Operating Conditions Research Articles

SFACIF: A safety function attack and anomaly industrial condition identified framework

High-stakes process industries require a harmonious relationship between the Safety Instrumented System (SIS) and the Basic Process Control System (BPCS) to guarantee the safety and stability of operations. As security threats to SIS intensify, the imperative to fortify it against cyber-attacks has never been more critical. SIS activates safety functions to bring the process to a safe state or shut it down under anomaly idustrial conditions. This raises two critical questions for SIS security: (1) how to differentiate between genuine industrial anomalies and data injected by attackers to prevent unnecessary shutdowns and economic losses; and (2) how to distinguish between attackers’ replayed data and normal operational data to avoid casualties resulting from delayed shutdowns. In addressing these challenges, we introduce SFACIF, a framework designed to effectively identify safety function attacks and anomaly industrial conditions. Inspired by advanced two out of three voting mechanisms and process monitoring technologies, our approach encompasses several innovative strategies. Initially, a deep learning-based time series prediction method is employed to generate benchmark data. Next, potential issues are identified by detecting deviations through pairwise comparisons between the predicted benchmark data, SIS observations, and BPCS observations. To account for the higher fault rates in BPCS and the presence of process noise, we apply a modified sliding window residual statistical method for analysis. Lastly, we introduce a novel coding scheme to interpret the results of the three-way comparison, enabling the identification of safety function attacks and anomaly industrial conditions. To validate the efficacy of SFACIF, we devised a physical simulation platform that mirrors real-world industrial environments, facilitating a rigorous assessment of our framework under operational conditions. The performance metrics underscore the superior capability of SFACIF, which achieved 99% accuracy and 1% false alarm rate. These results not only attest to the ability of SFACIF to accurately differentiate between various attack vectors but also highlight its proficiency in discerning between authentic and manipulated data.

Numerical study on temperature and thermal stress behaviors in silicon carbide heating elements within high-temperature annealing furnaces

In response to global sustainability goals, the transition from fossil fuel-based to electric silicon carbide (SiC) heating elements in continuous annealing furnaces is critical for reducing emissions, enhancing safety, and improving operational environments in the steel industry. This study investigates the cross-sectional temperature profiles and the resultant thermal stress of hollow cylindrical SiC heating elements under varied design conditions. To independently analyze the complex effects of multiple factors, both theoretical and numerical analyses were conducted using simplified boundary conditions in two dimensions, which closely simulate the actual temperature profiles observed in heaters within a continuous annealing line. The results indicate that the radial temperature gradient and resulting thermal stress in these elements are directly proportional to the surface heating load, with the maximum axial tensile stress occurring at the outer surface of the heater. Scenarios involving closely spaced multiple heaters or the introduction of cold steel strips lead to increased axial thermal stress due to additional circumferential temperature gradients. Conversely, the application of shield tubes, despite increasing the heater’s temperature, reduces thermal stress by homogenizing radiation within the tube. Consequently, optimizing heater configuration and operational conditions is essential in furnace design to effectively manage heaters’ temperature and thermal stress, thereby ensuring both efficiency and service longevity of the heating elements.

Bismuth sensitized iron oxide on exfoliated graphene oxide (Bi–Fe2O3@GO) for oxygen evaluation reaction

Electrochemical water splitting is a promising approach towards a sustainable and renewable energy source. However, the demand for high anodic potential and sluggish kinetics of oxygen evolution reaction (OER) restrict the efficiency and feasibility of the water-splitting process. In this quest, transition metal oxides and alloys are considered potential candidates owing to their natural occurrence and high redox potential for OER. However, many associated challenges in their use are still there to be addressed. Here, we designed a new class of bismuth-doped iron oxide on exfoliated graphene oxide by optimizing the metal loading on the conductive support to facilitate the flow of charge during catalysis. The catalytic ability of the synthesized Bi-doped nanocomposites was evaluated in activating the OER under extreme alkaline conditions (1 MKOH). On screening different combinations, 20Bi–Fe2O3@GO was identified as the most efficient and sustainable electrocatalyst even under harsh operating conditions, with an onset potential of 1.48 V and a Tafel slope of 65 mV/dec. The current study offers a new class of Bi-doped electrocatalysts, where the precise doping of Bi and the optimized loading of metal was found the key to achieving low onset potential and high current density to initiate OER.Graphical abstract

Identifying electrochemical processes by distribution of relaxation times in proton exchange membrane electrolyzers

Distribution of relaxation time (DRT) is used to interpret electrochemical impedance spectroscopy (EIS) for proton exchange membrane (PEM) water electrolyzers, with an attempt to separate overlapped relaxation processes in Nyquist plots. By varying operating conditions and catalyst loadings, four main relaxation peaks arising from EIS can be identified and successfully separated from low to high frequencies as (P1) mass transport, (P2) oxygen evolution reaction kinetics, (P3) reaction kinetics (with faster time constant than P2), and (P4) ionic transport. The shape, height, and frequency of the DRT peaks change with different membrane electrode assembly (MEA) configurations. Electron microscopy reveals distinct features from the cross-sectioned MEAs which verify critical DRT results in that increasing the iridium (Ir)-anode loading from 0.2 mgIr/cm2 to 1.5 mgIr/cm2 reduces kinetic losses due to higher site-access; a thick and compacted anode, however, also triggers higher ohmic resistances from membrane/catalyst layer hydration and increases transport losses due to longer ionomer pathways. DRT provides higher resolution to EIS for deconvoluting processes with different relaxation times and the quantification of DRT peaks improves the accounting of total losses from each process.

Experimental and Numerical Analysis of Thermal Fatigue of Grey Cast Iron Ingot Mould

This article presents the results of experimental studies and numerical calculations that were conducted to analyse the phenomena that occur during the operation of an ingot mould that is designed for casting steel ingots. The studies were conducted on an experimental stand in a foundry on an ingot mould that was designed to make ingots that weigh up to six tons; they consisted of determining the temperature of the ingot mould and measuring the displacements of its walls during filling with steel and cooling. These studies were used to create and verify a numerical model that was used to determine the temperatures, displacements, deformations, and stresses in ingot mould walls during the operating cycle using the FEM method. Microstructure studies of ingot cast iron that was subjected to thermal fatigue were also conducted on a laboratory stand; the temperature changes and test times were the same as those used under the normal operating conditions of the ingot mould. Cast iron samples were subjected to heating and cooling cycles within a range of 0 to 60 cycles; then, tensile tests were performed to determine their stress–strain curves. As a result of the conducted tests, a great influence was found of the number of cycles on decreases in the values of the modulus of elasticity and tensile strength—especially within a range of 0 to 10 cycles. A relationship was also found between the changes in these values and the image of the cast iron microstructure. Based on images of the cast iron microstructure after being subjected to different numbers of thermal fatigue cycles, the mechanism of the crack initiation and propagation was determined. The influence of the changes in the strength of the cast iron and the stress state that was determined by the FEM method on the durability of the tested type of ingot mould was analysed. The obtained research results will be useful for introducing design changes that are aimed at increasing the fatigue durability of ingot moulds.

Design and optimization of the jet cooling structure for permanent magnet synchronous motor

Permanent magnet synchronous motor (PMSM) is widely used in electric vehicles due to its high power density and wide speed range. However, when operating under long-term heavy load conditions, PMSM is prone to heat accumulation. It’s difficult to cool the motor with existing indirect cooling structures efficiently, which may lead to its high temperature and result in winding burnout or even permanent demagnetization of the magnets. In this paper, a novel cooling structure based on jet cooling is proposed to reduce the operating temperature of the PMSM efficiently and improve its stability. The temperature field model, which accounts for the influence of end windings, is developed to analyze and optimize the parameters of the jet cooling structure, leading to the determination of an optimal parameter set. By exploring the cooling effects of motors with different cooling structures under stable, extreme and mixed cycle operating conditions, it is proved that the jet cooling structure designed in this paper can effectively reduce the temperature of the motor and ensure its reliable operation. The results show that with the influence of the jet cooling structure designed in this paper, the maximum temperatures of the rotor and winding are reduced by 35.2℃ and 44.5℃ respectively.

Comprehensive Assessment of Ferroresonance and its Effects in Selected Distribution Substations in Nasarawa State, Nigeria

Ferroresonance in distribution networks generates harmful harmonics, excessive heating, and potential transformer failures, yet limited research focuses on its impact in Nigerian low-voltage systems. This study examines ferroresonance susceptibility in low-voltage distribution transformers, with an emphasis on core saturation, harmonic distortion, and grading capacitance effects under varied operational conditions across substations in Lafia, Akwanga, and Keffi. By analyzing transformer responses from 50V to 500V and harmonic profiles in Delta (1.12Ω) and Star-Grounded (1.53Ω) configurations, the research highlights transformer design's critical role in ferroresonance resilience. Findings reveal that increasing grading capacitance from 90 pF to 1550 pF substantially elevated peak voltages from 0.420kV to 2.400kV (Lafia), 2.450kV (Akwanga), and 2.540kV (Keffi), and currents from 28A, 26A and 27A to 103A, 118A, and 130A, respectively. Voltage THD similarly rose from 6.5%, 6.3% and 6.7% to 35.5%, 38.2%, and 36.0%, respective; with current THD climbing from 7.8% 7.5% and 7.9% to 40.2%, 44.1%, and 42.3% respectively, indicating varying ferroresonance susceptibility across the substations. Delta configurations show lower ferroresonance risk compared to Star-Grounded types, underscoring optimal winding configuration and capacitance management as key resilience factors. Recommendations include targeted harmonic filtering and precise capacitance management to stabilize transformer operation. Future research should consider broader transformer model diversity, adaptive control systems, and machine learning techniques for enhanced ferroresonance risk assessments.

Multi-objective optimization of nanofluid thermal performance in battery cold plates using computational fluid dynamics

Inspired by the tree root structure, this paper uses commercial CFD software to simulate and analyze the cold plate of three-dimensional battery, and focuses on the heat transfer problem of tree root sine pipe to improve the heat dissipation performance of LiFePO4 battery. Utilizing nanofluids as working fluids, the research explores the impact of channel geometry, discharge power, nanofluid type, volume fraction, initial temperature, and velocity on heat transfer characteristics. The results show that the heat transfer effect of sinusoidal pipeline is obviously improved compared with traditional pipeline. Among the tested nanofluids, a 5 % Cu-water mixture exhibited the highest heat transfer efficiency. Furthermore, higher initial nanofluid velocity and lower initial temperature led to reduced average cold plate temperatures. Response surface methodology and genetic algorithm were utilized to optimize the thermophysical properties and initial operating conditions of the nanofluid. The influencing factors, including initial temperature (288 K-298 K), initial velocity (0.05 m/s-0.25 m/s), and volume fraction (1 %-5 %), were analyzed with the objective of establishing a relationship between the average battery temperature and pressure drop. And the optimized solution identified an ideal combination of inlet velocity, temperature, and nanofluid volume fraction of 0.14 m/s, 288.00 K, and 4.41 %, respectively, maximizing heat dissipation while minimizing pressure loss.

ERGONOMICS AS A FACTOR IN ENSURING SAFETY DURING THE OPERATION OF CONSTRUCTION MACHINES ON THE EXAMPLE OF EXCAVATORS

Problem statement. To improve the safe working conditions of excavator operators, it is important to effectively manage ergonomic quality indicators, increase the reliability of excavators, and improve the sanitary and hygienic conditions and comfort of operators. The set of ergonomic indicators of the operator–excavator system, including controllability, occupancy, serviceability, masterability and manufacturability, defines the concept of ergonomics (a criterion category of quality management that is also considered as an object of management). Changes in construction affect the efficiency of the operator-excavator system, taking into account specific production and technical, natural and climatic, and socio-economic conditions. The re-equipment of construction sites with new generation excavators equipped with modern control, computer information and diagnostic systems, hardware and software for data transmission, processing and analysis not only improves the efficiency of construction work but also changes the safe nature of human-machine interaction. The purpose of the article. Ensuring safety during the operation of construction machines (excavators), taking into account ergonomics criteria, which is an urgent scientific task, the solution of which will improve working conditions and increase the efficiency of excavators. Conclusion. The conducted research has shown that the ergonomic component “man – machine – environment” on the example of improving excavators allows to increase the safety of machines and improve the working conditions of construction machine operators. The use of the mathematical apparatus of fuzzy set theory to evaluate and manage the ergonomics of excavators is due to the nature and specificity of the functioning of the elements of the “operator–excavator” system. Information about the system elements can be represented by subjective opinions or judgements, inaccurate data or errors in measurements and parameter calculations. Therefore, it is necessary to use mathematical tools that take into account quantitative and qualitative information presented in linguistic form.

Nitrous oxide abatement and valorization in an ammonia-fueled SOFC stack – Nitric oxide and electricity production

Nitrous oxide (N2O) is a harmful gas that strongly impacts climate change. Several strategies for denitrification have been addressed, where the use of solid oxide fuel cells (SOFCs) has been demonstrated to be attractive for N2O reduction and simultaneous electricity production. The reduction of N2O to N2 is studied for the first time at the cathode of an SOFC, where ammonia is supplied to the anode as fuel. A diluted ammonia stream is particularly interesting since it is normally available in HNO3 plants – the most important concentrated source of N2O emission – and is carbon-free. The combined reduction of N2O with the oxidation of NH3 allows the production of nitric oxide (NO) at the anode, a valuable precursor for HNO3 production.This work uses a commercial SOFC stack comprehending six cells, equipped with membrane electrode assemblies of LSM-CGO ‖ yttria-stabilized zirconia (YSZ) ‖ YSZ-NiO. Electrochemical Impedance Spectroscopy (EIS) was successfully employed to characterize the stack performance. Data were analyzed by combining a Distribution Function of Relaxation Times (DFRT) and Equivalent Circuit Models (ECMs), for different operating conditions, namely in terms of temperature and fuel feed composition. Three major processes were identified at the anode: one related to the adsorption/desorption of reactants on the surface of the electrocatalyst, a diffusion process of charge carriers/intermediate species to the triple phase boundary (TPB), and a charge-transfer process at the TPB. The electrochemical production of nitric oxide (NO) was investigated, and a 20 % selectivity towards NO production and an energy stack efficiency of 88 % was obtained. Overall, the current work provides a critical first step toward using SOFC to perform efficient N2O electroreduction using diluted ammonia as fuel.

Volumetric efficiency in motor-driven two-dimensional piston pumps with leakage and reverse flow under high pressure

This paper presents a volumetric efficiency model for high-pressure motor-driven 2D piston pumps, incorporating key factors such as axial internal and external leakage, circumferential leakage, and reverse flow. The model integrates hydraulic fluid compressibility and variations in flow coefficients to improve simulation accuracy. Co-simulation using AMESim and Simulink, along with experimental validation, demonstrates the model’s reliability across various operating conditions. The results show that rotational speed enhances volumetric efficiency due to its minimal effect on leakage and reverse flow, while pressure significantly reduces efficiency, particularly through reverse flow and circumferential leakage. Reducing trapped volume proves to be an effective strategy for minimizing reverse flow and improving overall pump performance. Additionally, refining flow coefficients to improve the accuracy of the simulation model remains an important area for further development.

Thermodynamic analysis of a novel concentrated solar power plant with integrated thermal energy storage

This research provides a detailed thermodynamic analysis of a new Concentrated Solar Power (CSP) plant with integrated Thermal Energy Storage (TES). The plant combines a central receiver tower with a supercritical CO2 (sCO2) Brayton power cycle and a hybrid sensible-latent heat storage system.The analysis shows significant improvements in energy and exergy efficiencies (41.3 % and 38.7 %, respectively) compared with conventional CSP plants. The integrated system’s optimal operating conditions are obtained with a receiver temperature of 750 °C, a TES capacity of 12 h, a solar multiple of 2.5, an s CO2 cycle with a turbine inlet temperature of 750 °C, and a pressure ratio of 2.8.The analysis of the TES performance shows the great potential of the hybrid storage system in improving dispatchability and capacity factors. The economic analysis shows acompetitive Levelized Cost of Electricity (LCOE), and the environmental impact assessment shows a great reduction in greenhouse gas emissions.The present study presents a blueprint for developing high-performance CSP systems with advanced components and operating conditions. It demonstrates the promising potential of the proposed CSP-TES system, a viable, efficient, sustainable, and cost-effective technology for power generation. This technology will enable us to address the global transition towards clean energy.

RESEARCH OF PHASE FORMATION IN TRANSPARENT GLASS-CERAMIC PROTECTIVE COATINGS FOR CERAMOGRANITE

The perspective of the development and introduction of porcelain stoneware by domestic producers using natural raw materials from the subsoil of Ukraine for the needs of the raw material and fuel-energy complex in the conditions of military operations has been established. The need to create new types of ceramic granite was determined, taking into account new approaches, regarding the use of alternative raw materials and modern technological principles of creating nanostructured glass materials. The purpose and tasks of the work are formulated, which determine the need to study the structure and phase composition of porcelain stoneware under the conditions of high-speed heat treatment. A hypothesis has been formulated regarding the production of transparent wear-resistant protective coatings based on high-calcium alkaline aluminosilicate frits, which consists in the possibility of forming a strengthened optically transparent sytalized glass structure with a high-speed heat treatment mode and the flow of surface crystallization to ensure a wear-resistant structure of the 4th degree. The processes of phase formation that take place during the heat treatment of the base frit and the protective coating for porcelain stoneware have been studied and the priority role of the metastable phase separation of glass in the formation of the sytalized structure has been determined. It was established that the formation of crystallization nuclei by means of metastable phase separation allows for the formation of a sytalized structure of the protective coating for ceramic granite with the content of crystalline phases of anorthite with a size smaller than the wavelength in the visible part of the spectrum and α-corundum in the near-surface layers of the glaze, which simultaneously ensures optical transparency and wear resistance of the developed coating. Transparent glass-ceramic coatings with high operational properties, developed and implemented in the production conditions of PrJSC «KhPZ», will significantly increase the competitiveness of domestic ceramic tiles and contribute to the stabilization of the market in the conditions of sustainable development of the state.

Optimization of steam-methane reforming process using PSA off gas

This study aims to analyze the effect of PSA off gas utilization on fuel processing system combined with PSA (Pressure Swing Adsorption) system to produce more than 99% hydrogen for LT-PEMFC (Low Temperature Proton Exchange Membrane Fuel Cell) supply. An analysis was performed to optimize the operating conditions of a fuel processing system coupled with a PSA system by utilizing PSA off-gas to supply hydrogen to a 10 kW LT-PEMFC system. The performance and efficiency of the entire system were investigated at a steam-methane reactor temperature of 600 °C–800 °C, a water gas conversion reactor temperature of 200 °C–400 °C, a PSA recovery ratio of 60%–95%, a pressure of 1 bar, and 9 bar using Aspen Plus®, Aspen adsorption®, and Aspen Energy Analyzer® simulators. The sensitivities of various parameters affecting the process were analyzed to obtain optimized conditions for the entire system. Simulation results show that the optimal reformer temperature depends on the PSA recovery. The overall maximum efficiency is 78.67% at a process pressure of 9 bar the PSA recovery ratio of 95% and a temperature of 800 °C. In contrast, the highest efficiency under the 1 bar process condition is 70.55%, with an operating temperature of 600 °C and PSA recovery of 95%, which is relatively lower than the 9 bar process. Subsequently, pinch analysis and economic analysis including exergy analysis according to PSA recovery were conducted on these processes, showing that the thermal efficiency of the 9 bar process is relatively higher. The economic analysis indicated that the optimal profit is achieved at a PSA recovery of approximately 70∼75% and more than 40.2% of energy can be saved by utilizing PSA off gas to supply reaction heat for methane-steam reforming.

Machine learning-based lifelong estimation of lithium plating potential: A path to health-aware fastest battery charging

To enable a shift from fossil fuels to renewable and sustainable transport, batteries must allow fast charging and exhibit extended lifetimes—objectives that traditionally conflict. Current charging technologies often compromise one attribute for the other, leading to either inconvenience or diminished resource efficiency in battery-powered vehicles. For lithium-ion batteries, the way to meet both objectives is for the lithium plating potential at the anode surface to remain positive. In this study, we address this challenge by introducing a novel method that involves real-time monitoring and control of the plating potential in lithium-ion battery cells throughout their lifespan. Our experimental results on three-electrode cells reveal that our approach can enable batteries to charge at least 30% faster while almost doubling their lifetime. To facilitate the adoption of these findings in commercial applications, we propose a machine learning-based framework for lifelong plating potential estimation, utilizing readily available battery data from electric vehicles. The resulting model demonstrates high fidelity and robustness under diverse operating conditions, achieving a mean absolute error of merely 3.37 mV. This research outlines a practical methodology to prevent lithium plating and enable the fastest health-conscious battery charging.

Investigation of transonic flows through an idealized ORC turbine vane using Delayed Detached Eddy simulations

An idealized transonic blade configuration is studied using Delayed Detached Eddy Simulations (DDES), with focus on the loss mechanisms associated with the base pressure and turbulent wake development. The working fluid is Novec649, which is commonly used in low temperature Organic Rankine Cycle (ORC) power plants. Due to the molecular complexity of the fluid, a lower pressure ratio and exit Mach number are achieved compared to an air flow through the same geometry, a phenomenon that becomes more pronounced when considering thermodynamic operating conditions that lead to stronger non-ideal gas behavior, and which is well captured by models of standard use in ORC design and analysis, such as Reynolds-Averaged Navier–Stokes (RANS) models. Overall, as the fluid isentropic exponent and the exit Mach number decrease, the losses tend to increase. When performing a breakdown of the losses, the wake region provides the dominant contribution. Unlike RANS models, the DDES resolves the largest turbulent scales in the wake region, allowing fine-detail analysis of the unsteady wake dynamics, namely vortex shedding, and its influence on the loss coefficients. In the low supersonic Mach number range considered (M2∼1–2), the vortex shedding exhibits a flapping motion in the reattachment region behind the trailing edge. The Strouhal number, classically formed with the diameter of the trailing edge, is found to increase with increasing outlet Mach number. However, when introducing a new scaling based on the neck width of the reattachment region, directly related to the shape of the recirculation bubble and the associated reattachment shocks, the Strouhal number collapses to a relatively constant value of about 0.3 in all cases. DDES also shows that, due to the large heat capacity of Novec649, temperature fluctuations in the wake are greatly reduced, leading to the suppression of the so-called energy separation phenomenon occurring in air flows. While RANS simulations capture satisfactorily the main features and global quantities of the flow, they fail in describing the flow around the trailing edge. This results in inaccurate estimates of the back pressure, which ultimately leads to an underestimation of the losses by about 20%. Unsteady RANS simulations can predict the wake unsteadiness, but do not capture the couplings between large coherent structures, the recirculation, and the shocks, also resulting in inaccurate performance predictions. Thus, the present result showcase the importance of using advanced scale-resolving simulations for improved analysis and design of ORC turbines.

Prediction of Corrosion Rate for Carbon Steel Using Regression Model with Commercial LPR Sensor Data

In this study, a model was proposed to predict the corrosion rate (Mils per Year, MPY) of carbon steel in a 3.5% NaCl solution, with the objective of comparing the effectiveness of a commercial LPR sensor against traditional electrochemical methods, using potentiostat-based LPR techniques. The primary factors considered in the experiments were temperature, flow velocity, and pH, tested through a full factorial design to identify the most influential variables. Statistical analysis showed that temperature and flow velocity had a significant effect on corrosion rate, with their interaction having the most substantial impact. In contrast, pH had no statistically significant influence within the tested conditions, likely due to the dominant effects of temperature and flow velocity in the high-salinity environment. The MPY data were validated through Tafel plots, immersion coupon tests, and other electrochemical techniques to confirm the reliability of the measurements. A regression model trained on 54 MPY data points demonstrated high accuracy, achieving a coefficient of determination (R2) of 0.9733. The model also provided reliable predictions for factor combinations excluded from the training dataset. Additionally, scenario-based evaluations highlighted the model’s performance under simulated operating conditions, while revealing challenges related to sensor contamination during long-term use. These findings emphasize the potential of commercial LPR sensors as effective tools for real-time corrosion monitoring and demonstrate the utility of the regression model in marine environments.

Unraveling Ion Migration Mechanisms under Operating Conditions in Perovskite Solar Cells by Variable-Load Transient Photoelectric Technique.

Ion migration in perovskite solar cells (PSCs) significantly impacts their photoelectric performance and physicochemical stability. Existing research has predominantly focused on inhibiting ion migration through chemical strategies or observing it under open-circuit or short-circuit conditions. This focus has led to a limited theoretical understanding and control of ion migration under practical conditions, constraining advances in long-term stability. In this study, we introduce a novel variable-load transient photoelectric technique (VL-TPT) to investigate ion migration dynamics in PSCs under practical operating conditions. Results show that ion accumulation correlates with photogenerated carrier concentration under open-circuit conditions. During operation, ion accumulation decreases with reduced load, because charge is transferred to the external circuit, leading to a reduction in carrier concentration within the device. An unusual increase in interface ions is observed at low loads due to interactions between charges accumulated in the potential well and ions. Introducing FA+ in MA0.75FA0.25PbI3 devices suppresses ion migration in the open-circuit state but accelerates interface ion buildup under operating conditions. These findings provide valuable insights for enhancing device stability and performance.

Parthenium hysterophorus invasive weed valorization into biochar for removal of pharmaceuticals and personal care products: Competitive adsorption analysis via batch and fixed–bed column systems

The proliferation of invasive weeds and emergence of new contaminants have become significant global concern, threatening human–health and environment. This investigation assesses performance of Parthenium hysterophorus weed–derived biochar (HPC and KPC) for removing acetaminophen (ACT) and metronidazole (MET) in single (ACT/MET) and multi–component (ACT + MET) systems in batch and column modes. Synthesized HPC and KPC were characterized through SEM, EDX, XRD, porosimetry, TGA and FTIR analyses. HPC displayed micropores, featuring surface area of 166.62 m2/g, while KPC exhibited mesopores with 146.16 m2/g surface area. The investigation in batch study includes exploring operating conditions like contact time (0–180 min), concentration (0.5–20 mg/L), biochar dose (0.25–4 g/L) and pH (2–12). At optimal conditions (1 h, pH 6.5 and 1 g/L dose), HPC achieved maximum sorption capacity 48.72 mg/g for MET and 32.10 mg/g for ACT, and KPC exhibited 18.41 mg/g for MET and 16.54 mg/g for ACT in batch mode. According to findings, pseudo–second–order and Langmuir models provided accurate–fit for batch experimental data. Furthermore, study also investigated influence of column operating conditions such as bed depth (3–9 cm), flow rate (0.25–1.00 L/h) and concentration (5–20 mg/L). In column, HPC outperformed KPC in removing ACT and MET, with breakthrough data fitting Thomas model. Both systems exhibit synergistic effect in simultaneously removing ACT and MET from multi–pollutant mixture. In summary, converting invasive weeds into biochar and employing it to remove emerging contaminants provides sustainable approach to protecting aquatic environment and invasive weeds management.

Study on the treatment of carbon black for slurry electrodes of all-iron redox flow batteries

All-iron redox flow batteries (IRFBs) are considered as potential energy storage devices due to the abundance of iron and durability. During the charging process, metallic iron is formed from Fe2+ and may block electrolyte paths in the negative porous electrode, decreasing reaction kinetics. Therefore, a slurry electrode using conductive particles in the electrolyte can be the solution to the problem. To study the effect of carbon black on the performance of slurry electrode, various surface modifications of carbon black are carried out to further enhance electrode performance. The surface morphology, X-ray diffraction, and electrochemical properties are investigated. The performance of the IRFB with various types of carbon black is evaluated at different operating conditions. Both acid and heat treatments of Ketjen black show higher performance than pristine Ketjen black. Thermally treated Ketjen black (H-KB) exhibits voltage efficiency, coulombic efficiency, and energy efficiency of 69 %, 95 %, and 65 %, respectively, at 20 mA cm−2. The durability of the IRFB using the H-KB slurry electrode shows an EE decreasing rate of around 1 % after 100 cycles at 20 mA cm−2.