Discover insights from thousands of peer-reviewed papers on microbial electrochemical systems
John Greenman, Arjuna Mendis, Jiseon You et al.
Frontiers in Robotics and AI · 2021
On the roadmap to building completely autonomous artificial bio-robots, all major aspects of robotic functions, namely, energy generation, processing, sensing, and actuation, need to be self-sustainable and function in the biological realm. Microbial Fuel Cells (MFCs) provide a platform technology for achieving this goal. In a series of experiments, we demonstrate that MFCs can be used as living, autonomous sensors in robotics. In this work, we focus on thermal sensing that is akin to thermoreceptors in mammalian entities. We therefore designed and tested an MFC-based thermosensor system for utilization within artificial bio-robots such as EcoBots. In open-loop sensor characterization, with a controlled load resistance and feed rate, the MFC thermoreceptor was able to detect stimuli of 1 min directed from a distance of 10 cm causing a temperature rise of ∼1°C at the thermoreceptor. The thermoreceptor responded to continuous stimuli with a minimum interval of 384 s. In a practical demonstration, a mobile robot was fitted with two artificial thermosensors, as environmental thermal detectors for thermotactic application, mimicking thermotaxis in biology. In closed-loop applications, continuous thermal stimuli were detected at a minimum time interval of 160 s, without the need for complete thermoreceptor recovery. This enabled the robot to detect thermal stimuli and steer away from a warmer thermal source within the rise of 1°C. We envision that the thermosensor can be used for future applications in robotics, including as a potential sensor mechanism for maintaining thermal homeostasis.
Michail-Antisthenis Tsompanas, Jiseon You, Hemma Philamore et al.
Frontiers in Robotics and AI · 2021
The development of biodegradable soft robotics requires an appropriate eco-friendly source of energy. The use of Microbial Fuel Cells (MFCs) is suggested as they can be designed completely from soft materials with little or no negative effects to the environment. Nonetheless, their responsiveness and functionality is not strictly defined as in other conventional technologies, i.e. lithium batteries. Consequently, the use of artificial intelligence methods in their control techniques is highly recommended. The use of neural networks, namely a nonlinear autoregressive network with exogenous inputs was employed to predict the electrical output of an MFC, given its previous outputs and feeding volumes. Thus, predicting MFC outputs as a time series, enables accurate determination of feeding intervals and quantities required for sustenance that can be incorporated in the behavioural repertoire of a soft robot.
Zhongcheng Lei, Hong Zhou, Wenshan Hu et al.
IEEE Transactions on Power Systems · 2024
Power systems are a crucial infrastructure to ensure a sustainable supply of electricity and are thus important for industrial, commercial and domestic consumption. As an interactive and visualizing enabling technology, the digital twin can be effectively applied to the training and education of students and operators in power systems. This article discusses a web-based communication system of power systems (CSPS) constructed with digital twin technologies, and provides a digital replica of the communication system and process as well as the remote monitoring and control of the physical system, the detailed design and implementation of which are presented. The functionalities and uses of the digital twin CSPS are also provided. To illustrate the effectiveness of the proposed digital twin CSPS, a case study with optical fiber line fault detection that emulates a real scenario is conducted, which includes remote control-based digital twin interactions and visualization.
J. K. Wallace, S. Rider, E. Serabyn et al.
Optics Express · 2015
Recent advances in digital technologies, such as high-speed computers and large-format digital imagers, have led to a burgeoning interest in the science and engineering of digital holographic microscopy (DHM). Here we report on a novel off-axis DHM, based on a twin-beam optical design, which avoids the limitations of prior systems, and provides many advantages, including compactness, intrinsic stability, robustness against misalignment, ease of use, and cost. These advantages are traded for a physically constrained sample volume, as well as a fixed fringe spacing. The first trade is not overly restrictive for most applications, and the latter provides for a pre-set assembly alignment that optimizes the spatial frequency sampling. Moreover, our new design supports use in both routine laboratory settings as well as extreme environments without any sacrifice in performance, enabling ready observation of microbial species in the field. The instrument design is presented in detail here, along with a demonstration of bacterial video imaging at sub-micrometer resolution at temperatures down to -15 °C.
C. Hayward, Harriet Whiley, N. J. Ashbolt
Current Opinion in Infectious Diseases · 2025
PURPOSE OF REVIEW This review examines the interplay between biological and anthropogenic factors in the development and persistence of antimicrobial resistance (AMR) within building plumbing systems, which is of particular concern in high risk setting such as healthcare facilities. The review highlights the role of biofilms and amoeba as reservoirs for AMR and explores how engineering and design decisions, governance structures, and cleaning protocols influence microbial resistance dynamics. RECENT FINDINGS Biofilms provide a protective environment that facilitates horizontal gene transfer and enhances bacterial resistance to disinfection. Amoeba-hosted bacteria can evade standard cleaning practices, further promoting AMR persistence. Emerging technologies, such as digital twin modelling, offer new opportunities to optimize risk mitigation strategies. However, more consideration is needed to be given to design or management decision that may have unintended consequences, such as unintended design outcomes, such as increased biofilm growth from tap mixers and low-flow fixtures, and ineffective cleaning protocols, which can inadvertently worsen AMR. SUMMARY Effectively managing AMR in plumbing systems requires a multidisciplinary approach that integrates microbiology, engineering, and policy. Data driven risk assessments can identify high-risk areas that may require design changes but also can enable targeted cleaning strategies, reducing reliance on widespread disinfection that may drive resistance. Future policies must consider system-wide implications to prevent unintended consequences. By addressing both biological and anthropogenic drivers, we can develop sustainable solutions to mitigate AMR risks in healthcare and beyond.
Fatemeh Sarshartehrani, Anthony Lee, Mohamed Azab et al.
2024 IEEE 15th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) · 2024
Critical infrastructures, such as water treatment plants (WTPs) and communication networks, are vital to our daily lives, providing essential resources. As these infrastructures increasingly rely on computer systems and internet networks, conducting cybersecurity training on expensive, real-world equipment becomes impractical due to the risk of operational interruptions. To address this challenge, we present a Digital Twin training platform that simulates three key cybersecurity concepts: Input Manipulation, Output Manipulation, and Denial of Service attacks, within the context of WTPs. These concepts are mapped to four critical functions: water level, chlorine level, water temperature, and the microbial water purification process. This paper primarily focuses on the design and development of the VR component of our digital twin platform, as well as the integration process with our hardware testbed. Initial investigations demonstrated significant potential for the experiential learning platform, serving as an effective tool for educating users about cybersecurity issues in mission-critical facilities such as WTPs.
Bichar Dip Shrestha Gurung, Manish Rayamajhi, Naina Maharjan et al.
bioRxiv (Cold Spring Harbor Laboratory) · 2025
Urban wastewater microbiomes are complex and temporally dynamic, offering valuable insight into community-scale microbial ecology and potential public health trends. However, existing wastewater-based studies often remain descriptive, lacking tools for predictive modeling. In this study, we introduce a digital twin framework that forecasts microbial abundance trajectories in urban wastewater using an interpretable generative model, Q-net. Trained on a 30-week longitudinal metagenomic dataset from seven wastewater treatment plants, the model captures temporal microbial dynamics with high fidelity (R2>0.97 for key taxa; R2=0.998 at the final timepoint). Beyond accurate forecasting, Q-net provides transparent model structure through conditional inference trees and enables simulation of realistic microbial trends under hypothetical scenarios. This work demonstrates the potential of digital twins to move wastewater microbiome studies from static snapshots to dynamic, predictive systems, with broad implications for environmental monitoring and microbial ecosystem modeling.
Jianye Xia, Dongjiao Long, Min Chen et al.
PubMed · 2025
As a strategic emerging industry, biomanufacturing faces core challenges in achieving precise optimization and efficient scale-up of fermentation processes. This review focuses on two critical aspects of fermentation-real-time sensing and intelligent control-and systematically summarizes the advancements in online monitoring technologies, artificial intelligence (AI)-driven optimization strategies, and digital twin applications. First, online monitoring technologies, ranging from conventional parameters (e.g., temperature, pH, and dissolved oxygen) to advanced sensing systems (e.g., online viable cell sensors, spectroscopy, and exhaust gas analysis), provide a data foundation for real-time microbial metabolic state characterization. Second, conventional static control relying on expert experience is evolving toward AI-driven dynamic optimization. The integration of machine learning technologies (e.g., artificial neural networks and support vector machines) and genetic algorithms significantly enhances the regulation efficiency of feeding strategies and process parameters. Finally, digital twin technology, integrating real-time sensing data with multi-scale models (e.g., cellular metabolic kinetics and reactor hydrodynamics), offers a novel paradigm for lifecycle optimization and rational scale-up of fermentation. Future advancements in closed-loop control systems based on intelligent sensing and digital twin are expected to accelerate the industrialization of innovative achievements in synthetic biology and drive biomanufacturing toward higher efficiency, intelligence, and sustainability.
Daniel Ayala-Ruiz, A. Atoche, E. Ruiz-Ibarra et al.
Wireless Communications and Mobile Computing · 2019
Long power wide area networks (LPWAN) systems play an important role in monitoring environmental conditions for smart cities applications. With the development of Internet of Things (IoT), wireless sensor networks (WSN), and energy harvesting devices, ultra-low power sensor nodes (SNs) are able to collect and monitor the information for environmental protection, urban planning, and risk prevention. This paper presents a WSN of self-powered IoT SNs energetically autonomous using Plant Microbial Fuel Cells (PMFCs). An energy harvesting device has been adapted with the PMFC to enable a batteryless operation of the SN providing power supply to the sensor network. The low-power communication feature of the SN network is used to monitor the environmental data with a dynamic power management strategy successfully designed for the PMFC-based LoRa sensor node. Environmental data of ozone (O3) and carbon dioxide (CO2) are monitored in real time through a web application providing IoT cloud services with security and privacy protocols.
Edith Osorio de la Rosa, J. V. Castillo, Mario Carmona Campos et al.
Sensors · 2019
The emergence of modern technologies, such as Wireless Sensor Networks (WSNs), the Internet-of-Things (IoT), and Machine-to-Machine (M2M) communications, involves the use of batteries, which pose a serious environmental risk, with billions of batteries disposed of every year. However, the combination of sensors and wireless communication devices is extremely power-hungry. Energy Harvesting (EH) is fundamental in enabling the use of low-power electronic devices that derive their energy from external sources, such as Microbial Fuel Cells (MFC), solar power, thermal and kinetic energy, among others. Plant Microbial Fuel Cell (PMFC) is a prominent clean energy source and a step towards the development of self-powered systems in indoor and outdoor environments. One of the main challenges with PMFCs is the dynamic power supply, dynamic charging rates and low-energy supply. In this paper, a PMFC-based energy harvester system is proposed for the implementation of autonomous self-powered sensor nodes with IoT and cloud-based service communication protocols. The PMFC design is specifically adapted with the proposed EH circuit for the implementation of IoT-WSN based applications. The PMFC-EH system has a maximum power point at 0.71 V, a current density of 5 mA cm−2, and a power density of 3.5 mW cm−2 with a single plant. Considering a sensor node with a current consumption of 0.35 mA, the PMFC-EH green energy system allows a power autonomy for real-time data processing of IoT-based low-power WSN systems.
J. Estrada-López, J. Vázquez-Castillo, A. Castillo-Atoche et al.
Energies · 2023
Intelligent sensing systems based on the edge-computing paradigm are essential for the implementation of Internet of Things (IoT) and Agriculture 4.0 applications. The development of edge-computing wireless sensing systems is required to improve the sensor’s accuracy in soil and data interpretation. Therefore, measuring and processing data at the edge, rather than sending it back to a data center or the cloud, is still an important issue in wireless sensor networks (WSNs). The challenge under this paradigm is to achieve a sustainable operation of the wireless sensing system powered with alternative renewable energy sources, such as plant microbial fuel cells (PMFCs). Consequently, the motivation of this study is to develop a sustainable forage-grass-power fuel cell solution to power an IoT Long-Range (LoRa) network for soil monitoring. The stenotaphrum secundatum grass plant is used as a microbial fuel cell proof of concept, implemented in a 0.015 m3-chamber with carbon plates as electrodes. The BQ25570 integrated circuit is employed to harvest the energy in a 4 F supercapacitor, which achieves a maximum generation capacity of 1.8 mW. The low-cost pH SEN0169 and the SHT10 temperature and humidity sensors are deployed to analyze the soil parameters. Following the edge-computing paradigm, the inverse problem methodology fused with a system identification solution is conducted, correcting the sensor errors due to non-linear hysteresis responses. An energy power management strategy is also programmed in the MSP430FR5994 microcontroller unit, achieving average power consumption of 1.51 mW, ∼19% less than the energy generated by the forage-grass-power fuel cell. Experimental results also demonstrate the energy sustainability capacity achieving a total of 18 consecutive transmissions with the LoRa network without the system’s shutting down.
Helbert da Rocha, Paolo Caruso, J. Pereira et al.
Sensors · 2023
Everyday tasks use sensors to monitor and provide information about processes in different scenarios, such as monitoring devices in manufacturing or homes. Sensors need to communicate, with or without wires, while providing secure information. Power can be derived from various energy sources, such as batteries, electrical power grids, and energy harvesting. Energy harvesting is a promising way to provide a sustainable and renewable source to power sensors by scavenging and converting energy from ambient energy sources. However, low energy is harvested through these methods. Therefore, it is becoming a challenge to design and deploy wireless sensor networks while ensuring the sensors have enough power to perform their tasks and communicate with each other through careful management and optimization, matching energy supply with demand. For this reason, data cryptography and authentication are needed to protect sensor communication. This paper studies how energy harvested with microbial fuel cells can be employed in algorithms used in data protection during sensor communication.
Masato Niwa, Zhenni Pan, S. Shimamoto
2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC) · 2020
The low power consumption in mW of the IEEE802.15.4/ZigBee standard is one of its feature, even though it requires the exchange of batteries. The cost of battery exchange for wireless sensors is considered as one of the critical problems for wireless sensor networks (WSN). Sediment microbial fuel cell (SMFC) can be a promising technology to replace conventional energy sources by renewable energy sources for wireless sensors, which has the potential to supply sustainable WSN without a replacement of batteries. However, SMFC cannot drive a microcontroller directly since it only provides ultra-low voltage and ultra-low current. In addition, from a general perspective, SMFC is costly to build for wireless sensors due to its materials costs. Considered about those challenges, this paper proposed a novel energy harvesting system for the ZigBee network which consists of the SMFC sensor and a power management circuit to accumulate adequate energy for load. Intermittent data transmission between the ZigBee end-device and coordinator is conducted with the designed energy harvesting system. The experimental results showed that the SMFC-powered ZigBee sensor device is eligible to enable intermittent communication in replacement of conventional battery.
E. Osorio-de-la-Rosa, J. Vázquez-Castillo, A. Castillo-Atoche et al.
IEEE Sensors Journal · 2021
Plant–Microbial Fuel Cell (P–MFC) is a renewable power source which generates bioelectricity through the plant-microbe interrelationship at the rhizosphere region of a plant. As a step toward sustainable wireless sensing, PMFC can harness the metabolism of microorganism as a catalyst and use organic matter to generate electrical energy. However, these energy sources tend to produce low power outputs (mW), and the P–MFC energy capacity can be affected by perturbations. The P–MFC needs to be analyzed for an accurate integration in harvester circuits and wireless technologies, such as LPWAN, to develop sustainable wireless communication applications. In this study, a P–MFC array is implemented as a promising self-sustainable green energy communication technology for Internet of Things (IoT)-based wireless sensor network (WSN). The serial-parallel configuration of the Dypsis lutescens plant type is characterized and adapted with an energy harvester (EH) circuit which manages the energy from P–MFC. An energy capacity model is proposed to analyze the supercapacitor’s charge response and the recovery effect after each Long-Range (LoRa) transmission of the sensor node. The integration of a power management strategy is used to improve the sustainable operation in each sensor node. Experimental results show an open circuit voltage of 1.75 V, and a short current circuit of 5.6 mA for the serial-parallel configuration of the P–MFC array. The test-scenarios demonstrate sustainable operation of the LoRa-WSNs after one month with a daily generation capacity of 80 J, which is sufficient for the WSN’s node operation.
Soichiro Hirose, Trang Nakamoto, Kozo Taguchi
Resourceedings · 2023
Environmental pollution is one of the problems that humankind must solve for a sustainable future. Monitoring of Chemical Oxygen Demand (COD) is an important indicator for monitoring the status of organic pollution in water. However, conventional methods for monitoring COD face high costs and complicated design issues. In this study, the use of microbial fuel cells (MFC) composed of low-cost and easy-to-fabricate electrodes using smoked charcoal from rice husks and Japanese ink was investigated for use in COD sensors. Rice husks are an industrial waste product. Therefore, they can be used at a low cost, and using them can help solve the waste problem, which is one of the causes of environmental pollution. With these materials, the electrodes were fabricated for the cost of $0.022/cm3. In addition, floating MFC was used for the sake of sensing COD in rivers, waterways, and lakes. The high physical stability of the block-shaped electrode used in this study allowed a biofilm to form on the anode surface by inserting the anode into the soil. The block-shaped electrodes were physically stable in solution. The results showed that there was a correlation between COD concentration (30~150 mg/L) and MFC voltage for more than four months. Block-shaped electrodes fabricated with rice husk smoked charcoal and Japanese ink would be a promising electrode for MFC to monitor COD in solution in real-time.
A. Revil, P. Fernandez, D. Mao et al.
The Leading Edge · 2015
A bioelectrochemical system was developed to facilitate biodegradation of an organic contaminant (propylene glycol) using a sandbox containing an iron bar that crossed the capillary fringe. In the days following the introduction of the organic contaminant, a strong negative electric potential anomaly (on the order of −35 to 50 mV) was observed at the top surface of the sandbox, evidencing the transport of electrons in the metallic bar and the degradation of the organic contaminant. The iron bar served to transmit electrons between the electron donor (i.e., biodegradation of the propylene glycol) and oxygen used as the terminal electron acceptor. Numerical modeling indicates that the source of current associated with the electric potential anomaly is at the position of the iron bar. The monitoring of this anomaly possibly can be used to monitor the amount of electrons passing through the electronic conductor and the radius of influence of the bioelectrochemical cells with respect to biodegradation of the organic contaminant.
Lu Li, Zeliang Zhu, Yi Yang et al.
2024 3rd Asian Conference on Frontiers of Power and Energy (ACFPE) · 2024
With the rapid growth in the scale of renewable energy in China, the number of trading entities is increasing and trading activities are becoming more and more frequent. There has been a phenomenon of unidentified green power sources and irregular transactions. Therefore, it is necessary to improve and standardize the rules and standards system of the renewable energy market. Blockchain technology shows great potential to break through technical bottlenecks, eliminate energy islands, and promote the gridding of energy markets by virtue of its traceability, immutability of information, and decentralization. This paper analyzes in detail the examples of blockchain technology applied to renewable energy transactions at home and abroad, and closely combines of China policy orientation and national conditions to comprehensively examine and reveal various problems currently facing of China renewable energy blockchain field. On the basis of these analyses, specific and feasible suggestions are put forward to provide useful ideas and references for the healthy and sustainable development of renewable energy blockchain in China.
Souvik Sengupta, Banhirup Sengupta, Amir Sinaeepourfard et al.
2024 6th International Conference on Blockchain Computing and Applications (BCCA) · 2024
Organizations worldwide are under pressure to reduce their use of non-renewable energy sources and carbon emissions due to their increasing negative impact on the ongoing climate crisis. Blockchain technology, popularized by its use in Bitcoin, has been adopted for various use cases but is criticized for its high energy consumption, depending on the consensus mechanism used. Consensus mechanisms are vital for securing blockchain networks by ensuring all nodes agree on the ledger’s state, but they often trade-off between low energy consumption and high security. This paper analyzes the critical factors contributing to power consumption in blockchain networks, focusing on consensus mechanisms and hashing techniques. Through a comprehensive State-of-the-Art (SOTA) review and algorithmic analysis, we examine how various consensus algorithms impact energy usage and detail the computational and space complexities of different hashing algorithms. We also investigate the energy profiles and reduction strategies of major blockchain platforms. Our findings highlight the potential to enhance blockchain energy efficiency without compromising security or performance, providing a foundation for future research in sustainable blockchain technologies.
Yongjun Lv
Frontiers in Energy Research · 2023
The pressing issues of climate change and the limited availability of non-renewable energy resources have created a growing need for sustainable energy alternatives. This study provides a comprehensive overview of the pressing need for sustainable energy solutions and the complex relationship between energy and the economy. The challenges and opportunities presented by the transition to sustainable energy sources are explored, including the need for investment in renewable energy technologies, policy changes to incentivize sustainable energy use, and the potential for job creation in the sustainable energy sector. On the other hand, it is recognized that there are considerable hurdles that need to be addressed, including the substantial initial expenses associated with establishing renewable energy systems, as well as the political and societal barriers to enacting change. The economic benefits of transitioning to sustainable energy, such as improved energy security, reduced dependence on fossil fuels, and the potential for increased economic growth, are evaluated. The complex relationship between energy and the economy is thoroughly analyzed, presenting a valuable contribution to the academic literature on sustainable energy. Furthermore, an inquiry is being made into the potential contribution of blockchain technology in advancing a sustainable energy landscape. This includes its ability to augment the effectiveness and openness of energy markets, as well as its capacity to assist in the assimilation of renewable energy resources. Hence, this research underscores the importance of transitioning to sustainable energy sources for their environmental and economic merits. The findings presented offer valuable insights to inform policy decisions and guide future research endeavors in this field. By promoting the advancement of sustainable energy technologies, this study contributes to the development of a more sustainable global economy.
Meriem Aoudia, Mustafa B. M. Alaraj, Omnia Abu Waraga et al.
Frontiers in Energy Research · 2024
With the rise of the 3Ds—decarbonization, decentralization, and digitalization—the number of electric vehicles is projected to increase, necessitating the implementation of modern technologies to avoid unnecessary energy wastage. Numerous studies have been developed proposing electric vehicle (EV) charging frameworks in networks empowered by renewable energy resources. In addition, more focus has recently been directed on incorporating blockchain technology to assure security and transparency in trading systems. However, fewer studies have delved into developing a practical implementation of their solution due to the complexity of the topic. Therefore, this paper thoroughly investigates integrating blockchain technology in electric vehicle charging systems, analyzing the existing practical implementation and their characteristics. It comprises 48 relevant studies between 2017 and 2023, covering the following main research areas: (i) renewable energy-based electric charging systems, (ii) blockchain frameworks used in energy trading, and (iii) performance metrics of simulated and implemented solutions. Results show that blockchain applications in EVs and energy trading systems are highly current, and researchers are actively exploring ways to improve their efficiency and effectiveness.
Shyam Agarwal, Shailesh Kapoor, Amit Jain
2024 IEEE 3rd International Conference on Electrical Power and Energy Systems (ICEPES) · 2024
The integration of renewable energy sources and technological advancements in the electricity grid has revolutionized the energy sector, paving way for the smart grid. Within this smart grid framework, prosumers possessing surplus energy aim to sell their surplus energy to consumers. However, conventional centralized energy trading methods used in smart grid for energy exchange poses challenges. To overcome these challenges, a decentralized system based on blockchain technology is employed for energy trading. This paper discusses the double auction mechanism-based energy trading which is facilitated by blockchain platform. It reviews existing research that uses double auction mechanism, based on blockchain for energy trading. Also, a case study is conducted in this paper on a smart microgrid, comprising two prosumers and one consumer, all connected with the main grid. Within this smart microgrid, energy trading takes place among prosumer and consumer, involving residential load. For the implementation of energy trading, a uniform price double auction mechanism, facilitated by blockchain is utilized. The blockchain platform chosen for this implementation is based on Ganache Platform. The results show that engaging blockchain technology in local energy trading leads to considerable cost savings for prosumers and consumers. These findings are presented in the paper, highlighting the advantages of the proposed approach.
Juan Zhang, Zeyu Lin, Junpeng Chen
International Journal of Electric Power and Energy Studies · 2024
The energy sector faces significant challenges related to supply chain traceability, including issues with transparency, data integrity, regulatory compliance, and fraud prevention. Blockchain technology, with its decentralized, transparent, and immutable ledger, offers promising solutions to these challenges. This review explores the application of blockchain technology in enhancing supply chain traceability in the energy sector. It examines the potential benefits in terms of visibility, data integrity, compliance, and sustainability, and discusses real-world applications, challenges, and future directions. Case studies from renewable energy, fossil fuels, and smart grids illustrate blockchain's impact. Despite the promising benefits, technical, regulatory, and implementation challenges remain. Future research and development, along with supportive policy frameworks, are essential for realizing blockchain's full potential in transforming the energy supply chain into a more efficient, transparent, and sustainable system.
Safa Otoum, I. A. Ridhawi, H. Mouftah
IEEE Internet of Things Journal · 2023
Through the digitization of essential functional processes, Industry 4.0 aims to build knowledgeable, networked, and stable value chains. Network trustworthiness is a critical component of network security that is built on positive interactions, guarantees, transparency, and accountability. Blockchain technology has drawn the attention of researchers in various fields of data science as a safe and low-cost platform to track a large number of eventual transactions. Such a technique is adaptable to the renewable energy-trade sector, which suffers from security and trustworthy issues. Having a decentralized energy infrastructure, that is supported by blockchain and artificial intelligence, enables smart and secure microgrid energy trading. The new age of industrial production will be highly versatile in terms of production volume and customization. As such a robust collaboration solution between consumers, businesses, and suppliers must be both secure and sustainable. In this article, we introduce a cooperative and distributed framework that relies on computing, communication, and intelligence capabilities of edge and end devices to enable secure energy trading, remote monitoring, and network trustworthiness. The blockchain and federated learning-enabled solution provide secure energy trading between different critical entities. Such a technique, coupled with 5G and beyond networks, would enable mass surveillance, monitoring, and analysis to occur at the edge. Performance evaluations are conducted to test the effectiveness of the proposed solution in terms of reliability and responsiveness in a vehicular network energy-trade scenario.
Muhammad Faheem, B. Raza, Muhammad Shoaib Bhutta et al.
IET Blockchain · 2024
The rapid and green energy transition is essential to deal with the fast‐growing energy needs in both public and industrial sectors. This has paved the way to integrate distributed renewable energy resources () such as solar, hydro, wind, and geothermal into the power grid (). Wind and solar are free, zero‐carbon emission, and everlasting power sources that contribute 5% and 7% of global electricity generation, respectively. Therefore, the fast, secure, and reliable integration of these green is critical to achieve the instant energy demands. Smart grid due to inherited characteristics such as intelligent sensing, computing, and communication technologies can effectively integrate the . However, the existing smart grid communication architecture faces various cyberattacks, resulting in poor integration, monitoring, and control of . In this respect, blockchain technology can provide fast, secure, and efficient end‐to‐end communication between in the smart grid. In this study, the authors propose a blockchain‐based resilient and secure scheme called for wireless sensor networks ‐based events monitoring and control in . Experimental studies and performance analyses are carried out to predict the efficiency of the proposed scheme by considering numerous standard metrics. The extensive numerical results demonstrated that the proposed scheme is significant in terms of secure, resilient, and reliable information transmission for in .
Andreas Zeiselmair, Bernd Steinkopf, Ulrich Gallersdörfer et al.
Frontiers in Blockchain · 2021
The energy system is becoming increasingly decentralized. This development requires integrating and coordinating a rising number of actors and small units in a complex system. Blockchain could provide a base infrastructure for new tools and platforms that address these tasks in various aspects—ranging from dispatch optimization or dynamic load adaption to (local) market mechanisms. Many of these applications are currently in development and subject to research projects. In decentralized energy markets especially, the optimized allocation of energy products demands complex computation. Combining these with distributed ledger technologies leads to bottlenecks and challenges regarding privacy requirements and performance due to limited storage and computational resources. Verifiable computation techniques promise a solution to these issues. This paper presents an overview of verifiable computation technologies, including trusted oracles, zkSNARKs, and multi-party computation. We further analyze their application in blockchain environments with a focus on energy-related applications. Applied to a distinct optimization problem of renewable energy certificates, we have evaluated these solution approaches and finally demonstrate an implementation of a Simplex-Optimization using zkSNARKs as a case study. We conclude with an assessment of the applicability of the described verifiable computation techniques and address limitations for large-scale deployment, followed by an outlook on current development trends.
Anees Fathima, Noor Ayesha, Zahira Tabassum et al.
Blockchain Applications for the Energy and Utilities Industry · 2025
Blockchain has evolved from supporting cryptocurrencies to transforming industries like finance, healthcare, and supply chain management. Emerging trends focus on scalability with Layer 2 solutions, sharding, and cross-chain interoperability. Sustainability efforts include transitioning to Proof-of-Stake, carbon-neutral blockchains, and renewable energy. AI integration enables decentralized models, secure data sharing, and AI-driven smart contracts. Governments explore CBDCs, while privacy technologies like Zero-Knowledge Proofs enhance security. Challenges remain in regulation, security risks, and adoption, but ongoing innovations are driving blockchain's widespread acceptance.
Saad Alateef, Amjad Aldweesh, Mohammad Alauthman et al.
Blockchain Applications for the Energy and Utilities Industry · 2025
This paper proposes a blockchain-based framework to optimize energy supply chain management, delineating its potential to transform energy sourcing, allocation, and consumption processes.The framework elucidates critical components such as decentralized record-keeping, smart contracts for automated transactions, and robust security protocols, thereby ensuring data integrity and resilience against cyberattacks. A prototype system is developed and tested to evaluate performance metrics, including scalability, transaction speed, and energy tracking accuracy.The results highlight the considerable benefits of blockchain, including enhanced transparency, cost efficiency, and improved stakeholder collaboration. Conclusively, the paper identifies current challenges ranging from technical scalability to regulatory hurdles and suggests future directions for augmenting blockchain's impact on energy supply chains, ultimately reinforcing the global transition towards more sustainable energy systems
Enrique Arias, Jose Antonio Mateo, Ali Maqousi et al.
Blockchain Applications for the Energy and Utilities Industry · 2025
Meteorological data is critical not only for climate modeling and weather prediction but also for renewable energy forecasting, demand response, and grid stability in the energy and utilities sector. Conventional data systems rely on centralized architectures vulnerable to single points of failure and poor traceability. This chapter presents a blockchain-based oraculus for storing and retrieving weather observations on an immutable ledger tailored for energy contexts. Specialized oracles, robust consensus, and secure data pipelines ensure tamper-proof storage. Testing confirms reliable retrieval for key stakeholders, including grid operators and regulators. The design supports accurate archiving, real-time ingestion, and flexible access control—vital for planning and operations. By offering a scalable pipeline addressing tampering and integrity, this framework fosters reliable, auditable meteorological systems.
Natalie Colantonio, Younggy Kim
ChemistrySelect · 2016
Abstract Advanced treatment, such as tight membrane filtration and ion exchange, can be applied for Pb 2+ removal from wastewater but these methods are expensive with a high demand for electric energy and chemicals. Microbial electrolysis cells (MECs) are an emerging wastewater treatment technology and MECs can remove Pb 2+ by reduction and precipitation at the cathode and biosorption at the anode; however, reduction at the anode has not been reported. We investigated Pb 2+ removal mechanisms using lab‐scale MECs. Using an anion exchange membrane, independent Pb 2+ removal in the anode and cathode chambers was observed at various voltage applications, including open circuit, 0.3 V, 0.6 V, and 0.9 V. A substantial amount of metallic Pb (0. 10 ± 0.02 mg) was found on the graphite fiber anode. Also, the observed anode potential (−0.15 to −0.33 V vs. SHE) indicated sufficient driving force for Pb 2+ reduction at the anode for the Pb 2+ concentration of 0.1 to 2.5 mg L −1 . Inactivation of exoelectrogens using ethanol resulted in no Pb 2+ removal. The findings show that Pb 2+ removal is achieved by various mechanisms in MECs, including electrodeposition at the anode by exoelectrogens.
Ananda Rao Hari, Krishna P. Katuri, Bruce E. Logan et al.
Scientific Reports · 2016
Abstract Anode potential has been shown to be a critical factor in the rate of acetate removal in microbial electrolysis cells (MECs), but studies with fermentable substrates and set potentials are lacking. Here, we examined the impact of three different set anode potentials (SAPs; −0.25, 0, and 0.25 V vs. standard hydrogen electrode) on the electrochemical performance, electron flux to various sinks, and anodic microbial community structure in two-chambered MECs fed with propionate. Electrical current (49–71%) and CH 4 (22.9–41%) were the largest electron sinks regardless of the potentials tested. Among the three SAPs tested, 0 V showed the highest electron flux to electrical current (71 ± 5%) and the lowest flux to CH 4 (22.9 ± 1.2%). In contrast, the SAP of −0.25 V had the lowest electron flux to current (49 ± 6%) and the highest flux to CH 4 (41.1 ± 2%). The most dominant genera detected on the anode of all three SAPs based on 16S rRNA gene sequencing were Geobacter, Smithella and Syntrophobacter , but their relative abundance varied among the tested SAPs. Microbial community analysis implies that complete degradation of propionate in all the tested SAPs was facilitated by syntrophic interactions between fermenters and Geobacter at the anode and ferementers and hydrogenotrophic methanogens in suspension.
Abhijeet P. Borole, Alex J. Lewis
Sustainable Energy & Fuels · 2017
Proton transfer in microbial electrochemical cells is as important as electron transfer. This study quantifies proton transfer rates in MEC for the first time. Control of flow rate and loading rate allows improvement in proton transfer rates enabling hydrogen productivities >10 L per L per day.
Ahmad Walid Ayoobi, Mehmet Inceoğlu
Energies · 2024
The building sector is a major contributor to resource consumption, energy use, and greenhouse gas emissions. Sustainable architecture offers a solution, leveraging Building Energy Modeling (BEM) for early-stage design optimization. This study explores the use of genetic algorithms for optimizing sustainable design strategies holistically. A comprehensive analysis and optimization model was developed using genetic algorithms to individually optimize various sustainable strategies. The optimized strategies were then applied to a pre-existing building in Kabul City, a region facing significant environmental challenges. To enhance accuracy, this study integrated energy simulations with Computational Fluid Dynamics (CFD). This research combines genetic algorithms with energy simulation and CFD analysis to optimize building design for a specific climate. Furthermore, it validates the optimized strategies through a real-world case study building. Optimizing the Window-to-Wall Ratio (WWR) and shading devices based on solar exposure significantly improved the building’s energy performance. South (S)-facing single windows and specific combinations of opposing and adjacent windows emerged as optimal configurations. The strategic optimization of building component materials led to substantial energy savings: a 58.6% reduction in window energy loss, 78.3% in wall loss, and 69.5% in roof loss. Additionally, the optimized pre-existing building achieved a 48.1% reduction in cooling demand, a 97.5% reduction in heating demand, and an overall energy reduction of 84.4%. Improved natural ventilation and controlled solar gain led to a 72.2% reduction in peak-month CO2 emissions. While this study focused on applicable passive design strategies, the integration of advanced technologies like Phase Change Materials (PCMs), kinetic shading devices, and renewable energy systems can further improve building performance and contribute to achieving net-zero buildings.
Leilei Xiao, Yiping Wang, E. Lichtfouse et al.
Frontiers in Microbiology · 2021
Recycling waste into new materials and energy is becoming a major challenge in the context of the future circular economy, calling for advanced methods of waste treatment. For instance, microbially-mediated anaerobic digestion is widely used for conversion of sewage sludge into biomethane, fertilizers and other products, yet the efficiency of microbial digestion is limited by the occurrence of antibiotics in sludges, originating from drug consumption for human and animal health. Here we present antibiotic levels in Chinese wastewater, then we review the effects of antibiotics on hydrolysis, acidogenesis and methanogenesis, with focus on macrolides, tetracyclines, β-lactams and antibiotic mixtures. We detail effects of antibiotics on fermentative bacteria and methanogenic archaea. Most results display adverse effects of antibiotics on anaerobic digestion, yet some antibiotics promote hydrolysis, acidogenesis and methanogenesis.
J. Kelly, Maxwell G. London, A. McCormick et al.
PLOS ONE · 2021
Microplastics are ubiquitous contaminants in aquatic habitats globally, and wastewater treatment plants (WWTPs) are point sources of microplastics. Within aquatic habitats microplastics are colonized by microbial biofilms, which can include pathogenic taxa and taxa associated with plastic breakdown. Microplastics enter WWTPs in sewage and exit in sludge or effluent, but the role that WWTPs play in establishing or modifying microplastic bacterial assemblages is unknown. We analyzed microplastics and associated biofilms in raw sewage, effluent water, and sludge from two WWTPs. Both plants retained >99% of influent microplastics in sludge, and sludge microplastics showed higher bacterial species richness and higher abundance of taxa associated with bioflocculation (e.g. Xanthomonas) than influent microplastics, suggesting that colonization of microplastics within the WWTP may play a role in retention. Microplastics in WWTP effluent included significantly lower abundances of some potentially pathogenic bacterial taxa (e.g. Campylobacteraceae) compared to influent microplastics; however, other potentially pathogenic taxa (e.g. Acinetobacter) remained abundant on effluent microplastics, and several taxa linked to plastic breakdown (e.g. Klebsiella, Pseudomonas, and Sphingomonas) were significantly more abundant on effluent compared to influent microplastics. These results indicate that diverse bacterial assemblages colonize microplastics within sewage and that WWTPs can play a significant role in modifying the microplastic-associated assemblages, which may affect the fate of microplastics within the WWTPs and the environment.
Nathan K. McLain, Melissa Gómez, E. Gachomo
Microbial Ecology · 2022
The practice of using recycled wastewater (RWW) has been successfully adopted to address the growing demand for clean water. However, chemicals of emerging concern (CECs) including pharmaceutical products remain in the RWW even after additional cleaning. When RWW is used to irrigate crops or landscapes, these chemicals can enter these and adjacent environments. Unfortunately, the overall composition and concentrations of CECs found in different RWW sources vary, and even the same source can vary over time. Therefore, we selected one compound that is found frequently and in high concentrations in many RWW sources, acetaminophen (APAP), to use for our study. Using greenhouse grown eggplants treated with APAP concentrations within the ranges found in RWW effluents, we investigated the short-term impacts of APAP on the soil bacterial population under agricultural settings. Using Illumina sequencing-based approaches, we showed that APAP has the potential to cause shifts in the microbial community most likely by positively selecting for bacteria that are capable of metabolizing the breakdown products of APAP such as glycosides and carboxylic acids. Community-level physiological profiles of carbon metabolism were evaluated using Biolog EcoPlate as a proxy for community functions. The Biolog plates indicated that the metabolism of amines, amino acids, carbohydrates, carboxylic acids, and polymers was significantly higher in the presence of APAP. Abundance of microorganisms of importance to plant health and productivity was altered by APAP. Our results indicate that the soil microbial community and functions could be altered by APAP at concentrations found in RWW. Our findings contribute to the knowledge base needed to guide policies regulating RWW reuse in agriculture and also highlight the need to further investigate the effects of CECs found in RWW on soil microbiomes.
L. Carles, S. Wullschleger, A. Joss et al.
bioRxiv (Cold Spring Harbor Laboratory) · 2022
Wastewater treatment plant effluents can impact microbial communities in receiving streams. However, little is known about the role of microorganisms in wastewater as opposed to other wastewater constituents, such as nutrients and micropollutants. We aimed therefore at determining the impact of wastewater microorganisms on the microbial diversity and function of periphyton, key microbial communities in streams. Periphyton was grown in flow-through channels that were continuously alimented with a mixture of stream water and unfiltered or ultra-filtered wastewater. Impacts were assessed on periphyton biomass, activities and tolerance to micropollutants, as well as on microbial diversity. Our results showed that wastewater microorganisms colonized periphyton and modified its community composition, resulting for instance in an increased abundance of Chloroflexi and a decreased abundance of diatoms and green algae. This led to shifts towards heterotrophy, as suggested by the changes in nutrient stoichiometry and the increased mineralization potential of carbon substrates. An increased tolerance towards micropollutants was only found for periphyton exposed to unfiltered wastewater but not to ultra-filtered wastewater, suggesting that wastewater microorganisms were responsible for this increased tolerance. Overall, our results highlight the need to consider the role of wastewater microorganisms when studying potential impacts of wastewater on the receiving water body. Environmental implication The present study investigates the impact of wastewater microorganisms on periphyton, i.e. communities forming the microbial skin of streambeds. We were able to disentangle specific effects of wastewater microorganisms in the context of the complex wastewater matrix. Indeed, wastewater microorganisms induced strong changes in periphyton community composition and function, suggesting the need to consider wastewater microbial communities as a stressor per se, similarly to, e.g., nutrients and micropollutants. Moreover, since periphyton is at the basis of the food web in streams, these changes may have consequences for higher trophic levels.
Shiwangi Kesarwani, Diksha Panwar, J. Mal et al.
Fermentation · 2022
The availability of clean water and the depletion of non-renewable resources provide challenges to modern society. The widespread use of conventional wastewater treatment necessitates significant financial and energy expenditure. Constructed Wetland Microbial Fuel Cells (CW-MFCs), a more recent alternative technology that incorporates a Microbial Fuel Cell (MFC) inside a Constructed Wetland (CW), can alleviate these problems. By utilizing a CW’s inherent redox gradient, MFC can produce electricity while also improving a CW’s capacity for wastewater treatment. Electroactive bacteria in the anaerobic zone oxidize the organic contaminants in the wastewater, releasing electrons and protons in the process. Through an external circuit, these electrons travel to the cathode and produce electricity. Researchers have demonstrated the potential of CW-MFC technology in harnessing bio-electricity from wastewater while achieving pollutant removal at the lab and pilot scales, using both domestic and industrial wastewater. However, several limitations, such as inadequate removal of nitrogen, phosphates, and toxic organic/inorganic pollutants, limits its applicability on a large scale. In addition, the whole system must be well optimized to achieve effective wastewater treatment along with energy, as the ecosystem of the CW-MFC is large, and has diverse biotic and abiotic components which interact with each other in a dynamic manner. Therefore, by modifying important components and optimizing various influencing factors, the performance of this hybrid system in terms of wastewater treatment and power generation can be improved, making CW-MFCs a cost-effective, cleaner, and more sustainable approach for wastewater treatment that can be used in real-world applications in the future.
S. Malik, Archna Dhasmana, S. Preetam et al.
Nanomaterials · 2022
Water scarcity due to contamination of water resources with different inorganic and organic contaminants is one of the foremost global concerns. It is due to rapid industrialization, fast urbanization, and the low efficiency of traditional wastewater treatment strategies. Conventional water treatment strategies, including chemical precipitation, membrane filtration, coagulation, ion exchange, solvent extraction, adsorption, and photolysis, are based on adopting various nanomaterials (NMs) with a high surface area, including carbon NMs, polymers, metals-based, and metal oxides. However, significant bottlenecks are toxicity, cost, secondary contamination, size and space constraints, energy efficiency, prolonged time consumption, output efficiency, and scalability. On the contrary, green NMs fabricated using microorganisms emerge as cost-effective, eco-friendly, sustainable, safe, and efficient substitutes for these traditional strategies. This review summarizes the state-of-the-art microbial-assisted green NMs and strategies including microbial cells, magnetotactic bacteria (MTB), bio-augmentation and integrated bioreactors for removing an extensive range of water contaminants addressing the challenges associated with traditional strategies. Furthermore, a comparative analysis of the efficacies of microbe-assisted green NM-based water remediation strategy with the traditional practices in light of crucial factors like reusability, regeneration, removal efficiency, and adsorption capacity has been presented. The associated challenges, their alternate solutions, and the cutting-edge prospects of microbial-assisted green nanobiotechnology with the integration of advanced tools including internet-of-nano-things, cloud computing, and artificial intelligence have been discussed. This review opens a new window to assist future research dedicated to sustainable and green nanobiotechnology-based strategies for environmental remediation applications.
G. Tsekouras, Panagiota M. Deligianni, F. Kanellos et al.
Frontiers in Energy Research · 2022
Microbial fuel cells (MFCs) have undergone great technological development in the last 20 years, but very little has been done to commercialize them. The simultaneous power production and wastewater treatment are features those greatly increase the interest in the use of MFCs. This kind of distributed power generation is renewable and friendly and can be easily integrated into a smart grid. However, there are some key issues with their commercialization: high construction costs, difficulty in developing high power structures, MFC lifespan, and maintaining a high level of efficiency. The objective of this article is to explore the possibilities of using MFCs in urban wastewater not only regarding the technical criteria of their application, but also mainly from an economic point of view, to determine the conditions through which the viability of the investment is ensured and the possibilities of their integration in a smart grid are identified. Initially, this article explores the implementation/configuration of a power plant with MFCs within an urban wastewater treatment plant on a theoretical basis. In addition, based on the corresponding physical quantities for urban wastewater treatment, the construction and operational costs are determined and the viability of the investment is examined based on classic economic criteria such as net present value, benefit–cost ratio, internal rate of return, and discounted payback period. Furthermore, sensitivity analysis is carried out, concerning both technical parameters, such as the percentage of organic matter removal, power density, sewage residence time, MFC efficiency, etc., and economical parameters, such as the reduction of construction costs due to change of materials, change of interest rate, and lifetime. The advantages and disadvantages of their use in smart grids is also analyzed. The results show that the use of MFCs for power generation cannot be utopian as long as they are integrated into the structure of a central wastewater treatment plant on the condition that the scale-up technical issues of MFCs are successfully addressed.
Yamini Koul, Viralkunvar Devda, Sunita Varjani et al.
Bioengineered · 2022
ABSTRACT Wastewater is one of the most common by-products of almost every industrial process. Treatment of wastewater alone, before disposal, necessitates an excess of energy. Environmental concerns over the use of fossil fuels as a source of energy have prompted a surge in demand for alternative energy sources and the development of sophisticated procedures to extract energy from unconventional sources. Treatment of municipal and industrial wastewater alone accounts for about 3% of global electricity use while the amount of energy embedded in the waste is at least 2–4 times greater than the energy required to treat the same effluent. The microbial electrolysis cell (MEC) is one of the most efficient technologies for waste-to-product conversion that uses electrochemically active bacteria to convert organic matter into hydrogen or a variety of by-products without polluting the environment. This paper highlights existing obstacles and future potential in the integration of Microbial Electrolysis Cell with other processes like anaerobic digestion coupled system, anaerobic membrane bioreactor and thermoelectric micro converter. Graphical abstract_R1