Macroscopic Behavior Research Articles

Preface

GeoShanghai is a series of international conferences on geotechnical engineering held in Shanghai quadrennially. The conference was inaugurated in 2006 and was successfully held in 2010, 2014 and 2018, with more than 1600 participants in total. Since the last conference, the geotechnical community has witnessed many advances both in fundamental understanding and engineering practices. To demonstrate the latest developments and promote collaborations in geotechnical engineering and related fields, we launch the 5th GeoShanghai International Conference to be held in May 2024.The intricate macroscopic behaviors of soil, along with the fundamental principles of geomechanics, are cornerstone elements in the field of geotechnical engineering. As we stand on the threshold of a new era marked by unprecedented advancements, it is imperative that we incorporate the most recent and pioneering insights into soil behavior and geomechanics into our discourse. This volume of the Geoshanghai proceedings is dedicated to achieving just that. Encompassing a broad spectrum of critical topics within soil behavior and geomechanics, this volume thoughtfully curates content including soil macroscopic behaviors, geomechanics from micro to macro, granular materials and unsaturated mechanics. As we convene for this international conference, let us delve into these pages with the aim of fostering a deeper understanding and sparking innovative solutions in the ever-evolving landscape of geotechnical engineering.This volume received a total of 74 papers from countries such as China, United States, Canada, Australia, Japan, Korea South, India, Botswana, and others, totaling 70 papers accepted. All papers were reviewed and the accepted papers will be submitted to IOP Conference Series: Earth and Environmental Science indexed by Scopus.Cordially yours,Matt Evans, Xiaoqiang Gu, Jidong Teng, Xiaoyu Song, Qiushi Chen, Annan Zhou, Weiwei ZhanThe editors of Volume 1: Soil Behavior and GeomechanicsList of Conference Steering Committee, International Advisory Committee, Technical Committee, Organizing Committee are available in this pdf.

Micromechanics of multiphase geomaterials based on micro-CT image analysis: unsaturated soil, vegetated soil, and bio-cementation

Under the influence of climate change, extreme weather events such as rainstorms may induce fluctuations in soil water content above the groundwater level, thereby causing geological disasters (e.g., landslides). To mitigate these hazards, green and low-carbon engineering measures such as vegetation reinforcement and bio-cementation are proposed. This study investigates the micromechanical properties of multiphase geomaterials—unsaturated soil, vegetation-reinforced sand, and bio-cemented sand—utilizing high-resolution computed tomography (CT) scanning technology and associated image analysis techniques. The findings are presented as follows: (1) a 4D examination of the macroscopic and microscopic behaviors of unsaturated granular materials under triaxial loading conditions was conducted using self-designed in situ CT scanning equipment. (2) Triaxial loading alters the distribution of phase interfacial surfaces in unsaturated soil, affecting its overall strength. This loading also increases the anisotropy of the solid skeleton and suction stress. (3) The global saturation of the root–soil complex diminishes with root growth, with pore distribution significantly influencing local saturation. (4) In the unsaturated MICP process, low-saturation conditions are preferable for effective cementation, although the saturation levels should be restricted to 20%. After calcification, the particle contact coordination number increases, maintaining the isotropy in the contact between the soil particles.

Bringing Artificial Intelligence (AI) into Environmental Toxicology Studies: A Perspective of AI-Enabled Zebrafish High-Throughput Screening.

The booming development of artificial intelligence (AI) has brought excitement to many research fields that could benefit from its big data analysis capability for causative relationship establishment and knowledge generation. In toxicology studies using zebrafish, the microscopic images and videos that illustrate the developmental stages, phenotypic morphologies, and animal behaviors possess great potential to facilitate rapid hazard assessment and dissection of the toxicity mechanism of environmental pollutants. However, the traditional manual observation approach is both labor-intensive and time-consuming. In this Perspective, we aim to summarize the current AI-enabled image and video analysis tools to realize the full potential of AI. For image analysis, AI-based tools allow fast and objective determination of morphological features and extraction of quantitative information from images of various sorts. The advantages of providing accurate and reproducible results while avoiding human intervention play a critical role in speeding up the screening process. For video analysis, AI-based tools enable the tracking of dynamic changes in both microscopic cellular events and macroscopic animal behaviors. The subtle changes revealed by video analysis could serve as sensitive indicators of adverse outcomes. With AI-based toxicity analysis in its infancy, exciting developments and applications are expected to appear in the years to come.

Exploring the combined effect of particle shape and friction on cell structures in granular packings via LS-DEM modeling

To comprehensively understand and predict the macroscopic behavior of a granular system, one must consider not only the properties of individual particles but also the local structures. In this study, we prepare mechanically stable granular packings of super disks using the two-dimensional level set discrete element method (LS-DEM). We identify the cells, the irreducible loops enclosed by contacting particles, in the prepared granular packings and then analyze the statistics of these structures. We find the following. (1) The packing fraction or mean coordination number of studied systems exhibits a non-trivial dependency on particle shapes and inter-particle frictions, making it challenging to establish a direct correlation between them. (2) Using the cell-based description as a bridge, we can measure the packing behavior without considering the influence of particle shape and inter-particle friction. Specifically, the mean coordination number can be explicitly represented as a function of the mean cell order according to Euler’s topological relation. Upon the assumption that all cells are regular polygons, we can also approximately estimate the rattlers-free packing fraction via the mean cell order. (3) We have observed a nearly linear relationship between the mean cell order and rattler fraction. This enables us to determine the packing fraction as well.

Controlling splat boundary network evolution towards the development of strong and ductile cold sprayed refractory metals: The role of powder characteristics

Feedstock powder characteristics such as composition (specific alloying elements and concentrations and impurity levels), microstructure, thickness/composition of surface oxide layers, and particle size distribution play a crucial role in determining the overall mechanical properties of cold sprayed deposits. Herein, we report on two deposits consolidated via cold spray processing from differently-sourced batches of nominally identical elemental refractory powders under identical spraying conditions, which exhibit bending strength and ductility values that differ by more than a factor of two – and with the weakest sample displaying negligible effective ductility. Through chemical, microstructural and micromechanical characterization of both the feedstock powders and cold sprayed deposits, we consider the possible influences of feedstock characteristics on the mechanical performance of cold spray consolidated deposits. It is shown that while differences in interstitial oxygen and hydrogen content may result in differences in the intrinsic yield characteristics of the feedstock material, both feedstocks maintain the ductile behavior required to induce good metallurgical bonding upon impact of optimally sized powder particles. We conclude that the deposits formed from the two feedstock powders are indistinguishable and exhibit high ductility when characterized locally within the relatively undeformed bulk of a single particle or splat. However, the two sprayed deposits show low ductility or brittle behavior when loaded in tension across intersplat boundary domains comprising material that has undergone extensive deformation. In addition, one feedstock incorporates a broader particle size distribution, with a long tail of larger-than-optimal particles. These larger particles are accelerated below the critical impact velocity, resulting in observed imperfect metallurgical bonding at splat interfaces and higher porosity at such intersplat boundaries. This result, combined with the overall differences in the morphology of the intersplat boundary network between the two deposits, explains the difference in macroscopic mechanical behavior. We conclude that accurate control of the powder feedstock particle size distribution is essential for optimizing the mechanical integrity of cold sprayed refractory elements and alloys.

Phase-field simulation and machine learning of low-field magneto-elastocaloric effect in a multiferroic composite

Achieving appreciable elastocaloric effect under low external field is critical for solid-state cooling technology. Here, a non-isothermal Phase-Field Model (PFM) coupling martensitic transformation with mechanics, heat transfer and magnetostrictive behavior is proposed to simulate Magneto-elastoCaloric Effect (M-eCE) that is induced by magnetic field in a multiferroic composite (e.g., Magnetostrictive-Shape Memory Alloys (MEA-SMA) composite). In the PFM, a nonlinear constitutive hyperbolic tangent model is utilized to model the macroscopic magnetostrictive behavior of MEA, and the heat transfer coupled with phase transformation is employed to calculate the adiabatic temperature change (ΔTad) during M-eC cooling cycles. The influences of magnetic field, geometrical dimension, and ambient temperature on ΔTad are comprehensively investigated. Machine Learning (ML) is further conducted on the database from PFM simulations to accelerate the prediction and design of MEA-SMA composite with an improved ΔTad. It is found that a large ΔTad of 10–14 K and a wide working temperature window of 30 K can be achieved under ultra-low magnetic field of 0.15–0.38 T by optimizing the composite’s geometrical dimension. The present work combining PFM and ML for evaluating M-eCE provides a theoretical framework for the optimization of M-eC cooling devices, and is also potentially extended to other multicaloric effects (e.g., electro-elastocaloric effect).

A multiscale micromechanical progressive elastic-damage model for cementitious composites featuring superabsorbent polymer (SAP)

A multiscale micromechanics-based progressive damage model is developed to investigate the overall mechanical behavior and the interfacial microcrack evolutions of the cementitious composites featuring superabsorbent polymer (SAP) under uniaxial tension. Elastic properties, progressive damage process, and homogenization procedure of cementitious composites are systematically integrated in this model. The effective elastic moduli of the composites are determined based on a multiscale micromechanical framework. According to the small strain assumption, the total strain tensor and the elastic-damage compliance tensor are additively decomposed into elastic and damage-induced components. The damage-induced strains and compliances are then deduced from micromechanics. To characterize the progressive elastic-damage induced by microcracks, stages of microcrack propagation are identified from the interface contact stress and the matrix cleavage stress. The complex potentials and stress intensity factors for kinked interface cracks are derived from the distributed dislocations method. By implementing the homogenization process, the macroscopic mechanical behavior is obtained from the micro/mesoscale. The results indicate that the material parameters have clear mechanical significance. Different parameters, such as the SAP addition ratio, aggregate content, initial interfacial crack size, and initial interfacial crack location, are revealed to be influential in the overall mechanical behavior of the composites. The proposed model can be generalized to other particle-reinforced composites with different constituent properties, which can potentially contribute to the design and optimization of durable composites.

R‐Vine Copulas for Data‐Driven Quantification of Descriptor Relationships in Porous Materials

AbstractLocal variations in the 3D microstructure can control the macroscopic behavior of heterogeneous porous materials. For example, the permittivity through porous sheets or membranes is governed by local high‐volume pathways or bottlenecks. Due to local variations, unfeasibly large amounts of microstructure data may be needed to reliably predict such material properties directly from image data. Here it is demonstrated that a vine copula approach provides parametric models for local microstructure descriptors that compactly capture the 3D microstructure including its local variations and efficiently probe it with respect to selected, measurable properties. In contrast to common methods of complexity reduction, the proposed approach creates parametric models for the multivariate probability distribution of high‐dimensional descriptor vectors that inherently contain the complex, nonlinear dependencies between these descriptors. Therein, material properties are offered in physically motivated distributions of microstructure descriptors rather than as normally distributed data. Applied to porous fiber networks (paper) before and after unidirectional compression, it is shown that the copula‐based models reveal material‐characteristic relationships between two or more microstructure descriptors. In this way, the presented modeling approach can provide deeper insight into the microscopic origin of effective macroscopic properties of heterogeneous porous materials.

In-situ 3D measurements of water films on the natural grain surface of porous rocks

During fluid displacement, e.g. in aquifers or other fluid reservoirs such as CO2 or H2 storage sites or hydrocarbon reservoirs, water films are expected to form along the internal pore surface due to its wetting properties and capillarity. Near connate water saturation, these water films would dominate the macroscopic multiphase flow behaviour when e.g. water penetrates the porous medium. We use Atomic Force Microscopy (AFM) to study the sub-pore scale configuration of microscale water films on the rough pore surface of Ketton and Estaillades rocks, after drainage of the medium with decane. Then, we compare the results with a numerical simulation and use a film flow model to estimate the relative permeability through these films, which can be potentially used to link the water film configuration to pore- and core-scale responses. We find that the surface coverage and connectivity of the water films varies substantially with capillary pressure. This can affect the permeability of the films up to several orders of magnitude and thus potentially dictate the displacement efficiency at the onset of imbibition, when the brine phase re-enters the pore space. The novel experimental workflow proposed in this study may help future digital assessment of multiphase flow behaviour near connate saturation.

Identification of extracellular polymeric substances layer barrier in chloroquine phosphate-disturbed anammox consortia and mechanism dissection on cytotoxic behavior by computational chemistry

The over-dosing use of chloroquine phosphate (CQ) poses severe threats to human beings and ecosystem due to the high persistence and biotoxicity. The discharge of CQ into wastewater would affect the biomass activity and process stability during the biological processes, e.g., anammox. However, the response mechanism of anammox consortia to CQ remain unknown. In this study, the accurate role of extracellular polymeric substances barrier in attenuating the negative effects of CQ, and the mechanism on cytotoxic behavior were dissected by molecular spectroscopy and computational chemistry. Low concentrations (≤6.0 mg/L) of CQ hardly affected the nitrogen removal performance due to the adaptive evolution of EPS barrier and anammox bacteria. Compact protein of EPS barrier can bind more CQ (0.24 mg) by hydrogen bond and van der Waals force, among which O-H and amide II region respond CQ binding preferentially. Importantly, EPS contributes to the microbiota reshape with selectively enriching Candidatus_Kuenenia for self-protection. Furthermore, the macroscopical cytotoxic behavior was dissected at a molecular level by CQ fate/distribution and computational chemistry, suggesting that the toxicity was ascribed to attack of CQ on functional proteins of anammox bacteria with atom N17 (f–=0.1209) and C2 (f+=0.1034) as the most active electrophilic and nucleophilic sites. This work would shed the light on the fate and risk of non-antibiotics in anammox process.

Microscopic thickening mechanisms of hydroxypropyl methyl cellulose ether anti-washout admixture and its impact on cementitious material rheology and anti-dispersal performance

The anti-washout admixture (AWA) serves as the primary constituent in the formulation of underwater non-dispersible concrete (NDC). In this study, hydroxypropyl methyl cellulose ether (HPMC) was chosen as AWA. Molecular dynamics simulations were employed to investigate the nanoscale thickening anti-washout mechanism of HPMC, while the impact of HPMC with varying viscosities on macroscopic behavior was examined by incorporating it into cement paste. Subsequently, NDC was prepared using HPMC, and its flowability, anti-dispersion properties, and rheological characteristics were assessed. The findings demonstrate that HPMC can establish stable Ca–O bonds with C–S–H, effectively mitigating water erosion and making it an ideal AWA. Additionally, the viscosity of HPMC significantly impacts its performance, with higher viscosities leading to enhanced thickening but reduced flowability. Thus, HPMC-15W emerges as a preferable AWA. The use of HPMC as an AWA in NDC results in a notable shear-thinning behavior, consistent with the modified-Bingham model, along with excellent resistance to underwater washout and self-compactness. In summary, this paper provides a deeper and more comprehensive understanding of the thickening mechanism of HPMC in cementitious materials through multi-level research.

Socioeconomic agents as active matter in nonequilibrium Sakoda-Schelling models.

How robust are socioeconomic agent-based models with respect to the details of the agents' decision rule? We tackle this question by considering an occupation model in the spirit of the Sakoda-Schelling model, historically introduced to shed light on segregation dynamics among human groups. For a large class of utility functions and decision rules, we pinpoint the nonequilibrium nature of the agent dynamics, while recovering an equilibrium-like phase separation phenomenology. Within the mean-field approximation we show how the model can be mapped, to some extent, onto an active matter field description. Finally, we consider nonreciprocal interactions between two populations and show how they can lead to nonsteady macroscopic behavior. We believe our approach provides a unifying framework to further study geography-dependent agent-based models, notably paving the way for joint consideration of population and price dynamics within a field theoretic approach.

Changes of surface properties of sucrose particles during grinding in a cocoa butter-based suspension and their influence on the macroscopic behavior of the suspension

Chocolate mass is a cocoa butter-based suspension, which mainly consists of sugar and cocoa particles dispersed in a continuous lipid phase. During chocolate manufacturing, sugar particles have to be ground to sizes below 25–30 µm. Such a fine grinding is carried out either by five roll refiners or by ball mills. Despite obtaining similar particle size distributions at the end, the grinding procedures result in different chocolate mass properties. The reasons for that are not fully understood, so far. Therefore, changes in particle sizes and surface properties of sucrose particles as well as their interactions with surrounding cocoa butter during the different grinding processes were investigated including atomic force microscopy techniques to characterize local surface states. It was found that especially the alteration of surfaces during continued grinding differed. In the case of roller grinding, surface states became more inhomogeneous and different surfaces states at microscopic level existed in parallel. More homogenous surfaces but with a higher degree of amorphous states were formed during grinding in the ball mill. Variations in macroscopic behavior of the suspension can be explained by the differences in interaction of particles with each other and with the surrounding lipid phase.

Coupling μ-computed tomography and multi-scale modelling to assess the mechanical performance of material extrusion metal components

The porosity defects arising in objects produced by metal Material Extrusion (MEX) additive manufacturing affect the macroscopic mechanical behaviour. This paper presents a new approach integrating μ-computed tomography (μXCT) and multi-scale finite element analysis to evaluate the mechanical performance of components fabricated by metal MEX. The porosity information from μXCT is mapped into the finite element model, allowing to define the volume fraction of porosity to each finite mesh element. Then, the Mori-Tanaka homogenization technique is used to estimate the effective mechanical properties in each integration point, assuming a representative volume element composed by a metal matrix with a void. The reliability of the proposed approach was assessed using tensile specimens of stainless steel 316L produced by metal MEX. The numerical predictions were compared with experimental measurements, namely the strain field evolution measured by digital image correlation (DIC). The results highlight the detrimental influence of the porosity distribution, evaluated in the specimen using μXCT, on the strain distribution during the loading stage. The numerical predictions are in agreement with the experimental measurements, i.e. the difference is lower than 11%. Therefore, the proposed approach offers valuable insights for evaluating the mechanical performance of components produced by metal MEX, focusing on the detrimental effects of porosity defects.

Validation study on a coarse-grained DEM-CFD simulation in a bead mill

A bead mill is often employed in powder processes. In the bead mill, the bead-particles move rapidly under high shear rate due to the moving structures. The discrete element method (DEM) coupled with the computational fluid dynamics (CFD) has been applied to simulate the bead-particle behavior for the optimization of the bead mill design and operating conditions. However, the existing DEM-CFD method faces essential problems regarding the substantial limit of the number of computational particles, stable calculations, and modeling of rapidly moving structures. To solve these problems, we newly investigate a numerical model combining the coarse-grained DEM-CFD, an implicit algorithm for the drag force term, and a scalar field-based wall boundary in the calculation of a bead mill commonly employed in industrial powder processes. In this study, our proposed model is shown to successfully simulate the macroscopic behavior of the bead-particles through the validation test of the coarse-grained DEM-CFD simulation in the bead mill system. Specifically, the macroscopic characteristics such as the particle location, the particle velocity, and total kinetic energy, are shown to agree well between the original particle system and coarse-grained particle systems. Consequently, this study illustrates the combination of the coarse-grained DEM-CFD, an implicit algorithm for the drag force term, and the scalar field-based wall boundary is essential for simulating the typically industrial bead mill, where an enormous number of bead-particles should be calculated in liquid under high shear rate.

A Review of Synthesis and Novel Transport Properties of Multivalent Manganate Perovskite: Progress, Opportunities, and Challenges

AbstractUnderstanding the microstructure of materials and their impact on performance is crucial for new electronic devices design. The strong interaction between multiple degrees of freedom (spin, orbit, charge, and lattice) within perovskite type oxides can generate rich electron phase diagrams. The microscopic modulation of manganese ions electron states in rare earth manganate perovskites is the root of many novel macroscopic quantum behaviors, such as giant magnetoresistance phenomenon. For ABO3 type perovskites, the differences of radii and valence states of A‐site ions are used to regulate the coexistence of B site manganese multivalent states (Mn3+, Mn4+, Mn5+), and its ordered structure in the metastable state will create a new combination of electronic states. The ordered arrangement of the multi‐dimensional space of electronic states can induce unique transport properties. Therefore, the preparation of manganate perovskites will provide strong chemical support to construct new generation quantum devices. This review summarizes the challenges and difficulties on constructing trivalent coexisting metastable phase in manganate perovskites through disproportionation reactions, and discusses the status and potential of designing ideal rectified p‐n junctions taking advantage of this unique structure. Finally, the foregrounds of new quantum states driven by this chemical reaction are prospected.

Meso-FE modelling for homogenization of the nonlinear orthotropic behavior of PTFE-coated fabric based on virtual fiber method

Compared to traditional textile composites, the coated fabric used in fabric membrane structures is much more flexible. Its macroscopic mechanical behavior is highly nonlinear, anisotropic, and shows stress ratio dependence during the loading process. The main reason is that the yarns within the coated fabric are not completely solidified, and there is a significant crimp interchange process in the yarns under load. This paper proposes a novel mesoscopic finite element (FE) model to predict the nonlinear orthotropic mechanical behavior of PTFE-coated fabric using the virtual fiber method (VFM). By comparing with experimental data, it is shown that the virtual fiber defined by the truss element can visually and effectively simulate the mechanical behavior of the internal fibers and reflect the crimp interchange process between two-way yarns. Combined with PBCs, it can effectively predict the uniaxial and biaxial tensile behaviors of the PTFE-coated fabric. Moreover, a new multi-scale model suitable for structural scale analysis of fabric membrane structures has been attempted by combining the direct FE2 (D-FE2) method with the proposed mesoscopic FE model. Local deformation mechanisms and macro response of fabric membrane structures can be observed simultaneously from these analyses, which provide a better understanding of the mechanical behavior of the fabric membrane structures.

Consequence of anisotropy on flocking: the discretized Vicsek model

We numerically study a discretized Vicsek model (DVM) with particles orienting in q possible orientations in two dimensions. The study investigates the significance of anisotropic orientation and microscopic interaction on macroscopic behavior. The DVM is an off-lattice flocking model like the active clock model (ACM; Chatterjee et al 2022 Europhys. Lett. 138 41001) but the dynamical rules of particle alignment and movement are inspired by the prototypical Vicsek model (VM). The DVM shows qualitatively similar properties as the ACM for intermediate noise strength where a transition from macrophase to microphase separation of the coexistence region is observed as q is increased. But for small q and noise strength, the liquid phase appearing in the ACM at low temperatures is replaced in the DVM by a configuration of multiple clusters with different polarizations, which does not exhibit any long-range order. We find that the dynamical rules have a profound influence on the overarching features of the flocking phase. We further identify the metastability of the ordered liquid phase subjected to a perturbation.

Micromechanical modeling of hollow cylinder torsional shear test on sand using discrete element method

Previous studies on the hollow cylinder torsional shear test (HCTST) have mainly focused on the macroscopic behavior, while the micromechanical responses in soil specimens with shaped particles have rarely been investigated. This paper develops a numerical model of the HCTST using the discrete element method (DEM). The method of bonded spheres in a hexagonal arrangement is proposed to generate flexible boundaries that can achieve real-time adjustment of the internal and external cell pressures and capture the inhomogeneous deformation in the radial direction during shearing. Representative angular particles are selected from Toyoura sand and reproduced in this model to approximate real sand particles. The model is then validated by comparing numerical and experimental results of HCTSTs on Toyoura sand with different major principal stress directions. Next, a series of HCTSTs with different combinations of major principal stress direction (α) and intermediate principal stress ratio (b) is simulated to quantitatively characterize the sand behavior under different shear conditions. The results show that the shaped particles are horizontally distributed before shearing, and the initial anisotropic packing structure further results in different stress–strain curves in cases with different α and b values. The distribution of force chains is affected by both α and b during the shear process, together with the formation of the shear bands in different patterns. The contact normal anisotropy and contact force anisotropy show different evolution patterns when either α or b varies, resulting in the differences in the non-coaxiality and other macroscopic responses. This study improves the understanding of the macroscopic response of sand from a microscopic perspective and provides valuable insights for the constitutive modeling of sand.

Structural phase coexistence enhances the energy storage density of (Bi0.5Na0.5)0.8Ba0.2Ti1-ySnyO3 lead-free ceramics

In the present study, BaSnO3 was introduced into polycrystalline NBT-BT ferroelectric ceramics and conducted a comprehensive investigation into the structural, dielectric, ferroelectric, and energy storage characteristics of the (Bi0.5Na0.5)0.8Ba0.2Ti1-ySnyO3 (BNBTS) ceramics. The coexistence of structural phases P4mm and Amm2 was observed through Rietveld refinement and also confirmed by Raman analysis. The formation energy decreases with an increase in substitution concentration favouring the formation of the orthorhombic phase. The SEM analysis revealed a denser microstructure characterised by smaller grain sizes, which favourably enhances energy storage density. Furthermore, Raman spectroscopic analysis unveiled a softening of Ti–O bonds, indicating the emergence of macroscopic relaxor behaviour. Dielectric studies provided evidence of a transition from ferroelectric to relaxor behaviour, an observation further confirmed by P-E loop measurements. This transition can be linked to the partial substitution of Sn4+ ions for Ti4+ ions, disrupting the ferroelectric long-range order within the matrix phase. Notably, the polarization-electric field (P-E) loop of BNBTS2 ceramics exhibited a substantial value of polarization (Ps) 30 μC/cm2 with a reduced value of remnant polarization (Pr) 2.29 μC/cm2. These characteristics contributed to the achievement of higher energy recovery (Wrec) and lower energy loss (Wloss) values, measuring 1.184 J/cm3 and 0.142 J/cm3, respectively, with a notable efficiency of 88.8%. Consequently, the system of ternary ceramics demonstrates promise as a potential option for energy storage ceramics among NBT-BT-based materials.