Effects of plasmapheresis frequency on health status and exercise performance in men: A randomized controlled trial.

BACKGROUND AND OBJECTIVES: Most research studies on the effects of repeated plasma donation are observational with different study limitations, resulting in high uncertainty on the link between repeated plasma donation and health consequences. Here, we prospectively investigated the safety of intensive or less intensive plasma donation protocols. MATERIALS AND METHODS: Sixty-three male subjects participated in this randomized controlled trial and were divided into low-frequency (LF, once/month, n = 16), high-frequency (HF, three times/month, n = 16), very high-frequency (VHF, two times/week, n = 16) and a placebo (P, once/month, n = 15) groups. Biochemical, haematological, clinical, physiological and exercise-related data were collected before (D0), after 1½ months (D42) and after 3 months (D84) of donation. RESULTS: In VHF, red blood cells, haemoglobin and haematocrit levels decreased while reticulocyte levels increased from D0 to D84. In both HF and VHF, plasma ferritin levels were lower at D42 and D84 compared to D0. In VHF, plasma levels of albumin, immunoglobulin G (IgG), immunoglobulin A (IgA) and immunoglobulin M (IgM) dropped from D0 to D42 and remained lower at D84 than at D0. In HF, plasma IgG, IgA and IgM were lower at D42, and IgG and IgM were lower at D84, compared to D0. Few adverse events were reported in HF and VHF. Repeated plasma donation had no effect on blood pressure, body composition or exercise performance. CONCLUSION: VHF plasmapheresis may result in a large reduction in ferritin and IgG levels. HF and VHF plasmapheresis may result in little to no difference in other biochemical, haematological, clinical, physiological and exercise-related parameters.

Design and Exploration of Benzene Like Azobis Triazoles for Long-range Push-Pull Photo-Switching Attributes.

This research paper presents a comprehensive study on the design and photovoltaic parameters of azobenzene type 24 photo switches (PSs) of triazole by density functional theory (DFT). The focus was on investigating how to create a long-range push-pull effect of different substituents on the PS properties for their application in photovoltaics by further substituent decoration. Their range of values for the maximum wavelength (λmax) ranged 315-556 nm while their HOMO-LUMO energies (Egaps) were 0.57-6.35eV. The stability of the PS was evaluated by measuring hardness (η) and softness (σ) values. Additionally, photovoltaic parameters such as open-circuit voltage (Voc), short-circuit current density (Jsc), fill factor (FF), and maximum power (Pmax) were calculated to assess the performance of the PS as photovoltaic materials. The results revealed that PSs 6 exhibited promising photovoltaic parameters to include Voc values ranging from 0.4-1.63eV, FF values ranging from 0.5438-0.929, Jsc values ranging from 19.27-50.75 mA/cm2, and Pmax values ranging from 14.72-75.91W. This indicates its potential as an efficient light-harvesting material for photovoltaic applications. Moreover, this study presents a pioneering investigation on the correlation between rotational velocity (R) and Mayer bond index (MBI) for the first time. The findings revealed a significant correlation between R and MBI, providing valuable insights into the structural dynamics of the PS. This novel finding opens up new avenues for understanding the structural dynamics of PS and their potential applications in various fields, including photovoltaics. The study provides valuable insights into the structure-property relationships of azobenzene-based PS and their suitability for photovoltaic devices. Further investigations are warranted to optimize the design of the PS, enhance their photovoltaic performance, and explore the underlying mechanisms of the correlation between R and MBIs.

Maximum power in evolution, ecology and economics.

Ludwig Boltzmann suggested that natural selection was fundamentally a struggle among organisms for available energy. Alfred Lotka argued that organisms that capture and use more energy than their competition will have a selective advantage in the evolutionary process, i.e. the Darwinian notion of evolution was based on a fundamental, generalized energy principle. He extended this general principle from the energetics of a single organism or species to the energetics of entire energy pathways through ecosystems. Howard Odum and Richard Pinkerton, building on Lotka, extended this concept to 'The maximum power principle' and applied it to many biological and physical systems including human economies. We examine this history and how these ideas relate to concepts from other disciplines including philosophy. But there has been considerable confusion in understanding and applying these concepts which we attempt to resolve while providing various examples from routine life and discussing some unresolved issues. This article is part of the theme issue 'Thermodynamics 2.0: Bridging the natural and social sciences (Part 2)'.

PV Panel Model Parameter Estimation by Using Neural Network.

Photovoltaic (PV) panels have been widely used as one of the solutions for green energy sources. Performance monitoring, fault diagnosis, and Control of Operation at Maximum Power Point (MPP) of PV panels became one of the popular research topics in the past. Model parameters could reflect the health conditions of a PV panel, and model parameter estimation can be applied to PV panel fault diagnosis. In this paper, we will propose a new algorithm for PV panel model parameters estimation by using a Neural Network (ANN) with a Numerical Current Prediction (NCP) layer. Output voltage and current signals (VI) after load perturbation are observed. An ANN is trained to estimate the PV panel model parameters, which is then fined tuned by the NCP to improve the accuracy to about 6%. During the testing stage, VI signals are input into the proposed ANN-NCP system. PV panel model parameters can then be estimated by the proposed algorithms, and the estimated model parameters can be then used for fault detection, health monitoring, and tracking operating points for MPP conditions.

Hybrid Control of the DC Microgrid Using Deep Neural Networks and Global Terminal Sliding Mode Control with the Exponential Reaching Law.

The direct current (DC) microgrid is one of the key research areas for our advancement toward carbon-free energy production. In this paper, a two-step controller is designed for the DC microgrid using a combination of the deep neural network (DNN) and exponential reaching law-based global terminal sliding mode control (ERL-GTSMC). The DC microgrid under consideration involves multiple renewable sources (wind, PV) and an energy storage unit (ESU) connected to a 700 V DC bus and a 4-12 kW residential load. The proposed control method eliminates the chattering phenomenon and offers quick reaching time by utilizing the exponential reaching law (ERL). In the two-step control configuration, first, DNNs are used to find maximum power point tracking (MPPT) reference values, and then ERL-based GTSMC is utilized to track the reference values. The real dynamics of energy sources and the DC bus are mathematically modeled, which increases the system's complexity. Through the use of Lyapunov stability criteria, the stability of the control system is examined. The effectiveness of the suggested hybrid control algorithm has been examined using MATLAB simulations. The proposed framework has been compared to traditional sliding mode control and terminal sliding mode control to showcase its superiority and robustness. Experimental tests based on the hardware-in-the-loop (HIL) setup are then conducted using 32-bit TMS320F28379D microcontrollers. Both MATLAB and HIL results show strong performance under a range of environmental circumstances and system uncertainties.

The Design of a Circularly Polarized Antenna Array with Flat-Top Beam for an Electronic Toll Collection System.

Electronic toll collection (ETC), known as a non-stop toll collection system which can automatically realize payment by setting the identification antenna at the entrance, is always suffering from information exchange interruption caused by beam switching. A circularly polarized sector beam antenna array operating at 5.8 GHz with flat-top coverage is proposed, based on the weighted constrained method of the maximum power transmission efficiency (WCMMPTE). By setting the test receiving antennas at the specific angles of the ETC antenna array to be designed, constraints on the received power are introduced to control the radiation pattern and obtain the optimized distribution of excitations for antenna elements. A 1-to-16 feeding network, based on the microstrip transmission line theory is designed to feed a 4 × 4 antenna array. Simulation results show that the half-power beamwidth covers an angular range of -30° to 30° while the axial ratio is below 3dB, which meets the ETC requirements. Furthermore, the gain fluctuation among the needed range of -30° to 30° is lower than 0.7 dB, which is suitable for the ETC system to achieve a stable signal strength and uninterrupted communication.

A Printed Dipole Array with Bidirectional Endfire Radiation for Tunnel Communication.

Tunnel communication always suffers from path loss and multipath effects caused by surrounding walls. Meanwhile, the traditional leaky coaxial cables are expensive to deploy, inconvenient to operate, and difficult to maintain, leading to many problems in practical use. To solve the abovementioned problems, a low-profile printed dipole array operating at 3.5 GHz with bidirectional endfire radiation is designed based on the method of maximum power transmission efficiency (MMPTE). By setting two virtual test receiving dipoles at the two opposite endfire directions and then maximizing the power transmission efficiency between the printed dipole array to be designed and the test receiving antennas, the optimal amplitudes and phases for the array elements are obtained. Based on the optimal distributions of excitations, the simulation results show that the proposed eight-element printed dipole array can simultaneously generate two mirrored endfire beams towards opposite directions. Furthermore, the corresponding normalized cross-polarization levels are lower than -22.3 dBi both in the azimuth and elevation planes. The peak endfire gain is 10.7 dBi with maintenance of higher than 10 dBi from 3.23 GHz to 3.66 GHz, which is suitable for tunnel communication.

A Compact and Efficient Boost Converter in a 28 nm CMOS with 90 mV Self-Startup and Maximum Output Voltage Tracking ZCS for Thermoelectric Energy Harvesting.

There are increasing demands for the Internet of Things (IoT), wearable electronics, and medical implants. Wearable devices provide various important daily applications by monitoring real-life human activities. They demand low-cost autonomous operation in a miniaturized form factor, which is challenging to realize using a rechargeable battery. One promising energy source is thermoelectric generators (TEGs), considered the only way to generate a small amount of electric power for the autonomous operation of wearable devices. In this work, we propose a compact and efficient converter system for energy harvesting from TEGs. The system consists of an 83.7% efficient boost converter and a 90 mV self-startup, sharing a single inductor. Innovated techniques are applied to adaptive maximum power point tracking (A-MPPT) and indirect zero current switching (I-ZCS) controllers for efficient operation. The startup circuit is realized using a gain-boosted tri-state buffer, which achieves 69.8% improved gain at the input VIN = 200 mV compared to the conventional approach. To extract the maximum power, we use an A-MPPT controller based on a simple capacitive divider, achieving 95.2% tracking efficiency. To address the challenge of realizing accurate voltage or current sensors, we propose an I-ZCS controller based on a new concept of maximum output voltage tracking (MOVT). The integrated circuit (IC) is fabricated using a 28 nm CMOS in a compact chip area of 0.03 mm2. The compact size, which has not been obtained with previous designs, is suitable for wearable device applications. Measured results show successful startup operation at an ultralow input, VIN = 90 mV. A peak conversion efficiency of 85.9% is achieved for the output of 1.07 mW.

Power Gain from Energy Harvesting Sources at High MPPT Sampling Rates.

Energy harvesting (EH) sources require the tracking of their maximum power point (MPP) to ensure that maximum energy is captured. This tracking process, performed by an MPP tracker (MPPT), is performed by periodically measuring the EH transducer's output at a given sampling rate. The harvested power as a function of the sampling parameters has been analyzed in a few works, but the power gain achieved with respect to the case of a much slower sampling rate than the EH source's frequency has not been assessed so far. In this work, simple expressions are obtained that predict this gain assuming a Thévenin equivalent for the EH transducer. It is shown that the power gain depends on the relationship between the square of AC to DC open circuit voltage of the EH transducer. On the other hand, it is proven that harvested power increases, using a suitable constant signal for the MPP voltage instead of tracking the MPP at a low sampling rate. Experimental results confirmed the theoretical predictions. First, a function generator with a series resistor of 1 kΩ was used, emulating a generic Thévenin equivalent EH. Three waveform types were used (sinus, square, and triangular) with a DC voltage of 2.5 V and AC rms voltage of 0.83 V. A commercial MPPT with a fixed sampling rate of 3 Hz was used and the frequency of the waveforms was changed from 50 mHz to 50 Hz, thus effectively emulating different sampling rates. Experimental power gains of 11.1%, 20.7%, and 7.43% were, respectively, achieved for the sinus, square, and triangular waves, mainly agreeing with the theoretical predicted ones. Then, experimental tests were carried out with a wave energy converter (WEC) embedded into a drifter and attached to a linear shaker, with a sinus excitation frequency of 2 Hz and peak-to-peak amplitude of 0.4 g, in order to emulate the drifter's movement under a sea environment. The WEC provided a sinus-like waveform. In this case, another commercial MPPT with a sampling period of 16 s was used for generating a slow sampling rate, whereas a custom MPPT with a sampling rate of 60 Hz was used for generating a high sampling rate. A power gain around 20% was achieved in this case, also agreeing with the predicted gain.

Improving Power Quality in Grid-Connected Photovoltaic Systems: A Comparative Analysis of Model Predictive Control in Three-Level and Two-Level Inverters.

The Single-Stage Grid-Connected Solar Photovoltaic (SSGC-SPV) topology has recently gained significant attention, as it offers promising advantages in terms of reducing overall losses and installation costs. We provide a comprehensive overview of the system components, which include the photovoltaic generator, the inverter, the Incremental Conductance Maximum Power Point Tracking (IC-MPPT) algorithm, and the PI regulator for DC bus voltage control. Moreover, this study presents detailed system configurations and control schemes for two types of inverters: 2L-3PVSI and 3L-3PNPC. In order to perform a comparative study between the two structures, we subjected them to the same irradiation profile using the same grid configuration. The Photovoltaic Array (PVA) irradiance is increased instantaneously, in 0.2 s, from 400 W/m2 to 800 W/m2, is kept at 800 W/m2 for 0.2 s, is then gradually decreased from 800 W/m2 to 200 W/m2 in 0.2 s, is then kept at 200 W/m2 for 0.2 s, and is then finally increased to 1000 W/m2 for 0.2 s. We explain the operational principles of these inverters and describe the various switching states involved in generating output voltages. To achieve effective control, we adopt the Finite Set-Model Predictive Control (FS-MPC) algorithm, due to the benefits of excellent dynamic responsiveness and precise current tracking abilities. This algorithm aims to minimise the cost function, while taking into account the dynamic behaviour of both the PV system and the inverter, including any associated delays. To evaluate the performance of the FS-MPC controller, we compare its application in the three-level inverter configuration with the two-level inverter setup. The DC bus voltage is maintained at 615 V using the PI controller. The objective is to achieve a Total Harmonic Distortion (THD) below 5%, with reference to the IEEE standards. The 2L-3PVSI inverter is above the threshold at an irradiance of 200 W/m2. The 3L-3PNPC inverter offers a great THD percentage, meaning improved quality of the power returned to the grid.

Environmental Sensing in High-Altitude Mountain Ecosystems Powered by Sedimentary Microbial Fuel Cells.

The increasing need for fresh water in a climate change scenario requires remote monitoring of water bodies in high-altitude mountain areas. This study aimed to explore the feasibility of SMFC operation in the presence of low dissolved oxygen concentrations for remote, on-site monitoring of physical environmental parameters in high-altitude mountainous areas. The implemented power management system (PMS) uses a reference SMFC (SMFCRef) to implement a quasi-maximum power point tracking (quasi-MPPT) algorithm to harvest energy stably. As a result, while transmitting in a point-to-point wireless sensor network topology, the system achieves an overall efficiency of 59.6%. Furthermore, the control mechanisms prevent energy waste and maintain a stable voltage despite the microbial fuel cell (MFC)'s high impedance, low time response, and low energy production. Moreover, our system enables a fundamental understanding of environmental systems and their resilience of adaptation strategies by being a low-cost, ecological, and environmentally friendly alternative to power-distributed and dynamic environmental sensing networks in high-altitude mountain ecosystems with anoxic environmental conditions.

Hysteresis in hybrid perovskite indoor photovoltaics.

Halide perovskite indoor photovoltaics (PV) are a viable solution to autonomously power the billions of sensors in the huge technology field of the Internet of Things. However, there exists a knowledge gap in the hysteresis behaviour of these photovoltaic devices under indoor lighting conditions. The present work is the first experimental study dedicated to exploring the degree of hysteresis in halide perovskite indoor photovoltaic devices by carrying out both transient J-V scan and steady state maximum power point tracking (MPPT) measurements. Dependence of hysteresis on device architecture, selection of electron transporting layers and the composition of the perovskite photoactive layers were investigated. Under indoor illumination, the p-i-n MAPbI3-based devices show consistently high power conversion efficiency (PCE) (stabilized PCE) of greater than 30% and negligible hysteresis behaviour, whereas the n-i-p MAPbI3 devices show poor performance (stabilized PCE ∼ 15%) with pronounced hysteresis effect. Our study also reveals that the n-i-p triple cation perovskite devices are more promising (stabilized PCE ∼ 25%) for indoor PV compared to n-i-p MAPbI3 due to their suppressed ion migration effects. It was observed that the divergence of the PCE values estimated from the J-V scan measurements, and the maximum power point tracking method is higher under indoor illumination compared to 1 Sun, and hence for halide perovskite-based indoor PV, the PCE from the MPPT measurements should be prioritized over the J-V scan measurements. The results from our study suggest the following approaches for maximizing the steady state PCE from halide perovskite indoor PV: (i) select perovskite active layer composition with suppressed ion migration effects (such as Cs-containing triple cation perovskites) and (ii) for the perovskite composition such as MAPbI3, where the ion migration is very active, p-i-n architecture with organic charge transport layers is beneficial over the n-i-p architecture with conventional metal oxides (such as TiO2, SnO2) as charge transport layers. This article is part of the theme issue 'Developing resilient energy systems'.

Increased maximum power output may improve speech recognition with bone conduction hearing devices.

OBJECTIVE: To investigate the influence of maximum power output of bone conduction hearing devices on speech recognition in quiet and in noise in experienced users of bone conduction hearing devices. DESIGN: Prospective, randomised cross-over investigation comparing speech recognition performance, subjective sound quality, and device preference between two bone conduction hearing devices with different maximum power outputs. STUDY SAMPLE: Sixteen adult subjects with conductive or mixed hearing loss. RESULTS: Both speech recognition in quiet and speech recognition in noise improved significantly when using the device with high vs. lower maximum power output. Mean improvement in word recognition score in quiet was 10.5% and the mean speech reception threshold in noise improved by 0.9 dB SNR. Compared to the device with lower maximum power output, the sound quality was rated significantly higher with the device with high maximum power output, which was also the device of preference for 81% of the subjects. CONCLUSION: Bone conduction hearing devices with higher maximum power output have the potential to improve speech recognition in both quiet and noisy listening environments.

A New Step in the Optimization of the Chambadal Model of the Carnot Engine.

This paper presents a new step in the optimization of the Chambadal model of the Carnot engine. It allows a sequential optimization of a model with internal irreversibilities. The optimization is performed successively with respect to various objectives (e.g., energy, efficiency, or power when introducing the duration of the cycle). New complementary results are reported, generalizing those recently published in the literature. In addition, the new concept of entropy production action is proposed. This concept induces new optimums concerning energy and power in the presence of internal irreversibilities inversely proportional to the cycle or transformation durations. This promising approach is related to applications but also to fundamental aspects.

Maximum Power Point Tracking Control for Non-Gaussian Wind Energy Conversion System by Using Survival Information Potential.

In this paper, a wind energy conversion system is studied to improve the conversion efficiency and maximize power output. Firstly, a nonlinear state space model is established with respect to shaft current, turbine rotational speed and power output in the wind energy conversion system. As the wind velocity can be descried as a non-Gaussian variable on the system model, the survival information potential is adopted to measure the uncertainty of the stochastic tracking error between the actual wind turbine rotation speed and the reference one. Secondly, to minimize the stochastic tracking error, the control input is obtained by recursively optimizing the performance index function which is constructed with consideration of both survival information potential and control input constraints. To avoid those complex probability formulation, a data driven method is adopted in the process of calculating the survival information potential. Finally, a simulation example is given to illustrate the efficiency of the proposed maximum power point tracking control method. The results demonstrate that by following this method, the actual wind turbine rotation speed can track the reference speed with less time, less overshoot and higher precision, and thus the power output can still be guaranteed under the influence of non-Gaussian wind noises.

Lower limb force-production capacities in alpine skiing disciplines.

Specific force capacities might be a limiting factor for alpine skiing performance, yet there is little consensus on the capabilities in question, and whether they differ between disciplines. We aimed to test discipline (speed and technical) and performance (event-specific world standing) effects on lower limb force-production qualities. National-level skiers (N = 31) performed loaded squat jumps and isometric mid-thigh pulls to detect dynamic force output at extremely low and high velocities and maximum isometric force and rate of force development, respectively. Discipline differences were assessed via a general linear model including performance and allowing for interaction effects, with performance associations further characterized via distinct Pearson's correlations. Jump height did not differentiate disciplines, with absolute power slightly higher in speed athletes (F(1,27)  = 4.42, P = .045, ω2  = 0.10), and neither variables were related to performance. Speed athletes possessed greater dynamic force at low velocities (F0 ; F(1,27)  = 13.8, P < .001, ω2  = 0.17), and greater relative and absolute maximum isometric force (F(1,25)  = 11.19-20.70, ω2  = 0.16-0.22, P < .003). Overall, higher ranked athletes possessed more force-dominant profiles (F(1,27)  = 16.28, ω2  = 0.34; r = 0.60 to 0.67, P < .001) and increased rate of force development characteristics (average and maximum, r = -0.50 to -0.82, P < .048). Very robust associations existed between maximum isometric force and speed performance (r = -0.88, P < .001), but only a trend for higher absolute isometric force in technical athletes (r = -0.49, P = .052). Alpine skiers display a preponderance for dynamic force output at low velocities, and isometric force for speed athletes, which highlights the interest in specific assessment and conditioning practices for ski athletes.

Review of Control Techniques in Microinverters.

The use of renewable energies sources is taking great importance due to the high demand for electricity and the decrease in the use of fossil fuels worldwide. In this context, electricity generation through photovoltaic panels is gaining a lot of interest due to the reduction in installation costs and the rapid advance of the development of new technologies. To minimize or reduce the negative impact of partial shading or mismatches of photovoltaic panels, many researchers have proposed four configurations that depend on the power ranges and the application. The microinverter is a promising solution in photovoltaic systems, due to its high efficiency of Maximum Power Point Tracking and high flexibility. However, there are several challenges to improve microinverter's reliability and conversion efficiency that depend on the proper control design and the power converter design. This paper presents a review of different control strategies in microinverters for different applications. The control strategies are described and compared based on stability, dynamic response, topologies, and control objectives. One of the most important results showed that there is little research regarding the stability and robustness analysis of the reviewed control strategies.

Promising MPPT Methods Combining Metaheuristic, Fuzzy-Logic and ANN Techniques for Grid-Connected Photovoltaic.

This paper addresses the improvement of tracking of the maximum power point upon the variations of the environmental conditions and hence improving photovoltaic efficiency. Rather than the traditional methods of maximum power point tracking, artificial intelligence is utilized to design a high-performance maximum power point tracking control system. In this paper, two artificial intelligence-based maximum power point tracking systems are proposed for grid-connected photovoltaic units. The first design is based on an optimized fuzzy logic control using genetic algorithm and particle swarm optimization for the maximum power point tracking system. In turn, the second design depends on the genetic algorithm-based artificial neural network. Each of the two artificial intelligence-based systems has its privileged response according to the solar radiation and temperature levels. Then, a novel combination of the two designs is introduced to maximize the efficiency of the maximum power point tracking system. The novelty of this paper is to employ the metaheuristic optimization technique with the well-known artificial intelligence techniques to provide a better tracking system to be used to harvest the maximum possible power from photovoltaic (PV) arrays. To affirm the efficiency of the proposed tracking systems, their simulation results are compared with some conventional tracking methods from the literature under different conditions. The findings emphasize their superiority in terms of tracking speed and output DC power, which also improve photovoltaic system efficiency.

Optimal Solutions for Underwater Capacitive Power Transfer.

Capacitive power transfer (CPT) has attracted attention for on-road electric vehicles, autonomous underwater vehicles, and electric ships charging applications. High power transfer capability and high efficiency are the main requirements of a CPT system. This paper proposes three possible solutions to achieve maximum efficiency, maximum power, or conjugate-matching. Each solution expresses the available load power and the efficiency of the CPT system as functions of capacitive coupling parameters and derives the required admittance of the load and the source. The experimental results demonstrated that the available power and the efficiency decrease by the increasing of the frequency from 300 kHz to 1 MHz and the separation distance change from 100 to 300 mm. The maximum efficiency solution gives 83% at 300 kHz and a distance of 100 mm, while the maximum power solution gives the maximum normalized power of 0.994 at the same frequency and distance. The CPT system can provide a good solution to charge electric ships and underwater vehicles over a wide separation distance and low-frequency ranges.

Ibuprofen degradation and energy generation in a microbial fuel cell using a bioanode fabricated from devil fish bone char.

Ibuprofen degradation and energy generation in a single-chamber Microbial Fuel Cell (MFC) were evaluated using a bioanode fabricated from devil fish bone char (BCA) synthesized by calcination in air atmosphere. Its performance was compared with conventional carbon felt (CF). Bone char textural properties were determined by nitrogen adsorption. Before and after, the bacterial colonization on the materials was analyzed by environmental scanning electron microscopy. Energy generation was evaluated by electrochemical techniques as open-circuit potential, linear sweep voltammetry, and electrochemical impedance spectroscopy. Ibuprofen degradation was analyzed by High-Performance Liquid Chromatography-Ultraviolet, and the chemical oxygen demand (COD) removal was measured. Results showed a specific area of 136 m2/g for BCA, having enough space to immobilize microorganisms. The micrographs confirmed the biofilm formation on the electrode materials. Over the 14 days, MFC with BCA reached a maximum power density of 4.26 mW/m2, 175% higher than CF, and an electron transfer resistance 2.1 times lower than it. This coincides with the COD removal and ibuprofen degradation efficiencies, which were 43.6% and 34% for BCA and 31.8% and 27% for CF. Hence, these findings confirmed that BCA in MFC could provide an alternative electrode material for ibuprofen degradation and energy generation.