Local Transition Research Articles

The forgotten bread oven: local bakeries, forests and energy transition in Nigeria

The forgotten bread oven: local bakeries, forests and energy transition in Nigeria

Single-particle excitations across the localization and many-body localization transition in quasiperiodic systems

Single-particle excitations across the localization and many-body localization transition in quasiperiodic systems

The role of Ca/Zr ratio on the local structure and phase transitions in lead-free (Ba,Ca)(Zr,Ti)O3

In this study, the structural phase transitions are investigated as a function of composition and temperature for polycrystalline x(Ba0.7Ca0.3)TiO3-(1 − x)Ba(Zr0.2Ti0.8)O3 (x = 0.40, 0.45, 0.50, 0.55, and 0.60) through a combination of Raman spectroscopy, synchrotron X-ray diffraction, and dielectric spectroscopy. The aim is to gain insight into the complex phase boundary region responsible for the excellent electromechanical properties. The results demonstrate the correlation between local site substitutions based on the stoichiometric variations to the microstructure and dielectric properties. The dielectric response has been correlated with the BCT/BZT content displaying a maximum depending on the phase content. Additionally, in situ temperature-dependent Raman, permittivity, and pair distribution function (PDF) studies were performed from −60 °C to 130 °C to highlight the structure and phase evolution. In particular, the in situ temperature-dependent Raman measurements reveal sudden discontinuities in the vibrational modes that correspond to the structural changes in the perovskite structure. Therefore, the results of the permittivity response, based on the average of a large volume, are consistent with the local structural changes obtained by other techniques. Indeed, correlations of Raman, X-ray diffraction, and PDFs obtained from synchrotron X-ray total scattering data, along with permittivity measurements allowed the identification of the discrete ferro- to paraelectric phase transitions and a more robust characterization. The rotation and distortion of the octahedral caused by oxygen displacement are driving forces behind symmetry changes and phase transitions, explaining the mechanism of polymorphic phase transition based on A- and B-site substitution. Therefore, this work provides a comprehensive understanding of temperature and composition-dependent phase transitions in BCZT.

A significant increase in carrier concentration in TiO2 by Sm doping

Sm-doped TiO2 thin films were synthesized by pulsed laser deposition. The luminescence and donor-generation properties of thin films annealed at various temperatures were investigated. The results showed that Sm-related emissions occurred in the temperature range 500 °C–800 °C. The donor densities in this temperature range were two orders of magnitude higher than that of the undoped TiO2 thin film. The effect of annealing within the temperature window indicates a local fine structural transition of the ligands around Sm3+ ions from T d symmetry to the lower C 4v one; these ions are effective luminescence centers in TiO2:Sm thin films. This local structural distortion also increases defect generation, and this increases the donor density in the same temperature region.

Microstructure Characterization and Mechanical Properties of Polymer‐Derived (HfxTa1−x)C/SiC Ceramic Prepared upon Field‐Assisted Sintering Technique/Spark Plasma Sintering

The high‐temperature microstructural evolution and mechanical properties of two SiC‐based polymer‐derived ceramics with different Hf:Ta molar ratios are investigated using electron microscopy techniques and manipulated by nanoindentation. The as‐pyrolyzed ceramic powder consists of an amorphous Si(HfxTa1−x)C(N,O) structure (where x = 0.2, 0.7) with localized nanocrystalline transition metal carbides (TMCs). Subsequent application of the field‐assisted sintering technique (FAST) for high‐temperature consolidation results in a crystalline (HfxTa1−x)C/SiC ultra‐high temperature ceramic nanocomposite. The microstructure contains powder particle‐sized grains and sinter necks between the former powder particles. The powder particles consist of a β‐SiC matrix and small TMCs. Large TMCs are observed on the internal surfaces of former powder particles. This is due to the pulsed direct current and the resulting Joule heating that facilitates diffusion as well as oxygen impurities. Sinter necks of large β‐SiC grains form during the FAST process. The microstructural regions are assessed using high‐throughput nanoindentation. The hardness for SiC/(Hf0.7Ta0.3)C is measured on the formed grains and the sinter necks giving mean hardness values of about 27 and 37 GPa, respectively.

Prerequisite-Enhanced Category-Aware Graph Neural Networks for Course Recommendation

The rapid development of Massive Open Online Courses (MOOCs) platforms has created an urgent need for an efficient personalized course recommender system that can assist learners of all backgrounds and levels of knowledge in selecting appropriate courses. Currently, most existing methods utilize a sequential recommendation paradigm that captures the user’s learning interests from their learning history, typically through recurrent or graph neural networks. However, fewer studies have explored how to incorporate principles of human learning at both the course and category levels to enhance course recommendations. In this article, we aim at addressing this gap by introducing a novel model, named Prerequisite-Enhanced Catory-Aware Graph Neural Network (PCGNN), for course recommendation. Specifically, we first construct a course prerequisite graph that reflects the human learning principles and further pre-train the course prerequisite relationships as the base embeddings for courses and categories. Then, to capture the user’s complex learning patterns, we build an item graph and a category graph from the user’s historical learning records, respectively: (1) the item graph reflects the course-level local learning transition patterns and (2) the category graph provides insight into the user’s long-term learning interest. Correspondingly, we propose a user interest encoder that employs a gated graph neural network to learn the course-level user interest embedding and design a category transition pattern encoder that utilizes GRU to yield the category-level user interest embedding. Finally, the two fine-grained user interest embeddings are fused to achieve precise course prediction. Extensive experiments on two real-world datasets demonstrate the effectiveness of PCGNN compared with other state-of-the-art methods.

Low voltage grid resilience: Evaluating electric vehicle charging strategies in the context of the grid development plan Germany

The ongoing transition to decentralized renewable energy sources and sector-coupled consumers is reshaping the energy system. Changes at lower grid levels can stress lines and transformers. Crucial for a successful local energy transition are grid relief measures. Battery electric vehicles contribute to higher loads on grid equipment but also offer flexibility. This paper assesses the influence of four different charging strategies for battery electric vehicles across five representative low-voltage grids based on the grid development plan in Germany for the years 2021, 2037, and 2045. Results indicate that grid stress, specifically capacity stress, will emerge by 2037 and 2045. Decentralized photovoltaic systems are the primary contributors to this stress due to high simultaneous generation. Up to nearly 20% of photovoltaic power may need to be curtailed in 2045, especially in rural grids during the summer, to prevent overloads.Charging strategies linked to wholesale power market prices can inadvertently lead to higher consumption-induced grid overloads, necessitating the consideration of local grid restrictions. Implementing grid-friendly charging strategies, such as reduced charging power or alignment with local photovoltaic production, can mitigate those grid overloads from almost 8% down to 0.11%. However, these charging strategies have limited impact on photovoltaic-induced overloads due to the low number of connected battery electric vehicles during the day.In summary, appropriate charging strategies can ease low-voltage grid stress and are suitable measures to manage the challenges of decentralized energy transition and battery-electric vehicle adoption.

Localized Dynamics in the Floquet Quantum East Model.

We introduce and study the discrete-time version of the quantum East model, an interacting quantum spin chain inspired by simple kinetically constrained models of classical glasses. Previous work has established that its continuous-time counterpart displays a disorder-free localization transition signaled by the appearance of an exponentially large (in the volume) family of nonthermal, localized eigenstates. Here we combine analytical and numerical approaches to show that (i)the transition persists for discrete times, in fact, it is present for any finite value of the time step apart from a zero measure set; (ii)it is directly detected by following the nonequilibrium dynamics of the fully polarized state. Our findings imply that the transition is currently observable in state-of-the-art platforms for digital quantum simulation.

Dynamical localization transition in the non-Hermitian lattice gauge theory

Local constraint in the lattice gauge theory provides an exotic mechanism that facilitates the disorder-free localization. However, the understanding of nonequilibrium dynamics in the non-Hermitian lattice gauge model remains limited. Here, we investigate the quench dynamics in a system of spinless fermions with nonreciprocal hopping in the Z2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\\mathbb{Z}}}_{2}$$\\end{document} gauge field. By employing a duality mapping, we systematically explore the non-Hermitian skin effect, localization-delocalization transition, and real-complex transition. Through the identification of diverse scaling behaviors of quantum mutual information for fermions and spins, we propose that the non-Hermitian quantum disentangled liquids exist both in the localized and delocalized phases, the former originates from the Z2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\\mathbb{Z}}}_{2}$$\\end{document} gauge field and the latter arises from the non-Hermitian skin effect. Furthermore, we demonstrate that the nonreciprocal dissipation causes the flow of quantum information. Our results provide valuable insights into the nonequilibrium dynamics in the gauge field, and may be experimentally validated using quantum simulators.

Bistability and chaotic behaviors in a 4D cancer oncolytic Virotherapy mathematical model: Pspice and FPGA implementations

Oncolytic viruses (OVs) exploit characteristics of mass cells and tumor-related reaction of the body to the presence of antigen, to lyse malignant cells and modulate the tumor microenvironment. However, the effective clinical utilization of these powerful treatment modules necessitates their logical control, especially in order to prevent solid and metastatic outgrowths. Hence, it is imperative to develop methods to protect a virus from the annihilating surroundings from the bloodstream when traveling to tumor locations. Our article reports on bistability and chaotic behavior in a 4D cancer virotherapy model. We find that unstable, stable and chaotic behaviors can appear in the model when tuning some of its parameters. With the help of the chart of dynamic behaviors in parameter spaces, numerical investigations of the system’s characteristics are analyzed followed by a discussion of the obtained results. It appears that the local transition change from an invariant one-torus (IT1) to its two-torus (IT2) counterpart can be found in the system and this undergoes a Neimark-Saker (NS) change of direction. As the increasing rate of immune effector enhance, the immune cells amount increases and as a consequence, the virotherapy dynamics becomes chaotic with a pronounced Lyapunov exponent. This can result to the failure of the virotherapy due to the interference of the immune cells with viruses. We also focus our study on the deign of ad-hoc electronic and Field Programmable Gate Arrays (FPGA) implementations of the cancer virotherapy’s model, to illustrate the obtained results.

Phenomenon of multiple reentrant localization in a double-stranded helix with transverse electric field

The present work explores the potential for observing multiple reentrant localization behavior in a double-stranded helical (DSH) system, extending beyond the conventional nearest-neighbor hopping (NNH) interaction. The DSH system is considered to have hopping dimerization in each strand, while also being subjected to a transverse electric field. The inclusion of an electric field serves the dual purpose of inducing quasi-periodic disorder and strand-wise staggered site energies. Two reentrant localization regions are identified: one exhibiting true extended behavior in the thermodynamic limit, while the second region shows quasi-extended characteristics with partial spreading within the helix. The DSH system exhibits three distinct single-particle mobility edges linked to localization transitions present in the system. The analysis in this study involves examining various parameters such as the single-particle energy spectrum, inverse participation ratio, local probability amplitude, and more. Our proposal, combining achievable hopping dimerization and induced correlated disorder, presents a unique opportunity to study phenomenon of reentrant localization, generating significant research interest.

Localization of light in three dimensions: A mobility edge in the imaginary axis in non-Hermitian Hamiltonians

Searching for Anderson localization of light in three dimensions has challenged experimental and theoretical research for the last decades. Here the problem is analyzed through large-scale numerical simulations, using a radiative Hamiltonian, i.e., a non-Hermitian long-range hopping Hamiltonian, well suited to model light-matter interaction in cold atomic clouds. Light interaction in atomic clouds is considered in the presence of positional and diagonal disorder. Due to the interplay of disorder and cooperative effects (sub- and super-radiance) a novel type of localization transition is shown to emerge, differing in several aspects from standard localization transitions which occur along the real energy axis. The localization transition discussed here is characterized by a mobility edge along the imaginary energy axis of the eigenvalues which is mostly independent of the real energy value of the eigenmodes. Differently from usual mobility edges it separates extended states from hybrid localized states and it manifests itself in the large moments of the participation ratio of the eigenstates. Our prediction of a mobility edge in the imaginary axis, i.e., depending on the eigenmode lifetime, paves the way to achieve control both in the time and space domains of open quantum systems.

A solver for subsonic flow around airfoils based on physics-informed neural networks and mesh transformation

Physics-informed neural networks (PINNs) have recently become a new popular method for solving forward and inverse problems governed by partial differential equations. However, in the flow around airfoils, the fluid is greatly accelerated near the leading edge, resulting in a local sharper transition, which is difficult to capture by PINNs. Therefore, PINNs are still rarely used to solve the flow around airfoils. In this study, we combine physical-informed neural networks with mesh transformation, using a neural network to learn the flow in the uniform computational space instead of physical space. Mesh transformation avoids the network from capturing the local sharper transition and learning flow with internal boundary (wall boundary). We successfully solve inviscid flow and provide an open-source subsonic flow solver for arbitrary airfoils. Our results show that the solver exhibits higher-order attributes, achieving nearly an order of magnitude error reduction over second-order finite volume method (FVM) on very sparse meshes. Limited by the learning ability and optimization difficulties of the neural network, the accuracy of this solver will not improve significantly with mesh refinement. Nevertheless, it achieves comparable accuracy and efficiency to second-order FVM on fine meshes. Finally, we highlight the significant advantage of the solver in solving parametric problems, as it can efficiently obtain solutions in the continuous parameter space about the angle of attack.

Study on city's energy transition: Evidence from the establishment of the new energy demonstration cities in China

Actively promoting city's energy transition is crucial for achieving SDG-7 and SDG-13. Taking the establishment of New Energy Demonstration Cities (NEDC) in China as a quasi-natural experiment, this paper employs difference-in-difference model to empirically test the impact of the NEDC policy on city's energy transition and its underlying mechanisms. The results demonstrate that the NEDC policy has significantly accelerated regional energy transition. Through an analysis of the internal motivation for energy transition, we find that this positive effect is predominantly driven by green demand-side rather than supply-side. Further examination of the external impetus for energy transition reveals that government governance, technology innovation, and the associated human and financial supports are key factors in propelling local energy transition. Our findings offer insights into the pathways of city's energy transition for China and other countries.

Collective Strong Coupling Modifies Aggregation and Solvation.

Intermolecular (Coulombic) interactions are pivotal for aggregation, solvation, and crystallization. We demonstrate that the collective strong coupling of several molecules to a single optical mode results in notable changes in the molecular excitations around a single perturbed molecule, thus representing an impurity in an otherwise ordered system. A competition between short-range coulombic and long-range photonic correlations inverts the local transition density in a polaritonic state, suggesting notable changes in the polarizability of the solvation shell. Our results provide an alternative perspective on recent work in polaritonic chemistry and pave the way for the rigorous treatment of cooperative effects in aggregation, solvation, and crystallization.

Comparing the impact of different adsorbed layers on the local glass transition of polymer matrices.

Chain adsorption to nanofiller interfaces creating bound layers has become central to understanding property changes in polymer nanocomposites. We determine the impact different kinds of adsorbed layers can have on the local glass transition temperature Tg of polymer matrices in a model film system using a localized fluorescence method. This work compares the adsorption and desorption of adsorbed layers grown in solution with the solution washing characteristics of adsorbed layers formed in the melt, leveraging knowledge about polymer adsorption in solution to infer the structure of adsorbed layers formed in the melt. In the limit of zero concentration after a long time in solution, we find that both kinds of adsorbed layers reach the same limiting adsorbed amount h∞(c → 0) ≈ 1 nm, appearing to evolve to the same thermodynamic equilibrium state of a near monolayer of surface coverage. We propose that melt annealing leads to a coarsening of polymer segment-surface contacts, increasing the length of trains and shrinking loops and tails, slowing the subsequent kinetics of these adsorbed chains in solution. Considering how the pyrene-labeled chains intermix with the adsorbed layer enables us to discriminate between the impact of tails, loops, and trains as threading of loops takes longer. We find that large fluffy loops, tails, and trains have little to no impact on the local Tg. A large 30K increase in local Tg is observed for 30-minsolvent washed well-annealed films at long intermixing times that we attribute to the threading of small tight loops.

Open data for energy networks: introducing DAVE—a data fusion tool for automated network generation

Developing a sustainable energy system for the future requires new ways of planning and operating energy infrastructure. A large part of this involves suitable network models. Real network data is not available for research without restrictions since energy networks are part of the critical infrastructure. Using open datasets and expert rules to generate non-restricted models is one solution to this. This paper introduces open data for energy networks generated by the open-source software “DAVE”. The Python-based data fusion tool DAVE can automatically generate customized energy network models quickly and on demand. The software collects data from various databases and uses appropriate methods to fuse them. The current version of the tool can create GIS-based power networks and gas transportation networks, with output that is compatible with common network simulation software. Further developments are planned for creating thermal and gas distribution networks, as these are important for local heat power transition. Implementing a quality description for fused datasets will also be included in future development.

Energy transition plans: How municipalities face the energy transition

Energy transition plans: How municipalities face the energy transition Municipalities need tools to manage and achieve the local energy transition, according to Gerard Laguna Benet, Researcher at BEE Group – CIMNE. The European Union (EU) takes significant steps towards decarbonisation,aiming to be climate-neutral by 2050. To reach this ambitious target, the EU introduced a roadmap which set a 55% reduction of greenhouse gas emissions, above 32% share of renewable energy and at least 32.5% of energy efficiency improvement by 2030.In this context, the municipalities have a significant role as the energy transition pushes Europe to a decentralised and local energy generation framework.On one side, municipalities have a role to play in taking exemplary action to reduce energy consumption in their buildings. On the other side, to lead Europe towards climate neutrality, it’s essential to make efforts at the local level, considering each region’s specific characteristics and challenges. Therefore, municipalities have a vital role in the European energy transition.

Effect of novel mixed impeller on local bubble size and flow regime transition in pilot scale gas-liquid stirred tank reactor

Abstract The flow generated in a gas-liquid stirred tank reactor highly depends on the design of the impeller and sparger. To better understand the contact between the phases and the mass and heat transfer rates, especially when the mass transfer is the limiting step, it is crucial to investigate the hydrodynamics generated by the impellers and its impact on the bubble size and their distribution, and gas volume fraction. In this work, experimental and numerical studies are performed with a novel mixed impeller in a pilot scale (T = 0.486 m) gas-liquid stirred tank reactor. The Sauter mean diameter, mean bubble diameter and bubble size distribution is determined at the different radial and axial regions by using high-speed imaging technique. Further, Euler-Euler simulations are performed to find the detailed flow field of novel mixed impeller used in the current study. Finally, the gassed power to impeller swept volume ratio is determined from the CFD and correlated with the Sauter mean diameter measured in the experiment in the impeller discharge region. It is found that the novel mixed impeller used in current work shows the similar behavior as the Rushton impeller in the impeller discharge region and it also provide good axial mixing.

ZDHHC5-mediated S-palmitoylation of FAK promotes its membrane localization and epithelial-mesenchymal transition in glioma

BackgroundAbnormal activation of FAK is associated with tumor development and metastasis. Through interactions with other intracellular signalling molecules, FAK influences cytoskeletal remodelling, modulation of adhesion signalling, and activation of transcription factors, promoting migration and invasion of tumor cells. However, the exact mechanism that regulates these processes remains unresolved. Herein, our findings indicate that the S-palmitoylation of FAK is crucial for both its membrane localization and activation.MethodsThe palmitoylation of FAK in U251 and T98G cells was assessed by an acyl-PEG exchange (APE) assay and a metabolic incorporation assay. Cellular palmitoylation was inhibited using 2-bromopalmitate, and the palmitoylation status and cellular localization of FAK were determined. A metabolic incorporation assay was used to identify the potential palmitoyl acyltransferase and the palmitoylation site of FAK. Cell Counting Kit-8 (CCK8) assays, colony formation assays, and Transwell assays were conducted to assess the impact of ZDHHC5 in GBM. Additionally, intracranial GBM xenografts were utilized to investigate the effects of genetically silencing ZDHHC5 on tumor growth.ResultsInhibiting FAK palmitoylation leads to its redistribution from the membrane to the cytoplasm and a decrease in its phosphorylation. Moreover, ZDHHC5, a protein-acyl-transferase (PAT), catalyzes this key modification of FAK at C456. Knockdown of ZDHHC5 abrogates the S-palmitoylation and membrane distribution of FAK and impairs cell proliferation, invasion, and epithelial-mesenchymal transition (EMT). Taken together, our research reveals the crucial role of ZDHHC5 as a PAT responsible for FAK S-palmitoylation, membrane localization, and activation.ConclusionsThese results imply that targeting the ZDHHC5/FAK axis has the potential to be a promising strategy for therapeutic interventions for glioblastoma (GBM).DK35umxSfc6RJzPPrNqiMTVideo