Search Results (10,139)

The intermittent and variable nature of solar energy poses challenges for maintaining stable thermal performance in solar heating systems. One effective approach to mitigate this limitation is to store surplus thermal energy during periods of high solar irradiance and release it when solar input is insufficient. Phase change materials (PCMs) are particularly suitable for this purpose due to their ability to absorb and release large amounts of latent heat during phase transition. The aim of this work is to develop a mathematical model of a flow-through tank containing a phase change material in the form of a spherical packed bed. Including longitudinal dispersion in the model equations allows for a more accurate description of the heat transfer process in a tank containing PCM elements. Simulation calculations based on the model were carried out to demonstrate its potential applicability to practical problems. The influence of the following parameters on the process was investigated: tank volume, water flow rate, phase change temperature, process duration, dispersion coefficient during water flow, radius of the packed-bed elements, and cyclic variations of the inlet water temperature. A significant influence of the axial dispersion coefficient in the tank containing PCM on the outlet water temperature profile was demonstrated. It was found that the internal heat transfer coefficient within the packing elements containing PCM falls within the range of 58–145 W/(m²K). Full article

Dual-phase layered microstructures containing alternating regions of soft and hard phases can produce alloys with a unique combination of strength and ductility. In this study, the molecular dynamics (MD) method was utilized to simulate nanoindentation of a Ni/NiTi/Ni nanostructured film (NSF). This film features a unique alternating FCC/B2/FCC microstructure, in which the B2-phase NiTi acts as a superelastic shape memory alloy (SMA). The results indicate that Ni/NiTi/Ni NSF significantly reduces its hardness due to the superelasticity of the B2 phase. The presence of the NiTi interlayer effectively blocks the propagation path of dislocations and stacking faults by transforming the local dislocations transferred from the upper layer into a large-scale coordinated phase transition, significantly reducing local deformation misalignment. As the thickness of the surface film λ increases, the dislocation slip plane propagating horizontally appears in the upper pure Ni layer. The thicker the surface film, the more horizontal slip planes are formed. This study provides new insights into the contact mechanical behavior of nanostructured films based on NiTi shape memory alloys from the perspective of atomic scale. Full article

Water is fundamental to structural integrity, stability, and functional properties of food systems, biomaterials, and biobased industries. The dynamics of hydration, including hydrogen bonding, hydration shell formation, plasticization, and phase transitions, dictate molecular behavior and exert broad influence on energy consumption, shelf life, biodegradability, and resource efficiency. However, the nonlinear and multiscale characteristics of hydration have constrained the predictive capabilities of conventional empirical methods. This study introduces a comprehensive framework that integrates foundational hydration science with advanced computational intelligence to model, predict, and optimize hydration-driven phenomena across diverse biopolymer classes. Leveraging classical insights into carbohydrate stereochemistry, protein hydrophobic hydration, and phospholipid-bound water, we demonstrate how computational approaches can reduce resource use in bioprocessing by 30–50% and optimize drying curves to lower energy consumption by 25%. By establishing hydration as a strategic design parameter, this work charts a pathway toward a resilient and sustainable economy where predictive error rates for hydration dynamics are significantly minimized through data-driven calibration. Full article

Technology upgrades are a central lever for sustainability, yet many optimization models primarily account for use-phase emissions and treat embodied impacts and technological change exogenously. We propose a multi-period mixed-integer optimization framework that couples upgrade timing, technology choice, and operations with a life-cycle assessment (LCA) structure. The model (i) separates use-phase and embodied impacts at the transition level, (ii) supports time-weighted valuation of impacts through a flexible weighting sequence (time value of carbon), and (iii) incorporates endogenous learning-by-doing that can reduce both investment costs and embodied impacts of future upgrades. We derive an exact Benders (L-shaped) decomposition that separates discrete upgrade dynamics from a linear operating subproblem. Computational experiments illustrate model behavior and report runtimes under an outer-loop implementation with open-source solvers, highlighting that decomposition becomes most beneficial when extensions substantially enlarge the dispatch layer (e.g., scenario expansion). Experiments also show that ignoring embodied impacts can mis-rank upgrade schedules and even violate life-cycle caps, that stronger time-weighting pushes upgrades earlier, and that learning can make staged upgrades economically preferable. Full article

The global population explosion and accelerated industrialization have led to an increasing shortage of fossil fuels and environmental contamination, underscoring the urgent need to develop innovative energy storage technologies to improve energy utilization efficiency. As pivotal components in thermal energy storage (TES) systems, phase change materials (PCMs) enable spatiotemporal matching between thermal energy supply and demand through latent heat absorption and release during phase transitions. Organic PCMs are considered ideal candidates for thermal energy storage due to their high energy storage density, stable phase transition temperature, low supercooling, and negligible phase separation. However, inherent drawbacks such as low thermal conductivity, liquid leakage, limited light absorption, and lack of functionality have hindered their widespread application in advanced thermal management systems. Herein, we systematically summarize cutting-edge functionalization strategies for PCMs, progressing from conventional methods like thermal conductive particle blending and microencapsulation to the emerging design of 3D porous thermally conductive skeletons, including metal foams, boron nitride aerogels, carbon-based aerogels, and MXene aerogels. These frameworks not only enhance thermal transport via continuous conductive pathways and impart shape stability through capillary encapsulation but also, when integrated with photo-thermal, electro-thermal, and magneto-thermal conversion properties, enable broad applications in solar photo-thermal/photo-thermo-electric conversion, thermal management of electronics and batteries, building efficiency, and wearable thermal regulation. The review further addresses current challenges and future directions, highlighting scalable 3D framework fabrication, the shift to active thermal management, and innovative applications beyond conventional domains. By establishing a microstructure–property–application correlation, this work provides valuable insights for developing next-generation high-performance multifunctional phase change composites. Full article

This study proposes a theoretical–empirical framework for analyzing political regimes based on a structural analogy between electoral behavior and spin-glass systems in statistical physics. Society is modeled as a system of interacting agents (voters) influenced by both interpersonal interactions and external factors such as media and institutions, formalized through a social Hamiltonian. By introducing a partition function and free energy, political regimes are interpreted as distinct macroscopic phases governed by four effective macro-parameters: external field, conformism, interaction heterogeneity, and inverse social temperature. Democratic societies correspond to a multistable regime characterized by sensitivity to initial conditions and replica symmetry breaking (RSB), reflecting the coexistence of competing social configurations. Authoritarian regimes, in contrast, arise when a strong unidirectional external field, high conformism, and low effective social temperature stabilize a single dominant macroscopic state, producing a regime analogous to replica symmetry (RS). A central result of the model is the distinction between the predictability of macroscopic outcomes and structural social multistability, as well as between natural and externally imposed homogenization of collective behavior. To illustrate the empirical relevance of the framework, the model is applied to the transition from the Weimar Republic to the National Socialist regime (1919–1933), using aggregated electoral data to construct proxy indicators for the effective parameters governing social interactions. The proposed approach enables structural identification of early signals of authoritarian transition through changes in the parameters of social dynamics. Full article

MicroRNAs (miRNAs) are small non-coding RNAs that play central roles in post-transcriptional gene regulation and cellular homeostasis maintenance. Dysregulation of miRNA expression is increasingly recognized as a key contributor to tissue injury during the acute phase and to disease progression in the chronic phase. Chronic kidney disease (CKD) commonly progresses and ultimately leads to kidney failure through interstitial fibrosis, which is the final common pathway of CKD progression. Interstitial fibrosis is driven not only by fibroblast activation but also by phenotypic transitions in injured tubular epithelial cells, infiltrating macrophages, and peritubular capillary cells. These multifaceted cellular pathways induce and exacerbate interstitial fibrosis, and several miRNAs have been identified as important regulators of these pathways. In addition to fibrotic pathophysiological features, disease-specific dysregulation of miRNAs has been increasingly detected in various causes of CKD, including diabetic kidney disease, chronic glomerulonephritis, and nephrosclerosis. In this review, we provide an integrated overview of miRNA-mediated regulation in CKD, with particular emphasis on cell lineage functions within fibrotic pathways and disease-specific roles. Finally, we discuss the emerging potential of miRNAs as biomarkers and therapeutic targets for CKD and highlight future research directions. Full article

Recent work on the evaluation of large language models emphasizes that the relevant unit of intelligence is not the artificial system alone but the human–AI hybrid. In parallel, topological and dynamical models of cognition based on Painlevé equations and non-semisimple topology propose that consciousness, intelligence, and creativity emerge from constrained long-horizon dynamics near criticality. This perspective article argues that these two research directions are deeply compatible. We show that the empirical framework for human–AI collaboration can be interpreted as a fusion process between complementary cognitive sectors: exploration (AI) and selection (human cognition). The dynamical mechanism underlying this fusion is identified with noisy phase locking between cognitive oscillators. Two independent routes to a universal $1/f$ spectral signature are developed: a geometric route through the WKB/Stokes analysis of Painlevé V confluence, and an arithmetic route through the Mangoldt function and harmonic interactions in phase-locked loops. We connect these results to the Bost–Connes quantum statistical model, whose phase transition at the pole of the Riemann zeta function provides an exact mathematical framework for the lock-in phase hypothesis of identity consolidation in AI systems. This synthesis suggests a unified research program for hybrid intelligence grounded in topology, dynamical systems, number theory, and real-world AI evaluation. Full article

Magnetic and structural transitions can interact significantly, leading to an enhanced magnetocaloric effect (MCE), also known as the giant or colossal effect. In this study, we investigate how subtle microstructural changes impact the magnetocaloric behavior of a MnCoGeB_0.02 alloy fabricated via suction casting. We obtained conical samples and analyzed them to understand their structure and magnetic properties. X-ray diffraction patterns revealed a coexistence of a metastable high-temperature hexagonal phase and a stable low-temperature orthorhombic phase in different regions of each cone. The presence and proportion of these phases determine the degree of magneto-structural coupling, which in turn influences the MCE. The magnetic entropy change (|ΔS_Peak|) varied notably among the samples, ranging from 12.3 to 6 Jkg⁻¹K⁻¹ under a magnetic field change of Δµ₀H = 5.0 T. These findings demonstrate that even minor microstructural changes caused by differences in solidification during suction casting can lead to noticeable variations in magnetocaloric performance. Understanding and controlling these microstructural details is vital for optimizing the functional behavior of MnCoGe-based materials. Full article

The properties of a Ca₉La(VO₄)₇ single crystal were studied using dielectric spectroscopy and second-harmonic generation. The crystal structure of Ca₉La(VO₄)₇ grown using the Czochralski technique was refined using single-crystal data. The distribution of Ca²⁺ and La³⁺ cations over structural positions was determined. The crystal structure refinement results were compared with those obtained previously from powder X-ray diffraction data. It was shown that the refinement carried out using two different data sets leads to approximately the same results for the distances in the polyhedra, but their distortion is significantly less in the case of using single-crystal data for calculation. Dielectric properties and conductivity measurements were performed on polished single-crystal wafers cut parallel and perpendicular to the c axis. Second-harmonic generation and dielectric temperature measurements revealed the presence of a reversible ferroelectric first-order phase transition at about 1224 K from the ferroelectric β-phase (space group R3c) to the paraelectric β′-phase. The ferroelectric–paraelectric phase transition is accompanied by a complex structural rearrangement, including a 60° rotation of the V1O₄ tetrahedron, as well as slight displacements of the Ca²⁺ and La³⁺ cations. It has been shown that the conductivity differs only slightly along the polar axis and perpendicular to it. Above the phase transition temperature, the activation energy of the conductivity is the same for all directions, E_a~1.2 eV. The influence of composition on the phase transition temperature and the formation of ferroelectric and nonlinear optical properties is discussed. Full article

Phase-change materials (PCMs) are capable of storing or releasing a substantial amount of thermal energy within a small volume through the latent heat of fusion during phase transitions of melting and solidification, i.e., from solid to liquid or vice versa, in a near isothermal process. However, commonly used organic PCMs, such as paraffin wax, exhibit very low thermal conductivity, contributing to an adverse increase in overall thermal resistance and, thus, a slow thermal response. This limitation often becomes a bottleneck for the system from a thermal performance standpoint. To mitigate this issue, the present work explores the fabrication of heat sinks incorporating nano-structured graphitic foams, including carbon foam (CF) and expanded graphite (EG), as well as micro-structured metal foams such as open-cell copper foam (OCCF), all impregnated with a paraffin-based PCM with a melting temperature near 37 °C. This study focuses on applying passive thermal management strategies to design efficient heat sinks capable of maintaining the temperatures of battery modules and electronic circuits within an acceptable thermal safety threshold for small satellites and spacecrafts, exemplified by the OPTIMUS and Pumpkin battery modules designed for CubeSats with a nominal cross-sectional area of almost 4″ × 4″. Temperature responses and average overall thermal resistances for fabricated heat sinks are accordingly assessed and compared in a vacuum chamber to simulate space conditions. Furthermore, the impact of operating pressure on the thermal performances of various heat sinks will be investigated by executing the same tests in both atmospheric and vacuum conditions. The findings demonstrate a superior thermal performance of composite heat sinks integrating carbon foam and copper foam into the paraffin PCM compared to the baseline PCM heat sink under both vacuum and atmospheric operating pressure conditions. Full article

Intending to improve building performance and environmental sustainability, vertical greenery systems (VGSs) are employed as effective nature-based solutions (NbSs), yet they often struggle to meet modern building energy demands alone. This study investigates the integration of VGSs with advanced façade technologies (AFTs) to develop multifunctional hybrid façades. A systematic review was conducted following PRISMA 2020 guidelines, combining bibliometric and thematic analyses of 415 publications (2015 to early 2026) from Scopus and Web of Science. The study categorizes AFT into adaptive, energy-generating, and high-performance façades. The results indicate that VGS–photovoltaic (PV) systems and double-skin (DS) systems are the most studied integration scenarios, providing significant thermal regulation and energy efficiency. However, significant gaps remain for kinetic, modular, bioactive, and glazing systems, particularly regarding standardized workflows and long-term lifecycle assessments (LCAs). The study reveals a transition of VGSs from passive aesthetic elements to active building components. To address these identified gaps, a four-phase design strategy—conceptualization, hybridization, optimization, and development—is proposed to guide architects and engineers in decision-making regarding generating optimized hybrid façades. Integrating VGSs with AFTs is essential for urban resilience and an alignment with Sustainable Development Goals. Future research should prioritize standardized integration protocols and the application of smart technologies like artificial intelligence (AI). Full article

Rare Earth Elements (REEs) represent strategic and critical raw materials for the energy transition and must therefore be integrated into efficient and functional recycling processes. Their adoption in electric motors is rapidly expanding, raising significant challenges for end-of-life (EoL) management, starting from the collection phase. In this context, this work proposes the integration of an image-based classification framework within the Waste Electrical and Electronic Equipment (WEEE) recycling pipeline to selectively identify electric motors containing permanent magnets (PMs) and direct them toward dedicated recycling processes for rare earth recovery. The proposed methodology relies on a Discriminative Transfer Learning (DTL) approach based on a ResNeXt convolutional neural network (CNN), adapted to a proprietary and heterogeneous dataset of electric motors acquired in an industrial recycling facility. The objective is twofold: first, to identify motors containing PMs; second, to classify motors into construction categories according to their likelihood of incorporating PMs. Experimental results show promising performance in terms of PM-containing motor detection capability, establishing a robust foundation for the automated recovery of REEs at an industrial scale. Furthermore, the model’s generalization capabilities can be further enhanced through the expansion of collaborative datasets and the integration of advanced scanning technologies. Full article

Background/Objectives: Floral bud morphogenesis is a critical developmental process determining yield potential in blueberry, yet the molecular regulatory mechanisms in leaves during this phase remain poorly understood. Methods: In this study, we employed a time-series transcriptomic approach to investigate leaf gene expression dynamics during floral bud morphogenesis in rabbiteye blueberry. Leaves were sampled at six time points spanning the critical developmental window from the cessation of summer shoot growth to bud swell and dormancy onset. Results: RNA-seq analysis generated 121.68 Gb of clean data, and weighted gene co-expression network analysis (WGCNA) identified four stage-specific modules (brown, red, blue, turquoise) significantly associated with distinct morphogenetic phases. The brown module (0–6W) was enriched in photosynthesis and hormone signaling pathways, while the red (9W) and blue (12W) modules featured protein processing, stress and hormone signaling, and carbohydrate metabolism. The turquoise module (15W) was dominated by carbon metabolism and flavonoid biosynthesis genes. Key flowering-related genes exhibited dynamic expression patterns: FT was specifically upregulated at the late stage (15W), AP2 genes peaked at mid-stage (9–12W), and COL9 showed early high expression (0–3W). Hormone-related gene analysis revealed extensive involvement of multiple pathways, with brassinosteroid (BR) signaling comprising the largest number of genes (101). Co-expression networks further identified hub genes, including FT, COL9, AP2, ERF1, SR160, LOX3-1, and transcription factor genes like MYB-related, as potential central regulators. Conclusions: Our findings demonstrate that blueberry leaves undergo a phased functional transition from a photosynthetic source to a hub for signal integration and metabolic support during floral bud morphogenesis, actively contributing to reproductive development through systemic signaling. This study provides novel insights into flowering regulation in woody perennials and establishes a foundation for marker-assisted breeding and cropping season management in blueberry. Full article

Driven by the goal of sustainable energy transitions, the integration of Inverter-Interfaced Distributed Generation (IIDG) has led to a continuous decline in the accuracy of single-phase grounding fault line selection in neutral non-effectively grounded distribution networks. Protection methods based on characteristic signal injection currently struggle to balance the differentiated requirements of fault detection sensitivity and equipment safety in networks with high-penetration IIDG. To address this issue, a high-frequency equivalent circuit model of the IIDG is established. The distribution patterns of the high-frequency characteristic current (HFCC) in distribution networks under high-penetration IIDG are analyzed. Subsequently, an adaptive HFCC injection strategy is proposed, which accounts for IIDG low-voltage ride-through (LVRT) requirements, fault identification sensitivity, and equipment safety constraints. Based on the amplitude and phase differences in the HFCC between faulty and healthy feeders, a fault line selection criterion is established. Consequently, an adaptive injection-based protection method for single-phase grounding fault is developed, considering the impact of high-penetration IIDG. Simulation results demonstrate that the proposed method accurately identifies the faulty feeder under various fault locations, transition resistances, and quantities of integrated IIDG units. The results further confirm the high adaptability and reliability of the method, thereby providing a robust technical foundation for the safe, reliable, and sustainable operation of modern power grids. Full article