Morphology and valence state evolution of Cu:Unraveling the impact on nitric oxide electroreduction

Ammonia(NH3)serves as a critical component in the fertilizer industry and fume gas denitrification.However,the conventional NH3production process,namely the Haber-Bosch process,leads to considerable energy consumption and waste gas emissions.To address this,electrocatalytic nitric oxide reduction reaction(NORR)has emerged as a promising strategy to bridge NH3consumption to NH3production,harnessing renewable electricity for a sustainable future.Copper(Cu)stands out as a prominent electrocatalyst for NO reduction,given its exceptional NH3yield and selectivity.However,a crucial aspect that remains insufficiently explored is the effects of morphology and valence states of Cu on the NORR performance.In this investigation,we synthesized CuO nanowires(CuO-NF)and Cu nanocubes(Cu-NF)as cathodes through an in situ growth method.Remarkably,CuO-NF exhibited an impressive NH3yield of 0.50±0.02 mg cm^(-2)h^(-1)at-0.6 V vs.reversible hydrogen electrode(RHE)with faradaic efficiency of29,68%±1,35%,surpassing that of Cu-NF(0.17±0.01 mg cm^(-2)h^(-1),16.18%±1.40%).Throughout the electroreduction process,secondary cubes were generated on the CuO-NF surface,preserving their nanosheet cluster morphology,sustained by an abundant supply of subsurface oxygen(s-O)even after an extended duration of 10 h,until s-O depletion ensued.Conversely,Cu-NF exhibited inadequate s-O content,leading to rapid crystal collapse within the same timeframe.The distinctive current-potential relationship,akin to a volcano-type curve,was attributed to distinct NO hydrogenation mechanisms.Further Tafel analysis revealed the exchange current density(i0)and standard heterogeneous rate constant(k0)for CuO-NF,yielding 3.44×10^(-6)A cm^(-2)and 3.77×10^(-6)cm^(-2)s^(-1)when NORR was driven by overpotentials.These findings revealed the potential of CuO-NF for NO reduction and provided insights into the intricate interplay between crystal morphology,valence states,and electrochemical performance.

Modeling time-dependent mechanical behavior of hard rock considering excavation-induced damage and complex 3D stress states

To investigate the long-term stability of deep rocks,a three-dimensional(3D)time-dependent model that accounts for excavation-induced damage and complex stress state is developed.This model comprises three main components:a 3D viscoplastic isotropic constitutive relation that considers excavation damage and complex stress state,a quantitative relationship between critical irreversible deformation and complex stress state,and evolution characteristics of strength parameters.The proposed model is implemented in a self-developed numerical code,i.e.CASRock.The reliability of the model is validated through experiments.It is indicated that the time-dependent fracturing potential index(xTFPI)at a given time during the attenuation creep stage shows a negative correlation with the extent of excavationinduced damage.The time-dependent fracturing process of rock demonstrates a distinct interval effect of the intermediate principal stress,thereby highlighting the 3D stress-dependent characteristic of the model.Finally,the influence of excavation-induced damage and intermediate principal stress on the time-dependent fracturing characteristics of the surrounding rocks around the tunnel is discussed.

Empowering neuromorphic computing with topological states

In 1980,scientist Klaus von Klitzing discovered the quantum Hall effect[1],a groundbreaking achievement that earned him the Nobel Prize in Physics in 1985.This discovery was a significant milestone in condensed matter physics,representing the first identification of topological quantum states.

Comparative Study of the Socioeconomic Characteristics and Digital Literacy Level of Agricultural Extension Personnel in Imo and Ebonyi States, South-East, Nigeria

The study comparatively analysed the socioeconomic characteristics and digital literacy level of Agricultural Extension personnel (AEP) in Ebonyi and Imo States, South-East, Nigeria. The specific objectives were to describe the socioeconomic characteristics of agricultural extension personnel in Ebonyi and Imo States, and to ascertain the digital literacy level of AEP in the studied states. Purposive sampling technique was used to select 312 Agricultural Extension personnel (132 from Ebonyi State Agricultural Development Program and 180 from Imo State Agricultural Development Program) for the study. Data were collected through the use of validated and structured questionnaire, and administered through the help of well-trained enumerators. Data were analysed using simple descriptive statistical tools such as percentages mean score, standard deviation and weighted mean. Findings indicated that they were more male in the both States (55.3% and 57.8%) for Ebonyi and Imo State respectively and that the average age of AEP in Ebonyi and Imo States were 44.7 years and 49.2 years respectively. It was further revealed that the majority (77.3% and 82.8%) had B.Sc./HND as their highest academic qualifications, belonged to professional organisations (62.1% and 75%), and were earning an average monthly income of N58,798 and N62,648 for Ebonyi and Imo State respectively. Also, it was revealed that their mean years of service were 12.4 years and 13.4 years for Ebonyi and Imo State respectively. Almost all of them (87.9% and 95.0%) own a smartphone, had access to the internet (80.3% and 90.0%), but do not own a laptop/ipad (82.6% and 72.8%) for Ebon-yi and Imo State respectively. Results further revealed that Agricultural extension personnel in both Ebonyi and Imo State respectively had low digital literacy level ( = 2.41 and 2.32). The study concluded that AEP in Ebonyi and Imo State respectively had similar socioeconomic characteristics and low level of digital literacy. The study recommended that the management of ADPs in both Ebonyi and Imo State should ensure the training of AEP in digital skills to enhance their digital literacy level to enable them use digital technologies in their work.

Microenvironment and electronic state modulation of Pd nanoparticles within MOFs for enhancing low-temperature activity towards DCPD hydrogenation

Precise control of the local environment and electronic state of the guest is an important method of controlling catalytic activity and reaction pathways.In this paper,guest Pd NPs were introduced into a series of host UiO-67 MOFs with different functional ligands and metal nodes,the microenvironment and local electronic structure of Pd is modulated by introducing bipyridine groups and changing metal nodes(Ce_(6)O_(6) or Zr_(6)O_(6)).The bipyridine groups not only promoted the dispersion Pd NPs,but also facilitated electron transfer between Pd and UiO-67 MOFs through the formation of Pd-N bridges.Compared with Zr6 clusters,the tunability and orbital hybridisation of the 4f electronic structure in the Ce_(6) clusters modulate the electronic structure of Pd through the construction of the Ce-O-Pd interfaces.The optimal catalyst Pd/UiO-67(Ce)-bpy presented excellent low-temperature activity towards dicyclopentadiene hydrogenation with a conversion of>99% and a selectivity of>99%(50℃,10 bar).The results show that the synergy of Ce-O-Pd and Pd-N promotes the formation of active Pd^(δ+),which not only enhances the adsorption of H_(2) and electron-rich C=C bonds,but also contributes to the reduction of proton migration distance and improves proton utilization efficiency.These results provide valuable insights for investigating the regulatory role of the host MOFs,the nature of host-guest interactions,and their correlation with catalytic performance.

Spectroscopy and molecule opacity investigation on excited states of SiS

The SiS molecule,which plays a significant role in space,has attracted a great deal of attention for many years.Due to complex interactions among its low-lying electronic states,precise information regarding the molecular structure of SiS is limited.To obtain accurate information about the structure of its excited states,the high-precision multireference configuration interaction(MRCI)method has been utilized.This method is used to calculate the potential energy curves(PECs)of the 18Λ–S states corresponding to the lowest dissociation limit of SiS.The core–valence correlation effect,Davidson’s correction and the scalar relativistic effect are also included to guarantee the precision of the MRCI calculation.Based on the calculated PECs,the spectroscopic constants of quasi-bound and bound electronic states are calculated and they are in accordance with previous experimental results.The transition dipole moments(TDMs)and dipole moments(DMs)are determined by the MRCI method.In addition,the abrupt variations of the DMs for the 1^(5)Σ^(+)and 2^(5)Σ^(+)states at the avoided crossing point are attributed to the variation of the electronic configuration.The opacity of SiS at a pressure of 100 atms is presented across a series of temperatures.With increasing temperature,the expanding population of excited states blurs the band boundaries.

Observation of flat-band localized state in a one-dimensional diamond momentum lattice of ultracold atoms

We investigated the one-dimensional diamond ladder in the momentum lattice platform. By inducing multiple twoand four-photon Bragg scatterings among specific momentum states, we achieved a flat band system based on the diamond model, precisely controlling the coupling strength and phase between individual lattice sites. Utilizing two lattice sites couplings, we generated a compact localized state associated with the flat band, which remained localized throughout the entire time evolution. We successfully realized the continuous shift of flat bands by adjusting the corresponding nearest neighbor hopping strength, enabling us to observe the complete localization process. This opens avenues for further exploration of more complex properties within flat-band systems, including investigating the robustness of flat-band localized states in disordered flat-band systems and exploring many-body localization in interacting flat-band systems.

Entanglement and Volume Monogamy Features of Permutation Symmetric N-Qubit Pure States with N-Distinct Spinors: GHZ and States

We explore the entanglement features of pure symmetric N-qubit states characterized by N-distinct spinors with a particular focus on the Greenberger-Horne-Zeilinger (GHZ) states and , an equal superposition of W and obverse W states. Along with a comparison of pairwise entanglement and monogamy properties, we explore the geometric information contained in them by constructing their canonical steering ellipsoids. We obtain the volume monogamy relations satisfied by states as a function of number of qubits and compare with the maximal monogamy property of GHZ states.

Cybersecurity Landscape on Remote State Estimation:A Comprehensive Review

Cyber-physical systems(CPSs)have emerged as an essential area of research in the last decade,providing a new paradigm for the integration of computational and physical units in modern control systems.Remote state estimation(RSE)is an indispensable functional module of CPSs.Recently,it has been demonstrated that malicious agents can manipulate data packets transmitted through unreliable channels of RSE,leading to severe estimation performance degradation.This paper aims to present an overview of recent advances in cyber-attacks and defensive countermeasures,with a specific focus on integrity attacks against RSE.Firstly,two representative frameworks for the synthesis of optimal deception attacks with various performance metrics and stealthiness constraints are discussed,which provide a deeper insight into the vulnerabilities of RSE.Secondly,a detailed review of typical attack detection and resilient estimation algorithms is included,illustrating the latest defensive measures safeguarding RSE from adversaries.Thirdly,some prevalent attacks impairing the confidentiality and data availability of RSE are examined from both attackers'and defenders'perspectives.Finally,several challenges and open problems are presented to inspire further exploration and future research in this field.

Modulation of Electronic States in Bimetallic-doped Nitrogen-Carbon Based Nanoparticles for Enhanced Oxygen Reduction Kinetics

Controlling the local electronic structure of active ingredients to improve the adsorption desorption characteristics of oxygen-containing intermediates over the electrochemical liquid-solid interfaces is a critical challenge in the field of oxygen reduction reaction(ORR)catalysis.Here,we offer a simple approach for modulating the electronic states of metal nanocrystals by bimetal co-doping into carbon-nitrogen substrate,allowing us to modulate the electronic structure of catalytic active centers.To test our strategy,we designed a typical bimetallic nanoparticle catalyst(Fe-Co NP/NC)to flexibly alter the reaction kinetics of ORR.Our results from synchrotron Xray absorption spectroscopy and X-ray photoelectron spectroscopy showed that the co-doping of iron and cobalt could optimize the intrinsic charge distribution of Fe-Co NP/NC catalyst,promoting the oxygen reduction kinetics and ultimately achieving remarkable ORR activity.Consequently,the carefully designed Fe-Co NP/NC exhibits an ultra-high kinetic current density at the operating voltage(71.94 mA/cm^(2)at 0.80 V),and the half-wave potential achieves 0.915 V,which is obviously better than that of the corresponding controls including Fe NP/NC,Co NP/NC.Our findings provide a unique perspective for optimizing the electronic structure of active centers to achieve higher ORR catalytic activity and faster kinetics.

Abnormal State Detection in Lithium-ion Battery Using Dynamic Frequency Memory and Correlation Attention LSTM Autoencoder

This paper addresses the challenge of identifying abnormal states in Lithium-ion Battery(LiB)time series data.As the energy sector increasingly focuses on integrating distributed energy resources,Virtual Power Plants(VPP)have become a vital new framework for energy management.LiBs are key in this context,owing to their high-efficiency energy storage capabilities essential for VPP operations.However,LiBs are prone to various abnormal states like overcharging,over-discharging,and internal short circuits,which impede power transmission efficiency.Traditional methods for detecting such abnormalities in LiB are too broad and lack precision for the dynamic and irregular nature of LiB data.In response,we introduce an innovative method:a Long Short-Term Memory(LSTM)autoencoder based on Dynamic Frequency Memory and Correlation Attention(DFMCA-LSTM-AE).This unsupervised,end-to-end approach is specifically designed for dynamically monitoring abnormal states in LiB data.The method starts with a Dynamic Frequency Fourier Transform module,which dynamically captures the frequency characteristics of time series data across three scales,incorporating a memory mechanism to reduce overgeneralization of abnormal frequencies.This is followed by integrating LSTM into both the encoder and decoder,enabling the model to effectively encode and decode the temporal relationships in the time series.Empirical tests on a real-world LiB dataset demonstrate that DFMCA-LSTM-AE outperforms existing models,achieving an average Area Under the Curve(AUC)of 90.73%and an F1 score of 83.83%.These results mark significant improvements over existing models,ranging from 2.4%–45.3%for AUC and 1.6%–28.9%for F1 score,showcasing the model’s enhanced accuracy and reliability in detecting abnormal states in LiB data.

Maternal Mortality Rates among Im/Migrant Populations in the United States

Introduction: Maternal mortality rates have more than doubled in the U.S over the last two decades, making it one of the few places in the world where maternal mortality is increasing. Differences in maternal mortality among certain races and ethnicities are known but few studies examine maternal mortality among immigrants. Since immigrants represent 13.7% of the U.S. population, it is essential to examine immigrant subsets to understand maternal mortality among this vulnerable population. Methods: A literature search identified 318 articles on maternal mortality and immigrants, with 12 articles from the U.S. The keywords included maternal mortality, United States, migrants, asylum seekers, immigrants, and disparities. Maternal mortality statistics were obtained from the World Health Organization and Center for Disease Control. Results: Studies analyzed in this review found an overall lower maternal mortality rate among immigrant women compared to U.S.-born women, except for Hispanic immigrant women. Black women had the highest maternal mortality rate, regardless of immigration status. Conclusion: Although the literature points to lower maternal mortality among immigrants, the data is still somewhat mixed, making it challenging to draw comprehensive conclusions. Additional research examining maternal mortality among Im/migrants in the U.S. is needed to guide future training among healthcare professionals and policymakers.

Interface state-based bound states in continuum and below-continuum-resonance modes with high-Q factors in the rotational periodic system

We have introduced a new approach to calculate the orbital angular momentum(OAM)of bound states in continuum(BICs)and below-continuum-resonance(BCR)modes in the rotational periodic system nested inside and outside by transforming the Bloch wave number from the translational periodic system.We extensively classify and study these BICs and BCR modes,which exhibit high-quality(high-Q)factors,in different regions relative to the interface of the system.These BICs and BCR modes with a high-Q factor have been studied in detail based on distinctive structural parameters and scattering theory.The outcomes of this research break the periodic limitation of interface state-based BICs,and realize more and higher symmetry interface state-based BICs and BCR modes.Moreover,we can control the region where light is captured by adjusting the frequency,and show that the Q factor of BICs is more closely related to the ordinal number of rings and the rotational symmetry number of the system.

Key Issues for Modelling, Operation, Management and Diagnosis of Lithium Batteries: Current States and Prospects

1 Introduction.With the continuous growth of the global population,the energy demand continues to increase.However,due to the dominance of fossil fuels in global energy and fossil fuels are non-renewable,it has led to the global energy crisis[1].Besides,the use of fossil fuels will generate a mass of air pollutants(e.g.,carbon dioxide,sulfur dioxide,etc.),which will cause serious environmental pollution,climate change[2],etc.To resolve the aforementioned issues,countries around the world have implemented a variety of measures hoping to fundamentally adjust the global energy structure and achieve sustainable development.Thereinto,“Paris Agreement”reached in 2015 under the framework of“United Nations Framework Convention on Climate Change”aims to control the increase in the average temperature of the globe to within 2°C below preindustrial levels,and thereafter to peak global greenhouse gas emissions as soon as possible,continuously decreasing thereafter[3].United Kingdom plans to reduce the average exhaust emissions of“new cars”to approximately 50–70 g/km by 20230,which is roughly half of what it is now[4].In addition,China proposed a plan at“United Nations General Assembly”in 2020 to peak carbon dioxide emissions by 2030 and strive to achieve carbon neutrality by 2060.It is a fact that the whole world is committed to changing the current energy structure,protecting the Earth’s ecology,and achieving global sustainable development[5].

Protected simultaneous quantum remote state preparation scheme by weak and reversal measurements in noisy environments

We discuss a quantum remote state preparation protocol by which two parties, Alice and Candy, prepare a single-qubit and a two-qubit state, respectively, at the site of the receiver Bob. The single-qubit state is known to Alice while the two-qubit state which is a non-maximally entangled Bell state is known to Candy. The three parties are connected through a single entangled state which acts as a quantum channel. We first describe the protocol in the ideal case when the entangled channel under use is in a pure state. After that, we consider the effect of amplitude damping(AD) noise on the quantum channel and describe the protocol executed through the noisy channel. The decrement of the fidelity is shown to occur with the increment in the noise parameter. This is shown by numerical computation in specific examples of the states to be created. Finally, we show that it is possible to maintain the label of fidelity to some extent and hence to decrease the effect of noise by the application of weak and reversal measurements. We also present a scheme for the generation of the five-qubit entangled resource which we require as a quantum channel. The generation scheme is run on the IBMQ platform.

Research on Transmission Line Tower Tilting and Foundation State Monitoring Technology Based onMulti-Sensor Cooperative Detection and Correction

The transmission line tower will be affected by bad weather and artificial subsidence caused by the foundation and other factors in the power transmission.The tower’s tilt and severe deformation will cause the building to collapse.Many small changes caused the tower’s collapse,but the early staff often could not intuitively notice the changes in the tower’s state.In the current tower online monitoring system,terminal equipment often needs to replace batteries frequently due to premature exhaustion of power.According to the need for real-time measurement of power line tower,this research designed a real-time monitoring device monitoring the transmission tower attitude tilting and foundation state based on the inertial sensor,the acceleration of 3 axis inertial sensor and angular velocity raw data to pole average filtering pre-processing,and then through the complementary filtering algorithm for comprehensive calculation of tilt angle,the system meets the demand for inclined online monitoring of power line poles and towers regarding measurement accuracy,with low cost and power consumption.The optimization multi-sensor cooperative detection and correction measured tilt angle result relative accuracy can reach 1.03%,which has specific promotion and application value since the system has the advantages of unattended and efficient calculation.

State-of-health estimation for fast-charging lithium-ion batteries based on a short charge curve using graph convolutional and long short-term memory networks

A fast-charging policy is widely employed to alleviate the inconvenience caused by the extended charging time of electric vehicles. However, fast charging exacerbates battery degradation and shortens battery lifespan. In addition, there is still a lack of tailored health estimations for fast-charging batteries;most existing methods are applicable at lower charging rates. This paper proposes a novel method for estimating the health of lithium-ion batteries, which is tailored for multi-stage constant current-constant voltage fast-charging policies. Initially, short charging segments are extracted by monitoring current switches,followed by deriving voltage sequences using interpolation techniques. Subsequently, a graph generation layer is used to transform the voltage sequence into graphical data. Furthermore, the integration of a graph convolution network with a long short-term memory network enables the extraction of information related to inter-node message transmission, capturing the key local and temporal features during the battery degradation process. Finally, this method is confirmed by utilizing aging data from 185 cells and 81 distinct fast-charging policies. The 4-minute charging duration achieves a balance between high accuracy in estimating battery state of health and low data requirements, with mean absolute errors and root mean square errors of 0.34% and 0.66%, respectively.

Modified filter for mean elements estimation with state jumping

To investigate the real-time mean orbital elements(MOEs)estimation problem under the influence of state jumping caused by non-fatal spacecraft collision or protective orbit trans-fer,a modified augmented square-root unscented Kalman filter(MASUKF)is proposed.The MASUKF is composed of sigma points calculation,time update,modified state jumping detec-tion,and measurement update.Compared with the filters used in the existing literature on MOEs estimation,it has three main characteristics.Firstly,the state vector is augmented from six to nine by the added thrust acceleration terms,which makes the fil-ter additionally give the state-jumping-thrust-acceleration esti-mation.Secondly,the normalized innovation is used for state jumping detection to set detection threshold concisely and make the filter detect various state jumping with low latency.Thirdly,when sate jumping is detected,the covariance matrix inflation will be done,and then an extra time update process will be con-ducted at this time instance before measurement update.In this way,the relatively large estimation error at the detection moment can significantly decrease.Finally,typical simulations are per-formed to illustrated the effectiveness of the method.

Wigner function of optical cumulant operator and its dissipation in thermo-entangled state representation

To conveniently calculate the Wigner function of the optical cumulant operator and its dissipation evolution in a thermal environment, in this paper, the thermo-entangled state representation is introduced to derive the general evolution formula of the Wigner function, and its relation to Weyl correspondence is also discussed. The method of integration within the ordered product of operators is essential to our discussion.

Modified DS np Chart Using Generalized Multiple Dependent State Sampling under Time Truncated Life Test

This study presents the design of a modified attributed control chart based on a double sampling(DS)np chart applied in combination with generalized multiple dependent state(GMDS)sampling to monitor the mean life of the product based on the time truncated life test employing theWeibull distribution.The control chart developed supports the examination of the mean lifespan variation for a particular product in the process of manufacturing.Three control limit levels are used:the warning control limit,inner control limit,and outer control limit.Together,they enhance the capability for variation detection.A genetic algorithm can be used for optimization during the in-control process,whereby the optimal parameters can be established for the proposed control chart.The control chart performance is assessed using the average run length,while the influence of the model parameters upon the control chart solution is assessed via sensitivity analysis based on an orthogonal experimental design withmultiple linear regression.A comparative study was conducted based on the out-of-control average run length,in which the developed control chart offered greater sensitivity in the detection of process shifts while making use of smaller samples on average than is the case for existing control charts.Finally,to exhibit the utility of the developed control chart,this paper presents its application using simulated data with parameters drawn from the real set of data.