Process System Research Articles

The role of nuclear energy in the sustainable energy system transition: a scoping review into the complexity of decision-making trade-offs and public participation in the United Kingdom

Purpose Nuclear energy is a contested topic, requiring trade-offs in energy independence, ethicality and uncertainty. Anthropogenic climate change complicates these decisions further, with nuclear energy competing with other low-carbon and sustainable energy sources. Decisions about nuclear energy’s role, as part of a sustainable energy system, must be made in cooperation with all stakeholders. However, it is unclear how the public is involved in these decisions in the UK. This study aims to address this gap, exploring the degree to which public participation has occurred in the UK. Design/methodology/approach This paper conducted a scoping review of public participation in UK nuclear energy decision-making in the context of sustainable energy transitions, where the government retains and promotes nuclear energy as part of a sustainable energy system. Following a systematic literary search, this paper reviewed 28 academic and grey literature documents. Findings Public participation has primarily been conducted as consultations rather than active participation. There is limited evidence that consultations have meaningfully contributed to politically and socially responsible (i.e. individuals and groups working together for community benefit) decision-making, with public opinion on nuclear energy’s role being divided and is influenced by how it is framed. Originality/value Social aspects of nuclear energy development have historically received less attention than environmental and economic elements; the role of engagement and participation is relatively rare. Modern literature reviews in this context are largely absent, a gap this paper originally contribute to. This paper suggest ways in which how effective, inclusive engagement process could contribute to a fairer, responsible decision-making process and energy system in the UK.

Residual and enduring effects of cannabis use on cognitive and psychomotor function: A study of adults during unrestricted cannabis use, short-term abstinence, and protracted abstinence.

The impact of cannabis on cognitive and psychomotor function is important to understand, given the role of the endocannabinoid system in these critical processes. The literature has shown robust acute negative effects of cannabis on cognition and psychomotor skills during intoxication, and to a lesser degree, persisting effects following short-term abstinence up to 4 weeks. However, whether these decrements resolve after long-term cessation of use remains unclear. We evaluated cognitive and psychomotor function in 31 adults with current cannabis use during unrestricted use (UNR) and after a 3-day abstinence (RES), 23 adults with former cannabis use (> 90 days abstinent; FU), and 58 nonusing controls (CON) using the cognition and motor batteries of the National Institutes of Health Toolbox. Linear mixed models showed no significant differences in cognitive and motor performance between UNR, RES, and FU groups. Group effects emerged such that CON outperformed UNR on the Oral Reading Recognition Test, and CON outperformed both UNR and RES on the Picture Vocabulary Test. In terms of psychomotor function, FU, RES, and UNR performed better than CON on the Grip Strength Test. In this comprehensive examination of cognitive and psychomotor performance in adults with cannabis use with 3 days to > 90 days of abstinence, our results indicated that the cognitive impacts of chronic, heavy cannabis use are observable during short-term abstinence but remit after > 90 days of abstinence. This highlights widespread impacts of cannabis use abstinence across cognitive and psychomotor domains. Future studies are needed to evaluate whether these effects are also observable with use reduction, as opposed to abstinence. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Lithium battery state of charge estimation based on improved variable forgetting factor recursive least squares method and adaptive Kalman filter joint algorithm

As one of the core functions of the battery management system, battery state of charge (SOC) estimation is crucial to battery life and safety. As the traditional recursive least squares method cannot adapt well to complex variable current conditions, this paper proposes a SOC estimation method that combines the improved variable forgetting factor recursive least squares (IVFFRLS) and the adaptive extended Kalman filter (AEKF). First, IVFFRLS removes the rounding operation of the original algorithm to improve the sensitivity to errors and uses a genetic algorithm to optimize the upper and lower bounds of the variable forgetting factor and the sensitivity coefficient to improve the accuracy of the VFFRLS algorithm. Meanwhile, AEKF introduces a noise covariance adaptive update link based on the covariance matching method to correct the system's process noise Q and measurement noise R in real time to improve the SOC estimation accuracy. Based on the second-order RC equivalent circuit model, the method proposed in this paper has good accuracy and robustness under four different working conditions. The experimental results show that compared with traditional methods, the proposed IVFFRLS-AEKF algorithm has higher SOC estimation accuracy and better robustness.

Influence of gate cutoff effect on flow mode conversion and energy dissipation during power-off of prototype tubular pump system

Understanding the cutoff effect of gates is essential for enhancing the overall quality of the pump system's power-off process, minimizing energy losses, and reducing potential risks associated with hydraulic transients. In this study, both numerical simulations and experimental investigations were conducted on the power-off process of a tubular pump system, considering scenarios with and without gate functionality. The simulations utilized a dynamic mesh method to model gate movement, incorporated the torque balance equation to determine the real-time impeller speed, and applied the 3D-VOF method for free surface modeling in reservoirs. Power-off experiments were performed on a model pump system and a prototype pump system to validate the numerical simulation results. To elucidate the mechanism of the gate's cutoff effect, flow modes during the power-off process were categorized based on the four-quadrant static test results of the pump, revealing the deviations between transient and static characteristics. By comparing the transient flow structures of the pump system under different gate operating states, specific energy dissipation behaviors during gate cutoff were analyzed. The research findings enhance the understanding of hydraulic transients, which is essential for developing more sustainable and resilient energy systems.

Rancang Bangun Mesin Pencacah Plastik Pet dengan Kapasitas 20 Kg/Jam

Shredding is one of the common recycling methods used for plastic waste processing. Along with the development of the era, conventional tools have begun to change to semi-automatic. Therefore, a shredding machine is needed for plastic waste processing with an automatic sensor system to facilitate operation. This design aims to determine the performance of a PET plastic shredding machine with the shredder shredding method. Pahl and Beitz is the method used in making this tool. In accordance with the method applied, the manufacture of the tool starts from planning, concept design, shape design, detailed design, documentation creation and realization of the tool. The testing process is carried out by testing the function of the machine and the function of the automatic sensor. The designed shredder machine has the following specifications: Dimensions of the tool are 950 x 365 x 1060 mm, capacity is 20 kg/hour, 3 phase ½ HP dynamo motor, rotation speed is 70 rpm, number of blades is 14 and material used on the blade is AISI 1080. The test results of this tool show that the tool can work to shred PET plastic, can shred 1 kg of plastic bottles in 2 minutes 45 seconds, the first shredded result is 150 mm maximum smallest size is 16 mm with 3 shredding processes, and can be operated with a sensor control system for the tool's work process. Keywords: shredding machine, garbage, plastic

A comprehensive decision-making approach for the application of biochar in agriculture to enhance water security: A GIS-AHP based approach

In the context of climate change, biochar application is a promising approach to mitigate the adverse effects of climate change on agriculture. However, the selection of suitable biochar produced from food waste and optimization of loading rates to improve soil quality remains a significant challenge. This study explores the potential impact of biochar application using an integrated analytical hierarchy process (AHP) and geographical information system (GIS) approach. The study first aims to develop an AHP model to prioritize the appropriate biochar source and dosage for soil amendment. The different biochar sources considered are: peas pod shell, pistachio shell, and mixed vegetable waste. The AHP design evaluated the weight percentage of different types of biochar amendments ranging from 0 % to 8 % based on soil quality, nutrient analysis and water retention capacity. Furthermore, an integrated spatial analysis case study was conducted for fodder farms across Qatar using GIS mapping with seasonal variation to evaluate the impact of biochar on water management. According to the AHP decision making, 2 % mixed vegetable waste biochar achieved the goal with the highest priority score, with a value of 0.29, followed by 2 % pistachio shell biochar with a score of 0.22. This is attributed to the high water retention rate determined from the experimental study. The 2% biochar amendment retained 20 % more water compared to the 0 % biochar. Results from the GIS mapping identified priority areas for improving water retention and soil quality. The evapotranspiration maps for winter and summer generated using GIS provide valuable insights into the spatial disributio of biochar application across Qatar fodder farms. The outcomes may encourage policymakers and stakeholders to consider valorizing food waste into biochar.

PID Controller Design for an E. coli Fed-Batch Fermentation Process System Using Chaotic Electromagnetic Field Optimization

This paper presents an optimal tuning of a proportional integral differential (PID) controller used to maintain glucose concentration at a desired set point. The PID controller synthesizes an appropriate feed rate profile for an E. coli fed-batch cultivation process. Mathematical models are developed based on dynamic mass balance equations for biomass, substrate, and product concentration of the E. coli BL21(DE3)pPhyt109 fed-batch cultivation for bacterial phytase extracellular production. For model parameter identification and PID tuning, a hybrid metaheuristic technique—chaotic electromagnetic field optimization (CEFO)—is proposed. In the hybridization, a chaotic map is used for the generation of a new electromagnetic particle instead of the electromagnetic field optimization (EFO) search strategy. The CEFO combines the exploitation capability of the EFO algorithm and the exploration power of ten different chaotic maps. The comparison of the results with classical EFO shows the superior behaviour of the designed CEFO. An improvement of 30% of the objective function is achieved by applying CEFO. Based on the obtained mathematical models, 10 PID controllers are tuned. The simulation experiments show that the designed controllers are robust, resulting in a good control system performance. The closed-loop transient responses for the corresponding controllers are similar to the estimated models. The settling time of the control system based on the third PID controller for all estimated models is approximately 9 min and the overshoot is approximately 15%. The proposed CEFO algorithm can be considered an effective methodology for mathematical modelling and achievement of high quality and better performance of the designed closed-loop system for cultivation processes.

Bipolar membrane electrodialysis for amine regeneration from amine chloride stream: Closing the amine utilization loop

The amine-based CO2 capture & mineral carbonation (CCMC) using alkaline slag emerges as a decarbonation means. However, being the most costly component in the process, amine is consumed in large quantity yet its regeneration is overlooked. Thus, to close the material utilization loop, this work proposed the bipolar membrane electrodialysis (BMED) technology for amine regeneration from its chloride streams. With customized BMED configurations, the recovery of two different amines(monoethanolamine (MEA) & 2-(Diethylamino)ethanol (DEAE)) was investigated respectively to reveal the separation mechanisms. This novel concept was firstly proved with a three-compartment configuration, where the cations (MEA+ or DEAE+) can pass through the cation exchange membrane and react with OH− generated by the bipolar membrane thus producing pure amine. The respective MEA and DEAE regeneration reached up to 95.1 % and 92.4 % within 10 h; while the yield of a useful byproduct 1.8 wt% HCl reached ∼ 71 %, which can be reused in CCMC. The results showed that the membrane played a key role: with standard anion exchange membrane (AEM), the Cl− transfer rate decreased with increasing feed concentration. Although the proton blocking AEM avoided H+ cross-over, the Cl− transfer was stable but exhibited up to 2.5-times lower transfer rate. Via a comprehensive parametric study, a modest current density (150 A/m2) was chosen to avoid significant energy penalty, corresponding to a power consumption of 10.3 kWh/(kg amine). Compared to the acid model, the base model of two-compartment configuration, had 2x higher amine yield and higher energy efficiency. This study revealed the performance-limiting factors in BMED, inspiring future design of efficient amine regeneration system for closed-loop CCMC process and contributing to sustainable processing towards carbon neutrality.

Unilateral consensus: Legitimation as a societal phenomenon in Luhmannian systems theory

AbstractFor Niklas Luhmann, the political system's primary function is the establishment of decision premises for future decisions, with these decisions being applied across different societal subsystems. However, Luhmann recognized that this resulted in the political system running the risk of de‐differentiating itself when producing collectively binding decisions. Luhmann solved this problem by restricting the political system's role, relegating it to society's sidelines. But there are many examples of where we would want the benefits of collectively binding decisions in society, such as planning systems. This raises the question how can we have decisions that serve as premises for future decisions across societal subsystems while maintaining each system's differentiation and legitimacy? To answer this question, we will redouble our focus on meaning in considering each system's legitimation process. Through the lens of meaning, we will show how legitimation can bring independent systems to make shared decisions, thus producing unilateral consensus.

Modeling and optimization for the continuous catalytic reforming process based on the hybrid surrogate optimization model

To address the modeling and optimization challenges of the complex reaction system in the continuous catalytic reforming process, a new integrated simulation and optimization framework is presented. First, a detailed mechanism model is established based on a reaction network involving 32 components and 50 reactions, coupled with mass transfer, heat transfer, pressure drop, and catalyst deactivation equations. Then, to solve the differential-algebraic equations in the mechanism model, a multi-objective hybrid optimization method with the adaptive infill strategy is introduced. GAMS and MATLAB are integrated to perform a joint iterative solution. Finally, two cases are conducted with the proposed algorithm. Results show that the mechanism model calculation deviations are below 4 % of reactor temperature, pressure, and composition distribution, and the Pareto front of various production plans is obtained. The accurate simulation and rapid trade-off optimization among the key goals can be achieved to provide scientific decision support for enterprise production.

A compliance assessment system for Incident Management process

The Incident Management (IM) process is one of the core activities for increasing the overall security level of organizations and better responding to cyber attacks. Different security frameworks (such as ITIL and ISO 27035) provide guidelines for designing and properly implementing an effective IM process. Currently, assessing the compliance of the actual process implemented by an organization with such frameworks is a complex task. The assessment is mainly manually performed and requires much effort in the analysis and evaluation. In this paper, we first propose a taxonomy of compliance deviations to classify and prioritize the impacts of non-compliant causes. We combine trace alignment techniques with a new proposed cost model for the analysis of process deviations rather than process traces to prioritize interventions. We put these contributions into use in a system that automatically assesses the IM process compliance with a reference process model (e.g., the one described in the chosen security framework). It supports the auditor with increased awareness of process issues to make more focused decisions and improve the process’s effectiveness. We propose a benchmark validation for the model, and we show the system’s capability through a usage scenario based on a publicly available dataset of a real IM log. The source code of all components, including the code used for benchmarking, is publicly available as open source on GitHub.

Completely noninvasive multi-analyte monitoring system for cell culture processes.

Although online monitoring of dissolved O2, pH, and dissolved CO2 is critical in bioprocesses, nearly all existing technologies require some level of direct contact with the cell culture environment, posing risks of contamination. This study addresses the need for an accurate, and completely noninvasive technique for simultaneous measurement of these analytes. A "non-contact" technique for simultaneous monitoring of dissolved O2, pH, and dissolved CO2 was developed. Instead of direct contact with the culture media, the measurements were made through permeable membranes via either a sampling port in the culture vessel wall or a flow cell. The efficacy of the "non-contact" technique was validated in Escherichia coli (E.coli), Chinese hamster ovary (CHO) culture processes, and dynamic environments created by sparging gases in cell culture medium. The measurements obtained through the developed techniques were comparable to those obtained through control methods. The noninvasive monitoring system can offer accurate, and contamination-minimized monitoring of critical process parameters including dissolved O2, pH, and dissolved CO2. These advancements will enhance the control and optimization of cell culture processes, promising improved cell culture performance.

Stability analysis of rolling mill system for flexible rolling process based on maximum Lyapunov exponent

Flexible rolling technology is the current development trend of strip production industry. However, due to the simultaneous change of mechanical, process and strip specification parameters in the flexible rolling process, the motion state of the system is difficult to analyze and stability control is hard to achieve. In this paper, the active motion characteristics of rolls in flexible rolling technology are considered, and the dynamic rolling process model is established to reflect the influence mechanism of process and specification parameters on the dynamic rolling force. The dynamic model of a 4-high rolling mill was developed and the structure-process-strip coupling strategy was applied to couple the models. The Runge-Kutta method was applied to solve the dynamic equation to obtain the maximum Lyapunov exponential spectrum for a single parameter variation. It is noteworthy that the two-parameter dynamics method was adopted to solve the dynamics on the two-parameter plane considering the nature of simultaneous variation of the system parameters, which solves the limitations of the traditional analytical method and is suitable for the application of the flexible rolling system. The results suggest that the parameters influence the motion state in the form of coupling, the influence pattern of each parameter on the stability is clarified, the evolution of the stable domain under the effect of parameter coupling is revealed, and the parameter matching strategy is determined. The results will provide a solution for the system parameter setting of flexible rolling technology and a theoretical reference for enhancing the stability of the rolling mill.

Implementation of Continuous Improvement (CI) in the Management of KKNI UIN Saizu Purwokerto Curriculum through the PPEPP Model

This study aims to analyze the management of the KKNI curriculum implemented at UIN Saizu Purwokerto and whether it has met continuous improvement (CI) with the model set out in SPMI, namely PPEPP which consists of curriculum determination, curriculum implementation, curriculum implementation evaluation, curriculum implementation control and curriculum improvement. This research is field research with a qualitative paradigm by exploring data from data sources of curriculum documents KKNI UIN Saizu Purwokerto and interview results from deputy Dean I for academic and learning affairs. The data were analyzed by qualitative descriptive analysis. The results of this study showed that the management of the KKNI curriculum at UIN Saizu Purwokerto applies the PPEPP model to meet continuous improvement (CI), especially in the process approach and system approach. Curriculum determination through the stages of preparing the drafting team, needs analysis, graduate profiles, learning outcomes, study materials, courses, credit weights, curriculum structure, curriculum draft review, and curriculum determination. The implementation of the curriculum includes the management of learning, courses, educators/lecturers, and education staff. Curriculum evaluation is carried out by formative evaluation and summative evaluation. Curriculum control is grouped into the control of faculties and universities as education providers. The curriculum development of UIN Saizu Purwokerto is carried out by looking at the fulfillment of analysis on graduate profiles, SKL CPL, course determination, course changes, content/topic/theme, depth of study, weight of credits, and distribution of courses.

A novel fault detection and identification method for complex chemical processes based on OSCAE and CNN

The safety and reliability of chemical processes are of paramount importance. However, due to the complicated heat, mass, and momentum transfer processes coupled with chemical reactions, and the interrelated effects among various equipment units, it is difficult to accurately detect and identify faults occurring in the chemical system. This study proposes an innovative fault diagnosis framework specifically designed for chemical systems. A method based on orthogonal self-attention convolutional autoencoder (OSCAE) is constructed for fault detection. The convolutional autoencoder is combined with an orthogonal attention mechanism to extract time-series characteristic information of the operational state, thereby achieving precise detection of fault conditions. Additionally, a convolutional neural network (CNN) model uses both raw signals and data reconstructed by OSCAE to identify different faults, which enhances the features of the input and enables highly accurate fault identification. The effectiveness and robustness of the propose method is validated with simulation data of our self-established chemical distillation system and the publicly available Tennessee Eastman process system. The diagnosis efficacy in fault detection and identification is validated by applying fault detection metrics, high-dimensional feature visualizations, and confusion matrix analyses across two case studies. This paper not only provides an effective diagnostic framework for chemical systems but also offers a usable benchmark dataset for chemical distillation systems to the academic community, with the hope that the research content can enhance the stability and reliability of chemical processes.

Dynamic data reconciliation based on elman neural network and particle filter

In the process of modern industries, complex nonlinear dynamic systems present high requirements for measured data. In the actual industrial process system, the measurement data obtained by sensors will inevitably be subject to noise disturbances from the equipment itself or from the outside environment. These noise disturbances will deteriorate the dynamic performance of the system to a certain extent and affect the industrial production. Particle filter (PF) can be used to infer the accurate outputs of nonlinear dynamic system from the contaminated measurement data, but PF is limited to the pre-known state space model. In the actual industrial process, it is difficult to summarize the internal behavior of the system and obtain the pre-known state space model. Therefore, it is impossible to directly use PF in the nonlinear dynamic system with unknown model. In order to solve the above problems, this paper proposes a dynamic data reconciliation method called ENN-PF, which combines Elman neural network (ENN) data-driven modeling with PF. In this method, ENN is used for data-driven modeling, that is, the system model is dynamically identified by using the input and output data of the system, and then the dynamic data reconciliation is carried out by using PF according to the model identified by ENN. Finally, the proposed ENN-PF method is validated by simulations and practical experiments to effectively reduce the interference of measurement noise and improve the dynamic performance of the system.

Analysis of Aluminum Alloy Double-Pulse MIG Welding Arc Signal Characteristics Based on Broadband Mode Decomposition

Welding voltage and current in arc signals are directly related to arc stability and welding quality. Process experiments with different parameters were organized according to the orthogonal experimental design method by constructing an aluminum alloy double-pulse metal inert gas (MIG) welding arc electric signal test platform. The data acquisition system of the aluminum alloy MIG welding process was established to obtain real-time arc signal information reflecting the welding process. The aluminum alloy’s collected double-pulse arc current signals are decomposed adaptively by broadband mode decomposition (BMD). The direct current (DC) signal, pulse signal, distortion signal, ripple signal, and noise signal are separated and extracted, and the composite multiscale fuzzy entropy (CMFE) is calculated for the component set of the electrical signal. The experimental results show that the current waveform obtained by the double-pulse MIG welding current signal is consistent with the corresponding weld forming diagram. Simultaneously, the composite multiscale fuzzy entropy is calculated for the arc characteristic parameters. The rationality of matching process parameters and arc stability of aluminum alloy's double-pulse MIG welding were evaluated.

LIFE CYCLE ANALYSIS OF BEVERAGE PACKAGING

Plastic is the leading food and item packaging material due to its lightweight characteristics. However, there have been alarming concerns over the past years since the large-scale introduction of plastic after the Second World War, and a total of 8.3 billion metric tons have been produced. This research aims to compare the environmental impact of the packaging design of several consumer products using life cycle analysis (LCA). Based on the openLCA open-source software, three beverage packaging types were compared: plastic bottles, glass bottles, and aluminium cans. The life cycle inventory (LCI) must be identified based on case studies, literature reviews and relevant assumptions to obtain the result. Then, each beverage packagings flows, process and product system was also required to be identified to run the openLCA software. The three types of packaging was compared within each CML category in terms of impact. The CML stands for "Centrum voor Milieukunde Leiden". It is a research institute of the Centre for Environmental Studies at Leiden University located in the Netherlands and a procedure used to estimate the measure of environmental impact caused by the product. Based on the CML eleven impact categories, the plastic bottle was ranked as the most impactful towards the environment, followed by glass bottles and aluminium cans as the least impactful. Other than that, it may be due to the quantity of material being used, the effect of the material during processing, and the recyclable ability.

Energy-efficient Vienna rectifier for electric vehicle battery charging stations

Global DC fast-charging infrastructure is being rapidly developed to accommodate the ever-increasing demand from the electric vehicle market. A major complication in the electric power system's process is the proliferation of ultra-fast charging (UFC) stations, which are known for their enormous power consumption and unpredictable, intermittent performance. By implementing grid-supportive features and ensuring an improved power consumption profile for the grid, installing regional energy storage can solve these challenges. This study presents a control approach for managing the grid-side AC/DC converters of rapid charging stations focused on future-oriented regulation. The paper primarily concentrates on various Vienna rectifier topologies. The technology, characteristics, benefits, and operational aspects of Vienna rectifier topologies are vital to improving the performance, efficiency, and grid integration of electric vehicle charging systems. Fast charging, grid stability, energy economy, and the smooth integration of electric vehicles into the electrical grid are all made possible by Vienna rectifiers. When used in battery energy storage systems (BESS) for electric vehicle charging infrastructure, Vienna rectifiers allow for effective discharge and charging of the batteries. The configurations and assessments of these converters are examined, assessed, and compared based on power output parameters, element count, power factor, THD, and efficiency. The Vienna rectifier has been identified as the best suitable DC fast-charging converter architecture for power levels exceeding 15 kW due to its exceptional efficiency, limited output voltage ripples, high power density, reduced current ripples, and reliable performance. Research on ways to improve electric vehicle charging infrastructure can be spurred by a better grasp of the Vienna rectifier's technological complexities and performance benefits, leading to greener and more efficient transportation options. As a result, the system's power density will eventually rise and elemental stress will decrease.

A one-pot hydrothermal synthesis of morphologically controllable yolk-shell structured CoFe glycerate spheres for oxygen evolution reaction

CoFe-based catalysts are efficient electrocatalysts for the oxygen evolution reaction (OER) in alkaline media. Here, we present a simple one-pot hydrothermal method for synthesizing a series of CoFe glycerates with controllable surface morphologies and investigate their potential as highly efficient catalysts for the OER in alkaline media. These CoFe glycerates exhibit a unique yolk-shell microsphere structure assembled from ultrathin nanosheets. The adjustment of the surface nanosheet size is achieved by varying the CoFe ratio, ensuring a more efficient electrocatalytic system for the OER process. Due to the abundant active sites provided by the yolk-shell structure and interleaved ultrathin nanosheets, Co3Fe1 glycerate (Co3Fe1 gly) demonstrates a low overpotential (283 mV) and a small Tafel slope (44.61 mV dec−1) at 10 mA cm−2. Additionally, Co3Fe1 gly exhibits excellent durability in alkaline electrolytes. Moreover, a series of characterizations demonstrate that the active sites of Co3Fe1 gly are the high-valence Co species generated during the OER process. This study opens a promising avenue for utilizing efficient and low-cost electrocatalysts to enhance OER performance.