Developed Scheme Research Articles

A Combined Physical-Mechanical and Hydrometallurgical Approach for Recovering Valuable Metals from Spent Lithium-ion Batteries

In this work, the chemical composition of electrode materials from two samples of lithium-ion batteries (LiB) is comprehensively investigated. The material balance of the physical and mechanical processing of the LiBs mixture is determined. The developed dry process scheme made it possible to extract the following components (wt.%): 15.6 plastic (ABS), 1.89 electronic materials (PP), 59.1 black mass (three types), 6.43 plastic (PVC), 2.97 Al, 6.31 Cu and 7.1 magnetic fraction (Fe). The thermodynamics of reductive leaching of LiCoO<sub>2</sub> in the H<sub>2</sub>SO<sub>4</sub>-HCOOH system was studied. It was calculated that the Gibbs energy of the leaching reaction at 363 K is -327.4 kJ/mol, the equilibrium constant is 2.02×10<sup>44</sup>. All these factors showed the potential of using formic acid as a reducing agent instead of the commonly used hydrogen peroxide solution. It is known to be unstable, since when the solution is heated from 20 to 50<sup>0</sup> C, the decomposition of H<sub>2</sub>O<sub>2</sub> increases 20 times, and the presence of copper sulfate, which usually accompanies the decomposition of the black mass in a sulfuric acid medium, leads to the destruction of 76% of hydrogen peroxide. Therefore, from a practical point of view, it was of interest to study the kinetics of cobalt dissolution from the cathode material in the H<sub>2</sub>SO<sub>4</sub>-HCOOH system. It was shown that the Crank-Ginstling-Braunstein equation agrees satisfactorily with the experimental data, which indicates intra-diffusion limitation of dissolution. The activation energy was determined. The optimal composition and conditions of the leaching solution for dissolving cobalt, lithium and associated transition metals from the black mass were determined. The thermodynamics and kinetics of dissolution of Ag, Au and Pd from electrode materials in a bromide-bromine solution were also studied.

Solution scheme development of the nonhomogeneous heat conduction equation in cylindrical coordinates with neumann boundary condition by finite difference method

Partial differential heat conduction equations are typically used to determine temperature distribution within any solid domain. The difficulty and complexity of the solution of the equation depend on differential equation characteristics, boundary conditions, coordinate systems, and the number of dependent variables. In the current study, the numerical solution schemes were developed by the Explicit Finite Difference and the Implicit Method- the Crank-Nicolson techniques for the partial differential heat conduction equation including heat generation term described as one-dimensional, time-dependent with the Neumann boundary conditions. The solution schemes were, then, applied to the battery problem including highly varying heat generation. Besides, the solution of the problem was performed by using Matlab pdepe solver to verify the developed schemes. Results suggest that the Crank-Nicolson scheme is unconditionally stable, whereas the explicit scheme is only stable when the Courant-Friedrichs-Lewy condition requirement is less than 0.3404. Comparing the developed schemes to the results obtained from the pdepe solver, the schemes are as reliable as the pdepe solver with certain grid structures. Besides, the developed numerical schemes allow for shorter computational times than the pdepe solver at the same grid structures when considering CPU times.

Distribution law of Chang 7 Member tight oil in the western Ordos Basin based on geological, logging and numerical simulation techniques

Abstract Fine characterization of oil plane distribution in highly heterogeneous tight sandstone is a prerequisite for efficient reservoir development. This study systematically evaluated the distribution characteristics of tight oil in the Chang 7 Member of the Western Ordos Basin using a large number of experimental tests, logging interpretation, and 3D modelling methods. The logging interpretation models of shale content, porosity, permeability, and oil saturation were constructed, and the effective reservoir was identified by establishing the intersection identification pattern of reservoir acoustic wave time difference and deep lateral resistivity. The 3D numerical simulation results showed that the tight oil is distributed between injection and production wells. The areas with high tight oil content are mainly distributed along the WE direction, and a series of high remaining oil zones are formed locally. Under the influence of long-term injection and production, a high permeability zone will be formed between wells, which is similar to a high-speed channel and will be flooded quickly, and a banded remaining oil retention zone will be formed around it. For the horizontal well flooding area, the water flooding range of the water injection well is small, and a large amount of remaining oil is enriched between water injection wells. Finally, the classification standard of the remaining oil in the Chang 72 sub-member of the study area is proposed, and then, the strategy of adopting different development and adjustment schemes according to different types of reservoirs is formed.

Assessing and mitigating transfer gaps through ecosystem interactions

The purpose of this paper is to determine the most appropriate model of cooperation between an enterprise and the innovation ecosystem of the territory based on the assessment of its readiness to implement joint innovation activities. One of the requirements necessary for the effectiveness of innovation activity is to ensure the continuity of innovation processes along the entire value chain. The peculiarities of different organizations and different levels of readiness of ecosystem participants for innovation activities lead to ambiguity in the choice of possible options for partnership interactions. The paper presents a scheme of development for the territory's innovation ecosystem based on the concept of a minimum viable ecosystem. The concept of transfer gap is introduced as a violation of the continuity of the process of transfer (transfer) of the results of innovation activity along the entire value chain, which does not allow to obtain a competitive result (an innovative product) and/or bring it to the consumer within a competitive timeframe. Researchers identify two components of the transfer gap: technological and managerial. We developed indicators and scales for their assessment. On the basis of analyzing the interests and risks of participants in innovation processes in all links of the innovation chain, the possibilities of the innovation ecosystem to dampen transfer gaps are identified. We form the model of overcoming transfer gaps on the basis of partnership interactions.

Empowering E-mobility: Day-ahead dynamic time of use tariff for electric vehicle charging

The greenhouse gases and preservation of the environment have been the most prioritized concern in many countries and international organizations, leading to set aims and initiatives for lowering the dependency on fossil fuels and minimizing carbon emissions. As a part of many initiatives, great emphasis is given to promoting electric vehicles (EVs) over their traditional carbon fuel-based counterpart. To support large-scale EV adoption, a dynamic tariff scheme is required that addresses complex issues like user comfort, savings, and utility revenue. In this research work, a dynamic pricing scheme is modeled for the centralized EV charging stations (EVCS) on a residential feeder. This pricing scheme integrates the existing static time of use (ToU) pricing to an hourly dynamic ToU tariff that varies according to the demand level in the residential feeder. The proposed tariff plan provides a day-ahead dynamic structure with a probable price variation range to aid the EV owners and the day-ahead charging mechanism to schedule the EVs beforehand. The developed scheme calculates the returns and adjusts the tariff including the demand charge and the recovery component on a daily, monthly, and yearly basis for the unsatisfactory investment revenue. Also, user convenience is ensured by setting the minimum possible tariff as well as satisfying the minimum revenue target with the integration of particle swarm optimization (PSO) in designing the pricing structure. The simulation results demonstrate the effectiveness of the proposed dynamic pricing scheme maintaining a trade-off between the interests of all parties involved. Moreover, the simulation outcome of the test case indicates that EV owners can save more than 32 % on charging bills if they plan correctly. On the other hand, the utility can earn more than 2.4 times the existing rate during the peak time of the residential feeder.

Joint optimization for service-caching, computation-offloading, and UAVs flight trajectories over rechargeable UAV-aided MEC using hierarchical multi-agent deep reinforcement learning

Due to the high mobility, high chance of line-of-sight (LoS) transmission, and flexible deployment, unmanned aerial vehicles (UAVs) have been used as mobile edge computing (MEC) servers to provide ubiquitous computation services to mobile users (MUs). However, the limited energy storage, caching capacity, and computation resources of UAVs bring new challenges for UAV-aided MEC, e.g., how to recharge UAVs and how to jointly optimize service-caching, computation-offloading, and UAVs flight trajectories. To overcome the above-mentioned difficulties, in this paper we study the joint optimization for service-caching, computation-offloading, and UAVs flight trajectories for UAV-aided MEC, where multiple rechargeable UAVs cooperatively provide MEC services to a number of MUs. First, we formulate an energy minimization problem to minimize all MUs' energy consumptions by taking into account the mobility of MUs and the energy replenishment of UAVs. Then, using the hierarchical multi-agent deep reinforcement learning (HMDRL), we develop a two-timescale based joint service-caching, computation-offloading, and UAVs flight trajectories scheme, called HMDRL-Based SCOFT. Using HMDRL-Based SCOFT, we derive UAVs' service-caching policies in each time frame, and then derive UAVs flight trajectories and MUs' computation-offloading in each time slot. Finally, we validate and evaluate the performances of our proposed HMDRL-Based SCOFT scheme through extensive simulations, which show that our developed scheme outperforms the other baseline schemes to converge faster and greatly reduce MUs' energy consumptions.

Economic Implications and Public Readiness for Urban Green Space Development in Agra: A Strategic Evaluation in the City of Taj

Urban green spaces (UGSs) improve the environmental value of the city as well as the quality of life for citizens. Unfortunately, many cities in India are lagging behind the minimum standard of UGS required in the city. For example, Agra city in India, one of the most famous tourist destinations in the world, represents two distinct realities of UGS in the same city. One is the focus of tourism, and the rest is the place of common people with very limited public green spaces, leading to multiple social issues (like spatial polarization, etc.). The secondary data concludes that the PPGC of Agra is lower than the standards, and the ongoing schemes are approached through quantitative methods. Despite having many UGS development schemes, Agra's UGS shows stalled growth. This research examines the policies and programs of UGS development (AMRUT, SCM, etc.) and reviews them to understand the unique gaps and possible regulatory interventions. The study includes an assessment of stakeholders' readiness to accept plausible UGS strategies using an analytical analysis approach. The primary data shows that PPP is the requirement for the integrated development of UGSs. The planners can make policies highlighting citizen's rights and responsibilities to enhance UGSs in Agra.

Hierarchical Distributed Adaptive Fault-Tolerant Control of Nonlinear Fractional-Order Multiagent Systems With Faults and Periodic Disturbances Using Event-Triggered Communication.

This article presents a distributed fault-tolerant control (FTC) scheme for nonlinear fractional-order (FO) multiagent systems (MASs) with the order lying in (0, 1], such that the proposed control architecture can be directly applied to both FO and integer-order (IO) systems without any modifications. To handle the unexpected actuator faults encountered by the FO MASs, a hierarchical FTC mechanism is developed for each system by constructing an event-triggered distributed FO estimator at the upper layer to estimate the leader system's output via conditionally triggered neighboring information, and an FTC unit at the lower layer to counteract the loss-of-effectiveness faults via Nussbaum function with FO criteria. To further address the unknown nonlinear functions involving bias faults and periodic disturbances, the Fourier series expansion technique is used to construct the input variables of fuzzy neural networks (FNNs), such that the FNNs with dynamically adjusted weight matrices, centers, and widths can be developed for each FO system to act as the learning module. It is shown by FO Lyapunov stability analysis that all follower systems can track the leader system against faults and periodic disturbances. Simulation results on FO systems and hardware-in-the-loop experiment results on IO fixed-wing unmanned aerial vehicles show the extensive feasibility of the developed scheme.

Digitally enhanced development of customised lubricant: Experimental and modelling studies of lubricant performance for hot stamping

Digitally enhanced technologies are transforming every aspect of the manufacturing sector towards the era of digital manufacturing. Traditional lubricant development methods involving systematic but time-consuming iterative processes is still extensively used in the metal forming industry. In the present study, a novel digitally enhanced lubricant development scheme was proposed by leveraging a mechanism-based interactive friction modelling framework and quantitative and comprehensive evaluation of lubricant performance via the data-centric lubricant limit diagrams. By predicting transient lubricant behaviour following the complex contact condition evolution experienced in actual forming operations, a close association and quantified relation between the lubricant performance and its properties such as viscosity, evaporation rate and fraction of dry matter was established. This can facilitate the optimisation efficiency of lubricant parameters and minimise the experimental cost for iterative lubricant trials. A case study was conducted in this work to develop a customised lubricant using this digitally enhance scheme for the target hot stamping process based on a benchmark lubricant as a reference. Further industrial forming tests of an automotive component were conducted to validate the ideal performance of the customised lubricant.

A fast and reliable semi-analytical method for assessing energy replenishment from fracturing-flooding in low-permeability and tight oil reservoirs

The development of low-permeability and tight oil reservoirs is challenged by insufficient natural energy and rapid production decline. Fracturing-flooding is a technique that relies on high-pressure and large-volume fluid injection to replenish reservoir energy, making it a significant method for rapidly boosting formation energy. To evaluate the energy replenishment effect of fracturing-flooding technology in low-permeability and tight reservoirs, this study proposes a semi-analytical method for quick calculation. This approach employs dimensionless simplification, Pedrosa's substitution, Laplace transformation, and Stehfest inversion methods to derive pressure solutions for both the stimulation region and the external matrix region, each with varying flow capacities. The average formation pressure (AFP) of the reservoir is determined using the area-weighted average method, and numerical verification is performed using a commercial simulator. A case study from the Binnan area, along with a sensitivity analysis, demonstrates that after 30 days of fracturing-flooding, the AFP of the reservoir increases to 46.97 MPa, the corresponding reservoir pressure coefficient rises from 1.2 to 1.68, and reservoir energy increases by 40%. The factors influencing energy replenishment are ranked as follows: reservoir thickness, injection rate, stress sensitivity coefficient, matrix permeability, stimulation region radius, and mobility ratio. This study provides theoretical guidance for optimizing fracturing-flooding development schemes in low-permeability and tight oil reservoirs and offers valuable reference for the industry.

Joint buffetings suppression and trajectory tracking by fuzzy-based super-twist sliding mode control: Application to a fast parallel robot for PnP operations

This paper deals with the suppression of robotic joint buffetings for enhanced precision of trajectory tracking by means of fuzzy-based super-twist sliding mode control, which is illustrated with a fast pick-and-place parallel robot for material handling. Prior to control design, the joint motions and torques are measure to identify the dynamic parameters of the robot with recursive least square method, which is experimentally validated for the further model-based control design. In order to suppress the joint buffetings and to improve the tracking accuracy, the control law by integrating fuzzy algorithm and second-order sliding mode control is designed, where the control performance is evaluated by observing the joint dynamics, compared to the classical computed torque control and fuzzy sliding mode variable structure control. The experimental results and comparative study show the effectiveness of the developed control scheme, regarding the joint buffetings suppression and trajectory tracking precision. The main contribution lies in the integrated fuzzy algorithm and second-order sliding mode control for the model-based control design, with acceptable computational cost and trajectory tracking accuracy, from the perspective of actual engineering application.

Enhancing fraud detection efficiency in mobile transactions through the integration of bidirectional 3d Quasi-Recurrent Neural network and blockchain technologies

Cases of financial fraud are increasing despite recent technical breakthroughs. It is tough to find authentic financial transaction data due to privacy issues and a lack of inter-organization synergy. However, for technologies based on data, such as machine learning to function accurately inside practical systems, they require actual data. This manuscript proposes a Fraud Detection (FD) Efficiency in Mobile Transactions through the Integration of Bidirectional 3D Quasi-Recurrent Neural Networks and Proof of Voting consensus Blockchain Technologies (Bi-3DQRNN-PoV-FD-MT). A dataset of Bitcoin transactions is employed in the suggested model. The banking sector’s Bitcoin transactions serve as the foundation for this dataset. Then the data balancing is performed using a Self-Adaptive Synthetic Over-Sampling Technique (SASOS). Then, the proposed framework utilizes the Bi-3DQRNN to determine if the information is fraudulent or not. Moreover, an intelligent Enhanced Artificial Gorilla Troops (EAGTO) Optimization algorithm is introduced to tune the weights of the model parameters. A blockchain-based proof of Voting (PoV) consensus algorithm is integrated with the proposed model for forecasting upcoming transactions. The developed scheme is instigated in Python and the performance provides 12.09%, 8.91%, and 6.92% higher accuracy compared with existing techniques like K-nearest neighbor- Distributed Blockchain Consortium (KNN-DBC), Decision tree-Ethereum blockchain-enabled smart contract (DT-EBSC) and Heterogeneous Graph Transformer Networks-Ethereum smart contract (HGTN-ESC).

The Effect of Multilateral Economic Cooperation on Sustainable Natural Resource Development

The relationship between natural resource development and sustainable development has long been a focus in academia. In the context of a new global economic cooperation system, many scholars argue that such cooperation can lead to a “resource curse” effect in partner countries, hindering their sustainable development. This study analyzed panel data from 64 countries from 2008 to 2020, using the Belt and Road Initiative as a representative of multilateral economic cooperation (MEC) policies. The aim was to examine the actual impact of multilateral economic cooperation on the sustainable development levels of partner countries and to explore the underlying mechanisms influencing these outcomes. First, we measured and identified the sustainable development index (SDI) under natural resource development schemes and the “resource curse” effect in these countries. Then, we employed a double machine learning approach to evaluate the policy effects of MEC on sustainable resource development. We constructed an interactive double machine learning model to examine and validate the specific mechanisms of resource development effects. The results indicate that the level of sustainable resource development in MEC countries is relatively low, and a “resource curse” effect already exists. However, participating in MEC suppresses this “curse” effect. By promoting innovation cooperation, institutional improvement, structural optimization, trade openness, and pollution reduction, MEC effectively enhances the sustainable development levels of partner countries.

Data Industry Green Development Promoted by Public Policy and Law in China

It is difficult to fully match the current green development initiatives in the context of public policy and industrial economy to the new infrastructure process driven by massive data. Its connotation and extension and the level of the rule of law need to be deepened to ensure that data production, processing, circulation, elimination, and other activities can achieve high-quality and sustainable development within the collaborative construction of hard facilities and the soft environment in the new era. Based on the practical needs of data industry green development in key areas, we can resolve the legal risk of data industry green development from three aspects: improving the legal level of green public policy, clarifying the green legal benchmark of data industry development, and improving the green legal system of digital society. Then, this paper considers the design of an environmental protection system based on hardware facilities and the structural and readable clean data system innovation of the soft data industry development framework mode so as to clarify the legalization scheme of data industry green development under the new infrastructure. Overall, achieving the green development of the data industry requires not only active attempts by China but also joint efforts by China and other countries.

In-Situ Sulfuration of CoAl Metal-Organic Framework for Enhanced Supercapacitor Properties.

Designing efficient electrode materials is necessary for supercapacitors but remains highly challenging. Herein, cobalt sulfide with crystalline/amorphous heterophase (denoted as Co(Al)S) derived from an Al metal-organic framework was constructed by ion exchange/acid etching and subsequent sulfidation strategy. It was found that rational sulfidation by adjusting the sulfur source concentration to a suitable level was favorable to form a 3D nanosheet-interconnected network architecture with a large specific surface area, which promoted ion/electron transport and charge separation. Benefiting from the features of the unique network structure and heterophase accompanied by aluminum, nitrogen and carbon coordinated in amorphous phase, the optimal Co(Al)S(10) exhibited a high specific capacity (1791.8 C g-1 at 1 A g-1), an outstanding rate capability and an excellent cycling stability. Furthermore, the as-assembled Co(Al)S//AC device afforded an energy density of 72.3 Wh kg-1 at a power density of 750 W kg-1, verifying that the Co(Al)S was a promising material for energy storage devices. The developed scheme is expected to promote the application of MOF-derived electrode materials in electrochemical energy storage and conversion fields.

Implementasi PLTS sebagai Supply Listrik Alternatif pada Fasilitas Masjid Qoryah Thoyyibah Kandang Limun

The Government of the Republic of Indonesia has long encouraged the use of renewable energy, but in fact there are still many people who use primary energy. Seeing this, the idea emerged from the Community Service Team by Bengkulu University lecturers to design and implement Solar Power Plants (PLTS). This renewable energy idea was implemented at the Qoryah Thoyyibah mosque, Kandang Limun Kota Bengkulu. The purpose of this service is the implementation of Appropriate Technology, namely PLTS for alternative energy supply at the Qoryah Thoyibah Mosque facility. So that if there is a power outage by PLN, the facilities at the Qoryah Thoyyibah Mosque can still operate according to their functions. This service method is carried out by two methods, namely counseling and implementation of PLTS Appropriate Technology. It is hoped that in the future by designing and building PLTS as an alternative energy source at the Qoryah Thoyyibah Kandang Limun mosque in Bengkulu City, the backup electricity supply will be fulfilled and we will not always depend on PLN, besides that it can also reduce the monthly cost of electricity at the Qoryah Thoyyibah Mosque. The result of Community Service activities with the 2023 Development scheme is that PLTS has been installed with an AC source to operate lighting lamps with a capacity of 100 WP for PLTS and lamps of 800 Watts. So that it can be operated as a source of lighting for Qoryah Thoyyibah mosque facilities in a state where there is no source from PLN.

‘Now you’ve said it, it’s like a big light bulb!’: enacting post observation feedback suggestions

Teaching observations have become a ubiquitous feature of teacher education programmes, development schemes and assessment regimes. Whilst the processes and procedures of classroom observation are well documented, the feedback which follows teaching observations has been given less attention. Most research into teaching observations focuses on eliciting teachers’ perspectives on their experiences of being observed. In contrast, we examine two aspects vital to teacher development and enhanced teaching practice: (1) post observation feedback talk; (2) teachers’ enactment of feedback following the feedback session. This article argues that examining feedback talk and how talk may influence enactment can help both observers and teachers maximise the effectiveness of teaching observations. We focus on suggestions, a common way of helping teachers to develop and improve. We analyse empirical examples of authentic post observation feedback talk to explore how suggestions are made and responded to, identifying features of suggestions which prompt teacher understanding and enactment. Analysis enables us to provide observers with concrete advice on how to make suggestions, thus showing the practical affordances and methodological warrant of analysing feedback talk.

Hydrogen-bond-based charge bridge in 1,3,6,8-Tetra(4-carboxyphenyl) pyrene/carbon nitride heterojunction for photocatalytic CO2 reduction

Constructing hydrogen bonds through the heterojunction is expected be a successful tactic for achieving efficient charge separation. Here, we presented a heterojunction between 1,3,6,8-Tetra(4-carboxyphenyl) pyrene (T) and carbon nitride (CN), named T/CN. Hydrogen bonds formed between carboxyl groups of T and pyridine N in CN through the heterojunction. T/CN exhibited improved visible light absorption and enhanced charge carrier separation. The yield of CH4 over T/CN reached up to 17.8 μmol·g−1·h−1, ∼7 times higher than that of CN (2.55 μmol·g−1·h−1). This work improved the photocatalytic performance of carbon nitride by synthesizing heterojunction catalysts containing hydrogen bonds, which provided a scheme for the diversified development of heterojunction catalysts.

Dynamic Event-Based Adaptive Fixed-Time Control for Uncertain Strict-Feedback Nonlinear Systems With State Constraints.

In this article, the event-triggered fixed-time tracking control is investigated for uncertain strict-feedback nonlinear systems involving state constraints. By employing the universal transformed function (UTF) and coordinate transformation techniques into backstepping design procedure, the proposed control scheme ensures that all states are constrained within the time-varying asymmetric boundaries, and meanwhile, the undesired feasibility condition existing in other constrained controllers can be removed elegantly. Different from the existing static event-triggered mechanism, a dynamic event-triggered mechanism (DETM) is devised via constructing a novel dynamic function, so that the communication burden from the controller to actuator is further alleviated. Furthermore, with the aid of adaptive neural network (NN) technique and generalized first-order filter, together with Lyapunov theory, it is proved that the states of closed-loop system converge to small regions around zero with fixed-time convergence rate. The simulation results confirm the benefits of developed scheme.

Study of the adjuvant properties of beta-glucans from <i>Saccharomyces Cerevisiae</i> yeast

To increase the effectiveness and immunogenicity of modern vaccines, especially subunit ones, it is required to use adjuvants. Polysaccharides, due to their safety and biocompatibility, are desirable candidates for the creation of vaccine adjuvants. The aim of our study was to develop a method for obtaining beta-Glucans from the yeast Saccharomyces cerevisiae cell wall, and evaluate their adjuvant properties. The high purity and non-toxicity of the resulting preparation was achieved by using enzyme complexes of cellulase and protease in combination with ultrasound (22 kHz) at the purification stage. The developed scheme allows for the yield of beta-Glucans up to 2 g from 100 g of the biomass of wet cells. The adjuvant properties of beta-Glucans were studied in 50 male BALB/c mice, weighing 16–18 g. Immunization was performed twice, with a 14-day interval, intramuscularly, 200 μl per animal. The recombinant receptor-binding domain (RBD) of the surface S protein of the SARS-CoV-2 virus (Wuhan-Hu-1 and B.1.617.2 (Delta)) was used as an antigen, at a dose of 50 μg per animal. A positive control group was administered with the antigen combined with aluminum hydroxide. As a negative control, mice injected with the saline solution were used. The titers of specific antibodies in the blood sera were determined by ELISA assays. RBD (Wuhan-Hu-1 and Delta), and S protein (Wuhan-Hu-1, Delta and Omicron) were used as antigens. The titers of virus-neutralizing antibodies were measured in neutralization tests using SARS-CoV-2 virus strains Wuhan-Hu-1, Delta (B.1.617.2) and Omicron (B.1.1.529). The results of the study have shown that beta-Glucans have the ability to enhance the production of specific and virus-neutralizing antibodies in mice immunized with RBD. The titers of specific and virus neutralizing antibodies are comparable to their levels in the group immunized with RBD and Al(OH)₃. It has been found in the experiments in white outbred ICR mice that the preparation belongs to practically non-toxic substances. Therefore, it can be concluded that the use of beta-Glucans could become a preferable alternative to the conventional adjuvants based on aluminum salts, being biocompatible, biodegradable and non-toxic substances of low labor-intensive production.