Upper Layer Research Articles

The Re-Crushing Spatiotemporal Evolution Law of Broken Coal in the Goaf for Sustainable Utilization of Abandoned Mines

The broken coal samples’ (BCS) re-crushing characteristics in the goaf during roof compaction directly affect the mechanics and seepage characteristics of the caving zone. This will further affect the safety of coal mining and the sustainable utilization of abandoned mines. Thus, the experiment of BCS compaction is carried out with the help of an acoustic emission (AE) monitoring system. The Hurst exponent changes of the AE counts at different stages were obtained using the R/S analysis method. The results indicate that the compaction and re-crushing of the BCS at the laboratory scale have long-term memory. When providing sufficient stress, the AE activity of BCS will continue to develop according to the current trend. Based on the AE breakage location technology, the spatial distribution re-crushing characteristics of the BCS are obtained. Re-crushing of the BCS demonstrates uniform breakage in the horizontal direction and layered breakage in the vertical direction. In the horizontal direction, the boundary area first began to break, and the damage gradually spread evenly to the central area. In the vertical direction, the upper layer was the first to be broken, and then the damage began to shift to the middle and lower layers.

Exploring Spatial Dynamics of Water Quality in a Tropical Lake Affected by Aquaculture

Lake Maninjau, like many surface water bodies worldwide, faces significant water pollution challenges due to extensive aquaculture activities, making it an ideal site to study the impact of fish farming on water quality, which has contributed to eutrophication and declining water quality. This study investigates the physicochemical parameters and pollution levels in the lake, aiming to provide insights into its environmental health. In August 2022, a comprehensive sampling campaign was undertaken at nine stations within the upper layers of open water and littoral zones of Lake Maninjau. In situ measurements, including temperature, dissolved oxygen, and pH, were conducted, accompanied by water sample collection for laboratory analysis of trace elements and heavy metals. Our study revealed notable variability in water parameters across different sites, with surface water layers exhibiting the greatest differences. While certain parameters such as temperature and conductivity remain relatively stable, pH levels show a decreasing trend with increasing water depth. Dissolved oxygen levels vary widely, while oxidation–reduction potential indicates water pollution, particularly in littoral zones. Potassium dominance within cations likely suggests anthropogenic influences, notably from aquaculture activities, that may also contribute to nutrient enrichment and heavy metal pollution. Elevated levels of total nitrogen and ammonia underscore the lake’s moderate pollution levels, with heavy metals such as mercury exceeding permissible limits, posing risks to aquatic life and human health.

Light-driven integration of diazotroph-derived nitrogen in euphotic nitrogen cycle

The bioavailable nitrogen fixed by diazotrophs is critical for sustaining productivity in the oligotrophic ocean. Despite this, understanding how diazotroph-derived nitrogen integrates into the nitrogen cycle within the euphotic zone remains unknown. Here, we investigated nitrogen fixation rates in the particulate and dissolved fractions within the euphotic zone of the North Pacific Subtropical Gyre. Our findings reveal the proportion of nitrogen fixation rates in the dissolved fraction increases with depth. Light manipulation experiments uncover that reduced light levels can stimulate the net release of diazotroph-derived nitrogen, aligning with our depth-related observations. Furthermore, we identify two distinct transfer pathways vertically associated with light-driven ecological niches. Specifically, the released diazotroph-derived nitrogen is transferred to non-diazotrophic plankton in the upper layers. Meanwhile, in the lower layers, it contributes to the nitrification process. Our results underscore the high bioavailability of diazotroph-derived nitrogen and its rapid integration into the nitrogen cycle through multiple pathways within the well-lit ocean.

Modeling the Effects of a Light Bridge on Properties of Magnetohydrodynamic Waves in Solar Pores

Solar pores are ideal magnetic structures for wave propagation and transport of energy radially outwards across the upper layers of the solar atmosphere. We aim to model the excitation and propagation of magnetohydrodynamic waves in a pore with a light bridge modeled as two interacting magnetic flux tubes separated by a thin, weaker-field layer. We solve the three-dimensional magnetohydrodynamic equations numerically and calculate the circulation as a measure of net torsional motion. We find that the interaction between flux tubes results in the natural excitation of propagating torsional Alfvén waves but find no torsional waves in the model with a single flux tube. The torsional Alfvén waves propagate with wave speeds matching the local Alfvén speed where wave amplitude peaks.

Heterotopically differentiated PDLSCs-laden 3D bioprinting scaffolds for concurrent oral hard and soft tissue regeneration

Following dental extraction, the alveolar bone and gingival tissues could undergo varying degrees of resorption, affecting subsequent implant integration and aesthetic outcomes. Adequate volume of both hard and soft tissues is essential for optimal results. Three-dimensional (3D) bioprinting technology offers the advantages of biomimicry, personalization, and precise spatial distribution, which are pivotal for enhancing the success and esthetics of dental restorations. In this study, we fabricated a construct with a natural transition and varying material concentrations by 3D bioprinting, comprising an upper layer of Collagen/Alginate/periodontal ligament stem cells (PDLSCs) and a lower layer of Collagen/nano-hydroxyapatite (nHA)/Alginate/PDLSCs. Characterization of the physicochemical properties revealed that the incorporation of nHA significantly enhanced the mechanical properties of both the bioink and the construct. Flow cytometry analysis confirmed the stemness of PDLSCs. Scanning electron microscopy (SEM) revealed that the construct possesses satisfactory pore density and a natural transition at the stratification point. The construct displayed good cell viability and proliferation, with the cellular movement observed at the stratification interface after bioprinting. Differentiation staining and quantitative reverse transcription-polymerase chain reaction (RT-qPCR) results demonstrated that PDLSCs within the 3D construct are capable of both osteogenic and fibroblastic differentiations. Ectopic transplantation in mice confirmed the biocompatibility of the construct. A rat tooth extraction model validated the construct's effectiveness in the integrated regeneration of both hard and soft tissues in alveolar ridge preservation (ARP). In conclusion, this personalized, concentration-varied 3D construct exhibits excellent biocompatibility and tissue preservation effects, holding significant potential for clinical application.  

A Design Method for Road Vehicles with Autonomous Driving Control

The past three decades have witnessed extensive studies on motion-planning and tracking-control for autonomous vehicles (AVs). There is, however, a lack of studies on effective design methods for AVs, which consist of the subsystems of the mechanical vehicle, tracking-control, motion-planning, etc. To tackle this problem, this paper proposes a design approach for AVs. The proposed method features a design framework with two layers: at the upper layer, a particle swarm optimization (PSO) algorithm serves as a solver to a multi-objective optimization problem for desired AV trajectory-tracking performance; at the lower layer, a coupled dynamic analysis is conducted among the three subsystems, i.e., a nonlinear model for the mechanical vehicle, a motion-planning module, and a controller based on nonlinear model predictive control (NLMPC) for direction control. The simulation results demonstrate that the proposed method can effectively determine the desired design variables for the NLMPC controller and the mechanical vehicle to achieve optimal trajectory-tracking performance. The research findings from this work provide guidelines for designing AVs.

Dynamics and Detection of Pulsed Tremor at Whakaari (White Island), Aotearoa New Zealand

AbstractVolcanic tremor is a crucial indicator for assessing the state and hazard potential of volcanic systems. At Whakaari (White Island volcano, Aotearoa New Zealand), a pulsed tremor signal emerged after a hydrothermal explosion in August 2012. The tremor accompanied the extrusion of a lava dome, before gradually disappearing prior to the onset of renewed hydrothermal activity in January 2013. We interpret this seismic signal to represent discrete gas transfers from a magmatic intrusion toward a permeable cap—possibly a hydrothermal seal—in the upper layers of Whakaari's hydrothermal system. Such tremor may thus be associated with heightened potential for hazardous explosive activity but is difficult to detect using conventional seismic monitoring parameters. To highlight the emergence of subtle periodic signals, we experiment with Lomb‐Scargle periodograms (LS). LS detect the tremor 5 days before it becomes visible in seismograms, thus facilitating the recognition of such elusive seismic patterns.

Effects of filling substrates on remediation performance and sulfur transformation of sulfate reducing packed-bed bioreactors treating acid mine drainage

The filling substrate is one of key factors influencing effectiveness of sulfate reducing packed-bed bioreactor (SRPB) treating acid mine drainage (AMD). The effects of four substrates (i.e. quartz sand, steel residue, biochar, and peanut shell) on remediation performance and sulfur transformation of SRPB treating AMD was studied. The results showed that steel residue and biochar improved sulfate reduction efficiency (61% and 49%) compared to quartz sand (32%), whereas peanut shell inhibited sulfate reduction efficiency (19%), attributed to its decomposition process leading to a severe accumulation of acetic acid. More amounts of sulfides generated in steel residue bioreactor were converted into acid volatile sulfide and elemental sulfur, resulting in a significant decrease in dissolved sulfide in the effluent. Metals (Fe, Al, Zn, Cd and Cr) except for Mn were effectively immobilized in the bioreactors, particularly for Al and Cd. Sulfate reducing bacteria and sulfide oxidizing bacteria lived symbiotically in all bioreactors which exhibited similar heterogeneity in microbial distribution and function, i.e. bacterial sulfate reduction mainly occurring in bottom-middle layers and photoautotrophic sulfide oxidation in upper layer close to outlet. The microbial response mechanism to various substrate environments was revealed through co-occurrence networks analysis. This study suggests that attention should be paid to the inhibitory effect of acetic acid accumulation on sulfate reduction when using sole lignocellulosic waste (peanut shell), and steel residue and biochar could be utilized as filling substances to promote sulfate reduction.

Full wavefield modeling and dispersion characteristics of underwater MASW

The underwater multichannel analysis of surface wave (UMASW) is becoming an essential tool for surveying subbottom shear wave velocity. Current practice is limited to interpretation based on the fundamental mode. This paper investigates the full dynamic response of the underwater-multilayered structure under two different types of sources (impact and explosion). Fundamental solutions in the transformed domain, after applying both Fourier transform and Fourier–Bessel transform, are derived utilizing the global stiffness matrix method, analogous to a 1-D finite element approach. Solutions in the physical domain are then obtained using the fast and accurate Fourier series and Fourier–Bessel series approach proposed in this paper. The most attractive feature of this novel approach is that the expansion coefficients (or Love numbers) can be pre-calculated, saved, and repeatedly used for other field points. Through numerical analyses, we quantitatively investigate the effect of the water depth and source/receiver types/locations on different wave features (i.e., Scholte, fast-guided, and acoustic modes) from different perspectives (i.e., dispersion curve, Green’s function, frequency-velocity spectrum (FVS), and waveform). We find that (1) unlike the impact source, stronger acoustic waves can be produced by the explosive source, which sometimes causes difficulty in identifying the Scholte waves. (2) The acoustic and interface-guided waves exhibit distinct behaviors depending on the source and receiver locations. Scholte waves and fast-guided waves are weakened when the source and receivers are elevated far from the water/soil interface. Moreover, (3) the response of the Scholte wave can be enhanced by muting the direct acoustic waves. However, (4) the fast-guided wave may also arise in underwater surveys when the Vs of the underlying half-space is much higher than those of the upper layers, exerting a significant influence on the shallow water scenarios and posing challenges for correct mode identification. With the ability to model the entire wavefield (or FVS) that takes into account all propagation modes and the actual survey configuration, inversion can be performed by fitting the entire FVS. This approach eliminates the need to pick dispersion curves and provides a more accurate and stronger model constraint.

On the issue of forecasting crop yields for the purposes of adaptive landscape agriculture

Long-term monitoring (1998–2023) of the yield of clover-timothy grass stands of the first year of use was carried out in order to find patterns of influence of landscape environmental conditions on it in various agroclimatic conditions. The research was conducted within the moraine hill located at the Gubino VNIIMZ agro-testing site in the Tver region. Soil-forming rocks are two-membered deposits consisting of an upper layer composed of relatively light rocks, underlain by moraine bouldery loam. The grass stands were exploited without fertilizers in a single-cut mode on a field divided into 120 plots. Using regression analysis, the influence of landscape and soil environment factors was determined: relief, physical and agrochemical properties of soils on grass yield, as well as the dependence of the degree of this impact on climatic conditions. It was found that the yield of perennial grasses is most strongly influenced by various fractions of the granulometric composition of soils – from stones to dust (up to 16 % of its variability) and the altitude of the location (up to 38 %), since the thermal and water-air characteristics of soils and vegetation largely depend on them. Terrain characteristics such as steepness and curvature of the surface have a minor impact on grass yield (up to 12 %). The degree of influence of agro-landscape environmental factors on the growth of grasses is largely regulated by fluctuations in weather conditions. “Climate scenarios” of a specific factor – sets of weather parameters under which its effect on the production process of a crop is manifested – in the years of sowing and mowing, as a rule, do not differ fundamentally. Knowing the nature of the influence of climatic factors allows us to more accurately predict crop yields within an agricultural landscape and, thus, optimize the location of crops on the territory of a particular farm.

Designing LiDAR‐Detectable Dark‐Tone Materials with High Near‐Infrared Reflectivity for Autonomous Driving: A Comprehensive Review

AbstractAutonomous driving relies on the precise recognition of objects using light detection and ranging (LiDAR) technology, that operates at a specific wavelength of 905 nm. Black objects, such as carbon black used in vehicle coating, tend to absorb this specific wavelength significantly, which limits the performance of LiDAR sensors. To address this issue, researchers have explored creating dark‐toned materials that can be detected by LiDAR with high NIR reflectivity while maintaining a true blackness (L* < 20 based on the CIE color coordinates). These materials fall into two categories: organic and inorganic pigments. Organic pigments can be synthetically adjusted to achieve true blackness by manipulating their functional groups, but achieving high NIR reflectivity remains challenging, often requiring a bilayer structure with NIR‐reflective white base and an upper layer of organic black pigments. Additionally, the need for hydrophobic additives and resistance to degradation from sunlight further restricts their use. In the case of inorganic pigments, the desired LiDAR‐detectable properties can be obtained through careful control of their composition, structure, and morphology, allowing for single‐layer coatings with appropriate design. This review highlights recent advancements in developing organic and inorganic LiDAR‐detectable black pigments and outlines future material design strategies for autonomous vehicle systems.

Mesoscopic shear evolution characteristics of frozen soil-concrete interface

The mechanical properties of frozen-concrete interfaces affect the stability and durability of engineering structures in cold regions. To investigate these properties, laboratory tests and numerical simulations were conducted to study the mesoscopic evolution of the shear stress-displacement relationship and the shearing process at the interface. The direct shear tests were performed at different environmental temperatures (−2 °C, −5 °C, and −10 °C) and normal stresses (100 kPa, 200 kPa, and 300 kPa) on the frozen soil-concrete interface, and Particle Flow Code (PFC) model of direct shear was developed. The mesoscopic parameters (particle displacement, rotation, force chain, stress, coordination number, porosity, fabric, etc.) of the interface during shearing were simulated using the PFC model. Moreover, the relationship among the interface temperature, cohesion, and friction coefficient was determined based on experimental data, and the accuracy of the PFC model was verified using previous experimental data. The results of the PFC shear model aligned well with those of the laboratory test, and the formation of shear bands was simulated well. The displacement of the soil particles on the upper layer outside the shear zone was uniform, and the direction was the same, whereas the particles inside the shear zone showed significant differences in the dislocation and rotation of the soil particles. The force chain, stress field, coordination number, and porosity were similar in the shear process and showed a concentrated distribution in the opposite direction of the shear motion, which reflected the consistency of the microcosmic response of the particles under the action of macroscopic external forces. The regression equations for the temperature, cohesion, and friction coefficient in this study can be used to simulate the shear behavior of frozen soil-concrete interfaces under different temperatures and normal stresses.

Artificial Grassland Revegetation Improves Soil Water Retention and Storage Capacity of the Degraded Hillside Alpine Meadow

ABSTRACTThe crucial role of soil water retention and storage in soil hydrology and the water cycle is well established. However, in sensitive and degraded ecosystems like alpine meadows, the effectiveness of revegetation in enhancing these critical functions remains understudied. This study investigates the effects of revegetating severely degraded hillside meadows with artificial grasslands on soil water retention and storage capacity in the Qinghai‐Tibetan Plateau. Soil analyses at a depth of 0–20 cm revealed significant improvements in soil properties after revegetation, with increases in soil organic matter content (86.8%), total porosity (11.9%), capillary porosity (31.6%), and clay content (13.5%). Both the saturated hydraulic conductivity (Ks) and field capacity (FC) increased markedly, by 9.7% and 63.7% in the upper layer (0–10 cm) and 21.7% and 69.6% in the lower layer (10–20 cm), respectively. Structural equation modeling identified bulk density, root mass density, FC, capillary porosity, and clay content as the dominant direct factors influencing Ks with path coefficients of −0.56, 0.30, −0.53, 0.57, and −0.12, respectively, while vegetation cover and aboveground biomass were found to have indirect influences. These findings demonstrate that revegetation with artificial grasslands effectively improves soil water retention and storage capacity in degraded hillside alpine meadows by regulating key soil hydraulic and physical properties. This enhanced water‐holding capacity has significant implications for understanding the dynamics of revegetation by artificial grassland establishment in improving ecosystem health and eco‐hydrological functions in these vulnerable environments. Furthermore, the study provides valuable insights and a theoretical basis for developing ecological restoration solutions for degraded hillside meadows in other alpine regions.

Variability of PAH Patterns in Upper Forest Soil (Sub)horizons—A Case Study From South‐Central Poland

ABSTRACTPolycyclic aromatic hydrocarbons (PAHs) are a class of contaminants characterized by their persistent and toxic nature. This study examines the variability in PAH distribution patterns in the upper layers of forest soils, focusing on the influence of different characteristics of individual soil (sub)horizons. A total of 130 samples were collected from five forest areas in south‐central Poland and analyzed for the 16 priority PAHs. Samples were taken from the organic fermentative‐humic (Ofh), humic (A), and humic‐eluvial (AE) (sub)horizons. The highest mean concentrations of total PAHs were found in the subhorizon‐Ofh (Ofh—1547 μg kg−1, A—1103 μg kg−1, AE—109 μg kg−1). The PAH content was significantly correlated with SOM content and pH, but this correlation was only significant in the horizon‐A. The percentage contributions of 3‐, 4‐, 5‐, and 6‐ring compounds to the total PAHs varied among the investigated soil (sub)horizons. The subhorizon‐Ofh had the highest percentage contribution of 6‐ring PAHs, 4‐ and 5‐ring PAHs were most prevalent in the horizon‐A, while 3‐ring compounds in the horizon‐AE. The variability in PAH patterns was also reflected in individual PAH ratios (BaA/BaA+Chr, IcdP/IcdP+BghiP), confirming the different behavior of 4‐, 5‐, and 6‐ring compounds in these (sub)horizons. This suggests that the retention of PAHs in the investigated (sub)horizons is influenced by several factors, including pH, degree of SOM decomposition, and mineral fraction, each to a different extent. Our findings reveal significant knowledge gaps regarding the behavior and accumulation of PAHs in soil (sub)horizons, underscoring the need for further research.

Randomised-crossover clinical trial on the substantivity of a single application of a gel containing chlorhexidine and o-cymen-5-ol on the oral biofilm and saliva

BackgroundNo clinical trials have evaluated the antimicrobial activity and substantivity of gel formulations containing chlorhexidine (CHX) and cymenol.ObjectiveTo compare the in situ antimicrobial effect and substantivity of a new 0.20% CHX + cymenol gel (test) with the current 0.20% CHX gel formulation (control) on salivary flora and dental plaque biofilm up to seven hours after a single application.MethodsA randomised-crossover clinical trial was conducted with 29 orally healthy volunteers participating in the development of Experiments 1 (saliva) and 2 (dental plaque biofilm). All subjects participated in both experiments and were randomly assigned to receive either the test or control gels. Samples were collected at baseline and five minutes and one, three, five, and seven hours after a single application of the products. The specimens were processed using confocal laser scanning microscopy after staining with the LIVE/DEAD® BacLight™ solution. Bacterial viability (BV) was quantified in the saliva and biofilm samples. The BV was calculated using the DenTiUS Biofilm software.ResultsIn Experiment 1, the mean baseline BV was significantly reduced five minutes after application in the test group (87.00% vs. 26.50%; p < 0.01). This effect was maintained throughout all sampling times and continued up to seven hours (40.40%, p < 0.01). The CHX control followed the same pattern. In Experiment 2, the mean baseline BV was also significantly lower five minutes after applying the test gel for: (1) the total thickness of biofilm (91.00% vs. 5.80%; p < 0.01); (2) the upper layer (91.29% vs. 3.94%; p < 0.01); and (3) the lower layer (86.29% vs. 3.83%; p < 0.01). The reduction of BV from baseline was observed for the full-thickness and by layers at all sampling moments and continued seven hours after application (21.30%, 24.13%, and 22.06%, respectively; p < 0.01). Again, the control group showed similar results. No significant differences between test and control gels were observed in either saliva or dental plaque biofilm at any sampling time.ConclusionsA 0.20% CHX + cymenol gel application demonstrates potent and immediate antimicrobial activity on salivary flora and de novo biofilm. This effect is maintained seven hours after application. Similar effects are obtained with a 0.20% CHX-only gel.

A coupled displacement-pressure model for elastic waves induce fluid flow in mature sandstone reservoirs

Elastic (seismic) wave stimulation is considered one of the unconventional enhanced oil recovery (EOR) methods. Increasing water quantity in the high permeability layer of a mature oil reservoir is highly challenging and can significantly decrease the ultimate recovery due to the reservoir heterogeneity. Using seismic waves can be considered low-cost, environmentally friendly, and illuminates the entire reservoir size compared to conventional EOR methods. A numerical model is developed by extending the Quintal approach for seismic attenuation due to wave-induced fluid flow (WIFF) to incorporate capillary pressure in partially saturated porous media and shift undrained boundary conditions to exclude external flow stress for drained boundary conditions. Therefore, the fluid distribution due to the capillary effect makes the developed finite element method (FEM) u-p model more widely applicable for oil recovery in mature reservoirs. A two-layer partially saturated media was subjected to compressive seismic stress at low frequency (3 Hz). The results indicated that the vertical displacement gradients of the bottom and upper layers decline with excitation time for both fully and partially saturated media. On the other hand, partially saturated pore pressure gradients of both the upper and bottom layers have higher amplitudes with excitation time than fully saturated pore pressure gradients due to the influence of capillar pressure. The cumulative crossflow oil volume for 180 days of continuous stimulation was 1176 bbl, 1032 bbl, and 648 bbl in low permeability layers: 200 md, 100 md, and 50 md, respectively. Therefore, the developed model has the potential for field-scale EOR applications. The study also suggests coupling elastic EOR with CO2 flooding to recover more oil due to increasing fluid mobility and relative permeability to oil in low-permeability reservoirs or tight formations.

Research on a Bridge Hybrid Isolation Control System Based on PID Active Control and Genetic Algorithm Optimization

A bridge hybrid isolation system, integrating both active and passive control strategies, is proposed and investigated to enhance seismic performance. The system is modeled as a two-layer structure, with the upper layer subjected to active control via a Proportional–Integral–Derivative (PID) controller, and the lower layer employing a conventional passive base isolation system. The displacement response of the superstructure is minimized by the control forces generated by the PID controller, which also accounts for the reaction forces transmitted to the lower isolation layer. To optimize the controller’s performance, a genetic algorithm is implemented for real-time tuning of the PID parameters. Numerical simulations, conducted using the Newmark method, are employed to assess the influence of active control on the lower isolation system. The results reveal that, while active control increases the peak displacement of the superstructure to some extent, it significantly prolongs the structural period, thus enhancing the system’s overall seismic resilience and stability.

Assessment of Physical and Mechanical Parameters of Spun-Bond Nonwoven Fabric.

The selection of an appropriate fabric for technical applications, such as protective masks, hinges on a thorough understanding of the fabric's physical and mechanical properties. This study addresses the challenge of selecting the optimal material structure for the upper layer of a protective mask, aiming to ensure adequate breathability while providing effective filtration against airborne particles and contaminants. We assessed and compared the physical-mechanical properties of five polymer spun-bond nonwoven fabrics from different suppliers. Our comprehensive evaluation included, as follows: a visual inspection; light permeability analysis; mass and thickness measurements; elongation and tensile strength tests; breathing resistance assessments; and filter penetration tests with paraffin oil. The results revealed significant variations in performance among the samples, with one fabric consistently outperforming the others across multiple parameters. Notably, this top-performing fabric met or exceeded the EN 149:2001+A1:2009 standard for breathing resistance and filtration efficiency and, in combination with additional filter layers, met the requirements or exceeded class FFP2 (filtering face piece). This study underscores the importance of meticulous material selection and quality control in optimizing PPE (personal protective equipment) performance and user safety, providing valuable insights for mask manufacturers and healthcare professionals.

A two-layer strategy for sustainable energy management of microgrid clusters with embedded energy storage system and demand-side flexibility provision

The intermittent nature of renewable energy generation and the fluctuating demands pose persistent challenges in microgrid operations. In response, stakeholders and operators have turned to clustering the geographically adjacent microgrids as a solution. In this context, this paper introduces a novel two-layer energy management strategy for microgrid clusters, utilizing demand-side flexibility and the capabilities of shared battery energy storage (SBES) to minimize operational costs and emissions, while ensuring a spinning reserve within individual microgrids to prevent load-shedding. In the lower layer, the proposed approach devises optimal day-ahead operation policies, while the upper layer employs a cooperative strategy to further optimize the operational efficiency across the entire cluster. The energy management problem is accurately formulated as a mixed integer quadratic programming (MIQP) optimization, which incorporates linear terms in the problem's constraints. The formulation accounts for operational costs associated with SBES including expenses of charging/discharging and changes in operating states (CiOS). Real-world case studies with a cluster of three microgrids in Australia validate the effectiveness of this approach. Results show a reduction in operational costs for the base case scenario by 6.96 % compared to conventional microgrid management strategies. Sensitivity analyses further demonstrate the economic benefits of varying SBES capacity and flexibility pricing, with savings ranging from 6.5 % to 8.1 %. The proposed strategy also reduces CO2 emissions by up to 11.6 %, while improving system reliability. This strategy holds promise for integration into distributed energy systems with high renewable penetration and clustered local grids, offering significant advantages for utility operators and end-users through improved energy efficiency and reduced emissions.

Artificial synapses based on HfOx/TiOy memristor devices for neuromorphic applications

As a result of enormous progress in nanoscale electronics, interest in artificial intelligence (AI) supported systems has also increased greatly. These systems are typically designed to process computationally intensive data. Parallel processing neural network architectures are particularly noteworthy for their ability to process dense data at high speeds, making them suitable candidates for AI algorithms. Due to their ability to combine processing and memory functions in a single device, memristors offer a significant advantage over other electronic platforms in terms of area scaling efficiency and energy savings. In this study, single-layer and bilayer metal-oxide HfOxand TiOymemristor devices inspired by biological synapses were fabricated by pulsed laser and magnetron sputtering deposition techniques in high vacuum with different oxide thicknesses. The structural and electrical properties of the fabricated devices were analysed using x-ray reflectivity, x-ray photoelectron spectroscopy, and standard two-probe electrical characterization measurements. The stoichiometry and degree of oxidation of the elements in the oxide material for each thin film were determined. Moreover, the switching characteristics of the metal oxide upper layer in bilayer devices indicated its potential as a selective layer for synapse. The devices successfully maintained the previous conductivity values, and the conductivity increased after each pulse and reached its maximum value. Furthermore, the study successfully observed synaptic behaviours with long-term potentiation, long-term depression (LTD), paired-pulse facilitation, and spike-timing-dependent plasticity, showcasing potential of the devices for neuromorphic computing applications.