Evolutionary Models Research Articles

Evolutionary game analysis on cross-border cooperative R&D of intelligent new energy vehicle industry

PurposeIntelligent new energy vehicles (INEVs) are becoming the competitive hotspot for the automobile industry. The major purpose of this study is to determine how to increase innovation efficiency through knowledge sharing and technology spill between new energy vehicle (NEV) enterprises and technology enterprises. This will help to improve the core competence of the automobile industry in China. Also, it serves as a guide for the growth of other strategic.Design/methodology/approachThe authors construct a tripartite evolutionary game model to study the cross-border cooperative innovation problem. Firstly, the payment matrix of NEV enterprise, technology enterprise and government is established, and the expected revenue of each participant is determined. Then, the replication dynamic equations and evolutionary stability strategies are analyzed. Finally, the theoretical research is validated through numerical simulation.FindingsResults showed that: (1) An optimal range of revenue distribution coefficient exists in the cross-border cooperation. (2) Factors like research and development (R&D) success rate, subsidies, resource and technology complementarity, and vehicles intelligence positively influence the evolution towards cooperative strategies. (3) Factors like technology spillover risk cost inhibit the evolution towards cooperative strategies. To be specific, when the technology spillover risk cost is greater than 2.5, two enterprises are inclined to choose independent R&D, and the government chooses to provide subsidy.Research limitations/implicationsThe research perspective and theoretical analysis are helpful to further explore the cross-border cooperation of the intelligent automobile industry. The findings suggest that the government can optimize the subsidy policy according to the R&D capability and resource allocation of automobile industry. Moreover, measures are needed to reduce the risk of technology spillovers to encourage enterprise to collaborate and innovate. The results can provide reference for enterprises’ strategic choice and government’s policy making.Originality/valueThe INEV industry has become an important development direction of the global automobile industry. However, there is limited research on cross-border cooperation of INEV industry. Hence, authors construct a tripartite evolutionary game model involving NEV enterprise, technology enterprise and the government, and explore the relationship of cooperation and competition among players in the INEV industry, which provides a new perspective for the development of the INEV industry.

Are early-type galaxies quenched by present-day environment? A study of dwarfs in the Fornax Cluster.

Galaxies undergo numerous transformative processes throughout their lifetimes that ultimately lead to the expulsion of gas and the cessation of star-forming activity. This phenomenon is commonly known as quenching, and in this study, we delve into the possibility that this process is caused by the environmental processes associated with the surrounding cluster. To this end, we used the results of our previous paper ---where we analyzed dwarf galaxies in the survey together with massive galaxies from the survey--- to compute the quenching time of each galaxy and compare it with the infall time into the cluster. Using as an approximation of the quenching time and deriving the infall time from phase-space models, we determined the probability of the quenching being produced by the local environment of galaxies. Our results reveal a relation between galaxy mass and quenching probability. Massive galaxies, down to exhibit a low, almost zero probability of quenching, suggesting their independence of environmental effects. As we move into the mass regime of dwarf galaxies, the probability increases with decreasing mass, highlighting their sensitivity to environmental quenching. For dwarfs, 36pm 9<!PCT!> of our observational data are consistent with this hypothesis, challenging the idea that the present-day cluster, Fornax, is the primary driver of quenching in the low-mass galaxies of our sample with stellar mass from to To further investigate the importance of environmental processes, we compared these results with cosmological simulations, selecting galaxies under similar conditions to our observational sample. Remarkably, the simulated sample shows lower quenching probabilities as we move down in mass, and barely 5pm 1<!PCT!> of galaxies meet the quenching criteria. This discrepancy between observations and simulations underlines the fact that the modelling of quenching is still in its infancy. In general, the number of observed galaxies quenched by their environment is lower than expected, which suggests that preprocessing plays a larger role in galaxy evolution. Ultimately, our results highlight the need for higher-quality simulations and refinement of galaxy formation and evolution models.

A diffuse interface model of tumour evolution under a finite elastic confinement

A diffuse interface model of tumour evolution under a finite elastic confinement

Constraints on PDS 70 b and c from the dust continuum emission of the circumplanetary discs considering in situ dust evolution

The young T Tauri star PDS 70 has two gas accreting planets sharing one large gap in a pre-transitional disc. Dust continuum emission from PDS 70 c has been detected by Atacama Large Millimeter/submillimeter Array (ALMA) Band 7, considered as the evidence of a circumplanetary disc. However, there has been no detection of the dust emission from the CPD of PDS 70 b. We constrain the planet mass and the gas accretion rate of the planets by introducing a model of dust evolution in the CPDs and reproducing the detection and non-detection of the dust emission. We first develop a 1D steady gas disc model of the CPDs reflecting the planet properties. We then calculate the radial distribution of the dust profiles considering the dust evolution in the gas disc and calculate the total flux density of dust thermal emission from the CPDs. We find positive correlations between the flux density of dust emission and three planet properties, the planet mass, gas accretion rate, and their product called `MMdot'. We then find that the MMdot of PDS 70 c is $ M_ J yr $, corresponding to the planet mass of $ J $ and the gas accretion rate of $ M_ J yr $. This is the first case to succeed in obtaining constraints on planet properties from the flux density of dust continuum emission from a CPD. We also find some loose constraints on the properties of PDS 70 b from the non-detection of its dust emission. We propose possible scenarios for PDS 70 b and c explaining the non-detection respectively detection of the dust emission from their CPDs. The first explanation is that planet c has larger planet mass, larger gas accretion rate, or both than planet b. The other possibility is that the CPD of planet c has a larger amount of dust supply, weaker turbulence, or both than that of planet b. If the dust supply to planet c is larger than b due to its closeness to the outer dust ring, it is also quantitatively consistent with that planet c has weaker Halpha line emission than planet b considering the dust extinction effect.

Research on triple helix innovation behaviour selection and influencing factors in innovation ecosystem

ABSTRACT The innovation ecosystem is the relatively stable state that constitutes the behavioural game of the main body, and the triple helix is the key to construct the innovation ecosystem. This paper explores the interactions between the triple helix in the innovation ecosystem by constructing an evolutionary game model to clarify their innovation behaviour choices and influencing factors. And further analyse the interaction regulations between subjects through parametric simulation. Based on the results of game modelling, the behavioural strategies are proposed to maintain the effective operation of the innovation ecosystem under the stable state of the three parties’ evolution. This research idea has a wide application in exploring the relationship between different subjects in the innovation ecosystem, providing theoretical and practical guidance for the choice of the innovation behaviour of government, enterprises, and universities in the innovation ecosystem.

The Impact of the Industrial Internet on the Innovation and Development Level of China’s Manufacturing Industry: Under the Perspective of Government Incentives

In the era of the digital economy, it has become an inevitable trend for manufacturing enterprises to establish industrial Internet platforms toward achieving transformation and innovative development. However, the current development model of industrial Internet platforms is still imperfect, wherein the application scenario is complex, the investment cost is too high, the return-on-investment cycle is too long, and other factors have hindered the willingness of manufacturing enterprises to employ cloud services and capital investment. For this reason, governments have introduced a series of relevant incentive policies to promote the development of industrial Internet platforms and the transformation and upgrading of manufacturing enterprises. Considering the role of government incentives, this study first constructs an evolutionary game model with local governments, manufacturing enterprises, and industrial Internet platforms as the main players. Then, the dynamic change process of each game player’s strategy choice and the stable state of the system evolution under multiple scenarios are analyzed, and the validity of the conclusions is verified through a numerical simulation analysis. Finally, the statistical data of 28 provinces in China from 2018 to 2020 are used to conduct an empirical test to explore the impact of the industrial Internet on the transformation and innovation development of the manufacturing industry and the role of government incentives. The results show that the development of the industrial Internet has a significant role in promoting the innovation and development of the manufacturing industry; government incentives can promote the innovation and development of the industrial Internet and manufacturing industry, but incentives should not be too generous; and the impact of developing the industrial Internet on the level of innovation input/output of the manufacturing industry shows obvious regional differences. This study takes the local government as an independent game participant into consideration, which enriches the research field of combining evolutionary game theory with the transformation and innovative development of the manufacturing industry. In addition, this study provides theoretical guidance and practical references for the government to formulate incentive policies to promote the development of industrial Internet platforms and for manufacturing enterprises to utilize these platforms to carry out innovation and perform upgrades.

Semi-supervised few-shot class-incremental learning based on dynamic topology evolution

Incremental learning of new classes is crucial to developing real-world artificial intelligence systems. However, in some cases, we can only use a limited number of images to train the incremental model due to the difficulty of obtaining them. Few-shot class-incremental learning (FSCIL) is a new paradigm of incremental learning, which continually learns new concepts from a few examples. This setup can quickly lead to catastrophic forgetting and overfitting problems, severely affecting model performance. To address these problems, we propose a dynamic topological evolution (DTE) model that unifies knowledge of old and new categories. In this work, we focus on a novel semi-supervised few-shot class-incremental learning (SSFSCIL) to incrementally learn new categories with a limited number of labeled samples and a large number of unlabeled samples. In detail, we use the Voronoi polygon criterion to divide the feature space and construct a Hebbian graph to represent topological relationships between classes. Then, the corresponding k-nearest neighbor subgraph is constructed for the new incremental task, and label propagation of graph nodes is carried out on the unlabeled set to generate the corresponding pseudo labels. Finally, the new category knowledge is evolved into the actual category knowledge by integrating the Hebbian graph and the k-nearest neighbor subgraph obtained in the new incremental task. Extensive experiments on the mini-ImageNet and CIFAR100 datasets show that the accuracy of the DTE outperforms the baseline and improves by 1.41% and 1.13% on the last incremental task. Furthermore, our methodology achieved a 35.6% time improvement compared to full-supervised methods on the CIFAR100 dataset. In addition to the experiments on the two datasets mentioned above, the validation of our proposed DTE model extends to the engineering application domain of the RESICS-45 aircraft image scene classification dataset.

CAI formation in the early Solar System

Calcium-aluminium-rich inclusions (CAIs) are the oldest dated solid materials in the Solar System, and are found as light-coloured crystalline ingredients in carbonaceous chondrite meteorites. Their formation time is commonly associated with age zero of the Solar System. Nevertheless, the physical and chemical processes that once led to the formation of these submillimetre- to centimetre-sized mineral particles in the early solar nebula are still a matter of debate. In this paper, we propose a pathway to form such inclusions during the earliest phases of disc evolution. We combine 1D viscous disc evolutionary models with 2D radiative transfer, equilibrium condensation, and new dust opacity calculations. We show that the viscous heating associated with the high accretion rates in the earliest evolutionary phases causes the midplane inside of about 0.5\,au to heat up to limiting temperatures of about 1500-1700\,K, but no further. These high temperatures force all refractory material components of the inherited interstellar dust grains to sublimate --- except for a few Al-Ca-Ti oxides, such as Al$_2$O$_3$, Ca$_2$Al$_2$SiO$_7$, and CaTiO$_3$. This is a recurring and very stable result in all our simulations, because these minerals form a natural thermostat. Once the Mg-Fe silicates are gone, the dust becomes more transparent and the heat is more efficiently transported to the disc surface, which prevents further warming. This thermostat mechanism keeps these minerals above their annealing temperature for hundreds of thousands of years, allowing them to form large pure crystalline particles. These particles are dragged out by the viscously spreading disc, and once they reach a distance of about 0.5\,au, the silicates recondense on the surface of the Ca-Al-rich particles, adding an amorphous silicate matrix. We estimate that this mechanism of CAI production works during the first 50\,000 years of disc evolution. These particles then continue to move outward and populate the entire disc up to radii of about 50\,au, before the accretion rate eventually subsides, the disc cools, and the particles start to drift inwards.

Ionised AGN outflows in the Goldfish galaxy : The illuminating and interacting red quasar eFEDSJ091157.4+014327 at z~0.6

Evolutionary models suggest that the initial growth phases of active galactic nuclei (AGN) and their central supermassive black holes (SMBHs) are dust-enshrouded and characterised by jet or wind outflows that should gradually clear the interstellar medium (ISM) in the host by heating and/or expelling the surrounding gas. eFEDSJ091157.4+014327 (zsim 0.6) was selected from X-ray samples of eROSITA (extended ROentgen Survey with an Imaging Telescope Array) for its characteristics: red colours, X--ray obscuration (N$ _H \,=\,$2.7times 1022 $) and luminous (L$_ X $=6.5times 1044\,$\; $), similar to those expected in quasars with outflows. It hosts an ionised outflow as revealed by a broad O III AA $ emission line in the SDSS integrated spectrum. For a proper characterisation of the outflow properties and their effects, we need spatially resolved information. We aim to explore the environment around the red quasar, morphology of the O III gas and characterise the kinematics, mass outflow rates and energetics within the system. We used spatially resolved spectroscopic data from Multi Unit Spectroscopic Explorer (MUSE) with an average seeing of 0.6" to construct flux, velocity and velocity dispersion maps. Thanks to the spatially resolved O III AA $ emission detected, we provide insights into the morphology and kinematics of the ionised gas and better estimates of the outflow properties. We find that the quasar is embedded in an interacting and merging system with three other galaxies sim 50 kpc from its nucleus. Spatially resolved kinematics reveal that the quasar has extended ionised outflows of up to 9.2$^ $ kpc with positive and negative velocities up to 1000\,$\; $ and $-$1200\,$\; $, respectively. The velocity dispersion (W$_ $) ranges from 600 $-$ 1800\,$\; $. We associate the presence of high-velocity components with the outflow. The total mass outflow rate is estimated to be sim 10 M$_ odot $ yr$^ $, a factor of sim 3 $-$ 7 higher than the previous findings for the same target and kinetic power of 2times 1042\,$\; $. Considering different AGN bolometric luminosities, the kinetic coupling efficiencies range from 0.01<!PCT!> $-$ 0.03<!PCT!> and the momentum boosts are sim 0.2. The kinetic coupling efficiency values are low, which indicates that the ionised outflow is not energetically relevant. These values don't align with the theoretical predictions of both radiation-pressure-driven outflows and energy-conserving mechanisms. However, note that our results are based only on the ionised phase while theoretical predictions are multi-phase. Moreover, the mass loading factor of sim 5 is an indication that these outflows are more likely AGN-driven than star formation-driven.

Research on the evolutionary control of unsafe behavior of construction personnel based on multi-field coupled-homogeneous analysis model.

Unsafe behavior among construction personnel poses significant risks in petroleum engineering construction projects. This study addresses this issue through the application of a multi-field coupled homogeneous analysis model. By conducting case analyses of petroleum engineering construction accidents and utilizing the WSR methodology, the influencing factors of unsafe behaviors among construction personnel are systematically categorized into organizational system factors, equipment management factors, and construction personnel factors. Subsequently, employing Risk coupling theory, the study delves into the analysis of these influencing factors, discussing their coupling mechanisms and classifications, and utilizing the N-K model to elucidate the coupling effect among them. Furthermore, a novel approach integrating coupling analysis and multi-agent modeling is employed to establish an evolutionary model of construction personnel's unsafe behavior. The findings reveal that a two-factor control method, concurrently reinforcing equipment and construction personnel management, significantly mitigates unsafe behavior. This study provides valuable insights into the evolution of unsafe behavior among construction personnel and offers a robust theoretical framework for targeted interventions. Significantly, it bears practical implications for guiding safety management practices within petroleum engineering construction enterprises. By effectively controlling unsafe behaviors and implementing targeted safety interventions, it contributes to fostering sustainable development within the petroleum engineering construction industry.

Multi-factor corrosion model of TP110TS steel in H2S/CO2 coexistence and life prediction of petroleum casings

The failure of petroleum casings due to the combined effects of CO2/H2S corrosion and internal pressure has become a main concern during the exploitation of high-temperature, high-pressure, and high-corrosion gas fields. Therefore, establishing a corrosion evolution model is crucial for accurately predicting the service life of casings. In this study, an analytical model describing the corrosion rate of casing steel TP110TS under different CO2/H2S partial pressures and applied stresses was established, combined with the mechanical-chemical effect. The weightlessness method was used to determine the model parameters from the experimental results using a multiple regression. Based on the elasticity, a service life prediction model considering mechanical property attenuation and casing stress fluctuation was established from the assumption of uniform thickness thinning. The effects of internal pressure and CO2/H2S partial pressures on the service life were analyzed. The corrosion rate initially decreased with time. However, the stress increased as the wall thickness decreases from corrosion. The stress-promoting corrosion effect gradually manifested, and the corrosion rate rapidly increased. The higher the internal pressure and H2S/CO2 partial pressure, the shorter was the service life of the casing. In the H2S/CO2 coexistence environment, the influence of H2S partial pressure was more significant than that of CO2.

Impact of main sequence mass loss on the appearance, structure, and evolution of Wolf-Rayet stars

Stellar winds are one of the most important drivers of massive star evolution and are a vital source of chemical, mechanical, and radiative feedback on the galactic scale. Despite its significance, mass loss remains a major uncertainty in stellar evolution models. In particular, the interdependencies between the different approaches and the subsequent evolutionary stages and predicted observable phenomena are far from being systematically understood. In this study, we examine the impact of main sequence mass loss on the structure of massive stars throughout their entire evolution. Particular focus is placed on the consequences in terms of entrance into the Wolf-Rayet regime and the subsequent evolution. Using the Geneva stellar evolution code (GENEC), we computed grids of single, nonrotating stellar models at solar and Large Magellanic Cloud (LMC) metallicities of initial masses between 20 and 120 solar masses, with two representative prescriptions for high and low main sequence mass loss. We obtain detailed numerical predictions regarding the structure and evolution of massive stars, and infer the role of main sequence mass loss by comparison of the mass-loss rate prescriptions. We present implications for the overall evolutionary trajectory, including the evolution of WR stars, as well as the effect on stellar yields and stellar populations. Mass loss during the main sequence plays an important role because of its ability to affect the sequence and duration of all subsequent phases. We identify several distinct evolutionary paths for massive stars, which are significantly influenced by the chosen main sequence mass-loss description. We also discuss the impact of uncertainties ---other than that regarding mass loss--- on the evolution, in particular those relating to convection. We further demonstrate that not only the total mass loss but also the specific mass-loss history throughout a star's life is a crucial determinant of many aspects, such as the resulting stellar yields.

Analysis of the evolution path of new energy system under polymorphic uncertainty—A case study of China

The exploration and promotion of new energy constitute a significant initiative for numerous countries in their pursuit of sustainable development and efforts to alleviate climate change. However, the influence of a multitude of uncertain factors on the evolutionary path of new energy is currently poorly studied. By establishing a dynamic evolution model for new energy under polymorphic uncertainty, this paper analyses the complex interaction between new energy, economic growth, and carbon trading over the period 2020–2060, using China as a case study. We employ numerical simulation and sensitivity analysis to investigate the evolutionary trajectories of the new energy system under various parameter value scenarios. We show that the evolutionary trajectories will undergo substantial fluctuations before 2030, subsequently stabilizing from 2030 onwards. The study highlights that an excessively rapid pace of new energy development is detrimental to new energy systems, whereas energy storage system deployment has the opposite effect. There exists a significant risk of the system collapsing as a result of slow new energy development, over-building energy storage facilities, or over-intervening in carbon trading. We also find that overdevelopment of energy storage system may have greater negative impacts on the economic system than underdevelopment.

Unveiling Agricultural Shifts through Stakeholder Interactions and Strategic Dynamics in Green Rice Production

This study explores the strategic interactions among the government, growers, and the public within the context of green rice production, employing an evolutionary game theory framework. Recognizing the intricate dynamics of agricultural sustainability, we construct a three-party evolutionary game model to investigate the strategic decision-making processes and stability conditions of each stakeholder. The model assesses how various strategies evolve under the influence of economic incentives, regulatory measures, and public engagement. Through analytical and numerical methods, including stability analysis and MATLAB 2020b simulations, we identify the Evolutionarily Stable Strategies (ESS) that signify sustainable practices in green rice production. The results reveal that as government incentives for green production increase and fines for non-green practices are enforced, the likelihood of growers adopting sustainable practices significantly rises. Furthermore, the strategic enhancement of economic incentives and reputational factors not only bolsters governmental regulatory commitment but also reduces the necessity for public supervision, demonstrating a systemic shift towards self-regulation and market-driven sustainability. The simulations demonstrate the system’s evolution towards a stable state where governmental regulation is fully enforced, growers adopt green production universally, and public supervision becomes redundant. The findings underscore the importance of designing policy interventions that harmonize economic and environmental objectives, suggesting that well-structured incentives and regulatory measures can catalyze the transition towards sustainable agricultural practices. Additionally, our study highlights the pivotal role of establishing effective incentive structures that ensure the economic benefits of green production outweigh the costs, facilitating an autonomous regulatory system. This study contributes to the understanding of how strategic interactions shaped by policy and market forces can foster agricultural sustainability.

Committing to the wrong artificial delegate in a collective-risk dilemma is better than directly committing mistakes

While autonomous artificial agents are assumed to perfectly execute the strategies they are programmed with, humans who design them may make mistakes. These mistakes may lead to a misalignment between the humans’ intended goals and their agents’ observed behavior, a problem of value alignment. Such an alignment problem may have particularly strong consequences when these autonomous systems are used in social contexts that involve some form of collective risk. By means of an evolutionary game theoretical model, we investigate whether errors in the configuration of artificial agents change the outcome of a collective-risk dilemma, in comparison to a scenario with no delegation. Delegation is here distinguished from no-delegation simply by the moment at which a mistake occurs: either when programming/choosing the agent (in case of delegation) or when executing the actions at each round of the game (in case of no-delegation). We find that, while errors decrease success rate, it is better to delegate and commit to a somewhat flawed strategy, perfectly executed by an autonomous agent, than to commit execution errors directly. Our model also shows that in the long-term, delegation strategies should be favored over no-delegation, if given the choice.

Evolutionary game and system dynamics for analysis on stakeholder strategies of regional high-speed rail project in investment decision stage

This paper studies the strategic choices under the conflict among stakeholders of regional high-speed rail project at the investment decision stage in the context of the ‘high-speed rail controversy’. This study develops a tripartite evolutionary game model among the central government, the local government and China Railway, analyzes the evolutionary stability strategy, discusses the influence of multiple factors on the choice of tripartite strategy, and further calculates and analyzes the stability of the equilibrium point in the tripartite evolutionary game system. Then the dynamic change trend of strategy choice brought by the change of each factor is investigated through system dynamics simulation. The results show that the lower the intervention cost and reward to the other two parties, and the increase of the opportunity cost of non-intervention and punishment to the other two parties, the faster the convergence of the central government's choice of intervention strategy. The increase of the rewards and punishments, and the increase of negotiation profits, non-negotiation costs, and loss of reputation for non-negotiation, and the decrease in the negotiation costs and non-negotiation profits all contribute to the shortening of the convergence time of the local government's choice of negotiation strategy. The increase of the rewards and punishments, the increase of support profits, the loss of reputation for non-support, and the decrease of the profits for non-support and the extra cost for support will promote the convergence of China Railway's choice of the support strategy. Finally, the simulation results are discussed so as to target feasible coordination strategies, which provides a theory basis for the practice of conflict coordination among stakeholders of regional high-speed rail project at the investment decision stage.

Wave Impacts On Cliffs: From The Field To The Laboratory

Rock coasts occupy over 50% of the global shoreline and many sandy beaches are underlain by coastal platforms and rocky cliffs. The problem of wave-driven cliff erosion is of great societal importance, with many coastal communities located on top of cliffs that are at risk from erosion. Continuing global mean sea level rise and changes in storminess are generally expected to exacerbate the erosion of coastlines (Hurst et al., 2016), as larger waves can reach the cliff toe without breaking offshore. However, the science underpinning wave-induced cliff erosion is still at a relatively early stage. Even the relative contributions of waves to cliff erosion, which include hydraulic forces, impulse pressures and abrasion, are not well resolved. Most insights into wave impacts on cliffs come from field observations of coastal ground motion during storm events (e.g. Young et al., 2011, Huppert et al., 2020). These field investigations demonstrate the dependence of large wave impacts on both water levels and wave conditions, and in some cases the correlation of periods of large ground motion with increased erosion (Earlie et al., 2015). Unsurprisingly, although large impacts generally occur at high tide during storms characterised by large significant wave heights, the largest impacts occur when tidal levels and storm surge combine to provide water levels that are conducive to the incident waves breaking on the cliffs (Thompson et al., 2019; 2022). Larger wave heights or shallower water levels tend to lead to breaking further offshore, with a broken wave interacting with the cliff, while smaller wave heights or deeper water levels may preclude strong wave breaking on the cliffs. There have been relatively few experimental studies into wave-driven cliff erosion; these were generally undertaken under very idealised wave conditions (e.g. Sunamura, 1977) and using materials that were either too soft to approximate natural rocks (e.g. Sunamura, 1977; 1982) or too hard to be eroded (Hansom et al., 2008). Although these experiments have informed the development of rocky coast evolution models, their results have not been replicated or verified, and rigorous scaling laws to link laboratory erosion rates to field time scales are currently lacking. However, considering cliffs as steep or vertical (natural) coastal structures, a large body of experimental work has been undertaken to investigate impact pressures and their implications for the failure of engineered structures (e.g. Peregrine, 2003, Bullock et al., 2007). These investigations are complicated by the inherent variability of the wave impact pressures, even within controlled experiments undertaken with highly repeatable incident wave conditions (Raby et al., 2022). Although field and laboratory data are valuable, it is still very challenging to quantify wave contributions to cliff erosion due to the relatively short durations and variable conditions of most field records. On the other hand, most controlled laboratory investigations have typically focused on loads on non-erodible engineered structures such as seawalls. The current project seeks to advance understanding of the fundamental mechanisms and timescales of wave-driven erosion on rocky cliffs, which will be vital in improving assessments of cliff erosion hazard in high-energy wave environments as sea levels rise.

Revealing Hydrogen Bond Effect in Rechargeable Aqueous Zinc‐Organic Batteries

The surrounding hydrogen bond (H‐bond) interaction around the active sites plays indispensable functions in enabling the organic electrode materials (OEMs) to fulfill their roles as ion reservoirs in aqueous zinc‐organic batteries (ZOBs). Despite important, there are still no works could fully shed its real effects light on. Herein, quinone‐based small molecules with a H‐bond evolution model has been rationally selected to disclose the regulation and equilibration of H‐bond interaction between OEMs, and OEM and the electrolyte. It has been found that only a suitable H‐bond interaction could make the OEMs fully liberate their potential performance. Accordingly, the 2,5‐diaminocyclohexa‐2,5‐diene‐1,4‐dione (DABQ) with elaborately designed H‐bond structure exhibits a capacity of 193.3 mA h g‐1 at a record‐high mass loading of 66.2 mg cm‐2 and 100% capacity retention after 1500 cycles at 5 A g‐1. In addition, the DABQ//Zn battery also possesses air‐rechargeable ability by utilizing the chemistry redox of proton. Our results put forward a specific pathway to precise utilization of H‐bond to liberate the performance of OEMs.

Multi‐agent behavioral strategy game and synergy evolution path of the retired power battery recycling system

Multi‐agent behavioral strategy game and synergy evolution path of the retired power battery recycling system

Revealing Hydrogen Bond Effect in Rechargeable Aqueous Zinc-Organic Batteries.

The surrounding hydrogen bond (H-bond) interaction around the active sites plays indispensable functions in enabling the organic electrode materials (OEMs) to fulfill their roles as ion reservoirs in aqueous zinc-organic batteries (ZOBs). Despite important, there are still no works could fully shed its real effects light on. Herein, quinone-based small molecules with a H-bond evolution model has been rationally selected to disclose the regulation and equilibration of H-bond interaction between OEMs, and OEM and the electrolyte. It has been found that only a suitable H-bond interaction could make the OEMs fully liberate their potential performance. Accordingly, the 2,5-diaminocyclohexa-2,5-diene-1,4-dione (DABQ) with elaborately designed H-bond structure exhibits a capacity of 193.3 mAh g-1 at a record-high mass loading of 66.2 mg cm-2 and 100 % capacity retention after 1500 cycles at 5 A g-1. In addition, the DABQ//Zn battery also possesses air-rechargeable ability by utilizing the chemistry redox of proton. Our results put forward a specific pathway to precise utilization of H-bond to liberate the performance of OEMs.