Charge Model Research Articles

Performance analysis of electrical signal output of multi-state flexoelectric structures with parameter uncertainties through quasi-Monte Carlo method

Flexoelectric effect is a more universal electromechanical coupling effect than piezoelectric effect. Flexoelectric beams as the main structural component of flexoelectric power signal output have broad application prospects in the next generation of micro–nano electromechanical systems. However, the electrical signal output of flexoelectric structures in macro-scale is far less than the output of the piezoelectric signal. Therefore, it is urgent to explore the influence of the parameter uncertainties on the electrical signal output of the flexoelectric structures, in order to improve the electrical signal output of flexoelectric materials with excellent design performance. Based on the quasi-static theory, the output voltage model and the output charge model of flexoelectric structures as well as the effective piezoelectric coefficient model are constructed. Then the influences of the flexoelectric parameters on the output voltage and the output charge are researched as well as the influence of the effective piezoelectric coefficient. Finally, the influences of uncertain parameters under different electrical states (e.g. the electrical open circuit and short circuit states) on the output performance of flexoelectric signal are studied by the quasi-Monte Carlo method, in order to further provide a reference for the reliability analysis and optimization design of the flexoelectric structures.

Phase envelopes in reservoir fill analysis: Two contrasting scenarios

Phase envelopes are routinely employed by reservoir engineers for fluid characterisation. These envelopes are controlled by reservoir fluid composition, pressure and temperature. As a result of increasing source-rock maturation, fluids with decreasing molecular weights and densities and increasing gas-to-oil ratios (and hence different phase envelopes) are generated, which are thus linked to fluid history. In addition to their importance for exploration, charge models can play a key role in constraining reservoir models and optimising field development, particularly when pressure–volume-temperature (PVT) data are properly integrated with fluid geochemistry. Two contrasting scenarios of fluid phase evolution from two different fields are presented, and their relations to charge analysis and reservoir models are discussed. The first example discusses the identification, based on hydrocarbon geochemistry complemented by overlapping modeled phase envelopes, of compartmentalised filling cycles in what was initially considered a single oil-rimmed gas accumulation. The second example presents an opposite scenario where two wet gas accumulations 20-km apart laterally and 400-feet average depth difference appear to represent a single more-expansive accumulation spread over areas of variable PVT conditions and reservoir qualities. The wet gas across both accumulations is characterised by a continuous phase evolution pattern that shrinks systematically (cricondentherm shifts to lower temperature and cricondenbar to lower pressure), suggestive of phase fractionation of a charge of single maturity. The proposed gas distribution model represents a discovery of a hybrid conventional and unconventional (tight sand) system, with potential for basin-centered gas. These findings provided better understanding of observed and projected fluids, impacting the development and completion plans by locating new gas producers. A recent well drilled midway between the two accumulations indeed tested wet gas, confirming fluid connectivity. Future work will attempt to link the gas distribution model with seismic attributes.

Influence of initiation modes on vibration frequency induced by single-hole blasting

To further reveal the blasting vibration frequency distribution characteristics induced by different initiation modes of the single borehole cylindrical charge, the PPV and Fourier dominant frequency formula under different initiation modes such as top initiation, bottom initiation, mid-point initiation, and two-point initiation are derived based on the Heelan equivalent unit short-column charge model. The results show that the dominant frequency distribution characteristics near the explosion source are as follows: two-point initiation > mid-point initiation > bottom initiation > top initiation; in the middle and far zones from the explosion source, the difference of dominant frequency induced by various initiation modes is insignificant; the attenuation curves of the dominant frequency of radial and vertical vibration abruptly change at the distance away from the blasting center of 20–50 m and 20–30 m, respectively. However, the curves of centroid frequency under different initiation modes attenuate smoothly with increasing distance, and the distribution rule is two-point initiation > mid-point initiation > bottom initiation > top initiation. In general, the influence of initiation mode on the particle vibration dominant frequency and centroid frequency is gradually weakened with increasing distance. Finally, the theoretical calculation is verified by the experimental data.

An Enhanced Electro-Thermal Coupled Model With Lithium Plating Detection for Lithium-Ion Battery at Low Temperatures

Lithium plating may occur when lithium-ion batteries are charged at a high current rate and low ambient temperature. As a result, the battery degradation is accelerated and the risk of thermal runaway is increased. Along these lines, an enhanced electro-thermal model was proposed in this work for charging at low temperature values. By considering the battery with a reference electrode, a dual RC model was built. The developed model can predict the anode potential to prevent the lithium plating. The thermal model and absolute state of charge (SOC) were integrated into the battery model to solve the SOC inconsistency caused by the battery temperature rise during the charging process. Then, the proposed electro-thermal model was used to predict the electrical and thermal characteristics of a 50 Ah battery under various charging rates and low ambient temperature values conditions. In addition, the prediction results were validated by the experiment data. The maximum errors of the cathode potential and battery terminal voltage were 0.058 V and 0.154 V, respectively, whereas the maximum cell temperature error was 0.88 °C. Based on the anode prediction electro-thermal coupling model, a segmented heating strategy without lithium plating was proposed to describe the fast battery charging procedure, which can reduce energy consumption by 16.1% and save charging time by nearly 10 minutes compared with the continuous high-power heating mode.

Orderly charging strategy for electric vehicles based on multi-level adjustability

The development of electric vehicles (EVs) is one of the essential ways to reduce environmental pollution. With the rapid growth in EVs, an orderly charging strategy based on multi-level adjustable charging power is proposed to address the problem of increasing peak-to-valley difference due to disorderly charging in different scenarios. Based on the information of multi-level adjustable charging power, information about staying in the residential area, and charging demands of EVs, this research designs a centralized charging mode with complete information under the centralized scenario and a decentralized charging mode with incomplete information under the decentralized scenario. This research takes the minimization of peak-to-valley difference in the residential area as the objective function and considers that the charging pile can have the function of multi-level adjustable charging power to support these two scenarios. Two charging modes of the charging pile are designed, and orderly charging model of EVs in the residential area is constructed. EVs can select charging time and charging power by using Bluetooth or code scanning in the charging pile. This research aims to design two orderly charging modes to effectively implement peak shaving and valley filling while ensuring the charging demand of EVs. This research uses the CPLEX solver in MATLAB to solve the objective. The simulation results show that EVs can reasonably select the multi-level adjustable charging power under different scenarios and provide a reference for engineering related to orderly charging. Strategy 4, proposed in this research, has the lowest peak-to-valley difference of the four strategies. The peak-to-valley difference is only 87 kW under the centralized scenario, and the peak-to-valley difference is 282 kW under the decentralized scenario.

Influence of Iodine Merz–Singh–Kollman Radius on the Calculated Charges and Hydration Free Energies of Iodinated Molecules

Empirical force field methods typically rely on point charges to describe the electrostatic interactions, which is problematic when anisotropy needs to be considered, as in the case of the electrostatic potential of covalently bound halogens that possess a positive site, termed [Formula: see text]-hole, surrounded by a large negative belt. To address this, an off-center point charge (extra point, EP) is usually placed at a given distance from the halogen to emulate the [Formula: see text]-hole and commonly used implementations are based on the restrained electrostatic potential (RESP) procedure to fit atomic charges, being one of the most used charge models. In this context, no specific Merz–Singh–Kollman (MK) radius for iodine is available in the literature, which is an essential parameter in the RESP fitting procedure. In this work, we explored the impact of the iodine MK radius on the obtained RESP charges for a set of 12 iodinated molecules. We verified that the relative root mean square (RRMS) values obtained with and without an EP kept decreasing with increasing radii for most compounds, thus impairing optimization using such a procedure. Nevertheless, the use of an iodine MK radius lower than 2 Å is not advisable since the RRMS kept decreasing considerably until this value was reached. Moreover, the performance of three iodine MK radii was studied with the estimation of the free energy of hydration ([Formula: see text] values using alchemical free energy calculations, which are particularly sensitive to the charges used. Despite the usage of different radii not leading to remarkable differences, our results indicate that using a value of 2.70 Å leads to lower mean absolute errors (MAE) and root mean squared error (RMSE) values when comparing the calculated with the experimental [Formula: see text] values.

Triggering triboelectric nanogenerator antibacterial Activities: Effect of charge polarity and host material correlation

Triboelectric nanogenerators (TENGs) offer promising motion-driven energy harvesting for human–machine interactions, particularly in wearable healthcare and biomedical devices. However, direct skin contact demands addressing aggressive bacterial growth risks. The “triangle” interaction between bacteria, electrical stimulation, and host materials has been investigated comprehensively in the present study to facilitate appropriate self-antibacterial designs for TENGs. In so doing, it was revealed that the growth of negatively charged bacterial models (Escherichia coli and Staphylococcus aureus) was inhibited by induced positively charged substrates (Al or graphene oxide (GO)), regardless of the host material's composition due to the direct electrostatic interactions. Electron capture from the bacterial respiratory chain by the substrates leads to the interruption of the bacterial energy supply. In response to negative charges, however, an appreciable host-dependent antibacterial behaviour was observed, with Al showing a negligible bactericidal effect, while GO exhibited robust antibacterial properties. This effect was assigned to reactive oxygen species (ROS) generation, triggered by shuttling the negative charges to the oxygen functional groups in GO, suppressing bacterial growth efficaciously. The observed correlation between the electrostatic charge polarity and the material composition of the substrates (hosting the bacteria) highlights the superiority of ROS induction in the antibacterial properties of TENG. These findings pave the way for developing innovative approaches to control bacterial growth effectively and enhance the applicability of TENGs as advanced wearable devices with inherent antibacterial capabilities.

Surrogate Model for the Effect of Charge State in Lithium-ion Battery Fires

Recently, the demand for eco-friendly energy sources, including batteries, has increased rapidly owing to growing climate and environmental problems. However, battery fire accidents are also increasing, and many researchers are focusing on the safe use of batteries and their flammability characteristics. Owing to the multiple battery types, conducting experiments is difficult in all cases, so various methods to model battery fires are being attempted. This study focuses on the effect of charge states and models surrogate fuels for battery thermal runaway. Three surrogate fuels were selected based on the battery components, and a method of increasing the oxygen concentration was adapted to model the effect that occurs when the charge states of a battery fire increases. As a result, the temperature and pressure increased in all cases, and it appears that the explosion caused by the battery thermal runaway can be simulated by the model. One of the results of this study is that ethane exposed to a high temperature not only contributes to the physical explosion of the battery but also increases the risk of chemical explosion as it decomposes in to H<sub>2</sub> and CH<sub>4</sub> .

Low speed impact simulation of explosive charge based on three-dimensional numerical manifold method

The present work addresses the challenge of evaluating the low speed impact response of polymer bonded explosive charges with three-dimensional numerical manifold method. Based on the cover-based contact theory, the contact algorithm is implemented by transforming position relationships between reference points a0 and entrance block E(A, B). Meanwhile, based on statistical micro-cracks, a Visco Scram mechanical model for the explosive charge is established. Using the classic Steven test, the influence of charge thickness, diameter, and warhead shape on the mechanical response are analyzed under low speed impact. The simulation results indicate that, increasing the thickness of the charge can effectively avoid internal damage of the explosive caused by projectile extrusion and holder confinement; Increasing the aspect ratio of the charge can alleviate the large deformation; Increasing the shape and size of the warhead can make the charge extrusion shallower, alleviating the concave shear damage of the charge. The simulation results verifies that the developed contact algorithm in this paper can effectively solve 3D impact problems, and provides guidance in the design of charge structures to some extent in the weapon system.

Earth Mover's Charge Transfer Distance: A General and Robust Approach for Describing Excited State Locality.

A novel approach for assessing the extent of electron displacement in optical transitions is proposed by implementing the Earth Mover's Distance (EMD) method, which quantifies the spatial dissimilarity between ground and excited state electron density distributions. In contrast to previous descriptors, this index provides a representative and intuitively understandable distance under a robust and computationally efficient scheme for all possible forms of locality, even in the most difficult to dissect topological cases. The theoretical differences among the existing indices and our method are first illustrated with the help of a simplified model system, followed by a benchmarking of several partial atomic charge models using experimentally relevant push-pull compounds with diverse symmetries. These same molecules are finally employed to further demonstrate the principal advantages of the EMD index and its capabilities in rationalizing charge transfer phenomena.

Improving Quantum Chemical Solvation Models by Dynamic Radii Adjustment for Continuum Solvation (DRACO).

We present the Dynamic Radii Adjustment for COntinuum solvation (DRACO) approach, which employs precomputed atomic partial charges and coordination numbers of the solute atoms to improve the solute cavity. As such, DRACO is compatible with major solvation models, improving their performance significantly and robustly at virtually no extra cost, especially for charged solutes. Combined with the purely electrostatic CPCM and COSMO models, DRACO reduces the mean absolute deviation (MAD) of the solvation free energy by up to 4.5 kcal mol-1 (67%) for a large data set of polar and ionic solutes. Even in combination with the highly empirical universal solvation model (SMD), DRACO substantially reduces the MAD for charged solutes by up to 1.5 kcal mol-1 (39%), while neutral solutes are slightly improved (0.2 kcal mol-1 or 16%). We present an interface of DRACO with two computationally efficient atomic charge models that enables fully automated, out-of-the-box calculations with the widely used program packages Orca and TurboMole.

Spectral information content of Compton scattering events in silicon photon counting detectors.

Silicon (Si) is a possible sensor material for photon counting detectors (PCDs). A major drawback of Si is that roughly two-thirds of x-ray interactions in the diagnostic energy range are Compton scattering. Because Compton scattering is an energy-insensitive process, it is commonly assumed that Compton events retain little spectral information. To quantify how much information can be recovered from Compton scattering events in models of Si PCDs. We built a simplified model of Si interactions including two interaction mechanisms: photoelectric effect and Compton scattering. We considered three different binning options that represent strategies for handling Compton events: in Compton censoring, all events under 38keV (the maximum energy possible from Compton scattering for a 120keV incident photon) were discarded; in Compton counting, all events between 1 and 38keV were placed into a single bin; in Compton binning, all events were placed into energy bins of uniform width. These were compared to the ideal detector, which always recorded the correct energy (i.e., 100% photoelectric effect). Every photon was assumed to interact once and only once with Si, and the energy bin width was 5keV. In the primary analysis, the Si detector was irradiated with a 120kV spectrum filtered by 30cm of water, with 99.5% of the arriving spectrum above 38keV so that there was good separation between photoelectric effect and Compton scattering, and the figures of merit were the Cramér-Rao lower bound (CRLB) of the variance of iodine and water basis material decomposition images, as well as the CRLB of virtual monoenergetic images (i.e., linear combinations of material images) that maximize iodine CNR or water CNR. We also constructed a local linear estimator that attains the CRLB. In secondary analyses, we applied other sources of spectral distortion: (1) a nonzero minimum energy threshold; (2) coarser, 10keV energy bins; and (3) a model of charge sharing. With our chosen spectrum, 67% of the interactions were Compton scattering. Consistent with this, the material decomposition variance for the Compton censoring model, averaged over both basis materials, was 258% greater than the ideal detector. If Compton events carried no spectral information, the Compton counting model would show similar variance. Instead, its basis material variance was 103% greater than the ideal detector, implying that Compton counts indeed carry significant spectral information. The Compton binning model had a basis material variance 60% greater than the ideal detector. The Compton binning model was not affected by a 5keV minimum energy threshold, but the variance increased from 60% to 107% when charge sharing was included and to 78% with coarser energy bins. For optimized CNR images, the average variance was 149%, 12%, and 10% higher than the ideal detector for the Compton censoring, counting, and binning models, reinforcing the hypothesis that Compton counts are useful for detection tasks and that precise energy assignments are not necessary. Substantial spectral information remains after Compton scattering events in silicon PCDs.

Competing platform owners’ entry and an OEM's cooperation response

AbstractThis paper develops a game‐theoretic model that examines the entry decisions of two competing platform owners with differentiated research and development (R&D) efficiency and the response strategy of an original equipment manufacturer (OEM) in selecting which platform to cooperate with. The OEM and platform owners compete on quality and price in the face of consumers with heterogeneous preferences across the dimensions of the device and platform. We analyze the interaction between the entry decisions of platform owners and the OEM's response strategy within two cooperation models. In the charging model, we find that in the absence of entry, the OEM prefers the high‐efficiency platform. When only one platform owner enters, the OEM prefers the low‐efficiency platform. If the differentiated R&D efficiency and the device differentiation cost are large, both platform owners will choose to enter and the OEM will cooperate with the low‐efficiency platform. In the bundling model, when only one platform owner enters, only at a large cost of device differentiation will the OEM cooperate with the platform that enters the market to weaken market competition. In particular, when only the high‐efficiency platform enters, it is interesting that there exists a large cost of device differentiation that makes the high‐efficiency platform more favorable in the case when the OEM cooperates with the low‐efficiency platform. Our study provides practical insights into platform entry and OEM response.

A customer satisfaction-based optimization model for the charging and discharging path and battery swapping stations’ site selection of electric vehicles

This paper studies the problem of considering customer satisfaction in the no-battery-swap mode and in the power-swap mode. First, with the goal of maximizing customer satisfaction, the total cost of charging and discharging and the minimum construction cost of swapping stations, the customer time window, and the load constraints of electric vehicles are considered. A model of electric vehicle charging and discharging route optimization and replacement station location without battery swapping behavior, considering customer satisfaction, is established, and then, a two-stage improved ant colony–genetic algorithm is designed to solve the model, and finally, the comparative analysis considers customer satisfaction. Based on the path optimization results and location decisions considering the cost of charging and discharging, the following conclusions are obtained: 1) electric vehicle route optimization and swap station location planning considering customer satisfaction can not only effectively reduce logistics distribution costs and replacement costs but also improve customer satisfaction levels. 2) Reducing the number of route crossings in the process of logistics distribution routes can save electricity costs for electric vehicles and logistics distribution costs, and help reduce the total cost of the entire logistics distribution network. 3) The gradient setting of the electricity price for electricity exchange will reduce the cost of electricity exchange, improve the utilization efficiency of the battery, reduce the cost of logistics and distribution, and improve the electricity exchange revenue of the electricity exchange station.

Securing Cloud Computing Environments: An Analysis of Multi-Tenancy Vulnerabilities and Countermeasures

The rise of cloud computing has brought significant advancements in scalability, flexibility, and cost-efficiency, with multi-tenancy emerging as a core feature that allows multiple tenants to share the same physical infrastructure. However, this shared environment introduces serious security vulnerabilities, including data breaches, side-channel attacks, denial of service (DoS) attacks, and insecure APIs, all of which threaten the confidentiality, integrity, and availability of tenant data. The problem statement addressed in this study revolves around the challenge of securing multi-tenant environments, where resource sharing can expose tenants to risks stemming from improper isolation, malicious actors, and insufficient security measures. This study contributes to the field by providing a comprehensive analysis of these vulnerabilities and assessing the effectiveness of various countermeasures, such as enhanced isolation techniques, encryption, and access control mechanisms. A multi-faceted methodology, including literature review, case study analysis, risk assessment, and experimental simulations, was employed to evaluate these risks and their mitigation. The results reveal that, while security solutions like encryption and isolation can reduce the attack success rate to 5%, they do introduce a performance overhead of 12%. Additionally, the study highlights the importance of adhering to regulatory agreement frameworks such as GDPR and HIPAA, realizing a compliance score of 9.2. In conclusion, the study demonstrates that effective implementation of security measures can expressively mitigate risks in multi-tenant cloud settings. However, it also highlights the trade-offs between show and security, urging cloud providers and leaseholders to adopt a shared charge model for ongoing monitoring and protection. Future technologies, such as AI-driven security results and zero-trust styles, are also submitted as likely advances to further support the security of cloud calculating systems.

Electric vehicle charging optimization strategy based on the mopso algorithm

Aiming at the problems of electric vehicle disorderly charging on grid load stability and charging cost, this study considers the grid load pressure and presents a multi-faceted optimized model for electric vehicle charging. The model is addressed by utilizing a particle swarm optimization algorithm designed for multiple objectives. The outcomes demonstrate that the charging framework built upon the multi-objective particle swarm algorithm has a fast convergence speed and can avoid the limitation of the local optimal solutions. Under the premise of reducing by managing the grid load fluctuation, the model effectively curbs the expense of vehicle charging while also minimizing peak-to-valley disparities in grid load.

Solubility of CO2 in salty water: adsorption, interfacial tension and salting out effect

In this work, we performed Molecular Dynamics simulations to investigate the solubility of CO 2 in both pure water and NaCl aqueous solutions, employing various force fields for water and NaCl. We first focussed on the solubility of CO 2 in TIP4P/2005 and TIP4P/Ice water models. We found that it was necessary to apply positive deviations to the energetic Lorentz-Berthelot combining rules for the cross interactions of water and CO 2 in both models to accurately replicate the experimental solubility of the gas. Then we found a negative adsorption of ions at the NaCl solution– CO 2 interface. We also observed an increase of the interfacial tensions of the system when adding salt which is related with the observed negative adsorption of the ions at the interface. Furthermore, we found that unit charge models tend to highly overestimate the change in the interfacial tension compared to scaled charge models. Finally, we also explored the salting out effect of CO 2 using different force fields for NaCl. Our findings indicate that unit charge force fields significantly overestimate the salting out effect of CO 2 while the scaled charge model Madrid-2019 accurately reproduces the experimental salting out effect of CO 2 in NaCl solutions.

Theory of Defect-Induced Crystal Field Perturbations in Rare-Earth Magnets.

We present a theory describing the single-ion anisotropy of rare-earth (RE) magnets in the presence of point defects. Taking the RE-lean 1∶12 magnet class as a prototype, we use first-principles calculations to show how the introduction of Ti substitutions into SmFe_{12} perturbs the crystal field, generating new coefficients due to the lower symmetry of the RE environment. We then demonstrate that these perturbations can be described extremely efficiently using a screened point charge model. We provide analytical expressions for the anisotropy energy that can be straightforwardly implemented in atomistic spin dynamics simulations, meaning that such simulations can be carried out for an arbitrary arrangement of point defects. The significant crystal field perturbations calculated here demonstrate that a sample that is single phase from a structural point of view can nonetheless have a dramatically varying anisotropy profile at the atomistic level if there is compositional disorder, which may influence localized magnetic objects like domain walls or skyrmions.

Will pay-per-view in the advanced charging model recover the business losses for online video companies in China?

The evolution of Internet technology is closely mirrored by the innovative business and profit models emerging within the platform economy. Integrating this economic framework, online video platforms are dynamically refining their pricing strategies to optimize profit margins. This paper, anchored in the theoretical construct of second-degree price discrimination, selects the Chinese online video platforms iQiyi and Tencent Video for in-depth case studies. It charts the progression of its pricing strategies and juxtaposes these with those of prominent international online video sites to highlight both congruities and divergences. The synthesis of theoretical models with real-world case studies culminates in strategic recommendations to foster the growth of Chinese online video platforms in the global Internet arena.

Mental models guide electric vehicle charging

To discover conceptual and behavioral barriers to electric vehicle (EV) charging, in-depth interviews were conducted in person with experienced and novice EV users. Mental models were found to affect vehicle charging strategies. Novice EV users drew from their existing mental models for petrol refueling and misapplied them to EV charging. Most experienced users had developed new mental models appropriate for the physical and temporal realities of EV charging—they are adapted to diverse rates of charge, EVs' longer energy filling duration, co-location of EV charging with certain user activities, and EVs drivers’ shorter equipment engagement time. Three predominant mental models for EV charging were found: 1. Monitor the fuel gauge, when low, seek a refill location (from liquid-fueling model), 2. Prior to a trip, plan where and when to charge, 3. Event-triggered charging (unique to the EV mental model). Misapplication of liquid fuel models to EVs has detrimental effects: more effort and more frequent anxiety regarding recharging, buyer choice of EV characteristics mismatched to need, manufacturer oversizing of batteries, policy overemphasis on fast public charging, and restricted opportunity to reduce load on the grid. Solutions are suggested to forestall or minimize these detrimental effects and facilitate EV adoption.