioreactor through the medium component by employing Taguchi methodology

This study investigates the optimization of submerged culture conditions for the production of extracellular cyclodextrin glucanotransferase (CGTase) enzyme by Bacillus macerans ATCC 8244, employing Taguchi orthogonal array (OA) experimental design methodology. Five critical factors - starch, peptone, temperature, pH, and agitation speed - were examined at two levels using an OA layout of L8 for the experimental design. Analysis revealed a significant enhancement in CGTase yield, with the modified culture conditions resulting in a 21.2% increase from 513.416 U/ml to 622.5 U/ml. The successful application of Taguchi's design methodology underscores its efficacy in optimizing enzyme production processes. This study highlights Taguchi's design potential as a valuable tool for improving CGTase production efficiency while minimizing resource consumption. Additionally, the utilization of a packed bed bioreactor (PBR) facilitated continuous production of β-cyclodextrin (β-CD), demonstrating stability over 10 days with only a slight decrease in productivity. The Km,app value was determined to be 23.4 mg starch/ml, indicating a slight increase.

Artificial Neural Network Modeling in the Presence of Uncertainty for Predicting Hydrogenation Degree in Continuous Nitrile Butadiene Rubber Processing

The transition from batch to continuous production in the catalytic hydrogenation of nitrile butadiene rubber (NBR) into hydrogenated NBR (HNBR) marks a significant advance for applications under demanding conditions. This study introduces a continuous process utilizing a static mixer (SM) reactor, which notably achieves a hydrogenation conversion rate exceeding 97%. We thoroughly review a mechanistic model of the SM reactor to elucidate the internal dynamics governing the hydrogenation process and address the inherent uncertainties in key parameters such as the Peclet number (Pe), dimensionless time (θτ), reaction coefficient (R), and flow rate coefficient (q). A comprehensive dataset generated from varied parameter values serves as the basis for training an artificial neural network (ANN), which is then compared against traditional models including linear regression, decision tree, and random forest in terms of efficacy. Our results clearly demonstrate the ANN’s superiority in predicting the degree of hydrogenation, achieving the lowest root mean squared error (RMSE) of 3.69 compared to 21.90 for linear regression, 4.94 for decision tree, and 7.51 for random forest. The ANN’s robust capability for modeling complex nonlinear relationships and dynamics significantly enhances decision-making, planning, and optimization of the reactor, reducing computational demands and operational costs. In other words, this approach allows users to rely on a single ML-based model instead of multiple mechanistic models for reflecting the effects of possible uncertainties. Additionally, a feature importance study validates the critical impact of time and element number on the hydrogenation process, further supporting the ANN’s predictive accuracy. These findings underscore the potential of ML-based models in streamlining and enhancing the efficiency of chemical production processes.

Magnesium implantation as a continuous hydrogen production generator for the treatment of myocardial infarction in rats

Molecular hydrogen is an emerging broad-spectrum antioxidant molecule that can be used to treat myocardial infarction (MI). However, with hydrogen inhalation, the concentration that can be reached within target organs is low and the duration of action is short, which makes it difficult to achieve high dose targeted delivery of hydrogen to the heart, seriously limiting the therapeutic potential of hydrogen for MI. As a result of reactions with the internal environment of the body, subcutaneous implantation of magnesium slices leads to continuous endogenous hydrogen production, leading to a higher hydrogen concentration and a longer duration of action in target organs. In this study, we propose magnesium implant-based hydrogen therapy for MI. After subcutaneous implantation of magnesium slices in the dorsum of rats, we measured hydrogen production and efficiency, and evaluated the safety of this approach. Compared with hydrogen inhalation, it significantly improved cardiac function in rats with MI. Magnesium implantation also cleared free radicals that were released as a result of mitochondrial dysfunction, as well as suppressing cardiomyocyte apoptosis.

Marine Prostanoids with Cytotoxic Activity from Octocoral Clavularia spp.

Octocoral of the genus Clavularia is a kind of marine invertebrate possessing abundant cytotoxic secondary metabolites, such as prostanoids and dolabellanes. In our continuous natural product study of C. spp., two previously undescribed prostanoids [clavulone I-15-one (1) and 12-O-deacetylclavulone I (2)] and eleven known analogs (3-13) were identified. The structures of these new compounds were elucidated based on analysis of their 1D and 2D NMR, HRESIMS, and IR data. Additionally, all tested prostanoids (1 and 3-13) showed potent cytotoxic activities against the human oral cancer cell line (Ca9-22). The major compound 3 showed cytotoxic activity against the Ca9-22 cells with the IC50 value of 2.11 ± 0.03 μg/mL, which echoes the cytotoxic effect of the coral extract. In addition, in silico tools were used to predict the possible effects of isolated compounds on human tumor cell lines and nitric oxide production, as well as the pharmacological potentials.

Cu-Mo Dual Sites in Cu-Doped MoSe2 for Enhanced Electrosynthesis of Urea.

The quest for sustainable urea production has directed attention toward electrocatalytic methods that bypass the energy-intensive traditional Haber-Bosch process. This study introduces an approach to urea synthesis through the coreduction of CO2 and NO3- using copper-doped molybdenum diselenide (Cu-MoSe2) with Cu-Mo dual sites as electrocatalysts. The electrocatalytic activity of the Cu-MoSe2 electrode is characterized by a urea yield rate of 1235 μg h-1 mgcat.-1 at -0.7 V versus the reversible hydrogen electrode and a maximum Faradaic efficiency of 23.43% at -0.6 V versus RHE. Besides, a continuous urea production with an enhanced average yield rate of 9145 μg h-1 mgcat.-1 can be achieved in a flow cell. These figures represent a substantial advancement over that of the baseline MoSe2 electrode. Density functional theory (DFT) calculations elucidate that Cu doping accelerates *NO2 deoxygenation and significantly decreases the energy barriers for C-N bond formation. Consequently, Cu-MoSe2 demonstrates a more favorable pathway for urea production, enhancing both the efficiency and feasibility of the process. This study offers valuable insights into electrode design and understanding of the facilitated electrochemical pathways.

Advances in Microfluidic-Based Core@Shell Nanoparticles Fabrication for Cancer Applications.

Current research in cancer therapy focuses on personalized therapies, through nanotechnology-based targeted drug delivery systems. Particularly, controlled drug release with nanoparticles (NPs) can be designed to safely transport various active agents, optimizing delivery to specific organs and tumors, minimizing side effects. The use of microfluidics (MFs) in this field has stood out against conventional methods by allowing precise control over parameters like size, structure, composition, and mechanical/biological properties of nanoscale carriers. This review compiles applications of microfluidics in the production of core-shell NPs (CSNPs) for cancer therapy, discussing the versatility inherent in various microchannel and/or micromixer setups and showcasing how these setups can be utilized individually or in combination, as well as how this technology allows the development of new advances in more efficient and controlled fabrication of core-shell nanoformulations. Recent biological studies have achieved an effective, safe, and controlled delivery of otherwise unreliable encapsulants such as small interfering RNA (siRNA), plasmid DNA (pDNA), and cisplatin as a result of precisely tuned fabrication of nanocarriers, showing that this technology is paving the way for innovative strategies in cancer therapy nanofabrication, characterized by continuous production and high reproducibility. Finally, this review analyzes the technical, biological, and technological limitations that currently prevent this technology from becoming the standard.

Scalable Customization of Crystallographic Plane Controllable Lithium Metal Anodes for Ultralong-Lasting Lithium Metal Batteries.

A formidable challenge to achieve the practical applications of rechargeable lithium (Li) metal batteries (RLMBs) is to suppress the uncontrollable growth of Li dendrites. One of the most effective solutions is to fabricate Li metal anodes with specific crystal plane, but still lack of a simple and high-efficient approach. Herein, a facile and controllable way for the scalable customization of polished Li metal anodes with highly preferred (110) and (200) crystallographic orientation (donating as polished Li(110) and polished Li(200), respectively) by regulating the times of accumulative roll bonding, is reported. According to the inherent characteristics of polished Li(110)/Li(200), the influence of Li atomic structure on the electrochemical performance of RLMBs is deeply elucidated by combining theoretical calculations with relative experimental proofs. In particular, a polished Li(110) crystal plane is demonstrated to induce Li+ uniform deposition, promoting the formation of flat and dense Li deposits. Impressively, the polished Li(110)||LiFePO4 full cells exhibit unprecedented cycling stability with 10000 cycles at 10 C almost without capacity degradation, indicating the great potential application prospect of such textured Li metal. More valuably, this work provides an important reference for low-cost, continued, and large-scale production of Li metal anodes with highly preferred crystal orientation through roll-to-roll manufacturability.

A novel development of a new single switch inductor coupled DC-DC converter for PV system with two-leg inverter

From the power generation history, the nonrenewable power sources utilization is falling extremely because of their demerits are high atmospheric pollution, more expensive, more catchment area for development, high fossil fuel transportation cost, less flexibility, and reliability. So, the sunlight systems are utilized in this work for feeding the power to the central grid. On the earth, the sunlight energy availability is more and it is more flexible for the installation. However, the sunlight photovoltaic (PV) module’s power production is very low. To improve the power generation of the PV network, a modified slider maximum power point tracking (MPPT) controller is proposed in the first objective and it is interfaced with the sunlight system for capturing more sunlight insolation thereby moving the functioning point of the solar system from local MPP place to required global MPP place. The features of this sliding controller are continuous peak power production, easy development, less power dissipation losses, plus good dynamic system response. In the second objective, the available voltage of the PV is low which improved from low level to high level by utilizing the Wide voltage supply-inductor coupled converter. The development of this circuit needed very less inductive, plus capacitive components. Also, it is developed by selecting a single switch. As a result, the entire network power production cost is reduced. In the third objective, a two-leg inverter is proposed for the transformation of the DC voltage supply into three-phase powers. The MATLAB/Simulink tool is used to investigate the overall system.

Wall-Immobilized Biocatalyst vs. Packed Bed in Miniaturized Continuous Reactors: Performances and Scale-Up.

Sustainable biocatalysis syntheses have gained considerable popularity over the years. However, further optimizations - notably to reduce costs - are required if the methods are to be successfully deployed in a range of areas. As part of this drive, various enzyme immobilization strategies have been studied, alongside process intensification from batch to continuous production. The flow bioreactor portfolio mainly ranges between packed bed reactors and wall-immobilized enzyme miniaturized reactors. Because of their simplicity, packed bed reactors are the most frequently encountered at lab-scale. However, at industrial scale, the growing pressure drop induced by the increase in equipment size hampers their implementation for some applications. Wall-immobilized miniaturized reactors require less pumping power, but a new problem arises due to their reduced enzyme-loading capacity. This review starts with a presentation of the current technology portfolio and a reminder of the metrics to be applied with flow bioreactors. Then, a benchmarking of the most recent relevant works is presented. The scale-up perspectives of the various options are presented in detail, highlighting key features of industrial requirements. One of the main objectives of this review is to clarify the strategies on which future study should center to maximize the performance of wall-immobilized enzyme reactors.