State Distribution Research Articles

Revealing the Mechanism of Alcohol Dehydroxylation and C-C Bond Formation through Concerted Catalysis by Ir/Cu Bimetallic Complexes.

The density functional theory (DFT) was employed to theoretically investigate the reaction mechanism of alcohol deoxygenation/trifluoromethylation. The substrate alcohol (R1) forms a complex (INT3) by binding with benzoxazole salts (NHCs). Under the influence of the photocatalyst ([IrIII]*) and quinuclidine, the C-H bond in INT3 is activated through either electron transfer-proton transfer (ETPT) or hydrogen atom transfer (HAT) mechanisms, resulting in the cleavage of C-O bonds and generation of deoxyalkyl radicals. The distribution of high-valent and low-valent states in the catalytic cycle of [Ir]-complexes is governed by the redox potential mechanism. Investigation was conducted on the source of hydrogen atom transfer reagents in the HAT reaction process under both optimal and nonoptimal conditions. The results demonstrate distinct reactivity among various radicals involved in the Cu-mediated radical capture process. Further investigations into INT3 activation modes, cycling facilitated by [Ir]-complexes, and understanding the role played by [Cu]-complexes in this reaction system provide a valuable theoretical foundation for comprehending and enhancing Ir/Cu bimetallic cooperative catalysis in alcohol deoxygenation/trifluoromethylation reactions. This provides anticipated theoretical support for future designs of more efficient and rational alcohol deoxygenation reactions.

Product State-Resolved Reactive Scattering Studies of the H + Cl2 (v0 = 1-3, j0 = 0) → HCl + Cl Reaction by the Time-Dependent Wave Packet Method.

The typical hydrogen atom plus halogen molecule reaction H + Cl2 → HCl + Cl has implications across many fields. In this paper, product state-resolved quantum dynamics calculations for the vibrationally excited reaction H + Cl2 (v0 = 1-3, j0 = 0) → HCl + Cl were conducted using the time-dependent wave packet method on a newly developed accurate potential energy surface. Numerical results indicate that the initial vibrational excitation of Cl2 does enhance the reactivity for this early barrier reaction, although less than the enhancement of the translational energy. The calculated product vibrational state-resolved integral cross sections and rate constants reveal that the product vibrational state distribution and the initial vibrational state of Cl2 are highly correlated. The thermal rate constant in the temperature range from 100 to 1000 K was given and is found to be in reasonable agreement with the experimental measurements.

A groovy laser processing route to achieving high power and energy lithium-ion batteries

3D-structured NMC622 with precisely controlled electrolyte channels were manufactured by incorporating femtosecond laser processing with conventional slurry casting. Demonstrated in a full cell for the first time, the 3D electrode structures mitigate plating and dendrite growth at the graphite electrode and lead to improved cycling performance, 75 % capacity retention vs 58 % after 500 cycles. 3D-structured NMC622 with a high areal capacity, 5.5 mAh cm−2, exhibits an areal capacity retention of ∼70 % and volumetric capacity exceeding 250 mAh cm−3 at ∼1.15C, three times and twice that of a conventional slurry-casted NMC622, respectively. The improved rate performance is attributed to the enhanced ionic transport and reduced charge transfer resistance facilitated by the 3D electrode structure, as shown through galvanostatic titration measurements. A finite element method-based 3D model illustrated the improved uniform distribution of Li-ion concentration and state of charge within the 3D-structured electrode. Additionally, the 3D electrode structure proved beneficial for wettability and accelerated electrolyte absorption, leading to improved manufacturing efficiency.

The entropy rate of Linear Additive Markov Processes.

This work derives a theoretical value for the entropy of a Linear Additive Markov Process (LAMP), an expressive but simple model able to generate sequences with a given autocorrelation structure. Our research establishes that the theoretical entropy rate of a LAMP model is equivalent to the theoretical entropy rate of the underlying first-order Markov Chain. The LAMP model captures complex relationships and long-range dependencies in data with similar expressibility to a higher-order Markov process. While a higher-order Markov process has a polynomial parameter space, a LAMP model is characterised only by a probability distribution and the transition matrix of an underlying first-order Markov Chain. This surprising result can be explained by the information balance between the additional structure imposed by the next state distribution of the LAMP model, and the additional randomness of each new transition. Understanding the entropy of the LAMP model provides a tool to model complex dependencies in data while retaining useful theoretical results. To emphasise the practical applications, we use the LAMP model to estimate the entropy rate of the LastFM, BrightKite, Wikispeedia and Reuters-21578 datasets. We compare estimates calculated using frequency probability estimates, a first-order Markov model and the LAMP model, also considering two approaches to ensure the transition matrix is irreducible. In most cases the LAMP entropy rates are lower than those of the alternatives, suggesting that LAMP model is better at accommodating structural dependencies in the processes, achieving a more accurate estimate of the true entropy.

Wavelength-Dependent Dynamics of the O(1D2) Channel in the 1Δu State Photodissociation of CO2.

The wavelength-dependent dynamics of the O(1D2) channel, formed by photoexcitation of CO2 to the 1Δu state at 143.53-153.03 nm, is investigated by using the time-sliced velocity-mapped ion imaging method. The measured ionic peaks of the O(1D2) images are analyzed to determine the total kinetic energy release (TKER) spectra and image anisotropy parameters. The structures observed in the TKER spectra can be directly assigned to the ro-vibrational state distributions of the counter CO photofragments. Compared to those observed at 157 and 155 nm, the highly rotationally excited CO photofragments still obviously appear in v = 0 and 1, but the fraction of rotational excitations is significantly reduced. Conversely, the CO photofragments exhibit substantially higher vibrational excitations, implying that the nearly linear 21A' state also contributes to dissociation in addition to the bend configuration. The image anisotropy parameters display an extremely slow decreasing trend with an increase of the CO ro-vibrational state besides those for the highest ro-vibrationally excited CO photofragments. Nevertheless, the nonaxial recoil effect, suggested in previous photodissociation studies of CO2 and other triatomic molecular systems, is still appropriate to explain the observations of internal energy dependences of image anisotropy parameters.

An investigation into the reduction mechanism of temperature-magnetic stress relief based on DO3 crystal

This study assesses a novel method proposed by the research group for reducing residual stress through temperature-magnetic stress relief (TMSR). Experimental findings indicate that this approach yields significant reductions in residual stress. Microscopic analysis reveals that following TMSR treatment, the labyrinthine domains within the material diminish while the parallel domains increase, prompting atomic migration and dislocation in regions of elevated stress. Moreover, utilizing density functional theory, this paper investigates the intrinsic strengthening mechanism of TMSR. The findings indicate that the atomic magnetic moment of the Fe3C (DO3) crystal exhibits an approximately increasing trend within a specific temperature range. This observation underscores the thermo-magnetic coupling strengthening effect inherent in the DO3 ferromagnetic crystal, which constitutes a pivotal element in the enhancement effect of TMSR. Furthermore, an examination of changes in the energy band distribution and electronic density of states at varying temperatures sheds light on the underlying cause of fluctuations in the atomic magnetic moment. The research outcomes indicate that upon surpassing a certain temperature threshold, the crystal phase undergoes changes, leading to fluctuations in the atomic magnetic moment. This study contributes novel insights aimed at enhancing comprehension of the TMSR method.

Phase-Modified Strongly Coupled δ/ε-MnO2 Homojunction Cathode for Kinetics-Enhanced Zinc-Ion Batteries.

Rechargeable Zn-MnO2 batteries using mild water electrolytes have garnered significant interest owing to their impressive theoretical energy density and eco-friendly characteristics. However, MnO2 suffers from huge structural changes during the cycles, resulting in very poor stability at high charge-discharge depths. Briefly, the above problems are caused by slow kinetic processes and the dissolution of Mn atoms in the cycles. In this paper, a 2D homojunction electrode material (δ/ε-MnO2) based on δ-MnO2 and ε-MnO2 has been prepared by a two-step electrochemical deposition method. According to the DFT calculations, the charge transfer and bonding between interfaces result in the generation of electronic states near the Fermi surface, giving δ/ε-MnO2 a more continuous distribution of electron states and better conductivity, which is conducive to the rapid insertion/extraction of Zn2+ and H+. Moreover, the strongly coupled Mn-O-Mn interfacial bond can effectively impede dissolution of Mn atoms and thus maintain the structural integrity of δ/ε-MnO2 during the cycles. Accordingly, the δ/ε-MnO2 cathode exhibits high capacity (383 mAh g-1 at 0.1 A g-1), superior rate performance (150 mAh g-1 at 5 A g-1), and excellent cycling stability over 2000 cycles (91.3% at 3 A g-1). Profoundly, this unique homojunction provides a novel paradigm for reasonable selection of different components.

State-to-state study of non-equilibrium recombination of oxygen and nitrogen molecules.

Rapidly cooled mixtures are of interest for several applications, including hypersonic flows due to the presence of strong cooling temperature gradients in regions such as hypersonic boundary layers and expanding nozzles. There have been very few studies of rapidly cooled mixtures using the high-fidelity rovibrational databases afforded by abinitio potential energy surfaces. This work makes use of existing rovibrational state-specific databases to study rapidly cooled mixtures. In particular, we seek to understand the importance of thermal non-equilibrium in recombining mixtures using both rovibrational and vibrational state-to-state methods for oxygen and nitrogen molecules. We find that although there is significant non-equilibrium during recombination, it is well captured by the vibrational state-specific approach. Finally, we compare the global recombination rate computed based on the state-specific recombination rate coefficients and the global recombination rate computed based on the time local dissociation rate coefficient, which is reversed using the principle of detailed balance. The local dissociation rate coefficient is computed by weighting the state-specific dissociation rate coefficients with the state-specific distribution of energy states. We find a large difference between these rates, highlighting a potential source of errors in hypersonic flow predictions.

Efficient Dynamic Distributed Resource Slicing in 6G Multi-Access Edge Computing Networks With Online ADMM and Message Passing Graph Neural Networks

We consider the problem of resource slicing in the 6 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> generation multi-access edge computing (6G-MEC) network. The network includes many non-stationary space-air-ground-sea nodes with dynamic, unstable connections and resources, where any node can be in one of two hidden states: i) reliable – when the node generates/propagates no data errors; ii) unreliable – when the node can generate/propagate random errors. We show that solving this problem is challenging, since it represents a non-deterministic polynomial-time (NP) hard dynamic combinatorial optimization problem depending on the unknown distribution of hidden nodes' states and time-varying parameters (connections and resources of nodes) which can only be observed locally. To tackle these challenges, we develop a new deep learning (DL) model based on the message passing graph neural network (MPNN) to estimate hidden nodes' states in dynamic network environments. We then propose a novel algorithm based on the integration of MPNN-based DL and online alternating direction method of multipliers (ADMM) – extension of the well-known classical “static” ADMM to dynamic settings, where the slicing problem is solved distributedly, in real time, based on local information. We prove that our algorithm converges to a global optimum of our problem with a superior performance even in the highly-dynamic, unreliable scenarios.

Electron Spin Polarization Engineering in Ferromagnetic Bioheterojunction for Sonotherapy of Osteomyelitis

AbstractElectron spinning polarization has garnered increased attention for its potential to enhance device properties. However, its application in life health, specifically in anti‐infection and tissue repair, remains under‐explored. In this study, a ferromagnetic heterojunction CF (Fe3O4/TiO2) is constructed with spin‐polarized electrons, demonstrating efficient antibiosis performance with ultrasound (US) assistance. The antibacterial mechanism is elucidated as follows: spin‐polarized metallic states of Fe3O4 induce an asymmetric distribution in the electron spin state of TiO2, increasing the density of states of spin‐polarized electrons near the Fermi level of CF. Under US treatment, the built‐in electric field and spin‐polarized electrons in CF synergistically suppress the recombination of sono‐activated carriers, promoting reactive oxygen species (ROS) production. Simultaneously, the bacterial membrane is influenced by the micromagnetic field induced by spin‐polarized electrons, causing a severe disturbance in the bacterial respiratory chain. The combined damage from ROS and disturbed respiratory chain results in bacterial death. Fortunately, the micromagnetic field built by CF activates specific mechanosensitive ion channels, including TREK1, Piezo1, and related pathways, enhancing osteoblast differentiation. Sonotherapy using CF exhibits an excellent therapeutic effect in treating osteomyelitis. This study provides novel insights into manipulating spin electrons for applications in life health.

Particle simulation of the confinement of the plasma blanket in the magnetic mirror

A new guiding center particle code Guiding center Mirror Simulation is developed to simulate the evolution and confinement of the axisymmetric plasma blanket in the magnetic mirror field generated by a pair of Helmholtz coils. The simulation results indicate that this plasma blanket maintains its shape throughout evolution, and the steady state distributions of both density and electrostatic potential are obtained. The correlation between the plasma density and the characteristic confinement time is also investigated. Generally, the characteristic confinement time decreases with increasing density. When the density is low enough, it is approximately the pitch angle scattering time of the trapped electrons. When the density increases, it comes to several times of the ion transit time evaluated with the Bohm velocity. These results have the potential for experimental applications.

Observation of 3D acoustic quantum Hall states

Quantum Hall effect, the quantized transport phenomenon of electrons under strong magnetic fields, remains one of the hottest research topics in condensed matter physics since its discovery in 2D electronic systems. Recently, as a great advance in the research of quantum Hall effects, the quantum Hall effect in 3D systems, despite its big challenge, has been achieved in the bulk ZrTe5 and Cd3As2 materials. Interestingly, Cd3As2 is a Weyl semimetal, and quantum Hall effect is hosted by the Fermi arc states on opposite surfaces via the Weyl nodes of the bulk, and induced by the unique edge states on the boundaries of the opposite surfaces. However, such intriguing edge state distribution has not yet been experimentally observed. Here, we aim to reveal experimentally the unusual edge states of Fermi arcs in acoustic Weyl system with the aid of pseudo-magnetic field. Benefiting from the macroscopic nature of acoustic crystals, the pseudo-magnetic field is introduced by elaborately designed the gradient on-site energy, and the edge states of Fermi arcs on the boundaries of the opposite surfaces are unambiguously demonstrated in experiments. Our system serves as an ideal and highly tunable platform to explore the Hall physics in 3D system, and has the potential in the application of new acoustic devices.

CT-based assessment of the stress state of dog spines

An urgent task of biomechanics is the study of the influence of external loads on the human musculoskeletal system, one of the main elements of which is the vertebral column. In this case, research involves considering the spine as a complex system consisting of vertebrae and the intervertebral discs that articulate them. At the moment, there are many works devoted to determining the causes of various abnormalities in the tissue fibers between the vertebrae, which leads to the development of discopathy. Dogs are the most susceptible to such changes due to their genetic predisposition. Thus, in this work, studies were carried out on the cervical spine of three animals: yorkshire terrier, russian toy terrier and half–breed. During the work, numerical modeling of samples was performed using computed tomography data. Computational experiments were carried out using the finite element method and made it possible to determine the stress state taking into account the distribution of the mechanical properties of the material. The tests corresponded to longitudinal compression of the samples. Based on the results obtained, the compressive stress field was determined, the reliability of the values was assessed according to the energy error, and the von Mises stress intensity and the rigidity of the resulting structure were calculated. Analysis of the results showed that the highest stress values are achieved between the vertebrae of the border sections of the cervical spine. On average, a sample of the Yorkshire Terrier breed is predisposed to experience greater stress compared to the results of other dogs in the experimental group. The highest rigidity corresponded to half–breed: twice as much as the average value for dwarf breeds. The distribution of the energy error showed that the areas with the highest values correspond to finite elements at the boundary between different phases of the medium. Thus, the results obtained in the framework of the study make it possible to establish the nature of the distribution of the stress state in the intervertebral discs, as well as to identify the strength indicators of the vertebral columns, taking into account the mechanical properties of various biological tissues.

Optimization Design and Experiment of a Cotton Straw-Crushing Device Based on Computational Fluid Dynamics

In order to design the structure and optimize the working parameters of a straw-crushing device, and to improve the qualified rate of straw-crushing length and the rate of straw fluidity, the influence of the airflow characteristics and pressure distribution in the working state of the crushing chamber and the different structure and working parameters of the straw-crushing device on the airflow field were studied based on the computational fluid dynamics (CFD) software Fluent 19.2. The simulation results show that by changing the rotation speed of the cutter shaft, the negative pressure and mass flow rate of the inlet surface of the flow field reach the maximum values of 63.6 Pa and 1.64 kg/s, respectively, when the rotation speed of the cutter shaft is 2000 rpm, which proves that the rotation speed of the cutter shaft increases, and the feeding performance also increases. In the case of 0, 8 and 16 air knives, the peak flow velocity in the crushing chamber is 43.1 m/s, 50.1 m/s and 54.48 m/s, respectively, and the airflow in the crushing chamber is improved to a certain extent, which proves the feasibility of the air knives’ structure. In order to verify the simulation results, a field experiment was carried out. The results showed that the qualified rate of straw crushing was 94.13% and the drop rate was 4.26% under the conditions of a cutter shaft speed of 1800 rpm, a machine forward speed of 6 km/h and a height of 80 mm of the cutter off the ground. The field experiment and simulation show that the qualified rate of crushing increases with the increase in the rotation speed of the cutter shaft, but the increase rate slows down, and the random speed decreases. The drop rate decreases with the increase in tool height and tool speed. The air knife structure improves the crushing qualification rate and significantly reduces the drop rate, which verifies the simulation accuracy. This study provides a theoretical basis for the optimization of straw-crushing devices.

Application of a metallic-magnetic calorimeter for high-resolution x-ray spectroscopy of Fe at an EBIT

In this work, we present an experiment conducted at the S-EBIT-I ion trap of GSI. It involved the study of ion-electron collisions of Fe and Ba ions in various charge states with the electron beam. Characteristic x-ray radiation emitted during the continuous interaction was recorded utilizing an energy-dispersive maXs-30 detector based on metallic-magnetic calorimeter (MMC) technology. Optimizations to the applied sensitivity-drift correction and energy calibration procedures significantly improved the achieved energy resolution compared to previous applications of a similar detector. This made it possible to individually resolve and identify overlapping x-ray lines of iron and barium in a wide spectral range. As a demonstration of the outstanding detector performance, we used the recorded spectral data to extract an estimate of the charge state distribution of Fe ions in the trap. This experiment campaign marks an important milestone in the ongoing effort to enable the deployment of MMC detectors for future high-precision measurements in fundamental physics experiments.

Novel intelligent blind information reconciliation for LDPC codes in quantum key distribution systems

Information reconciliation is an important step in quantum key distribution (QKD). As a good channel coding technology, LDPC (low-density parity-check) code perform well in information reconciliation. In this paper, we investigate a new approach, namely blind information reconciliation. In our approach, after the state distribution is carried out by Alice and the measurements are taken by Bob, Alice can select an appropriate LDPC encoder (parity-check matrix) from the predefined candidate pool according to the estimated QBER (quantum bit-error-rate). Bob can use the expectation–maximization (EM) estimator and the maximum average log-likelihood ratio (LLR) detector to blindly identify parity-check matrices associated with not only different code-rates but also different codeword-lengths Alice employed. Moreover, puncturing and shortening can also be invoked to adjust the code-rate slightly to improve the error-correction performance. Monte Carlo simulations have demonstrated that our proposed new blind information-reconciliation scheme can successfully identify the parity-check matrix even under high QBER conditions, reduce the interactive communication-rounds, and improve the reconciliation efficiency in comparison with the conventional rate-adaptive LDPC coding scheme without QBER estimation.

No Prior Mask: Eliminate Redundant Action for Deep Reinforcement Learning

The large action space is one fundamental obstacle to deploying Reinforcement Learning methods in the real world. The numerous redundant actions will cause the agents to make repeated or invalid attempts, even leading to task failure. Although current algorithms conduct some initial explorations for this issue, they either suffer from rule-based systems or depend on expert demonstrations, which significantly limits their applicability in many real-world settings. In this work, we examine the theoretical analysis of what action can be eliminated in policy optimization and propose a novel redundant action filtering mechanism. Unlike other works, our method constructs the similarity factor by estimating the distance between the state distributions, which requires no prior knowledge. In addition, we combine the modified inverse model to avoid extensive computation in high-dimensional state space. We reveal the underlying structure of action spaces and propose a simple yet efficient redundant action filtering mechanism named No Prior Mask (NPM) based on the above techniques. We show the superior performance of our method by conducting extensive experiments on high-dimensional, pixel-input, and stochastic problems with various action redundancy tasks. Our code is public online at https://github.com/zhongdy15/npm.

Optically and electrically controlled switchers and electron beam splitters based on topological edge states

Recently, topological edge states have attracted rapid attention for designing low-power consumption electronics due to their topological protection and suppression of backscattering. We study the transport properties of inner and outer edge states in a three-terminal device composed of hybrid zigzag graphene nanoribbons based on our derived formulas of local bond current and transmission coefficient with the wave-function matching technique. Particularly, by electrically modulating inner edge state in the conductor region, the valley current can be flipped as the charge current that is switched into one lead or split into two transmitted leads, leading to the charge switchers and electron beam splitters when the incident lead and transmitted leads are set as antichiral inner edge state and chiral edge states, respectively. Furthermore, when three leads are both modulated as antichiral inner edge state by the spatially varying off-resonant circularly polarized (ORCP) light, the charge switchers and electron beam splitters are accordingly converted into the valley switchers and electron beam splitters. The behavior of the switchers and splitters originates from the cooperative effects of the lager wave-vector mismatch between different valleys, and the distributions of lateral and vertical inner edge states. Moreover, the proposed devices could be cut off by the staggered electric field due to the gap effect, and are robust against the edge magnetism and the spin-orbit coupling. These findings are expected to apply for optically and electrically controlled topological devices.

Fatigue life prediction of notched components under size effect based on strain energy density gradient

AbstractIn practical mechanical components, the characteristic of geometric discontinuous generates non‐uniform energy field near the notch, which affects the local damage evolution process of the notched specimens. Therefore, it is particularly crucial to formulate a parameter that can characterize such inhomogeneous state distribution. First, a strain energy density gradient factor is introduced to describe the complexity of strain energy density distribution near the notch. Meanwhile, a size effect factor is given considering the strain energy gradient factor and notch geometry parameter. Then, taking into account the impact of phase difference, a direct damage parameter considering non‐proportionality of different multiaxial load levels is developed. Furtherly, the modified strain energy density parameter is determined. Finally, the comparison between the proposed model and the other three models emphasizes the advantages of the model.

Accelerate Multi-Agent Reinforcement Learning in Zero-Sum Games with Subgame Curriculum Learning

Learning Nash equilibrium (NE) in complex zero-sum games with multi-agent reinforcement learning (MARL) can be extremely computationally expensive. Curriculum learning is an effective way to accelerate learning, but an under-explored dimension for generating a curriculum is the difficulty-to-learn of the subgames –games induced by starting from a specific state. In this work, we present a novel subgame curriculum learning framework for zero-sum games. It adopts an adaptive initial state distribution by resetting agents to some previously visited states where they can quickly learn to improve performance. Building upon this framework, we derive a subgame selection metric that approximates the squared distance to NE values and further adopt a particle-based state sampler for subgame generation. Integrating these techniques leads to our new algorithm, Subgame Automatic Curriculum Learning (SACL), which is a realization of the subgame curriculum learning framework. SACL can be combined with any MARL algorithm such as MAPPO. Experiments in the particle-world environment and Google Research Football environment show SACL produces much stronger policies than baselines. In the challenging hide-and-seek quadrant environment, SACL produces all four emergent stages and uses only half the samples of MAPPO with self-play. The project website is at https://sites.google.com/view/sacl-neurips.