Optimal Operation Research Articles

Research on cooperative operation optimization method of internet data center alliance considering diversified flexibility

With the rapid development of large-scale internet data center in China, the goal of carbon peak and carbon neutrality has put forward higher requirements for low-carbon economic operation of internet data center. Considering complementary advantages among internet data centers, this paper proposes a cooperative operation optimization method of internet data center alliance based on diversified flexibility. Firstly, a cooperative operation structure of alliance considering electricity and carbon trading between members was built, as well as the diversified flexibility model considering carbon capture and power to gas device. Then, a cooperative optimization operation model of alliance was constructed based on Nash bargaining theory, and the allocation of cooperation benefit among members can be realized based on electrical carbon contribution rate. In order to improve solution convergence, the alternating direction multiplier method is improved by penalty factor updating and correction factor modeling method. Finally, the proposed method is applied to the demonstration project of “East Data and West Computing” in Qingyang, Gansu, China, and the trial run results are consistent with the theory analysis. On the one hand, the diversified flexibility and the electricity and carbon trading between members can effectively reduce the total cost and carbon emissions of alliance. On the other hand, the cooperation benefits distribution strategy based on the electrical carbon contribution rate can effectively enhance enthusiasm of members to participate in alliance. The improved alternating direction multiplier method can achieve distributed optimization of alliance, protect the privacy of each member, and has good convergence and scalability.

Selective electrosorption of heavy metal ions from wastewater with S-doped hierarchical porous carbon derived from waste Camellia oleifera shell

Capacitive deionization (CDI) has garnered significant attention in desalination and the removal of heavy metal ions. The quest for cost-effective and high-performance electrode materials is crucial to advance CDI applications. Herein, we report a sulfur-doped hierarchical porous carbon (SPC) derived from waste camellia oleifera shells via a sustainable hydrothermal carbonization process followed by KOH/ammonium salt activation. The optimized SPC-0.2 exhibits exceptional characteristics, featuring a high specific surface area of 1875 m2 g−1 and substantial sulfur doping at 8.65 %, leading to enhanced specific capacitance (161.3 F g−1) in a 1 M NaCl solution. Under optimal operating conditions (1.2 V, 10 mL min−1, 500 mg L−1 NaCl), the SPC-0.2 electrode achieves a notable desalination capacity of 26.64 mg g−1. In particular, the electrode can selectively remove >99 % of Cr3+ and Cu2+ ions (each 10 mg L−1) in a 100 mg L−1 NaCl solution. This high selectivity is attributed to the formation of sulfides via low adsorption energies between the doped sulfur atoms and the targeted heavy metal ions. Furthermore, the SPC-0.2 electrode demonstrates robust reusability and high efficiency in the actual water body. Collectively, our findings underscore the significant potential of the synthesized SPC as an electrode material for CDI, particularly in the selective capacitive removal of heavy metal ions from wastewater. This work not only contributes to the circular economy by using waste biomass, but also offers a viable solution for environmental remediation.

Ultrasensitive xylene sensor based on RuO2-modified BiVO4 nanosheets

Two-dimensional (2D) BiVO4 nanosheets (NSs), featuring distinctive chemical properties and dangling-bond-rich surfaces, are promising for developing high-performance gas sensors. However, the previously reported 2D BiVO4 NSs-based devices suffer from a low responsivity and poor selectivity. In this work, we introduce RuO2 nanoparticles to boost the gas sensing properties of 2D BiVO4 NSs-based sensor. Intriguingly, the RuO2-decoration changes the selectivity of the corresponding gas sensor from acetone to xylene. Compared to the pristine BiVO4 sensor, the RuO2-BiVO4 sensor displays a reduced optimal operating temperature of 260℃ and exhibits a response of 19.0–5 ppm xylene, reaching a five-fold enhancement. Simultaneously, the RuO2-BiVO4 sensor also exhibits a rapid response and recovery time of 10 and 25 s respectively, as well as robust long-term stability with less than 5 % variation in response after a storage of 60 days. The improvement in sensing performance can be attributed to the RuO2-decoration from three aspects: heterojunction construction, surface state modulation and gas oxidation catalysis on the surface. This work not only provides a high-performance xylene sensing material but also provides insightful comprehension regarding the modification effects of RuO2.

Furloughing Employees with Uncertain Return? Management of Labor Frictions and Inventory Under Demand Shock

We assess how a retailer can manage inventories and labor under an extreme condition such as a temporary negative demand shock due to a pandemic or an economic turmoil. This analysis incorporates labor market frictions whereby firms incur deadweight costs associated with hiring and firing employees, as well as the option to furlough labor. We examine the impact of these frictions on a retail firm's optimal operating policies around inventory level, furlough, and layoffs. We find that labor market frictions condition the inventory and the level of employment in two ways. First, they lead to underinvestment in inventories, which limits recovery and employment in the postshock period. Second, high labor market frictions motivate the firm to conservatively downsize workforce during the negative demand period leading to higher employment, when compared to downsizing without friction. A significant contribution of our study lies in delineating the optimal furlough decisions and quantifying the impact of the furlough option on inventory and labor decisions. We demonstrate the conditions under which it is optimal for the retailer to either (i) fully downsize labor and leverage the furlough option in the labor market, or (ii) maintain excess labor while also opting to furlough a portion of the workforce. During an extreme event such as a temporary negative demand shock, our results highlight the need for a coordinated effort when implementing governmental subsidy policies on alleviating labor and inventory reductions by accounting for labor market frictions and furlough support.

Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm

In this paper, a new method is designed to effectively determine the parameters of proton exchange membrane fuel cells (PEMFCs), i.e., ξ1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\xi }_{1}$$\\end{document}, ξ2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\xi }_{2}$$\\end{document}, ξ3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\xi }_{3}$$\\end{document}, ξ4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\xi }_{4}$$\\end{document}, RC\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${R}_{\ ext{C}}$$\\end{document}, λ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\lambda$$\\end{document}, and b\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$b$$\\end{document}. The fuel cells (FCs) involve multiple variable quantities with complex non-linear behaviours, demanding accurate modelling to ensure optimal operation. An accurate model of these FCs is essential to evaluate their performance accurately. Furthermore, the design of the FCs significantly impacts simulation studies, which are crucial for various technological applications. This study proposed an improved parameter estimation procedure for PEMFCs by using the GOOSE algorithm, which was inspired by the adaptive behaviours found in geese during their relaxing and foraging times. The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. In order to validate the proposed algorithm, a number of experiments using various datasets were conducted and compared the outcomes with different state-of-the-art algorithms. The outcomes indicate that the proposed GOOSE algorithm not only produced promising results but also exhibited superior performance in comparison to other similar algorithms. This approach demonstrates the ability of the GOOSE algorithm to simulate complex systems and enhances the robustness and adaptability of the simulation tool by integrating essential behaviours into the computational framework. The proposed strategy facilitates the development of more accurate and effective advancements in the utilization of FCs.

Enhancing tensile properties of polymer‐based triply periodic minimal surface metamaterial structures: Investigating the impact of post‐curing time and layer thickness via response surface methodology

AbstractThis research aims to explore the influence of post‐curing time and layer thickness on the tensile characteristics of various triply periodic minimal surface (TPMS) structures produced by mask stereolithography (MSLA). The study determined the best post‐curing duration, layer thickness, and TPMS lattice type to improve ultimate tensile strength (UTS) and absorbed energy. To experimentally evaluate the tensile characteristics, a dog bone‐shaped specimen was utilized. Three distinct TPMS structures, Gyroid (G), Neovius (N), and Diamond (D), were present in the test region. After investigating many process factors with response surface methodology (RSM), optimization methods are applied to find their best printing procedure. The work shows the novel use of RSM to optimize post‐curing and printing parameters on TPMS structure mechanical properties during manufacturing. According to the optimization results, the biggest factor affecting UTS is layer thickness, while the most significant factor increasing energy is curing time. The optimal operating parameters for MSLA printing based on the optimization results are a layer thickness of 0.05 mm, a post‐curing period of 40 min, and a lattice type of N. The optimum responses corresponding to the optimum parameters were determined as 7.16 MPa for UTS and 18.16 J for energy.Highlights Optimized the production process parameters of TPMS geometries. Compared TPMS structures for mechanical performance. Identified optimal input parameters to improve UTS and energy absorption. Conducted comprehensive experimental evaluations to validate the optimization.

Benchmarking in data envelopment analysis: balanced efforts to achieve realistic targets

AbstractThe minimum distance models have undoubtedly represented a significant advance for the establishment of targets in Data Envelopment Analysis (DEA). These models may help in defining improvement plans that require the least overall effort from the inefficient Decision Making Units (DMUs). Despite the advantages that come with Closest Targets, in some cases unsatisfactory results may be given, since improvement plans, even in that context, differ considerably from the actual performances. This generally occurs because all the effort employed to reach the efficient DEA frontier is channeled into just a few variables. In certain contexts these exorbitant efforts in some inputs/outputs become unapproachable. In fact, proposals for sequential improvement plans can be found in the literature. It could happen that the sequential improvement plans continue to be so demanding in some variable that it would be difficult to achieve such targets. We propose an alternative approach where the improvement plans require similar efforts in the different variables that participate in the analysis. In the absence of information about the limitations of improvement in the different inputs/outputs, we consider that a plausible and conservative solution would be the one where an equitable redistribution of efforts would be possible. In this paper, we propose different approaches with the aim of reaching an impartial distribution of efforts to achieve optimal operating levels without neglecting the overall effort required. Therefore, we offer different alternatives for planning improvements directed towards DEA efficient targets, where the decision-maker can choose the one that best suits their circumstances. Moreover, and as something new in the benchmarking DEA context, we will study which properties satisfy the targets generated by the different models proposed. Finally, an empirical example used in the literature serves to illustrate the methodology proposed.

Examination of nonideal film growth in batch atomic layer deposition for plasma-resistant coatings

Atomic layer deposition (ALD) can be used to fabricate protective coatings including moisture barrier layers for organic light emitting diodes, anticorrosion layers for photoelectrodes, and plasma-resistant coating for semiconductor manufacturing equipment, which necessitates the deposition of large and thick ALD films via batch ALD. However, batch ALD for the fabrication of large-area and thick coatings exhibits nonideal film growth, a phenomenon that cannot solely be explained by transient concentration distribution within the deposition chamber. This paper describes the application of precursor “exposure” (in the unit of Langmuir, or Pa s), defined as the integral of concentration over time, as a metric to assess the growth per cycle (GPC) distribution under nonideal ALD conditions, demonstrating that the local GPC correlates well with the cumulative precursor exposure at that site. Consequently, this measure can effectively predict the nonuniformity (NU) distribution of film thickness and facilitate the determination of optimal operating conditions that ensure maximal uniformity of exposure. Under this condition, the intrafilm NU of ALD-grown Al2O3 film (nominal thickness 300 nm) was reduced to 1.2%, and the interfilm NU is diminished to as low as 3.3%. These values represent reductions of 40% and 45%, respectively, compared to the NU levels observed under nonideal conditions (insufficient trimethylaluminum, TMA exposure downstream). The plasma etch rate of ALD-deposited films is merely 4.3 nm/min, representing a reduction of one-half compared to films deposited under nonideal conditions (9.8 nm/min) with overload TMA exposure downstream leading to chemical vapor deposition-like reactions.

Optoelectronics Interfaces for a VLC System for UHD Audio-Visual Content Transmission in a Passenger Van: HW Design.

This work aims to provide the hardware (HW) design of the optoelectronics interfaces for a visible-light communication (VLC) system that can be employed for several use cases. Potential applications include the transmission of ultra-high-definition (UHD) streaming video through existing reading lamps installed in passenger vans. In this use case, visible light is employed for the downlink, while infrared light is used for the uplink channel, acting as a remote controller. Two primary components -a Light Fidelity (LiFi) router and a USB dongle-were designed and implemented. The 'LiFi Router', handling the downlink channel, comprises components such as a visible Light-Emitting Diode (LED) and an infrared receiver. Operating at a supply voltage of 12 V and consuming current at 920 mA, it is compatible with standard voltage buses found in transport vehicles. The 'USB dongle', responsible for the uplink, incorporates an infrared LED and a receiver optimized for visible light. The USB dongle works at a supply voltage of 5 V and shows a current consumption of 1.12 A, making it well suited for direct connection to a universal serial bus (USB) port. The bandwidth achieved for the downlink is 11.66 MHz, while the uplink's bandwidth is 12.27 MHz. A system competent at streaming UHD video with the feature of being single-input multiple-output (SIMO) was successfully implemented via the custom hardware design of the optical transceivers and optoelectronics interfaces. To ensure the system's correct performance at a distance of 110 cm, the minimum signal-to-noise ratio (SNRmin) for both optical links was maintained at 10.74 dB. We conducted a proof-of-concept test of the VLC system in a passenger van and verified its optimal operation, effectively illustrating its performance in a real operating environment. Exemplifying potential implementations possible with the hardware system designed in this work, a bit rate of 15.2 Mbps was reached with On-Off Keying (OOK), and 11.25 Mbps was obtained with Quadrature Phase Shift Keying (QPSK) using Orthogonal Frequency-Division Multiplexing (OFDM) obtaining a bit-error rate (BER) of 3.3259 × 10-5 in a passenger van at a distance of 72.5 cm between the LiFi router and the USB dongle. As a final addition, a solar panel was installed on the passenger van's roof to power the user's laptop and the USB dongle via a power bank battery. It took 13.4 h to charge the battery, yielding a battery life of 22.3 h. This characteristic renders the user's side of the system entirely self-powered.

User-needs-oriented shared DC charging resources optimal configuration and operation for improving EV penetration in old residential communities

The charging limitation of electric vehicles (EVs) in old residential communities (ORCs) derived from insufficient electricity capacity and parking spaces significantly impacts residents' quality of life and impedes urban sustainability. Considering economic and social factors, ORCs are likely to persist worldwide for the foreseeable future. To tackle these challenges, this paper proposes the scheme of shared DC fast charging stations to address the EV charging issues in ORCs. Specific methods involve minimizing the charging station spaces and charging infrastructure investment, while optimizing the photovoltaic (PV) and energy storage capacity. Additionally, a coordinated charging strategy based on dynamic price is designed to guide users in choosing the initial charging time, enhancing EV charging infrastructure utilization and EV penetration. This work is predominantly driven by human needs, integrating surveys on human behavior related to charging station locations and charging times. This case study is based on a real-life ORC in Shenzhen, China. By utilizing the proposed dynamic-pricing coordinated charging strategy tailored to the station capacity, the maximum EV penetration rate is to be achieved with satisfying EV charging demand. Furthermore, the implementation of dynamic pricing effectively guides users to adjust charging behavior, achieving the peak-shaving and valley-filling performance of load curves.

Integrated deep eutectic solvent extraction and resin adsorption for recovering polyphenols from citrus reticulata Blanco peels: Process optimization, compositional analysis, and activity determination

The recovery of polyphenols from Citrus reticulata Blanco peels was studied based on integrated deep eutectic solvent (DES) extraction and resin adsorption. The DES prepared with choline chloride and ethylene glycol (molar ratio 1:4) and hydrophobic interaction/weakly acidic cation exchange mixed-mode adsorption resin HD-1 were used as the extractant and adsorbent respectively. The operating parameters of integrated process were optimized using completely randomized design and response surface methodology (RSM). The extraction kinetics was studied and the composition of extract was analyzed by UPLC-MS. Finally, the antioxidant activity of extract and its inhibitory ability on α-glucosidase and α-amylase were determined. Under the optimal operating conditions (liquid–solid ratio of 20:1, extraction temperature of 43 °C, extraction time of 4.8 h, resin amount of 6.6 g), the polyphenols yield of integrated process was increased by 2.15-fold and the time was shortened by 52.48 % compared with that of traditional sequential process. The extraction kinetic curves of both integrated and sequential processes conformed to pseudo-first-order kinetic model, and the extraction speed of integrated process was significantly higher than that of sequential process. The main polyphenols in extract were neohesperidoside, poncirin, narirutin, and hesperidin, etc. The extract exhibited a strong antioxidant capacity with DPPH free radical scavenging rate of extract reached 79.54 % of that of vitamin C. The inhibition ratios of extract against α-glucosidase and α-amylase were 97.81 % and 427 % of that of acarbose respectively. The results indicated that the extract has a potential application for prevention and control of type 2 diabetes mellitus.

Bayesian optimization for quick determination of operating variables of simulated moving bed chromatography

The Simulated Moving Bed (SMB) is a continuous chromatographic separation process that operates on the principle of counter-current movement between the solid and liquid phases. Due to periodic switching of feed and product ports across numerous connected columns, adjusting SMB operating variables such as feed and product flow rates and switching time to achieve desired separations is challenging. While equilibrium theory can help narrow the search space, obtaining essential information such as accurate adsorption isotherms is crucial. This requirement, combined with often highly stringent production specifications, makes it challenging to identify even a feasible operating condition, let alone an optimal one. Trial-and-error-based approaches are often impractical as reaching cyclic steady state can be time-consuming, and any waste produced during this period can lead to significant economic losses. While rigorous dynamic models are available, they are computationally intensive and often do not accurately mirror actual process behavior. To address these challenges, the use of Bayesian Optimization (BO) is proposed to sequentially approach optimal SMB operation. Furthermore, it is suggested to employ the simpler True Moving Bed (TMB) model as a prior for the BO, which significantly accelerates convergence. This approach is demonstrated on an SMB process for cresol separation. Initially, the effectiveness of the BO using the TMB model is examined to gain insights into its behavior. Subsequently, we apply BO to the rigorous SMB model, informed by prior knowledge from the TMB model. Our results show that the developed BO framework rapidly converges to the optimal operating parameters that satisfy the purity constraints. We examine the efficiency improvements over various search algorithms and highlight the advantages of using the TMB model as a prior.

Biodegradation and Detoxification of Some Dyes by Crude Lignin Peroxidase Complex Produced by Escherichia coli Accession No: LR0250096.1 and Pseudomonas aeruginosa Accession No: CP031449.2

Synthetic and untreated dyes discharged in wastewater effluents are a threat to an ecosystem. This study investigated dye degradation and detoxification efficiency of crude lignin peroxidase separately obtained from the cultures of Escherichia coli (LR0250096.1) and Pseudomonas aeruginosa (CP031449.2). The ability of the crude lignin peroxidase to degrade Malachite Green (MG), Remazol Brilliant Blue R (RBBR), Congo Red (CR), and Azure B (AZ) was evaluated at different operating conditions (enzyme, dye, and hydrogen peroxide concentrations; pH; temperature; and contact time). The ability of the degraded dyes to support the growth of bacteria was also investigated. The observed optimum operating conditions for lignin peroxidase extracts of the Escherichia coli on AZ were 20 mg/mL enzyme concentration, 50 mg/L dye, pH 7.0, temperature 50 °C, and 1.5 mM hydrogen peroxide within 20–50 min of incubation time and on MG were 20 mg/mL, 50 mg/L, 9.0, 30 °C, 0.1 mM, and 20 min, respectively. The enzyme extract from Pseudomonas aeruginosa on AZ demonstrated optimum operation conditions of 20 mg/mL, 50 mg/L, pH 9.0, 40 °C, 1.5 mM, and 50 min, respectively and on MG, they were 20 mg/mL, 50 mg/L, 6.0, 30 °C, 1.0 mM, and 20 min, respectively). The prepared enzyme showed an appreciable degradative effect on CR and RBBR compared with commercial lignin peroxidase. The degraded dyes were able to support the growth of two Gram-positive (Bacillus cereus and Staphylococcus aureus), and two Gram-negative (Proteus mirabilis and Escherichia coli) bacteria, indicating the efficiency and the potential use of the enzyme complexes in the clean-up of industrial dyes’ waste.

Two-Stage Robust Optimization of Integrated Energy Systems Considering Uncertainty in Carbon Source Load

Integrated Energy Systems (IESs) interconnect various energy networks to achieve coordinated planning and optimized operation among heterogeneous energy subsystems, making them a hot topic in current energy research. However, with the high integration of renewable energy sources, their fluctuation characteristics introduce uncertainties to the entire system, including the corresponding indirect carbon emissions from electricity. To address these issues, this paper constructs a two-stage, three-layer robust optimization operation model for IESs from day-ahead to intra-day. The model analyzes the uncertainties in carbon emission intensity at grid-connected nodes, as well as the uncertainty characteristics of photovoltaic, wind turbine, and cooling, heating, and electricity loads, expressed using polyhedral uncertainty sets. It standardizes the modeling of internal equipment in the IES, introduces carbon emission trading mechanisms, and constructs a low-carbon economic model, transforming the objective function and constraints into a compact form. The column-and-constraint generation algorithm is applied to transform the three-layer model into a single-layer main problem and a two-layer subproblem for iterative solution. The Karush–Kuhn–Tucker (KKT) condition is used to convert the two-layer subproblem into a linear programming model. A case study conducted on a park shows that while the introduction of uncertainty optimization increases system costs and carbon emissions compared to deterministic optimization, the scheduling strategy is more stable, significantly reducing the impact of uncertainties on the system. Moreover, the proposed strategy reduces total costs by 5.03% and carbon emissions by 1.25% compared to scenarios considering only source load uncertainty, fully verifying that the proposed method improves the economic and low-carbon performance of the system.

FEATURES FOR OPTIMISING THE PROPERTIES OF COMPOSITE MATERIALS BASED ON ACRYLIC MONOMERS

Further development of research in the field of acrylic composites is aimed at creating modifiers with specified properties that will improve the characteristics of composites in specific application conditions; developing optimal ratios of composite components to ensure the required properties; developing universal mathematical models that will predict the properties of composites depending on the composition and curing conditions; searching for new applications for acrylic composites, such as industrial and civil engineering. Among all organic compounds, acrylic compounds demonstrate the highest rate of strength gain over a wide temperature range. This is due to the low activation energy of the polymerisation process of acrylic monomers, which is triggered by special initiators. Due to this feature, acrylic composites can cure even at low temperatures and gain high strength in a short time. However, despite the obvious advantages, there are a number of questions that require further research: how does the rate of strength gain and other properties of acrylic composites change at different temperatures? How does changing the ratio of composite components (pliable, filler, initiator) affect its properties? How does the curing process of acrylic composites work at the molecular level? Determining the answers to these questions will make it possible to select the optimal ratio of components to obtain a material with the required properties, control the rate of strength gain of the composite by changing the temperature and composition, and use acrylic composites in a wider range of temperature conditions. Thus, a deep understanding of the processes that occur during the curing of acrylic composites is a prerequisite for their effective use in various industries and construction. The aim of the study is to comprehensively study the properties of composite materials based on methyl methacrylate (MMA) for the purpose of their effective use. Research objectives: determination of the optimal temperature regime to achieve maximum composite strength in the shortest possible time (1.5-2 hours). Study the effect of various fillers and other components on the strength, durability and other properties of the material. Identification of effective ways to modify MMA to increase the strength of the composite. Development of methods for controlling the rate of strength gain to ensure optimal operation. Assessment of the durability of the adhesive bond under various operating conditions. Comparison of the properties of the developed composites with existing materials. The results of the study will make it possible to develop new, more efficient composite materials for repair work that will be widely used in construction, industry and other sectors. Keywords: acrylic composites, modification, methyl methacrylate, strength, temperature, curing, repair.

Highly selective triethylamine gas sensor based on ZnO/Ti3C2Tx MXene self-assembly heterostructure

MXenes, as new two-dimensional transition metal compounds, has become promising sensing materials due to the excellent metal conductivity, abundant adsorption sites and the terminal groups of -O, -OH and -F. In this study, we report the well-etched accordion-like Ti3C2Tx by removing Al layer in Ti3AlC2, where Tx represents a wealth of terminal functional groups (-OH, -F, -O, etc.). In addition, unique hierarchical self-assembly ZnO/Ti3C2Tx nanocomposites are synthesized by hydrothermal method. The Brunauer-Emmett-Teller Method investigation also shows that the ZnO/Ti3C2Tx nanocomposites has a specific surface area of about 22.08 m2/g, and the pore size is mainly located at 11.1 nm. The innovative nanostructure is conducive to the adsorption and response of gas molecules. By investigating the gas sensitive properties of the sensors, it is found that the response of the ZnO/Ti3C2Tx sensor to triethylamine (TEA) is improved by 66 times and 1.58 times over that of pure Ti3C2Tx and ZnO, and the optimal operating temperature is 60℃ lower than that of pure ZnO. In addition, the LOD (Low Of Detection) of about 32.7 ppb indicates that the ZnO/Ti3C2Tx sensor is suitable for the detection of low concentrations TEA. The sensing performances of the ZnO/Ti3C2Tx sensor at a high humidity of 75 % RH verifies the strong sensing performance in high humidity environment. Furthermore, the composite sensor stabilize in 6 repetitive tests and present slight decrease in response value over 30 days. The excellent TEA sensitive properties indicate that the ZnO/Ti3C2Tx nanocomposite sensor may have promising applications in the gas sensitive field.

Performance evaluation and sensitivity analysis of polyethyleneimine-based sorbent in a circulating fluidized bed carbon dioxide capture unit

Greenhouse gases, particularly carbon dioxide, have increased the Earth’s average temperature by 1 °C, which has resulted in significant consequences for human life. To prevent further global warming and maintain a stable lifespan, it is imperative to achieve carbon neutrality. Post-combustion capture using an amine-based aqueous solvent is an advanced technology that has gained attention, but there are challenges such as corrosion, environmental impact, and energy consumption associated with it. This study aims to evaluate the performance of a polyethyleneimine-based sorbent in a circulating fluidized bed carbon dioxide capture unit and to determine the optimal operating conditions through sensitivity analysis. Various variables, including carbon dioxide concentration, water vapor content, desorber temperature, and sorbent residence time, were analyzed. The unit was continuously operated for 128 h even under challenging conditions with higher oxygen concentrations than the actual flue gases, and sorbent degradation was negligible. The results showed a 55 % carbon dioxide removal efficiency, a dynamic sorption capacity of 0.041 g-CO2/g-sorbent, and a regeneration heat energy of 4.2 GJ/tCO2. Sensitivity analysis revealed that there was minimal improvement even with changes in the absorber structure and physical properties of the sorbent. Only an increase in the sorbent reaction rate had a significant effect. If the reaction rate were to double, the carbon dioxide removal efficiency would reach 90 %, with a dynamic sorption capacity of 0.068 g-CO2/g-sorbent and regeneration heat energy of 2.9 GJ/tCO2.

Discovery of Quality by Design-Based Extraction Technology and the Quality Standard of Jinhua Finger Citron Essential Oil.

Jinhua finger citron is one of the traditional specialties of Jinhua with a long history of cultivation. The current study highlighted the advantages of using the quality by design approach to optimize the ultrasonic-assisted distillation extraction of Jinhua finger citron essential oil. The yield of Jinhua finger citron essential oil was regarded as a potential critical quality attribute. Potential critical process parameters were screened by the definitive screening design. Finally, the design space of the essential oil extraction process was constructed. The optimal operating space included an auxiliary NaCl concentration range of 9-12.00%, a soak temperature range of 30-50 °C, a distillation time range of 3.5-4.00 h, an ultrasonic power range of 200-300 W, a solid-liquid ratio range of 1:3-1:3.5, and a soak time range of 40-80 min. On this basis, the relative density, refractive index, and pH values of different batches of Jinhua finger citron essential oil were checked. The involved batches were analyzed by gas chromatography (GC), and gas chromatographic fingerprints were established by identifying major compounds, including d-limonene, γ-terpinene, and 5,7-dimethoxycoumarin. Based on the "quality by design" strategy, the extraction process of Jinhua finger citron essential oil established in this study was robust, reliable, and flexible.

Optimization of Biodiesel Production from Jatropha Oil and its Impact on Engine Performance and Emissions Using Response Surface Methodology

This study aims to improve biodiesel production by assessing the effects of biodiesel-diesel fuel blends on engine performance and emissions using response surface methodology (RSM). The biodiesel was produced by the transesterification process. Here we see how the molar ratio (A), catalyst quantity (B), reaction temperature (C), and reaction time (D) affect the biodiesel conversion rate. During optimization, a Box-Behnken design (BBD) based on RSM was employed. Ideal conditions for achieving a biodiesel yield of 98.2069% were a B of 0.811601 wt%, a C of 75.8837°C, a D of 98.2069 min, and A of 10935:1. Adjusting parameters like engine speed and biodiesel fuel mix ratio enhanced engine behavior and condensed exhaust emissions. The trials were structured utilizing the central composite design (CCD) technique grounded on RSM. The optimum operating criteria for the engine were evaluated to be a biodiesel ratio of 12.5845% and speed of engine is 2011.24 rpm. Under these conditions, the power output was 50.0817kW, torque was 254.757 Nm, smoke opacity was 6.48966%, CO emissions were 270.009 ppm, and NOx emissions were 819.573 ppm.

Numerical Investigation on the Influence of Substrate Board Thermal Conductivity on Electronic Component Temperature Regulation

This study presents a detailed numerical analysis of substrate boards made from various materials (FR-4, Si cladding, and Cu cladding) with nine electronic components mounted on them. Each component is subjected to different heat fluxes, and the analysis covers both natural convection (NC) and forced convection (FC) modes of heat transfer at air velocities of 4m/s and 6m/s. The findings reveal that at an air velocity of 6m/s, using a copper cladding board significantly lowers the temperatures of the electronic components by 340C to 540C compared to FR-4 and Si cladding boards. Additionally, the copper cladding reduces the required air-cooling velocity by 2m/s and achieves a temperature reduction for the IC chips ranging from 3.500C to 13.120C. It is recommended to use an air velocity of 4m/s with copper cladding to minimize fan power consumption while maintaining component temperatures below 1250C. These results provide crucial insights for thermal design engineers, aiding in the selection of appropriate substrate boards for effective thermal management of electronic components. The study emphasizes the benefits of copper cladding in distributing heat more uniformly, reducing energy consumption, and maintaining optimal operating temperatures. Furthermore, it suggests that placing high heat-dissipating components at inlet or outlet points can minimize thermal interactions and overall configuration temperatures. The research offers valuable guidance to the heat transfer community, particularly electronic thermal designers, by highlighting the importance of substrate material choice and component placement in enhancing the reliability and lifespan of integrated circuits (ICs). The comprehensive analysis and recommendations serve as a vital resource for optimizing thermal control strategies in electronic devices, ultimately contributing to improved performance and durability.