Large-scale Storage Research Articles

Investigation of the part load behavior for the R-Graz cycle with pure oxygen and hydrogen fuel

ABSTRACT In order to address the future demands for large-scale and efficient hydrogen storage and utilization, while considering the need of power dispatch and peak shaving, in this article, based on the cycle part load models and the conceptual design of the main components, the R-Graz cycle design parameters have been reoptimized, and subsequently, an analysis of the part load behavior and performance characteristics was conducted. The results show that within the load range discussed in this paper, i.e., 50% to 100%, the components of the R-Graz cycle are well matched, enabling high-efficiency operation. The net cycle efficiencies are 64.4% and 71.0% for 50% and 100% load respectively. Within this wide load range, the performance of the R-Graz cycle surpasses that of the Graz cycle consistently. When the load decreases, key parameters of the R-Graz cycle’s main components, such as rotational speed, pressure, temperature, mass flow rate and split ratio also decrease. Performance analysis under varying load conditions reveals that the maximum temperature in the cycle is a critical parameter affecting the efficiency of the R-Graz cycle. The research findings of this article lay the foundation for the practical application of the R-Graz cycle.

Mechanical stirring of bulk-stored maize in steel bins to suppress maize weevils and other beetle populations

This study investigates the effectiveness of periodic stirring as a non-chemical approach to suppress maize weevils, Sitophilus zeamais, and other beetle populations in large-scale grain storage bins. The research was conducted in a farm steel bin with a diameter of 9.8 m holding 127 Mg of maize, and a control bin of diameter 7.3 m holding 102 Mg of maize. Both bins were loaded with maize at 13% moisture and infested at a commercial tolerance rate of 2 weevils/kg of maize. Probe traps monitored beetle populations except for S. zeamais before stirring was initiated. Maize samples were collected at depths of 0, 0.9, 1.8 and 2.7 m with a vacuum-probe sampler prior to stirring and at 10, 20, 30 and 40 days of continuous stirring machine operation. Stirring achieved 100% control of live S. zeamais while the control bin experienced an increase in its S. zeamais population after 40 days. The stirring process also led to a significant reduction in dominant beetle populations such as hairy fungus beetles, Typhaea stercorea, and foreign grain beetles, Ahasuerus advena. Although the quality of maize in both bins changed at different depths and storage times, the treatment bin had higher bulk density (732.7 ± 3.98 kg/m3 to 768.9 ± 2.41 kg/m3), lower insect damage (0.02 ± 0.02% to 0.9 ± 0.28%), and higher allowable storage time (>249 days). Moisture content and molded kernels increased in the control bin, reaching 26.4 ± 1.29% and 3.2 ± 0.53%, respectively. The average percentage of broken corn and foreign material (BCFM) in the sweepings on the floor of the emptied treatment bin was 6.5 times higher than that in the control bin. Calculated packing factor values below 1.5 from the sweepings indicated that BCFM concentrations did not affect airflow. Stirring maize provides an alternative to the use of chemicals to control stored maize insect pests at a production scale.

Design and Implementation of Management Information System for University Library

With the rapid development of the Internet, information processing work in universities has also increased, from libraries to electronic book management platforms, everything is available. Although the number of libraries we have is constantly increasing and people's attention to them is also increasing, their existence is often universal, non-existent, and sometimes incomplete, which brings great difficulties to our daily management. Analyzed the workflow and functional requirements of university libraries, and applied them in practice to achieve better results. On this basis, the paper provides a detailed analysis of the main functions and various forms of the enterprise financial management information system. SQL Server 2008 is a database based system with high confidentiality and large-scale storage capacity. Through this concept and approach, one can better grasp and grasp the business skills required in daily work and work, greatly improving work efficiency. A library MIS based on AIS/S model was constructed using an A/S model and a SQL Server database. This software is user centered and librarian centered. They proposed a system to the library that maximized its workflow and improved its service management and supply.

The local disorder induced by high-entropy doping results in highly stable cathode materials for aqueous potassium-ion batteries

Aqueous potassium-ion batteries are poised to become leading candidates for next-generation large-scale storage technology due to their low cost and safety features. However, the stability of aqueous potassium-ion battery materials faces significant challenges. The large ionic radius of potassium ions causes significant stress changes in the ordered crystal structure of the materials during the charge-discharge process. To address this issue, we synthesized high-entropy-doped layered manganese oxide (HE-KMO). High-entropy doping reconstructed the electron cloud distribution between the layers of HE-KMO, causing local disorder in HE-KMO. Local disorder reduces the transport barrier by inducing the transport of potassium ions and alleviates the stress on the material. It prevented phase transitions of HE-KMO during charging and discharging, improving the stability of HE-KMO. We used HE-KMO in the cathode material of aqueous potassium-ion batteries. Under a current of 5 A g−1, HE-KMO maintains an outstanding capacity retention after 5000 cycles.

Cloud Computing for Large-Scale Resource Computation and Storage in Machine Learning

With the rapid development of Internet technology, cloud computing technology has gradually entered people's lives. Cloud computing provides users with various IT resources (computing, storage, etc.) in data centers all over the world through the Internet. Currently, there are hundreds of thousands of servers in large-scale data centers, and effective management of resources in such large-scale data centers is a major problem in academia and industry. This article explores the importance and pervasive use of cloud computing and machine learning in today's technology landscape. As the global cloud computing market size and the application of machine learning technologies continue to grow, the demand for computing and storage resources is also increasing. This paper aims to solve the challenges of large-scale resource computing and storage requirements in machine learning, and puts forward a solution how to give full play to the advantages of cloud computing platform and combine machine learning algorithms and technologies. Through practical data and case studies, we highlight the application scenarios, advantages and challenges of cloud computing in machine learning, and look forward to the future development trend.

Hydrogen adsorption and diffusion behavior in kaolinite slit for underground hydrogen storage: A hybrid GCMC-MD simulation study

Underground hydrogen storage (UHS) in reservoirs offers the opportunity for large-scale and long-term storage of hydrogen. In order to understand the fundamental mechanisms of hydrogen storage and transportation, it is crucial to study the adsorption and diffusion behavior of hydrogen in reservoirs. By utilizing a hybrid GCMC and MD simulation procedure, we investigated the adsorption and diffusion behavior of hydrogen in kaolinite slit with pore sizes ranging from 1 to 20 nm at pressures up to 30 MPa and temperatures ranging from 303 to 423 K. Hydrogen distribution, excess adsorption, diffusion coefficient, and gas–solid interaction energy were analyzed in relation to pore size, temperature, pressure, and mineralogy. When pores are larger than 5 nm, most of the hydrogen is located in the bulk phase, resulting in insignificant hydrogen loss due to adsorption. Therefore, reservoirs with pores larger than 5 nm are suitable for UHS. Reservoirs with low temperatures and high hydrogen pressures are conducive to UHS, but the hydrogen mobility is reduced. The mineralogy of the formation results in pore surfaces with different charge properties, which significantly affects hydrogen storage. Although van der Waals interaction dominates the gas–solid interaction, Coulomb interaction remains important. The negatively charged pore surface mitigates the gas–solid Coulomb interaction, thereby preventing hydrogen loss through adsorption. This study enhances our understanding of hydrogen storage mechanisms in subsurface porous media and elucidates the influence of various factors. Consequently, it provides a theoretical framework for selecting UHS sites.

CO2 Storage Site Analysis, Screening, and Resource Estimation for Cenozoic Offshore Reservoirs in the Central Gulf of Mexico

The storage potential of hydrocarbon reservoirs in the central Gulf of Mexico (GOM) makes future development of CO2 storage projects in those areas promising for secure, large-scale, and long-term storage purposes. Focusing on the producing and depleted hydrocarbon fields in the continental slope of the central GOM, this paper analyzed, assessed, and screened the producing sands and evaluated their CO2 storage potential. A live interactive CO2 storage site screening system was built in the SAS® Viya system with a broad range of screening criteria combined from published studies. This offers the users a real-time assessment of the storage sites and enables them to adjust the filters and visualize the results to determine the most suitable filter range. The CO2 storage resources of the sands were estimated using a volumetric equation and the correlation developed by the National Energy Technology Laboratory (NETL). The results of this study indicate that 1.05 gigatons of CO2 storage resources are available in the developed reservoirs at the upper slope area of the central GOM. The Mississippi Canyon and Green Canyon protraction areas contain the fields with the largest storage resources.

Recent Advances in Reversible Liquid Organic Hydrogen Carrier Systems: From Hydrogen Carriers to Catalysts.

Liquid organic hydrogen carriers (LOHCs) have gained significant attention for large-scale hydrogen storage due to their remarkable gravimetric hydrogen storage capacity (HSC) and compatibility with existing oil and gas transportation networks for long-distance transport. However, the practical application of reversible LOHC systems has been constrained by the intrinsic thermodynamic properties of hydrogen carriers and the performances of associated catalysts in the (de)hydrogenation cycles. To overcome these challenges, thermodynamically favored carriers, high-performance catalysts, and catalytic procedures need to be developed. Here, significant advances in recent years have been summarized, primarily centered on regular LOHC systems catalyzed by homogeneous and heterogeneous catalysts, including dehydrogenative aromatization of cycloalkanes to arenes and N-heterocyclics to N-heteroarenes, as well as reverse hydrogenation processes. Furthermore, with the development of metal complexes for dehydrogenative coupling, a new family of reversible LOHC systems based on alcohols is described that can release H2 under relatively mild conditions. Finally, views on the next steps and challenges in the field of LOHC technology are provided, emphasizing new resources for low-cost hydrogen carriers, high-performance catalysts, catalytic technologies, and application scenarios.

Simulations-based investigation of the effectiveness of fire suppression techniques for safe, large-scale storage of Li-ion batteries

Thermal runaway and subsequent fire in Li-ion cells and battery packs is of much concern in the safety of practical electrochemical energy storage systems. While much of the past work in this direction has focused on single cells or small packs, there is a relative lack of understanding of thermal runaway related fire and fire suppression strategies for large-scale systems, for example in storage and transportation of Li-ion cells. This work presents a simulations-based investigation of strategies for effective prevention and suppression of thermal runaway propagation and resulting fire in pallets containing a large number of Li-ion cells. The impact of location, orientation and flowrate in sprinklers supplying a liquid coolant is quantitatively investigated. It is shown that a minimum flowrate is needed for effective fire containment, beyond which, additional flowrate does not offer much incremental benefit. The orientation of sprinklers with respect to the trigger pallet undergoing thermal runaway is found to strongly impact the effectiveness of fire suppression. Fire suppression in the case of vertically stacked pallets is also investigated. Interesting synergistic effects involving a combination of liquid coolant along with one or more suppressant gases is demonstrated. The key output of this work is a computational model that quantitatively predicts the effectiveness of fire suppression techniques for battery transportation and storage. Results presented here offer a fundamental understanding of an important practical problem in battery-based energy storage. Results may form the basis of design and optimization to ensure the safety of large-scale storage and transportation of Li-ion cells.

A conceptual CO2 fill-and-spill mega-fairway in the UK Southern North Sea: A new approach to identify and optimise large-scale underground carbon storage (CCS)

This work explores the subsurface CO2 storage potential in UKCS Quadrants 43–44, by integrating 3D seismic interpretation, regional wellbore data and CO2 migration modelling. We show 11 Bunter Sandstone domes linked together in a fill-and-spill “Bunter Mega-Fairway”. These traps host a theoretical storage capacity of 8.4 Gt CO2 (≈3–4 times the filled-to-spill theoretical capacity of the proposed Endurance storage site), while lessening CO2 leakage risks.Within the mega-fairway, the Triassic Bunter Sandstone reservoir shows a P10-P90 thickness of 78–219 m, along with moderate-high porosities (11–28 %) and permeabilities (9–669 mD). A regionally-connected reservoir is suggested from spatially consistent, near-hydrostatic aquifer pressure gradients (≈0.51 psi/ft). The top-seal is laterally effective and structural closures are lower than the CO2 columns necessary to breach the seal.At the mega-fairway storage depths, CO2 would inhabit the reservoir as a supercritical fluid, enabling it to naturally migrate buoyantly from one trap to another, away from strategically-placed injector sites. Through the integration of migration spill-point modelling, multi-physics seabed monitoring nodes and fill-and-spill injection management, the maximum storage capacity could be achieved, while alleviating CO2 leakage hazards and potentially decreasing the number of injector wells.Exploiting fill-and-spill fairways for CCS is a new concept with vast worldwide applicability.

Machine Learning-Based Interfacial Tension Equations for (H2 + CO2)-Water/Brine Systems over a Wide Range of Temperature and Pressure.

Large-scale underground hydrogen storage (UHS) plays a vital role in energy transition. H2-brine interfacial tension (IFT) is a crucial parameter in structural trapping in underground geological locations and gas-water two-phase flow in subsurface porous media. On the other hand, cushion gas, such as CO2, is often co-injected with H2 to retain reservoir pressure. Therefore, it is imperative to accurately predict the (H2 + CO2)-water/brine IFT under UHS conditions. While there have been a number of experimental measurements on H2-water/brine and (H2 + CO2)-water/brine IFT, an accurate and efficient (H2 + CO2)-water/brine IFT model under UHS conditions is still lacking. In this work, we use molecular dynamics (MD) simulations to generate an extensive (H2 + CO2)-water/brine IFT databank (840 data points) over a wide range of temperature (from 298 to 373 K), pressure (from 50 to 400 bar), gas composition, and brine salinity (up to 3.15 mol/kg) for typical UHS conditions, which is used to develop an accurate and efficient machine learning (ML)-based IFT equation. Our ML-based IFT equation is validated by comparing to available experimental data and other IFT equations for various systems (H2-brine/water, CO2-brine/water, and (H2 + CO2)-brine/water), rendering generally good performance (with R2 = 0.902 against 601 experimental data points). The developed ML-based IFT equation can be readily applied and implemented in reservoir simulations and other UHS applications.

Multiscale Model for Hydrogen Transport and Storage in Shale Reservoirs

Summary Utilizing underground geological structures for hydrogen storage is an effective approach for energy transformation. The depleted shale reservoirs can be considered as promising options for large-scale hydrogen storage because of the vast storage capacity, high containment security, and low operation cost. However, it is challenging to characterize the hydrogen transportation mechanism and estimate hydrogen storage potential in shale formations from multiscale perspectives. In this paper, we propose a multiscale model for hydrogen transport and storage in partially depleted hydraulically fractured shale reservoirs, considering the effects of gas diffusion, adsorption, slip flow, and continuous flow. By the Laplace transformation and Pedrosa substitution, a computationally effective semi-analytical solution was derived and validated with a commercial numerical simulator. A hydrogen storage capacity (HSC) assessment workflow is proposed using a typical shale reservoir in the Appalachian Basin as a case study. The results indicate that the storage capacity can reach up to 31.92×108 m3 at a high constrained injection pressure. In addition, the HSC is strongly controlled by the adsorption property, diffusion coefficient, shale composition, flow capacity between different scale media, and mobility ratio. The influence of most reservoir parameters on storage potential is negligible at low constrained pressure but critical at high constrained pressure. Such a model can be used as a robust pressure predictor and storage capacity estimator for hydrogen storage projects in partially depleted shale reservoirs.

Trifunctional Rb+-Intercalation Enhancing the Electrochemical Cyclability of Ammonium Vanadate Cathode for Aqueous Zinc Ion Batteries.

Rechargeable aqueous zinc-ion batteries (AZIBs) have been highly desired due to their low cost, intrinsic safety, environmental friendliness, and great potential in large-scale power storage systems. However, their practical applications are impeded by unstable long-term electrochemical performances induced by microstructure degradation of the cathode material, hydrogen evolution reaction in the electrolyte, and dendritic growth on the zinc anode upon cycling. In this work, rubidium cations (Rb+) are introduced to synthesize an Rb+-preintercalated NH4V4O10 (NVO-Rb) composite. The contribution of Rb+ ions as pillars in V-O interlayers to facilitating Zn2+ storage is investigated first, and then the influences of partial Rb+ ions from the NVO-Rb cathode on the aqueous electrolyte and zinc anode are specially inspected from different viewpoints. Based on a series of characterization results, it is comprehensively elucidated that the partial Rb+ ions into the electrolyte suppress the generation of byproducts on the cathode and regulate the dendrite growth on the zinc anode, thus effectively promoting the long-term electrochemical performances of NVO-based AZIBs. The assembled Zn∥Zn(CF3SO3)2∥NVO-Rb cell can exhibit a high specific capacity and optimized Zn2+ diffusion kinetics, especially an improved electrochemical cyclability with a capacity retention of 87.6% at 5 A g-1 over 10000 cycles. This study enlightens the multiple roles of cation-preintercalation in the layered structure material and provides a feasible strategy for the development of high-performance aqueous batteries.

Integration of curtailed wind into flexible electrified heating networks with demand-side response and thermal storage: Practicalities and need for market mechanisms

Increasingly high renewable penetration in electrified energy systems causes increasing levels of curtailment that must eventually be mitigated. System flexibility, energy storage and demand-side response in the form of flexible heating and cooling demands are efficient solutions for curtailment mitigation, however challenges remain such as the economic benefits of energy storage and the financial impacts of curtailment mitigation on consumers, among others. In this paper the mitigation of curtailed wind energy, incentivised with discount payments, through flexible electrified heating networks with demand-side response and thermal energy storage is investigated with a genetic optimisation algorithm, and results are analysed in terms of overall costs, technical feasibility and level of curtailed wind use from the perspective of the network operator and consumer. It is found that large-scale thermal storage lowers the cost and increases levels of curtailed wind integration, and allows district heating networks to run almost entirely on otherwise curtailed wind energy (up to 97.0 % in the example considered here). However without adequate market mechanisms, demand-side response is financially beneficial to all stakeholders only at low levels; with a split cost approach, financial incentives or market mechanisms are necessary for higher levels of, and more efficient, wind curtailment mitigation.

Switchable Charge Storage Mechanism via in Situ Activation of MXene Enables High Capacitance and Stability in Aqueous Electrolytes.

The need for reliable renewable energy storage devices has become increasingly important. However, the performance of current electrochemical energy storage devices is limited by either low energy or power densities and short lifespans. Herein, we report the synthesis and characterization of multilayer Ti4N3Tx MXene in various aqueous electrolytes. We demonstrate that Ti4N3Tx can be electrochemically activated through continuous cation intercalation over a 10 day period using cyclic voltammetry. A wide operating window of 2 V is maintained throughout activation. After activation, capacitance at 2 mV s-1 increases by 300%, 140%, and 500% in 1 M H2SO4, 1 M MgSO4, and 1 M KOH, respectively, while maintaining ∼600 F g-1 at 2 mV s-1 after 50000 cycles in 1 M H2SO4. This activation process is possibly attributed to the unique morphology of the multilayered material, allowing cation intercalation to increase access to redox-active sites between layers. This work adds to the growing repository of electrochemically stable MXenes reported for aqueous energy storage applications. These findings offer a reliable option for reliable energy storage devices with potential applications in large-scale grid storage and electric vehicles.

Full-cycle enhancing condensate recovery-underground gas storage by integrating cyclic gas flooding and storage from gas condensate reservoirs

Underground gas storage (UGS) is efficient in large-scale natural gas storage and peak regulation. However, UGS operation based on gas-condensate reservoirs are challenging due to complicated phase behavior and multi-phase flow considering trapped condensate. This paper presents a method for full-cycle enhancing condensate oil recovery (EOR)-UGS by integrating cyclic gas flooding and storage from gas-condensate reservoirs. Full-cycle EOR-UGS is defined by four stages, including primary depletion, cyclic gas flooding, collaborative gas production and UGS operation. The EOR mechanisms of each stage are analyzed by experiments and simulation. Cyclic gas flooding can reduce drop out of condensate. The reasonable volume of cyclic gas flooding is 0.5 HCPV, enhancing condensate recovery factor by 42.8%. During the collaborative stage, gas injection can effectively evaporate and drive the condensate towards production wells. After five collaborative cycles, the condensate recovery factor is further enhanced by 21.8% and gas storage capacity can be increased more than 30%. Finally, optimal full-cycle EOR-UGS schemes can enhance condensate recovery factor by 69.92%. Compared with gas flooding to 1.5 HCPV followed by constructing UGS, the full-cycle EOR-UGS integration can improve condensate recovery factor by 7.37%. This work provides a new idea for UGS construction and operation based on gas-condensate reservoirs.

Innovative Power Generation Technologies for Improved Household Energy Delivery and Sustainable Future: Classical Solutions from ENEA Research Centre, Trisaia Italy

The present communication is focused predominantly on important R&D solutions relevant to renewable energy technologies covering the following: (i) Innovative heat transfer fluid and thermal storage technology based on a molten salt mixture developed by ENEA for large-scale heat storage. The system uses a parabolic trough collector, compared with diathermic oil, which allows higher operating temperature, resulting in significant benefits to the plant’s operation, safety and the environment. (ii) The world’s first solar disk powered by air micro turbine developed by ENEA. (iii) An innovative steam-explosion prototype plant installed at ENEA for the pre-treatment of lignocellulosic biomass and the fractionation of bio components to generate ethanol from lignocellulosic material using hemicellulose and lignin. (iv) The production of hydrogen-enriched biogas using steam as the gasification agent, which helps in obtaining nearly nitrogen-free product gas and with a high calorific value of around 12 MJ/Nm3 dry gas and a high percentage of hydrogen (up to 55%) while using steam as the gasifying agent in the presence of a catalyst. (v) A rotary kiln plant, with the main purpose being to develop and optimize a thermo-chemical process to convert used rubber tyres so as to recover material and energy, as well as other solid products, with high value-added “Activated carbon” and synthesis gas.

"Cell Disk" DNA Storage System Capable of Random Reading and Rewriting.

DNA has emerged as an appealing material for information storage due to its great storage density and durability. Random reading and rewriting are essential tasks for practical large-scale data storage. However, they are currently difficult to implement simultaneously in a single DNA-based storage system, strongly limiting their practicability. Here, a "Cell Disk" storage system is presented, achieving high-density in vivo DNA data storage that enables both random reading and rewriting. In this system, each yeast cell is used as a chamber to store information, similar to a "disk block" but with the ability to self-replicate. Specifically, each genome of yeast cell has a customized CRISPR/Cas9-based "lock-and-key" module inserted, which allows selective retrieval, erasure, or rewriting of the targeted cell "block" from a pool of cells ("disk"). Additionally, a codec algorithm with lossless compression ability is developed to improve the information density of each cell "block". As a proof of concept, target-specific reading and rewriting of the compressed data from a mimic cell "disk" comprising up to 105 "blocks" are demonstrated and achieve high specificity and reliability. The "Cell Disk" system described here concurrently supports random reading and rewriting, and it should have great scalability for practical data storage use.

Semi-analytical model of a large-scale water pit heat storage for the long-term thermal applications

Solar district heating systems reduce carbon emissions effectively. Large-scale water pit thermal energy storages (PTES) have high heat capacities, low costs per cubic volume, and long lifetimes. Integrating PTES with a solar heating system can significantly increase solar heating efficiency and alleviate the time and climate constraints of renewable energy. An improved TRNSYS semi-analytical model of PTES (Type 1535–1301) is proposed based on the finite difference method. The model is characterized by discretizing the energy equation and then combining it with the analytical solution of the full differential equation to find the temperature variation. The model is validated with a full year measurement on a Danish PTES. In addition, a parametric investigation of grid discretization, storage geometry, soil properties, and diffuser location is performed. The control strategies are investigated to best utilize the PTES for demand response. The results indicate that the Type 1535–1301 model accurately predicts the year-round thermal performance of the PTES. The differences between the calculated and measured energies are lower than 1.3 %, and the differences between the calculated and measured temperatures are lower than 2.8 K. With an increase of the slope angle of the PTES side wall, the top and side heat losses decrease, and the storage temperature and thermal stratification effectiveness improve. Furthermore, the relative Fourier number (Fom) is proposed to represent the soil thermal diffusivity. The rise ofFom leads to an increase of heat loss and a decrease of storage efficiency. The analysis show that the top diffuser is best located at the highest position, and the bottom diffuser is best placed at the lowest position. At the same time, the middle diffuser is best placed at 29 % of the total volume from top to bottom. The semi-analytical model in this paper decreases the annual heat transfer computation time for a single grid to 57 ms. The model has been embedded into TRNSYS for convenient system prediction. The findings of this paper can be used as a reference for engineering practice and subsequent research.

A review of electrochemical cells and liquid metal battery (LMB) parameter development

Liquid Metal Battery (LMB) technology is a new research area born from a different economic and political climate that has the ability to address the deficiencies of a society where electrical energy storage alternative are lacking. The United States government has begun to fund scholarly research work at its top industrial and national laboratories. This was to develop liquid metal battery cells for energy storage solutions. This research was encouraged during the Cold War battle for scientific superiority. Intensive research then drifted towards high energy rechargeable batteries, which work better for automobiles and other applications. Intensive research has been carried out on the development of electrochemical rechargeable all-liquid energy storage batteries. The recent request for green energy transfer and storage for various applications, ranging from small-scale to large-scale power storage, has increased energy storage advancements and explorations. The criteria of high energy density, low cost, and extensive energy storage provision have been met through lithium-ion batteries, sodium-ion batteries, and Liquid Metal Battery development. The objective of this research is to establish that liquid metal battery technology could provide research concepts that give projections of the probable electrode metals that could be harnessed for LMB development. Thus, at the end of this research, it was discovered that the parameter estimation of the Li//Cd-Sb combination is most viable for LMB production when compared with Li//Cd-Bi, Li-Bi, and Li-Cd constituents. This unique constituent of the LMB parameter estimation would yield a better outcome for LMB development.