Littérature scientifique sur le sujet « Insulating-To-Metal transition »

The role of orbital ordering on metal–insulator transition in transition-metal oxides is investigated by the cluster self-consistent field approach in the strong correlation regime. A clear dependence of the insulating gap of single-particle excitation spectra on the orbital order parameter is found. The thermal fluctuation drives the orbital order–disorder transition, diminishes the gap and leads to the metal–insulator transition. The unusual temperature dependence of the orbital polarization in the orbital insulator is also manifested in the resonant X-ray scattering intensity.

In conventional metals, charge carriers basically move freely. In correlated electron materials, however, the electrons may become localized because of strong Coulomb interactions, resulting in an insulating state. Despite considerable progress in the last decades, elucidating the driving mechanisms that suppress metallic charge transport, the spatial evolution of this phase transition remains poorly understood on a microscopic scale. Here, we use cryogenic scanning near-field optical microscopy to study the metal-to-insulator transition in an electronically driven charge-ordered system with a 20-nm spatial resolution. In contrast to common mean-field considerations, we observe pronounced phase segregation with a sharp boundary between metallic and insulating regions evidencing its first-order nature. Considerable strain in the crystal spatially modulates the effective electronic correlations within a few micrometers, leading to an extended “zebra” pattern of metallic and insulating stripes. We can directly monitor the spatial strain distribution via a gradual enhancement of the optical conductivity as the energy gap is depressed. Our observations shed new light on previous analyses of correlation-driven metal-insulator transitions.

The band structure calculations of perovskite transition metal compound LaRhO 3 performed using 'tight binding linear muffin tin orbital' (TB-LMTO) method within local density approximation (LDA) under ambient and high pressures are reported here. Our calculations are able to successfully explain the insulating nature of the system and the insulator-to-metal transition (IMT) is observed for the reduced volume of 0.90. The first electronic structure calculation reported here for LaRhO 3 enables us to compare it with that of LaCoO 3 which brings out the role played by the d bands. These studies lead to distinguish between these two insulating systems and LaCoO 3 is found to be a charge transfer (CT) insulator which is in agreement with the recent experimental observations whereas LaRhO 3 is a conventional band insulator. Further, the equilibrium lattice constant, bulk modulus, its first derivative, and metallization volume obtained from the total energy calculations for expanded and reduced cell volumes are also reported for LaRhO 3.

Metal-insulator transition (MIT) underlies many remarkable and technologically important phenomena in VO2. Even though its monoclinic structure had before been the reserve of the insulating state, recent experiments have observed an unexpected monoclinic metallic state. Here, we use a modified approach combining first-principles calculations with orbital-biased potentials to reproduce the correct stability ordering and electronic structures of different phases of VO2. We identify a ferromagnetic monoclinic metal that is likely to be the experimentally observed mysterious metastable state. Furthermore, the calculations show that an isostructural insulator-metal electronic transition is followed by the lattice distortion from the monoclinic structure to the rutile one. These results not only explain the experimental observations of the monoclinic metallic state and the decoupled structural and electronic transitions of VO2, but also provide a useful understanding for the metal-insulator transition in other strongly correlated d electron systems.

Double perovskites, A2BB'O6, containing mixed transition metal ions have exhibited numerous desirable properties such as colossal magnetoresistance, half metallic transport, and high temperature ferrimagnetism. However, a predictive understanding of the superexchange mechanisms which control the magnetism of these materials when they are insulating and B is 3d transition metal and B' is a 4d or 5d transition metal has remained elusive. In this work, a number of insulating double perovskite osmates, A2BOsO6 (A=Sr,Ca,La; B=Cr,Fe,Co,Ni) have been chosen and studied using magnetometry, specific heat, XMCD, and neutron powder diffraction techniques in order to systematically probe the effects of electronic configuration and bonding geometry on the magnetic ground state. It is concluded that the magnetic properties of these materials are controlled by a competition between short range B–O–Os and long range superexchange interactions which are sensitive to bonding geometry resulting in tunability of the magnetic ground state.

The 1/f noise level in polycrystalline indium oxide thin films and of zinc oxide accumulation layers is found to be much higher than that usually observed in metals. A systematic study of the flicker noise properties in these systems reveals a correlation between the 1/f noise magnitude and the proximity of the system to the insulating phase. In fact, the noise appears to increase dramatically close to the Anderson transition but when the average transport properties exhibited by the system are still diffusive. For static disorder that exceeds the critical value characterized by KFl≃1 the system exhibits insulating behavior and the noise level saturates at a rather high, but disorder independent value. The similarity of these findings to the behavior of the magnetic-field-induced Conductance Fluctuations in this system will be pointed out to suggest a common physical origin. This leads to the prediction of high levels of 1/f in all electronic systems that are close to the metal-insulator transition.

Coulomb correlations can manifest in exotic properties in solids, but how these properties can be accessed and ultimately manipulated in real time is not well understood. The insulator-to-metal phase transition in vanadium dioxide (VO2) is a canonical example of such correlations. Here, few-femtosecond extreme UV transient absorption spectroscopy (FXTAS) at the vanadiumM2,3edge is used to track the insulator-to-metal phase transition in VO2. This technique allows observation of the bulk material in real time, follows the photoexcitation process in both the insulating and metallic phases, probes the subsequent relaxation in the metallic phase, and measures the phase-transition dynamics in the insulating phase. An understanding of the VO2absorption spectrum in the extreme UV is developed using atomic cluster model calculations, revealing V3+/d2character of the vanadium center. We find that the insulator-to-metal phase transition occurs on a timescale of 26 ± 6 fs and leaves the system in a long-lived excited state of the metallic phase, driven by a change in orbital occupation. Potential interpretations based on electronic screening effects and lattice dynamics are discussed. A Mott–Hubbard-type mechanism is favored, as the observed timescales and d2nature of the vanadium metal centers are inconsistent with a Peierls driving force. The findings provide a combined experimental and theoretical roadmap for using time-resolved extreme UV spectroscopy to investigate nonequilibrium dynamics in strongly correlated materials.

Alors que les exigences en matière d'IA augmentent, de nouveaux paradigmes informatiques deviennent essentiels. Les architectures traditionnelles de von Neumann peinent à répondre aux exigences intensives de l'IA. L'informatique neuromorphique, inspirée par le cerveau, intègre traitement et mémoire pour une computation plus rapide et efficace, idéale pour des applications d'IA comme l'apprentissage profond et la reconnaissance de formes. Les matériaux clés pour l'informatique neuromorphique incluent les synaptors et les neuristors. Les memristors, des mémoires non volatiles fabriquées à partir d'oxydes tels que HfO2 et TiO2, imitent le comportement synaptique en changeant d'état via des filaments à l'échelle nanométrique ou des transitions de phase. Quant aux neuristors, ils imitent le celui du déclenchement des neurones en utilisant des memristors et des circuits résistance-condensateur reproduisant le modèle LIF (Leaky, Integrate, and Fire). À température ambiante, l’isolant de Mott VO2 remplit les fonctions neuronales en formant des chemins conducteurs volatiles. Cependant, les synaptors et les neuristors nécessitent souvent des matériaux différents. L'optimisation de VO2 comme synapse pourrait lui permettre de remplir les deux fonctions à température ambiante.Étudier des systèmes à séparation de phases comme VO2 reste complexe en raison des inhomogénéités. Les avancées en microscopie infrarouge et optique permettent désormais d'imager ces régions avec une résolution nanométrique. Les techniques de champ proche peuvent sonder la conductivité locale à l'échelle nanométrique. Cependant, ces sondes ont des limites : (i) des scans longs pour les inhomogénéités plus grandes et (ii) des transitions de phase induites par la température causant des dérives thermiques et des comparaisons d'images difficiles. Pour y remédier, nous avons développé un système de microscopie optique à champ lointain pour étudier les transitions de phase dans le VO2. Ce système exploite le contraste optique entre les phases isolantes et métalliques, observable des nanomètres aux microns.Nous avons mis en œuvre différents protocoles de température en imagerie continue, compensant la dérive thermique et alignant des images nettes. Cela permet des traces temporelles de pixels uniques pour indiquer les températures spécifiques de transition de phase. Nous avons tout d’abord cartographié la température critique (Tc), la largeur de transition (ΔTc) et leur netteté (δTc). Ces cartographies pourraient permettre d'adapter les propriétés du VO2 pour des applications spécifiques comme les dispositifs de mémoire et les composants à commutation rapide. Nous avons également présenté la première imagerie optique de la mémoire à inversion de rampe (RRM) dans le VO2, montrant l'évolution des clusters pendant l'entraînement thermique. L'accumulation de mémoire se produit aux frontières des clusters et à l'intérieur des patchs, suggérant une diffusion préférentielle des défauts ponctuels.De plus, nous avons mené une analyse d'apprentissage automatique (ML) des motifs fractals dans le VO2, en utilisant le ML pour classifier l'Hamiltonien, conduisant à la formation de motifs. Notre réseau neuronal convolutionnel (CNN) a atteint une haute précision avec des données synthétiques et expérimentales, confirmant la formation de motifs due à la proximité d'un point critique du modèle Ising 2D à champ aléatoire. Cela, combiné à la réduction de symétrie et à la quantification de confiance, offre un puissant nouvel outil pour analyser les transitions de phase complexes dans les matériaux corrélés. Notre recherche fournit une nouvelle méthode de caractérisation optique pour comprendre la dynamique de transition du VO2 et introduit des approches innovantes pour des applications non-mémoires. Ces perspectives posent les bases d'études futures explorant le potentiel de la RRM et étendant les cadres ML à d'autres matériaux corrélés
As AI demands grow, new computing paradigms are essential. Traditional von Neumann architectures struggle with intensive AI requirements. Neuromorphic computing, inspired by the brain, integrates processing and memory for faster, efficient computation, ideal for AI applications like deep learning and pattern recognition.Key materials for neuromorphic computing include synaptors and neuristors. Memristors, non-volatile memories made from oxides like HfO2 and TiO2, mimic synaptic behavior by switching states via nanoscale filaments or phase transitions. Neuristors emulate neuron spiking behavior using memristors and resistance-capacitance circuits to replicate the Leaky, Integrate, and Fire model. Mott insulators like VO2 mimic neuron-like behavior by forming volatile conductive pathways. However, synaptors and neuristors often require different materials. Optimizing VO2 for synaptic behavior could enable it to serve both functions at room temperature.Studying phase-separated systems like VO2 is complex due to inhomogeneities. Advances in infrared and optical microscopy now allow imaging these regions with nanometer-scale resolution. Near-field techniques, using atomic force microscopes coupled to IR lasers, can probe local conductivity at the nanoscale. However, these probes have limitations: (i) long scans for larger inhomogeneities and (ii) temperature-driven phase transitions causing temperature drifts and difficult imaging comparisons.To address these, we developed a far-field optical microscopy setup to study VO2 phase transitions. This setup leverages optical contrast between insulating and metallic phases, observable from nanometers to microns. We applied different temperature protocols while continuously imaging, counteracting temperature drift and aligning sharp images. This enables single-pixel time traces to indicate specific phase transition temperatures.We first mapped critical temperature (Tc), transition width (ΔTc), and transition sharpness (δTc) in VO2. These maps could enable tailoring VO2 properties for specific applications like memory devices and fast switching components.We also presented the first optical imaging of ramp reversal memory (RRM) in VO2, showing cluster evolution during thermal subloop training. Memory accumulation occurs at cluster boundaries and within patches, suggesting preferential diffusion of point defects. This could enhance memory effects through defect engineering, improving memory devices' robustness and stability.Additionally, we pursued a machine learning (ML) analysis of fractal patterns in VO2, using ML to classify the Hamiltonian driving pattern formation. Our convolutional neural network (CNN) achieved high accuracy with synthetic and experimental data, confirming pattern formation driven by proximity to a critical point of the two-dimensional random field Ising model. This framework, combined with symmetry reduction and confidence quantification, offers a new powerful tool for analyzing complex phase transitions in correlated materials.Our research provides a new optical characterization method for understanding VO2 transition dynamics and introduces innovative approaches for optimizing VO2 for non-memory applications. These insights lay a foundation for future studies that explore RRM's potential, and extend ML frameworks to other correlated materials

The fundamental and technological importance of transition metal oxides, and the relationship of the present work to previous monographs dealing with transition metal oxides are reviewed. The relatively abundant 3d-transition metal oxides are contrasted with the rarer 4d- and 5d-transition metal oxides that exhibit a unique interplay between spin-orbit, exchange, crystalline electric field and Coulomb correlations. The combined effect of these fundamental interactions yields peculiar quantum states and empirical trends that markedly differ from those of their 3d counterparts. General trends in the electronic structure are related to generalized phase diagrams of the magnetic and insulating ground states. The intriguing absence of experimental evidence for predicted topological states and superconductivity in these materials are discussed.

Abstract As we have seen in Chapter 3, the metal-non-metal transition in doped semiconductors has attracted renewed interest in the light of the localization problem. We mentioned in Chapter 1 that recent theoretical work in the field has followed two main lines of approach. The first approach starts from the nearly free electron picture in the metallic regime and then covers the effect of localization due to disorder. The second line of approach, on the other hand, covers the insulating phase and starts from the Anderson localized regime itself. This approach, which describes the system by a tight-binding picture, is particularly suitable for the donor concentration region where the localization length is of the order of average donor separation. Thus these two approaches for disordered systems may be compared with the two complementary approaches for perfect crystals, i.e. the Bloch electron approach and the tight-binding approach. The final goal of both approaches is of course the same—an accurate description of the metal-non-metal transition.

Two-dimensional (2D) materials have gained prominence as memory devices and in next generation computing platforms, such as neuromorphic computing. Semi-metallic graphene is used as electrodes in memory devices with reduced power consumption. Insulating and semiconducting 2D materials exhibit memristive behavior, thus finding use in random access memory and as analog memory for artificial synapses. The switching in memory devices with 2D materials is due to the formation of localized conductive filaments, due to the unique interface between the 2D material and the metal electrode, or by means of phase transition. Synaptic devices are realized with ferroelectric 2D materials. Charge trapping in transistors and floating gate field effect transistors is used to realize non-volatile memory. The large family of 2D materials offers a variety of options to realize memristive stacks and transistors for memory and neuromorphic computing.

Our work demonstrates a tunable reflectance filter based on a metal-hydrogel-metal structure responsive to humidity and temperature. The filter employs a hydrogel as an insulating layer. Swelling/deswelling and the volume phase transition of the hydrogel allow continuous reversible humidity- and/or temperature-induced tuning of the optical resonance.

Abstract The high-purity electron-doped manganites Sm1-xCaxMnO3 nanopowder were prepared by the solid-state reaction method, then the bulk material were obtained through granulation, molding, calcining, grinding and polishing. SCMO nanoparticles with 200 nm were obtained by the sol-gal process. The phase and surface morphology of these materials were characterized by X-ray diffraction and Scanning electron microscope and other experiments. The variable resistivity of the bulk materials were measured by two-wire method in the temperature range of 100–420K. The thermal conductivity was measured by the Laser Flash method. The results show that different doping ratios can change the phase transition temperature of the metal-insulation state. The temperature changed from 0 to 50 °C. The TMI could be regulated to room temperature. When the temperature is high than the TMI, it performs as metal state, on the contrary, it performs as an insulating state.

Several oxides of vanadium undergo a transition from a semiconductor or insulating state to a metal phase at a critical temperature. VO2 undergoes this transition near 68°C, while V2O5 undergoes a similar phase transition near 257°C, and V2O3 undergoes a similar transition near 150 K. During the transition a change in oxide crystal structure is accompanied by large changes in electrical and optical behavior. Thin films of vanadium oxides are capable of reversibly switching from the semiconductor to the metallic state at high speeds with high spatial resolution. Therefore, these oxides have potential use, particularly in thin film form, for a wide variety of applications involving thermally activated electronic or optical switching devices. Such films are of considerable technical interest because of applications in chemical sensors, energy-conserving coatings, transparent conductors, and switching materials. The numerous potential electronic, optic, and optoelectronic device applications which have been suggested have stimulated work on the preparation of thin films by a variety of techniques, including chemical vapor deposition, solgel, evaporation, and sputter deposition.