Dry Cell Research Articles

해양 모빌리티 서비스 다양화를 위한 상업용 스마트 잠수정 디자인 연구

Coastal areas worldwide, including South Korea, are actively promoting the marine leisure industry as an economic growth driver. With the emergence of experiential consumption trends today, there is a growing demand for underwater leisure activities, highlighting the need for various underwater transportation devices to meet market demands. Based on the government's policy to develop the marine mobility industry, this study aims to conduct a case analysis of tourist and commercial submersibles and propose new designs accordingly. The proposed design is an 11-seater tourist submersible equipped with high-efficiency electric batteries and AI-based autonomous systems to enhance efficiency and safety, thereby maximizing the scalability of marine mobility services while protecting sustainable tourism and economic productivity. The next-gen submersible opens up new dimensions for underwater tourism, providing immersive experiences to travelers. Furthermore, it presents environmental management, such as ecotourism in coastal areas and marine protected areas, fostering future possibilities for expanding the marine leisure industry, promoting environmental conservation, and stimulating economic growth.

Real driving cycle based SoC and battery temperature prediction for electric vehicle using AI models

The increase in electric vehicles has surpassed expectations leading to the eventual replacement of traditional IC (internal combustion) engine vehicles. However, to achieve this, it is crucial to research and develop more efficient and reliable electric batteries to create a sustainable transportation system. The performance of the battery directly impacts the power and range of the vehicle making battery management research imperative. Accurate estimation of battery state of charge (SoC) and temperature is vital for the overall performance, drivability and safety of the vehicle. This paper proposes a comprehensive approach to create an AI-based model to estimate the battery SoC and temperature that matches the performance of conventional vehicles. Various regression models are used as prediction models and the results are presented. These insights offer valuable understandings of battery thermal behavior, aiding in the design of an effective battery management system.

Synthesis of graphene-based nanocomposites with superior doxycycline removal efficiency and antimicrobial studies

Herein, we report the successful preparation of high-quality graphene (G) nanosheets up to the kg scale using an electrochemical technique using graphite rods from scrap dry cell batteries. The as-prepared graphene was then decorated in-stiu with niobium oxide (Nb2O5) and silver (Ag) nanoparticles to prepare Nb2O5@G and Ag@G nanocomposites. Powdered X-ray diffraction (p-XRD), Fourier-transform (FT-IR) infrared spectroscopy, UV–visible (UV–vis) spectroscopy, Raman spectroscopy, and scanning electron microscopy (SEM) were used to characterize the as-prepared nanocomposite material. This binary Nb2O5@G nanocomposite was subsequently used to degrade doxycycline antibiotic with an efficiency of 98.5 % in 120 min under visible light conditions. To determine the optimal scope of the as-prepared composite catalyst, degradation studies were performed at different pH values, photocatalyst doses and temperatures. Kinetics studies revealed that the processes followed pseudo-first-order kinetics. In addition, the as-synthesized graphene, Nb2O5@G and Ag@G nanocomposites were used for selective application against E. coli bacterial strains. Overall, Ag@G has shown good potential application prospects in the development of antibacterial materials in comparison with Nb2O5@G and pristine graphene. This study highlights the potential of as-prepared graphene-based nanocomposites for use in waste treatment and environmental bioremediation.

Design and research of heat dissipation system of electric vehicle lithium-ion battery pack based on artificial intelligence optimization algorithm

This research focuses on the design of heat dissipation system for lithium-ion battery packs of electric vehicles, and adopts artificial intelligence optimization algorithm to improve the heat dissipation efficiency of the system. By integrating genetic algorithms and particle swarm optimization, the research goal is to optimize key design parameters of the cooling system to improve temperature control and extend battery life. In the process of algorithm implementation, genetic algorithm improves the diversity of population through crossover and mutation operations, thus enhancing the global search ability. Particle swarm optimization (PSO) improves local search accuracy and convergence speed by dynamically adjusting inertia weight and learning factor. The effects of different design schemes on heat dissipation performance were systematically evaluated by using computational fluid dynamics (CFD) software. The experimental results show that the efficiency of the cooling system is significantly improved after the application of the optimization algorithm, especially in the aspects of temperature distribution uniformity and maximum temperature reduction. The optimization algorithm also successfully shortens the thermal response time of the system and improves the adaptability and stability of the system under different working conditions. The computational complexity and execution time of these algorithms are also analyzed, which proves the efficiency and feasibility of these algorithms in practical applications. This study demonstrates the practicability and effectiveness of artificial intelligence optimization algorithm in the design of heat dissipation system of lithium-ion battery pack for electric vehicles, and provides valuable reference and practical guidance for the progress of heat dissipation technology of electric vehicles in the future.

Treatment of sewage sludge with γ‐ray irradiation for volatile fatty acids and lipid production

AbstractThe production of value‐added products from sewage sludge is considered to be one of the solutions for the sustainable management of sludge in wastewater treatment plants (WWTPs). The presence of carbon, nitrogen, and phosphorus sources has made the sewage sludge of WWTPs a valuable and low‐cost substrate for the production of fermentative products. In the current study, a process was developed for microbial lipid production from two types of sewage sludge from a WWTP in northern Isfahan: anaerobic digester inlet sludge (DIS) and anaerobic digester outlet sludge (DOS). This process was based on the release of volatile fatty acids (VFAs) from the sludge by combinations of γ‐ray irradiation, anaerobic digestion, and acidogenic fermentation followed by utilization of VFAs in a microbial process by the oleaginous yeast Cryptococcus aureus UIMC65. After γ‐ray irradiation, the acidogenic fermentation of the treated sludge released 72% of the organic matter content of the sludge with acidification efficiency of 12% leading to 0.516 g L−1 VFAs. The oleaginous fermentation of the released VFAs for 7 days was accompanied by production of 1.58 g L−1 dry cell biomass with 40% lipid content. The results of this study indicate that the sewage sludge from urban WWTP has the potential to be used for the production of microbial lipids.

Coordination dynamics between fuel cell and battery technologies in the transition to clean cars

Significant progress reconciling economic activities with a stable climate requires radical and rapid technological change in multiple sectors. Here, we study the case of the automotive industry's transition to electric vehicles, which involved choosing between two different technologies: fuel cell electric vehicles (FCEVs) or battery electric vehicles (BEVs). We know very little about the role that such technological uncertainty plays in shaping the strategies of firms, the efficacy of technological and climate policies, and the speed of technological transitions. Here, we explain that the choice between these two technologies posed a global and multisectoral coordination game, due to technological complementarities and the global organization of the industry's markets and supply chains. We use data on patents, supply-chain relationships, and national policies to document historical trends and industry dynamics for these two technologies. While the industry initially focused on FCEVs, around 2008, the technological paradigm shifted to BEVs. National-level policies had a limited ability to coordinate global players around a type of clean car technology. Instead, exogenous innovation spillovers from outside the automotive sector played a critical role in solving this coordination game in favor of BEVs. Our results suggest that global and cross-sectoral technology policies may be needed to accelerate low-carbon technological change in other sectors, such as shipping or aviation. This enriches the existing theoretical paradigm, which ignores the scale of interdependencies between technologies and firms.

Comparison of techniques based on frequency response analysis for state of health estimation in lithium-ion batteries

Frequency response analysis (FRA) methods are commonly used in the field of State of Health (SOH) estimation for Lithium-ion batteries (Libs). However, identifying their appropriate application scenarios can be challenging. This paper presents four FRA techniques, including electrochemical impedance spectra (EIS), mid-frequency and low-frequency domain equivalent circuit model (MLECM), distribution of relaxation time (DRT) and non-linear FRA (NFRA) technique. This paper proposes two estimation frameworks, machine learning and curve fitting, to be applied to each of the four techniques. Eight SOH estimation models are developed by linking the extracted feature parameters to the battery capacity variations. The paper compares the accuracy of estimation, estimation range, and other properties of the eight models. Application scenarios are identified for the techniques by using three classification methods: different estimation frameworks, frequency response linearity, and impedance technique. The results demonstrate that MLF is recommended for scenarios with a large amount of battery data, while CFF is recommended for scenarios with a small amount of data. NFRA could be applied to electric vehicle power batteries, while LFRA is recommended to be used for retired batteries. EIS method is recommended for complex and dynamic scenarios, while non-EIS method is recommended for scenarios that require high accuracy.

Methodology for social life cycle impact assessment enhanced with gender aspects applied to electric vehicle Li-ion batteries

Abstract Purpose The objective of this study is to assess the potential social risks and benefits of EV Li-ion batteries by combining the S-LCA framework with gender aspects throughout all the life cycle phases of the battery. Methods The social life cycle assessment (S-LCA) methodology has been applied to determine social concerns about a lithium-ion (Li-ion) battery pack design for electric vehicles (EVs) from cradle to grave. A questionnaire based on UNEP S-LCA guidelines and literature case studies of S-LCA on batteries and the energy industry has been prepared for each of the stakeholder categories and distributed among experts in the Li-ion battery sector (more than 21 industrial and academic experts representing the whole battery value chain). Furthermore, the social assessment also includes updated gender aspects to provide wider and more comprehensive social impacts to ensure a gender-neutral approach. Results and discussion The Li-ion battery presents a positive social impact in all the stakeholder categories evaluated, where the worker category has the best social performance driven by the highest score (scores range from 0 to 1, where 0 is the worst social performance and 1 is the best) in 13 indicators out of 23. Furthermore, local community, consumers, and society categories have a good social performance attributed to the absence of involuntary resettlement of individuals, the possibility of the product being reused for other purposes and technology accessible and affordable to developing countries, among others. Four out of seven indicators to evaluate the gender aspects and impacts have the highest score, demonstrating a commitment to fostering an inclusive and equitable work environment. The end-of-life phase presents a positive social performance with a score of 0.77 out of 1 attributed to the presence of infrastructure to dispose of product components other than landfill and incineration responsibly, the possibility of the product to be reused for other purposes and clear information provided to consumers on end-of-life options, among others. Conclusions The study presents generally good social impact and gender neutrality on the battery pack design. It gives an insight into the actual status of Li-ion battery social and gender impacts, and the results can be useful to policymakers to design and implement strategies for the welfare of various stakeholders.

Reduction of Oxygen Production by Algal Cells in the Presence of O-Chlorobenzylidene Malononitrile.

Chemical compounds, such as the CS gas employed in military operations, have a number of characteristics that impact the ecosystem by upsetting its natural balance. In this work, the toxicity limit and microorganism's reaction to the oxidative stress induced by O-chlorobenzylidenemalonitrile, a chemical found in CS gas, were assessed in relation to the green algae Chlorella pyrenoidosa. A number of parameters, including the cell growth curve, the percent inhibition in yield, the dry cell weight, the percentage viability and productivity of algal biomass flocculation activity, and the change in oxygen production, were analyzed in order to comprehend the toxicological mechanisms of O-chlorobenzylidenemalonitrile on algal culture. Using fluorescence and Fourier transform infrared spectroscopy (FTIR), the content of chlorophyll pigments was determined. The values obtained for pH during the adaptation period of the C. pyrenoidosa culture were between 6.0 and 6.8, O2 had values between 6.5 and 7.0 mg/L, and the conductivity was 165-210 µS/cm. For the 20 µg/mL O-chlorobenzylidenemalonitrile concentration, the cell viability percentage was over 97.4%, and for the 150 µg/mL O-chlorobenzylidenemalonitrile concentration was 74%. The ECb50 value for C. pyrenoidosa was determined from the slope of the calibration curve; it was estimated by extrapolation to the value of 298.24 µg/mL. With the help of this study, basic information on the toxicity of O-chlorobenzylidenemalonitrile to aquatic creatures will be available, which will serve as a foundation for evaluating the possible effects on aquatic ecosystems. The management of the decontamination of the impacted areas could take the results into consideration.

Sodium iodide dopant mediated enhancements in energy storage characteristics of polysaccharide polymer electrolytes

Sodium iodide dopant influencing the properties of polysaccharide polymer sodium carboxymethyl cellulose is analyzed in this work by FTIR, XRD, DSC, TGA, SEM, UTM, and electrical. Solvation of I− and Na+ ions by the −OH group has disrupted the intra– and intermolecular hydrogen bonds between the polymers escorting to a decrease in crystallinity and creating a pathway for ion diffusion. The formation of transient crosslink and the physical environment created by the polymer-ion interaction have affected the rigidity of the polymer chains as well as the thermal stability of the NaCMC−NaI system. I− ion influences the ESW of the NaCMC−NaI system by forming various iodine species. Trapping of the I− ion for the NaCMC70−NaI30 sample has resulted in a drop in ionic conductivity manifested in the transient ionic current curve. A cation transference number of 0.14 indicates the dominance of anion in the ion conduction mechanism. An energy density of 720 mWhkg−1 and power density of 60 mWkg−1 was achieved for a dry cell incorporated with a CI25 sample as the electrolyte and separator.

Omics-enabled understanding of electric aircraft battery electrolytes

Omics-enabled understanding of electric aircraft battery electrolytes

Smart Operation Control of Power and Heat Demands in Active Distribution Grids Leveraging Energy Flexibility

Demand flexibility plays a crucial role in mitigating the intermittency of renewable power sources. This paper focuses on an active distribution grid that incorporates flexible heat and electric demands, specifically heat pumps (HPs) and electric vehicles (EVs). Additionally, it addresses photovoltaic (PV) power generation facilities and electrical batteries to enhance demand flexibility. To exploit demand flexibility from both heat and electric demand, along with the integration of PVs and batteries, Control and Communication Mechanisms (CCMs) are formulated. These CCMs integrate demand flexibility into the distribution grids to obtain economic benefits for private households and, at the same time, facilitate voltage control. Concerning EVs, the paper discusses voltage-based droop control, scheduled charging, priority charging, and up-/down-power regulation to optimize the charging and discharging operations. For heat demands, the on-off operation of the HPs integrated with phase change material (PCM) storage is optimized to unlock heat-to-power flexibility. The HP controllers aim to ensure as much self-consumption as possible and provide voltage support for the distribution grid while ensuring the thermal comfort of residents. Finally, the developed CCMs are implemented on a small and representative community of an active distribution grid with eight houses using Power Factory software and DIgSILENT simulation language (DSL). This scalable size of the active distribution network facilitates the careful study of symbiotic interaction among the flexible load, generation, and different houses thoroughly. The simulation results confirm that the integration of flexible demands into the grid using the designed CCMs results in the grid benefiting from stabilized voltage control, especially during peak demand hours.

Molecular and Morphological Assessment of the Impact of Gas Flares on the Fungal Abundance and Diversity in soils of Niger Delta Area, Nigeria

Fungal abundance and diversity in soils of three communities flow stations (ID, IR and OB) owned by an unnamed oil exploration firm operating in the Niger Delta area for about five decades were determined using nucleic acid analytical methods. Top soil (0-15 cm) samples were collected from mini pits using sterile bottles at 50, 100 and 150 meters from the flare barrier of each community flow station and soil samples from the control was taken at 2.5 kilometers during the dry and wet seasons. The fungal properties were determined first using the cultural method of serial dilution method which revealed the presence of the following fungi; Aspergillus sp, and penicillium chrysogenum at 50 m away from flare in all the three flow stations during the dry seasons and in the wet season Aspergillus sp, penicillium chrysogenum, Mucor sp., yeast cells, A. niger, and Rhizopus sp. At 100 m away from flare, Mucor sp, A. niger and rhizopus were isolated in all three-flow station in the dry season and in the wet season, Yeast cells, A. niger, Aspegillus sp. and Rhizopus were isolated. P. chrysogenum, Aspergillus sp. and yeast cells were isolated at 150 m away from flare in the dry season and in the same distance, yeast cells, A. niger aggregate, A. niger and P. chrysogenum were isolated. At the control site, during the dry season, A. niger, P. chrysogenum, Aspergillus sp., Rhizopus sp. and Botryodiplodia threobome were isolated in the dry and A. niger, P. chrysogenum and yeast in the wet season. Fungal DNA was extracted using Norgen fungal genomic DNA extraction kits for the molecular analysis to establish the true characteristics and species identity of the isolates earlier identified with cultural methods. This revealed the presence of the following fungi upon sequence blast on NCBI database; Aspergillus fumigatus (Aspergillus fumigatus brown 2 (abr2) gene, complete cds strain), Aspergillus fumigatus (Aspergillus fumigates strain IHM 15988 pigment biosynthesis protein), Fusarium phyllophilum , Fusarium graminearum, Aspergillus oryzae (a strain of Aspergillus niger) Aspergillus oryzae (niger). Findings from this work have shown that molecular technique gave the exact identity of fungal species isolated from study area. All six (6) molecularly identified fungi were isolated from the three-study flow station and in both seasons. The Aspergillus group was dominant as a result of their ability to adapt to the flare environment

A REVIEW ON HYBRID ELECTRIC VEHICLES USING VARIOUS ENERGY STORAGE: A MODERN APPLICATION OF RENEWABLE ENERGY SOURCES

Climate change, diminishing reserves of fossil fuels, and energy security demand alternatives to our current course of energy usage and consumption. Energy storage technology has become an enabling technology for renewable energy applications and enhancing power quality in the transmission and distribution power systems. There are various types of energy storage technology are present nowadays, including compressed air energy storage(CAES), flywheel energy storage(FES), pumped hydro energy storage(PHES), battery energy storage(BES), flow battery energy storage(FBES), super conducting magnetic energy storage(SMES), super capacitor energy storage(SCES), hydrogen energy storage, synthetic fuels, and thermal energy storage(TES) and today’s one of the most talked technology using these Energy storage system is Electric Vehicles. Electric vehicles are superior to internal combustion engines (ICE) in efficiency, endurance, durability, acceleration capability and simplicity. Also, they can recover some energy during regenerative braking and they are also friendly with the environment. There are now four types of electric cars: battery electric vehicles (BEVs), plug-in hybrid electric vehicles (PHEVs), conventional hybrid electric vehicles (HEVs), and fuel-cell electric vehicles (FCEVs). And there are three charging methods for electric vehicles, namely conductive, inductive, and battery exchange. This paper will show a detail study of different energy storage systems’ characteristics with their suitability as a storage unit of Electric vehicle.

Development of an efficient process to extract C‐phycocyanin from marine cyanobacterial strains and evaluation of its bioactive potential

AbstractBACKGROUNDPhycocyanin (PC), a natural blue photosynthetic pigment found in cyanobacteria, rhodophyta and cryptophyta has numerous applications in biotechnology and the food industry. The phycocyanin extraction method has a significant impact on its bioactivities, purity index, cost and potential applications; thus, the development of an efficient extraction strategy continues to be a primary research goal.RESULTSThis study evaluated the efficacy of different methods for the extraction of cyanobacterial phycocyanin (C‐PC) from three marine cyanobacterial isolates, namely Arthrospira platensis, Phormidium sp. and Pseudoscillatoria sp. wet biomass. The pretreatment step of soaking biomass in extraction buffer for 60 min, followed by a combination of freeze–thaw (one cycle; 2 h) and sonication (2 min) treatment was found to be the most effective extraction strategy, producing the highest C‐PC yield (16.19 ± 0.34%, 15.89 ± 0.61% and 15.56 ± 0.69% dry cell weight for strains A. platensis, Phormidium sp. and Pseudoscillatoria sp., respectively). Furthermore, a biomass‐to‐solvent ratio of 0.02 g mL−1 was optimal to attain food‐grade purity ((A620/A280) ≥ 0.7). Bioactivity evaluation of crude and purified C‐PC exhibited its potential as antioxidant compounds and as an antimicrobial agent with significant inhibitory effects against various pathogenic microorganisms.CONCLUSIONThe study proposed an efficient and cost‐effective C‐PC extraction process for cyanobacteria and highlighted the potential of C‐PC as a valuable bioactive compound with various applications. © 2024 Society of Chemical Industry (SCI).

Friendly Environmental Strategies to Recycle Zinc-Carbon Batteries for Excellent Gel Polymer Electrolyte (PVA-ZnSO4-H2SO4) and Carbon Materials for Symmetrical Solid-State Supercapacitors.

In this report, we introduce a novel idea to prepare a redox additive in a gel polymer electrolyte system of PVA-ZnSO4-H2SO4 based on zinc-carbon battery recycling. Here, zinc cans from spent zinc-carbon batteries are dissolved completely in 1 M H2SO4 to obtain a redox additive in an aqueous electrolyte of ZnSO4-H2SO4. Moreover, carbon nanoparticles and graphene nanosheets were synthesized from carbon rod and carbon powder from spent zinc-carbon batteries by only one step of washing and electrochemical exfoliation, respectively, which have good electrochemical capability. The three-electrode system using a ZnSO4-H2SO4 electrolyte with carbon nanoparticles and graphene nanosheets as working electrodes shows high electrochemical adaptability, which points out its promising application in supercapacitor devices. Thus, the symmetrical solid-state supercapacitor devices based on the sandwich structure of graphene nanosheets/PVA-ZnSO4-H2SO4/graphene nanosheets illustrated the highest energy density of 39.17 W h kg-1 at a power density of 1700 W kg-1. While symmetrical devices based on carbon nanoparticles/PVA-ZnSO4-H2SO4/carbon nanoparticles exhibited a maximum energy density of 35.65 W h kg-1 at a power density of 1700 W kg-1. Moreover, these devices illustrate strong durability after 5000 cycles, with approximately 90.2% and 73.1% remaining, respectively. These results provide a promising strategy for almost completely recycling zinc-carbon batteries, one of the most popular dry batteries.

Simulation and Testing of Self-Reconfigurable Battery Advanced Functions for Automotive Application

This article presents the design and production work carried out jointly by Vitesco Technologies and the CEA in order to build a Self-Reconfigurable Battery (SRB) demonstrator representative of an electric vehicle traction battery pack. The literature demonstrates that the use of an SRB allows for individual bypassing or serialization of each cell in a battery pack, enabling control of the voltage output and dynamic balancing of the battery pack during all phases of vehicle use. The simulations and tests presented in this article confirm that the use of an SRB results in a 6% reduction in energy consumption compared to a Conventional Battery Pack (CBP) on a driving profile based on WLTP cycles. Additionally, an SRB enhances fast charging performance, with a charging time that is 22% faster than a CBP. Furthermore, it is shown that an SRB without a voltage inversion capability can still be connected directly to the AC grid for charging without the need for a dedicated converter, using only a single diode bridge rectifier for the whole system.

Comprehensive Multidisciplinary Electric Vehicle Modeling: Investigating the Effect of Vehicle Design on Energy Consumption and Efficiency

In this study, an electric vehicle (EV) dynamic model is devised that amalgamates mechanical design aspects—such as aerodynamic effects, tire friction, and vehicle frontal area—with crucial components of the electrical infrastructure, including the electric motor, power converters, and battery systems. Verification of the model is executed through a comprehensive multidisciplinary analysis utilizing CATIA, ANSYS Electromagnetics, ANSYS Fluent, and MATLAB–Simulink tools, which are applied to evaluate two alternative lightweight EV prototypes. The process involves initial computations of critical inputs for the dynamic model, including aerodynamic lift (C1), drag coefficients (Cd), and frontal area (Af). Subsequent stages entail the detailed design and analysis of a 2 kW brushless permanent magnet electric motor in ANSYS Electromagnetics to map efficiency contours across various speed–torque values. Integration of these parameters into a MATLAB–Simulink dynamic model, connected with motor drive inverter and battery models, allows for simulation-based energy consumption analysis under race track slope profiles. Remarkably, the findings underscore the considerable impact of neglected parameters on energy consumption, often exceeding fifty percent of the total. Consequently, an energy-efficient EV prototype is manufactured and rigorously tested under specified drive conditions, affirming the validation of the comprehensive multidisciplinary EV dynamic model.

Cohesive phycoremediation of pyrene by freshwater microalgae Selenastrum sp. and biodiesel production and its assessment.

In this study, the freshwater microalgae Selenastrum sp. was assessed for the effective degradation of pyrene and simultaneous production of biodiesel from pyrene-tolerant biomass. The growth of algae was determined based on the cell dry weight, cell density, chlorophyll content, and biomass productivity under different pyrene concentrations. Further, lipids from pyrene tolerant culture were converted into biodiesel by acid-catalyzed transesterification, which was characterized for the total fatty acid profile by gas chromatography. Increased pyrene concentration revealed less biomass yield and productivity after 20days of treatment, indicating potent pyrene biodegradation by Selenastrum sp. Biomass yield was unaffected till the 20mg/L pyrene. A 95% of pyrene bioremediation was observed at 20days of culturing. Lipid accumulation of 22.14%, as evident from the estimation of the total lipid content, indicated a marginal increase in corroborating pyrene stress in the culture. Fatty acid methyl esters yield of 63.06% (% per 100g lipids) was noticed from the pyrene tolerant culture. Moreover, fatty acid profile analysis of biodiesel produced under 10mg/L and 20mg/L pyrene conditionshowed escalated levels of desirable fatty acids in Selenastrum sp., compared to the control. Further, Selenastrum sp. and other freshwater microalgae are catalogued for sustainable development goals attainment by 2030, as per the UNSDG (United Nations Sustainable Development Goals) agenda. Critical applications for the Selenastrum sp. in bioremediation of pyrene, along with biodiesel production, are enumerated for sustainableand renewable energy production and resource management.

Use of xDomain Vehicle Simulation for Electric Vehicle HV Battery Health Prediction

Use of xDomain Vehicle Simulation for Electric Vehicle HV Battery Health Prediction