Operating Conditions Research Articles

Pendant Group Functionalization of Cyclic Olefin for High Temperature and High-Density Energy Storage.

High-temperature flexible polymer dielectrics are critical for high-power-density energy storage and conversion under harsh operating conditions. These types of dielectrics will need to simultaneously possess a high bandgap, dielectric constant and glass transition temperature - a substantial challenge when designing novel dielectric polymers. In this work, by varying halogen substituents of an aromatic pendant hanging off a bicyclic mainchain polymer, a class of high-temperature olefins with adjustable thermal stability are obtained, all with uncompromised large bandgaps. Halogens substitution of the pendant groups at para or ortho position of polyoxanorborneneimides (PONB) imparts it with tunable high glass transition temperature from ∼220 to 245°C, while with also moderate dielectric constant of ∼ 2.8-3.0 and high breakdown strength of ∼625-800MV/m. A high energy density of 7.1 J/cc at 200°C is achieved with p-POClNB, representing the highest reported energy density among all-organic homo-polymer dielectrics. Molecular dynamic simulations and ultrafast infrared spectroscopy were used to probe the free volume element distribution and chain relaxations of the polymers to provide insights to the dielectric thermal properties. An increase in free volume element is observed with the change in the pendant group from fluorine to bromine at the para position; however, a decrease in free volume element is observed as we change the pendant group from fluorine to chlorine at the ortho position because of the steric hindrance. Overall, the dielectric constant and band gap remain stable while the glass transition temperature changes more obviously. Consequently, by proper designing the pendant groups, the thermal stability of PONB can be improved for harsh condition electrification. This article is protected by copyright. All rights reserved.

One-Shot Remote Integration of Macromolecular Synaptic Elements on a Chip for Ultrathin Flexible Neural Network System.

The field of biomimetic electronics that mimic synaptic functions has expanded significantly to overcome the limitations of the von Neumann bottleneck. However, the scaling down of the technology has led to an increasingly intricate manufacturing process. To address the issue, we present a one-shot integrable electropolymerization (OSIEP) method with remote controllability for the deposition of synaptic elements on a chip by exploiting bipolar electrochemistry. Condensing synthesis, deposition, and patterning into a single fabrication step was achieved by combining alternating-current voltage superimposed on direct-current voltage-bipolar electropolymerization and a specially designed dual source/drain bipolar electrodes. As a result, uniform 6 × 5 arrays of poly(3,4-ethylenedioxythiophene) (PEDOT) channels were successfully fabricated on flexible ultrathin parylene substrates in one-shot process. The channels exhibited highly uniform characteristics and were directly used as electrochemical synaptic transistor with synaptic plasticity over 100 seconds. The synaptic transistors have demonstrated promising performance in an artificial neural network (NN) simulation, achieving a high recognition accuracy of 95.20%. Additionally, the array of synaptic transistor was easily reconfigured to a multi-gate synaptic circuit to implement the principles of operant conditioning. These results provide a compelling fabrication strategy for realizing cost-effective and disposable NN systems with high integration density. This article is protected by copyright. All rights reserved.

Protocell Flow Reactors for Enzyme and Whole-cell Mediated Biocatalysis.

The design and construction of continuous flow biochemical reactorscomprising immobilized biocatalysts have generated great interest in the efficient synthesis of value-added chemicals. Living cells use compartmentalization and reaction-diffusion processes for spatiotemporal regulation of biocatalytic reactions and implementing these strategies into continuous flow reactors could offer new opportunities in reactor design and application.Herein, we demonstrate the fabrication ofprotocell-based continuous flow reactors for enzyme and whole-cell mediated biocatalysis. We employ semipermeable membranized coacervate vesicles as model protocells that spontaneously sequester enzymes or accumulate living bacteria to produce embodied microreactors capable of single- or multiple-step catalytic reactions. By packing millions of the enzyme/bacteria-containing coacervate vesicles in a glass column, we demonstrate a facile, cost-effective, and modular methodology capable of performing oxidoreductase, peroxidase and lipolytic reactions, enzyme-mediated L-DOPA synthesis and whole-cell glycolysis under continuous flow conditions. We show that the protocell-nested enzymes and bacterial cellsexhibit enhanced activities and stability under deleterious operating conditions compared with their non-encapsulated counterparts. Our results provide a step towards the engineering of continuous flow reactors based on cell-like microscale agents and offer opportunities in the development of green and sustainable industrial bioprocessing. This article is protected by copyright. All rights reserved.

Optimization of the on/off status configuration of control units in an active vibration isolation system—experiment

Active vibration isolation (AVI) is an important measure to attenuate vibration transmission in underwater vehicles and multiple active control units are usually used to attenuate low frequency vibrations induced by power equipment. Under certain operation conditions, however, the pre-installed control units in an AVI system may be redundant. Hence, it is necessary to optimize the on/off status configuration of all the control units. An optimization approach is proposed for configuration optimization of control units and validated by experiments. The criterion of the proposed approach is derived from the vibration responses of the monitoring points. The involved optimization, formulated as a constrained 0–1 nonlinear programming problem, utilizes the on/off status of control units as the input variable and the number of active units as the constraint. Optimized configurations were obtained by solving the nonlinear programming problem and deployed to the experimental system. The test results have demonstrated that vibration of the monitoring points can be effectively suppressed by activating only a portion of control units, and the configurations corresponding to maximum vibration reduction vary with different excitations.

Investigating the influence of Saccharomyces cerevisiae on microbial fuel cell performance through bioelectrochemical and biochemical approaches under varied operating conditions

Investigating the influence of Saccharomyces cerevisiae on microbial fuel cell performance through bioelectrochemical and biochemical approaches under varied operating conditions

(Digital Presentation) The Effect of Coating Quality on Water Transport in the Gas Diffusion Layer of PEM Fuel Cells

Present study examines the impact of the quality of the GDL non-wetting coating on water transport. It is found that there are two distinct regions defined by the coating quality which present fundamentally distinct behaviours, one region characterized by few coating defects with the second marked by significant coating degradation. Simulations consider the influence of heterogeneous wetting and pinning conditions on protruding water droplets in contact with the GDL fibrous matrix. The mixed-non-wetting behaviour for a uniform non-wetting coating having less than 25% defects is characterized by a high breakthrough pressure, yielding improved transport properties in the stable displacement regime. The coating degrades under normal operating conditions and it changes the water transport characteristics unfavorably through a significant decrease in breakthrough pressure, and an up to six-fold increase in droplet volume. Various degrees of coating degradation are considered and the corresponding Laplace pressure is determined as a function of droplet volumes at breakthrough.

Global receptive field graph attention network for unsupervised domain adaptation fault diagnosis in variable operating conditions

Global receptive field graph attention network for unsupervised domain adaptation fault diagnosis in variable operating conditions

In-situ X-ray Fluorescence Analysis of In-plane Cerium-ion Distribution Under Humidity Gradients in Proton Exchange Membrane

Cerium ions are incorporated into proton exchange membranes (PEMs) of fuel cells to mitigate its chemical degradation caused by radical species. However, under fuel cell operating conditions, cerium ions move in in-plane direction in the cell by humidity gradient. This cerium ion transport results in cerium ion depletion leading to accelerated chemical degradation. This study developed an in-situ and operando measurement technique utilizing synchrotron high-energy X-ray fluorescence spectroscopy to monitor the cerium ion transport across the membrane under the in-plane humidity gradient. This method effectively tracks the dynamic behavior of cerium ions under fuel cell operating conditions.

Numerical study of powder flow characteristics of coaxial nozzle direct energy deposition at different operating and design conditions

Numerical study of powder flow characteristics of coaxial nozzle direct energy deposition at different operating and design conditions

Enhanced Randomized Harris Hawk Optimization of PI Controller for Power Flow Control in the Microgrid with the PV-Wind-Battery System

Microgrids, characterized by their ability to work individually or in combination with the main power system, play a pivotal role in addressing the growing demand for reliable and sustainable energy solutions. This work concentrates on the integration of sustainable energy sources, specifically photovoltaic (PV), and wind generation and a battery storage system within a microgrid framework. Additionally, a power flow control strategy is implemented to enhance the dynamic behaviour and stability of the microgrid. The proportional-integral (PI) controller is a fundamental component in regulating the microgrid's power flow, ensuring optimal performance under varying operating conditions. However, tuning the PI controller parameters is a difficult task because of the dynamic and nonlinear nature of renewable energy sources. In this work, the application of the Enhanced Randomized Harris Hawk Optimization (HHO) to fine-tune the PI controller is proposed, using the algorithm's ability to mimic the hunting behaviour of hawks in finding optimal solutions. The PV-Wind-Battery microgrid system is modelled, and the proposed algorithm is employed to optimize the PI controller parameters for efficient energy management. The ERHHO algorithm's exploration-exploitation balance is harnessed to navigate the complex solution space and converge to optimal PI controller settings, thereby enhancing the microgrid's stability and performance. The study evaluates the effectiveness of the proposed Enhanced Randomized Harris Hawk Optimization-based PI controller tuning through comprehensive simulations. Performance metrics such as transient response, overshoot, settling time, and steady-state error are analysed to validate the robustness and efficiency of the proposed method. The outcomes of this research contribute to the advancement of microgrid control strategies, offering a novel approach to PI controller tuning in the context of diverse renewable energy sources. The integration of the Harris Hawk Optimization algorithm provides a promising avenue for enhancing the operational efficiency and reliability of microgrids, paving the way for sustainable and resilient energy systems in the aspect of growing energy landscapes.

The Science of Creating Brand Associations: A Continuous Trinity Model Linking Brand Associations to Learning Processes

Abstract The continuous trinity model (CTM) of brand associations integrates 50 years of consumer learning research with recent conceptualizations of consciousness. Three types of brand associations are proposed at the representational level (expectations, meaning, and affect), corresponding to three types of learning at the process level (predictive learning, referential learning, and direct affect transfer). A core proposition derived from research on automaticity holds that the operating conditions of the learning processes vary on a continuum from mostly System 2 for predictive learning to mostly System 1 for direct affect transfer, with referential learning as a mix of the two. The CTM aims to bring clarity and structure to a complex literature by highlighting the web of interrelations between operating principles (“what” brand associations are learned), operating processes (“how” brand associations are learned), and operating conditions (“when” brand associations are learned). For consumer and learning researchers, the CTM outlines an agenda for future research and guidelines to improve conceptual and methodological clarity. For brand managers, the CTM provides tactical recommendations (a “toolkit”) for structuring advertising campaigns to create desired brand associations and strategic recommendations for managing brand partnerships. For policymakers, the CTM offers guidance on types of advertisements requiring closer scrutiny.

Sludge deep dewatering by liquefied dimethyl ether: selection of operating conditions based on response surface methodology

ABSTRACT Sludge is an inevitable by-product of the sewage treatment process and its high moisture content poses significant challenges for its treatment and disposal. This study focuses on the technology of sludge deep dewatering using liquefied dimethyl ether (DME) and explores the relationship between operating parameters (DME/sludge ratio, extraction time and stirring speed) and the water content of the sludge after deep dewatering. After deep dewatering, the sludge's lower heating value (LHV) was significantly increased. The dehydrated filtrate is highly biodegradable and could be treated together with sewage. Based on the response surface method of central composite design, a second-order regression model of the above three variables and sludge water content as the response was established. Finally, the operating conditions diagram was drawn by target water content (36.96 wt.%) which meets the requirement of self-sustained incineration and model equation. This study provides a valuable perspective on sludge drying and fuelisation.

Electrical behavior and water phase transformation in multi‐walled carbon nanotube/polytetrafluoroethylene composite films

AbstractMulti‐walled carbon nanotubes (MWCNTs) with excellent physiochemical properties have been recently applied to energy/power generation and storage systems encompassing polymer electrolyte membrane fuel cells (PEMFCs). However, there is a lack of investigations of the properties of MWCNT composites themselves under the actual operating conditions of systems. In this paper, MWCNTs/polytetrafluoroethylene (PTFE) composites were fabricated as electric and hydrophobic components for energy/power systems. The electrical properties, heating behavior, hydrophobicity, and water evaporation behavior of the composites are characterized within the operating voltage ranges of PEMFC. With 50% MWCNT content, the conductivity and the contact angle were 11.83 S/cm, and the contact angle 128.1°, respectively. The MWCNT/PTFE composite film showed a linear temperature rise with voltages and rapid temperature saturation within 40 s. The rate in the initial heating range was measured at 0.5°C/s for the voltage of 0.5 V. The voltage increase induced an exponential decrease in the height of water droplets on the composite surface. The evaporation rate increased almost 10‐fold, from 0.013 mm/min at 0.0 V to 0.12 mm/min at 1.0 V. The proposed characteristics of the functional composite provide insights into the material requirements for electrochemical devices, including PEMFC.Highlights Multi‐walled carbon nanotube/polytetrafluoroethylene composites can be applied to energy storage and power generation. Key properties of the composites are proposed for polymer electrolyte membrane fuel cell (PEMFC) operating conditions. The composite has a fast heating by high conductivity and temperature uniformity. Water‐vapor transformation under PEMFC operating voltage is quantified.

Feeding frequency efficacy on biogas yield of oily substrate anaerobic digestion in continuous stir tank reactor

ABSTRACT Anaerobic treatment of oily substrate, known as grease trap waste (GTW), was investigated for its practicability via continuous stirred tank reactor (CSTR) at different operating conditions and selected recovery strategies of feeding frequency efficacy. This study determine the performance of feeding frequency efficacy, namely feeding every 24 hours (R24H) and feeding every 12 hours (R12H). Under organic loading rate (OLR) of 2.2 gCOD/L.day, R12H exhibited methane composition of 57%, methane production rate of 0.27 LCH4/L.day, and methane yield of 0.14 LCH4/gCODremoved. At the same OLR, R24H recorded methane composition of 60%, methane production rate of 0.29 LCH4/L.day and similar methane yield as R12H. Findings indicated that R24H showed performance comparable to that of R12H. Given minor variation observed in performance, it is recommended that plant operators may consider scheduling 2 times feeding per day for low loading conditions and switch to 1 time feeding per day for higher loading conditions. This strategy is designed to balance the system and prevent shock loads, which could lead to plant shutdowns. This mechanism will induce their conversion to volatile fatty acids (VFAs); thus, reducing the risk of acid accumulation and pH drops, which could inhibit methanogens to produce methane, especially for oily substrate.

Silver-graphene oxide nanocomposite doping chitosan/PVA membrane for arsenic (III) elimination from aqueous solution

Abstract Heavy metals and pathogens from contaminated water sources may undoubtedly be removed by creating an efficient bio-adsorbent based on functional spots. Thus, the goal of this work was to produce chitosan (Ch)-polyvinyl alcohol (PVA) biofilm decorated with graphene oxide (GO) sheets doped with silver nanoparticles (AgNPs). The nanostructure of prepared GO/Ag nanosheets is examined by transmission electron microscope (TEM). The fabricated film (GO/Ag Ch-PVA) is compared by the control films (Ch, PVA and Ch-PVA). Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), and tensile strength are used to study the films' structure. Also, the antimicrobial activity was assessed for the films. After doping the polymer matrix with GO/Ag, the obtained findings were compared to other control films, and it was discovered that the tensile strength increased to about 46.18 MPa. 
Moreover, the adsorption experiment for arsenic As (III) ions is explored by the prepared film at different operating conditions. The obtained results validated the enhanced adsorption ability of the GO/Ag Ch-PVA film towards As (III) with the highest adsorption capacity of 54.3 mg/g obtained from the isotherm model of Langmuir. Moreover, kinetic mathematical models for the adsorption effectiveness of GO/Ag Ch-PVA film are proposed. The results gathered demonstrated that GO/Ag Ch-PVA film is a potentially useful material for eliminating As (III) and microbial strains from essential water resource applications. 

Li–Yorke chaos for composition operators on Orlicz spaces

Li–Yorke chaos for composition operators on Orlicz spaces

Fluorescent Composite Nano‐ and Microparticles Based on Xanthene Dyes and Iron Oxides

AbstractModern industry actively uses metal structural materials to create innovative devices and components. In order to prevent emergency situations in production, nondestructive testing methods are used to detect defects on the surface of the material being developed. Among the methods of nondestructive testing, one can highlight the method of luminescent magnetic flaw detection, which allows identifying defects on the surface and under the surface of the test sample with minimal effort. It is known that in some cases, the magnetic‐powder method cannot achieve the required sensitivity due to the shape and location of defects themselves or due to certain conditions of object operation. To increase the visibility and sensitivity, magnetic nano‐ and microparticles can be conjugated with the dyes. Iron oxide nanoparticles (Fe3O4, γ‐Fe2O3) can be used as such magnetic particles, since they are quite easy to obtain and have low toxicity, high chemical stability, and a wide variety of magnetic properties. To ensure fluorescence of magnetic particles, a wide variety of fluorescent dyes associated with such particles are used. The dyes can include morin, naphthalimide derivatives, as well as semiconductor quantum dots. This article provides a review of fluorescent composite micro‐ and nanoparticles based on xanthene dyes (rhodamine, fluorescein, and pyronine). Such dyes are economically available luminophores, have good binding to the surface of magnetic particles, and therefore can be suitable for luminescent magnetic flaw detection. This review article discusses methods for producing composite nano‐ and microparticles of iron oxides with xanthene dyes and provides prospects of using composite nano‐ and microparticles in nondestructive testing methods.

Revealing the contribution of corporate sustainability practices to financial performance: Case of BIST Sustainability 25 Index companies

The purpose of the paper is to study the impact of corporate sustainability practices on the financial performance of companies included in the BIST Sustainability 25 Index. To assess the efficiency and quality of corporate sustainability, general (ESG Disclosure Index) and partial (Environmental Disclosure Index, Social Disclosure Index, and Corporate Governance Disclosure Index) indices were used, calculated based on content analysis of sustainability reports. Based on the two given types of indices and four types of financial performance indicators (return on assets, return on equity, assets turnover ratio, and Tobin’s Q), two types of regression models (GEN models and PART models) were built, and eight analytical models were examined. Company size and leverage were included as control variables in each model. The regression analysis results were contradictory, partially confirming the conclusions of some scientists and refuting the findings of others. A study of GEN models revealed that companies implementing more effective general corporate sustainability practices have a significant positive impact only on return on equity; as for other measures (return on assets, assets turnover ratio, and Tobin’s Q), an insignificant relationship between them and ESG Disclosure Index was found. Results of the PART models analysis revealed a significant positive effect of the Social Disclosure Index on return on equity and assets turnover ratio and a negative relationship between the Corporate Governance Disclosure Index and assets turnover ratio. Using control variables for the two types of models showed a significant negative effect of company size on Tobin’s Q. AcknowledgmentThis study was supported by the Ministry of Education and Culture of Ukraine within the project “Development of a mechanism for the sustainable development of economic systems in the conditions of military operations and post-war recovery of the economy” (Registration number of the project: 0124U000463).

Combustion Diagnosis in a Spark-Ignition Engine Fueled with Syngas at Different CO/H2 and Diluent Ratios

The gasification of residues into syngas offers a versatile gaseous fuel that can be used to produce heat and power in various applications. However, the application of syngas in engines presents several challenges due to the changes in its composition. Such variations can significantly alter the optimal operational conditions of the engines that are fueled with syngas, resulting in combustion instability, high engine variability, and misfires. In this context, this work presents an experimental investigation conducted on a port-fuel injection spark-ignition optical research engine using three different syngas mixtures, with a particular focus on the effects of CO/H2 and diluent ratios. A comparative analysis is made against methane, considered as the baseline fuel. The in-cylinder pressure and related parameters are examined as indicators of combustion behavior. Additionally, 2D cycle-resolved digital visualization is employed to trace flame front propagation. Custom image processing techniques are applied to estimate flame speed, displacement, and morphological parameters. The engine runs at a constant speed (900 rpm) and with full throttle like stationary engine applications. The excess air–fuel ratios vary from 1.0 to 1.4 by adjusting the injection time and the spark timing according to the maximum brake torque of the baseline fuel. A thermodynamic analysis revealed notable trends in in-cylinder pressure traces, indicative of differences in combustion evolution and peak pressures among the syngas mixtures and methane. Moreover, the study quantified parameters such as the mass fraction burned, combustion stability (COVIMEP), and fuel conversion efficiency. The analysis provided insights into flame morphology, propagation speed, and distortion under varying conditions, shedding light on the influence of fuel composition and air dilution. Overall, the results contribute to advancing the understanding of syngas combustion behavior in SI engines and hold implications for optimizing engine performance and developing numerical models.

Review of Data Processing Methods Used in Predictive Maintenance for Next Generation Heavy Machinery

Vibration-based condition monitoring plays an important role in maintaining reliable and effective heavy machinery in various sectors. Heavy machinery involves major investments and is frequently subjected to extreme operating conditions. Therefore, prompt fault identification and preventive maintenance are important for reducing costly breakdowns and maintaining operational safety. In this review, we look at different methods of vibration data processing in the context of vibration-based condition monitoring for heavy machinery. We divided primary approaches related to vibration data processing into three categories–signal processing methods, preprocessing-based techniques and artificial intelligence-based methods. We highlight the importance of these methods in improving the reliability and effectiveness of heavy machinery condition monitoring systems, highlighting the importance of precise and automated fault detection systems. To improve machinery performance and operational efficiency, this review aims to provide information on current developments and future directions in vibration-based condition monitoring by addressing issues like imbalanced data and integrating cutting-edge techniques like anomaly detection algorithms.