Electric Field Model Research Articles

Modeling and Simulation of Electric and Magnetic Fields of a Short Dipole Antenna at Low Frequencies in the Far Field

Modeling and Simulation of Electric and Magnetic Fields of a Short Dipole Antenna at Low Frequencies in the Far Field

Enabling Electric Field Model of Microscopically Realistic Brain.

Modeling brain stimulation at the microscopic scale may reveal new paradigms for a variety of stimulation modalities. We present the largest map of distributions of the extracellular electric field to date within a layer L2/L3 mouse primary visual cortex brain sample, which was enabled by automated analysis of serial section electron microscopy images with improved handling of image defects (250×140×90 μm 3 volume). We used the map to identify microscopic perturbations of the extracellular electric field and their effect on the activating thresholds of individual neurons. Previous relevant studies modeled a macroscopically homogeneous cortical volume. Result: Our immediate result is a reduction of the predicted stimulation field strength necessary for neuronal activation by a factor of approximately 0.7 (or by 30%) on average, due to microscopic perturbations of the extracellular electric field-an electric field "spatial noise" with a mean value of zero. Although this result is largely sample-specific, it aligns with experimental data indicating that existing macroscopic theories substantially overestimate the electric fields necessary for brain stimulation. Currently, there is a discrepancy between macroscopic volumetric brain modeling for brain stimulation and experimental results: experiments typically reveal lower electric intensities required for brain stimulation. This study is arguably the first attempt to model brain stimulation at the microscopic scale, enabled by automated analysis of modern scanning electron microscopy images of the brain. The immediate result is a prediction of lower electric field intensities necessary for brain stimulation, with an average reduction factor of 0.7.

A phase I trial of accelerated intermittent theta burst rTMS for amnestic MCI

BackgroundEmerging evidence suggests that repetitive transcranial magnetic stimulation (rTMS) enhances cognition in mild cognitive impairment (MCI). Accelerated intermittent theta burst stimulation (iTBS) rTMS protocols are promising as they substantially reduce...

Enhancement of pool boiling under reduced gravity by the synergistic effect of non-uniform surface structure and electric field: A lattice Boltzmann study

In this paper, a novel non-uniformly structured surface with primary and secondary pillars is conceived to be coupled with the action of an electric field to enhance pool boiling under reduced gravity. On the surface, the secondary pillars are distributed diagonally. A three-dimensional thermal lattice Boltzmann (LB) model combined with an electric field model is employed to investigate the boiling heat transfer performance on the non-uniformly pillar-structured surface and the associated boiling enhancement mechanism. It is found that the synergistic effect of the non-uniform surface structure and the electric field leads to a non-equilibrium electric force that causes the bubbles to be pushed away from the center of the heating surface, which promotes an earlier departure of the bubbles and provides more paths for the fresh liquid replenishment. As a result, the boiling performance under reduced gravity can be significantly enhanced by utilizing such a synergistic effect, with both the critical heat flux (CHF) and the maximum heat transfer coefficient (HTC) on the non-uniformly pillar-structured surface exceeding those on a uniformly pillar-structured surface under normal gravity. Moreover, the influences of the distribution of the secondary pillars on the boiling performance under reduced gravity are also studied. It is shown that the non-uniformly pillar-structured surface whose secondary pillars are distributed diagonally performs much better than those with the secondary pillars being distributed crossly and centrally, and the synergistic effect of the non-uniform surface structure and the electric field results from tuning the distribution of the non-uniform electric force.

Study on micro electrochemical milling with programmable dynamic eccentric rotating electrode

Micro electrochemical machining (ECM) has the advantages of non-contact machining, no tool loss and no residual stress, and has great development potential in the field of microstructure manufacturing. However, the micron-scale machining gap is difficult to renew and discharge the electrolyte and electrolytic products in time. In this paper, a novel micro ECM with programmable dynamic eccentric rotating electrode (DER-ECM) is proposed, which can effectively improve the discharge of electrolytic products in the machining area. According to the process characteristics, a disc flexure hinge structure with one-stage amplification was designed, which was driven by a piezo-ceramic actuator, and the programmable eccentricity ranging from 0 to 20 μm. The multi-physics model of flow field and electric field of DER-ECM, micro ECM with eccentric rotating electrode (ER-ECM) and micro ECM with rotating electrode (R-ECM) were established. The theoretical simulation results showed that the flow rate generated by DER-ECM at the bottom of the electrode is 97 times that of ER-ECM. The current density generated by DER-ECM showed periodic pulsation, and the pulsation period was determined by the driving frequency of the piezo-ceramic actuator. The experimental results showed that DER-ECM could effectively eliminate the surface spike of the workpiece in the bottom machining area and effectively improve the machining accuracy. The micro-groove widths obtained under DER-ECM, ER-ECM and R-ECM were 418 μm, 446 μm and 468 μm, respectively. In addition, the influence of three types of dynamic eccentric rotation electrode trajectories on DER-ECM was studied. The experimental results showed that the sawtooth dynamic eccentric rotation electrode had better machining accuracy. Theoretical simulation and experimental results showed that DER-ECM could improve the flow field and achieve higher machining efficiency and machining localization.

Precision Network Modeling of Transcranial Magnetic Stimulation Across Individuals Suggests Therapeutic Targets and Potential for Improvement.

Higher-order cognitive and affective functions are supported by large-scale networks in the brain. Dysfunction in different networks is proposed to associate with distinct symptoms in neuropsychiatric disorders. However, the specific networks targeted by current clinical transcranial magnetic stimulation (TMS) approaches are unclear. While standard-of-care TMS relies on scalp-based landmarks, recent FDA-approved TMS protocols use individualized functional connectivity with the subgenual anterior cingulate cortex (sgACC) to optimize TMS targeting. Leveraging previous work on precision network estimation and recent advances in network-level TMS targeting, we demonstrate that clinical TMS approaches target different functional networks between individuals. Homotopic scalp positions (left F3 and right F4) target different networks within and across individuals, and right F4 generally favors a right-lateralized control network. We also modeled the impact of targeting the dorsolateral prefrontal cortex (dlPFC) zone anticorrelated with the sgACC and found that the individual-specific anticorrelated region variably targets a network coupled to reward circuitry. Combining individualized, precision network mapping and electric field (E-field) modeling, we further illustrate how modeling can be deployed to prospectively target distinct closely localized association networks in the dlPFC with meaningful spatial selectivity and E-field intensity and retrospectively assess network engagement. Critically, we demonstrate the feasibility and reliability of this approach in an independent cohort of participants (including those with Major Depressive Disorder) who underwent repeated sessions of TMS to distinct networks, with precise targeting derived from a low-burden single session of data. Lastly, our findings emphasize differences between selectivity and maximal intensity, highlighting the need to consider both metrics in precision TMS efforts.

Continuous Nanofiber Bundle Production Using Helical Spinnerets with Different Configurations in Needleless Electrospinning

This study investigates the production of continuous nanofiber bundles using needleless electrospinning with a focus on helical spinneret configurations. It delves into the effects of spinneret diameter, pitch length, and thickness on nanofiber bundle characteristics, employing polyacrylonitrile as the polymer. The research highlights the significant impact of these parameters on the nanofiber morphology, bundle width, productivity, and deposition properties of nanofiber bundles. Scanning electron microscopy imaging, bundle depositions analyses, and electric field modeling with COMSOL Multiphysics are applied for the nanofiber bundles electrospun by helical spinnerets. As the diameter of the spinneret increases, productivity, bundle width, deposition ratio, deposition intensity, and deposition homogeneity are increased significantly. Additionally, an increase in spinneret thickness leads to a decrease in average nanofiber diameter. Specifically, increasing the spinneret diameter from 30 to 50 mm, pitch length from 20 to 40 mm, and reducing thickness from 3 to 1 mm increases productivity by 170%, 72%, and 32%, respectively. As a result of practical and modeling studies on helical spinnerets, the optimized parameters are determined as 1 mm thickness, 40 mm pitch length, and 50 mm diameter.

Concurrent tDCS-fMRI after stroke reveals link between attention network organization and motor improvement

Restoring motor function after stroke necessitates involvement of numerous cognitive systems. However, the impact of damage to motor and cognitive network organization on recovery is not well understood. To discover correlates of successful recovery, we explored imaging characteristics in chronic stroke subjects by combining noninvasive brain stimulation and fMRI. Twenty stroke survivors (6 months or more after stroke) were randomly assigned to a single session of transcranial direct current stimulation (tDCS) or sham during image acquisition. Twenty healthy subjects were included as controls. tDCS was limited to 10 min at 2 mA to serve as a mode of network modulation rather than therapeutic delivery. Fugl-Meyer Assessments (FMA) revealed significant motor improvement in the chronic stroke group receiving active stimulation (p = 0.0005). Motor changes in this group were correlated in a data-driven fashion with imaging features, including functional connectivity (FC), surface-based morphometry, electric field modeling and network topology, focusing on relevant regions of interest. We observed stimulation-related changes in FC in supplementary motor (p = 0.0029), inferior frontal gyrus (p = 0.0058), and temporo-occipital (p = 0.0095) areas, though these were not directly related to motor improvement. The feature most strongly associated with FMA improvement in the chronic stroke cohort was graph topology of the dorsal attention network (DAN), one of the regions surveyed and one with direct connections to each of the areas with FC changes. Chronic stroke subjects with a greater degree of motor improvement had lower signal transmission cost through the DAN (p = 0.029). While the study was limited by a small stroke cohort with moderate severity and variable lesion location, these results nevertheless suggest a top-down role for higher order areas such as attention in helping to orchestrate the stroke recovery process.

The Potential Changes and Stereocilia Movements during the Cochlear Sound Perception Process

Sound vibrations generate electrical signals called cochlear potentials, which can reflect cochlear stereocilia movement and outer hair cells (OHC) mechanical activity. However, because the cochlear structure is delicate and complex, it is difficult for existing measurement techniques to pinpoint the origin of potentials. This limitation in measurement capability makes it difficult to fully understand the contribution of stereocilia and transduction channels to cochlear potentials. In view of this, firstly, this article obtains the stereocilia movement generated by basilar membrane (BM) vibration based on the positional relationship between the various structures of the organ Corti. Secondly, Kirchhoff’s law is used to establish an electric field model of the cochlear cavity, and the stereocilia movement is embedded in the electric field by combining the gated spring model. Finally, a force-electric coupling mathematical model of the cochlea is established. The results indicated that the resistance variation between different cavities in the cochlea leads to a sharp tuning curve. As the displacement of the BM increased, the longitudinal potential along the cochlea continued to move toward the base. The decrease in stereocilia stiffness reduced the deflection angle, thereby reducing the transduction current and lymphatic potential.

Systematic cross-species comparison of prefrontal cortex functional networks targeted via transcranial magnetic stimulation

Abstract Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation method that safely modulates neural activity in vivo. Its precision in targeting specific brain networks makes TMS invaluable in diverse clinical applications. For example, TMS is used to treat depression by targeting prefrontal brain networks and their connection to other brain regions. Despite its widespread use, however, the underlying neural mechanisms of TMS are not completely understood. Non-human primates (NHPs) offer an ideal model to study TMS mechanisms through invasive electrophysiological recordings. As such, bridging the gap between NHP experiments and human applications is imperative to ensure translational relevance. Here, we systematically compare the TMS-targeted functional networks in the prefrontal cortex in humans and NHPs. We combine TMS electric field modeling in humans and macaques with resting-state functional magnetic resonance imaging (fMRI) data to compare the functional networks targeted via TMS across species. Distinct stimulation zones in macaque and human models arose, each exhibiting differences in impacted networks (macaque: Frontoparietal Network, Somatomotor Network; human: Frontoparietal Network, Default Network). We identified differences in brain gyrification and functional organization across species as the underlying cause of found network differences. The TMS-network profiles we identified will allow researchers to establish consistency in network stimulation across species, aiding in the translational efforts to develop improved TMS functional network targeting approaches.

Dielectrophoresis effect on anti-icing characteristics of superhydrophobic surface

In present study, icing experiment using semiconductor refrigeration method and 3D LBM (Lattice Boltzmann method) simulation by employing improved Shan-Chen model coupling the electric field model are conducted to confirm dielectrophoresis effect on freezing characterisitic of a sessile droplet at superhydrophobic surface. Tests are performed with the same droplet diameter of d = 2.6 mm, cold wall temperature of TW = -5 °C and ambient condition (TA = 20 °C, RH = 48%). The sessile droplet freezing process is recorded at different contact angles and electric field intensities. The improved Shan-Chen model with large density ratio (ρl/ρv = 36.55), electric field model and new wettability model are applied to simulate droplet deformation. The present results show that the droplet icing time has a positive relationship with contact angle and electric field intensity, the droplet icing time is extended up to about 40 times by the couple effect of superhydrophobic coating and the electric field. The size of droplet-solid interface and electric-induced convection are the key factors of anti-icing performance.

Toward methodologies for motor imagery enhancement: a tDCS-BCI study

ABSTRACT Motor imagery (MI) becomes a powerful rehabilitation tool, particularly when combined with brain–computer interfaces (BCI). Therefore, methods to improve MI accuracy are a trending topic in the BCI field. Here, we examined the effects of transcranial direct current stimulation (tDCS) and MI priming on the MI signature in an EEG-based MI-BCI triple-blind study. Thirty healthy younger adults participated in this study and were designated to one of two priming groups: A bimanual tracking task and a MI task as primers for MI-BCI. During the performance of the primer task, participants received anodal and sham tDCS in two randomized sessions with a one-week wash-out period between sessions. Subsequently, participants performed an EEG-driven BCI-MI task. EEG time–frequency analyses revealed that desynchronization of the Beta Region precedes desynchronization in the Alpha Region, implying that the Beta frequency band might be best-suited to extract MI signatures as it could lead to faster MI-BCI. Contrary to our hypotheses, no effect of tDCS or priming task on EEG activity during the BCI-MI task was found. Future research should carefully consider the added value of tDCS and priming tasks BCI performance improvement. Electric field modeling studies and high-definition tDCS motor cortex stimulation might be promising avenues.

Analysis of Transformer GSB Bushing Fault Causes Based on Finite Element Simulation

Abstract In response to a sudden explosion and fire fault during the operation of a GSB dry-type transformer bushing in a certain power grid company, based on the structural parameters of the bushing measured by the supplier and on-site, a reverse design of the capacitor core was carried out on the faulty bushing. Based on the measured parameters and reverse design results, a finite element simulation model of the bushing electric field and structural force field was established. Calculate the electric field distribution of the casing under normal operation, 60s power frequency withstand voltage, lightning impulse, operation impulse, and other operating conditions; Conduct finite element simulation of structural mechanics to calculate the stress distribution of the casing under conditions such as cantilever load and short circuit impact; Based on the discharge traces discovered during disassembly, simulation calculations were conducted by assuming the defect situation of the casing, and the electric field distribution of the casing under different defect types was quantitatively analyzed. The simulation calculation results of the electric field under various working conditions have verified that the occurrence of this fault is the result of multiple defects working together, providing quantitative support for fault analysis and providing a certain reference for the operation and maintenance of similar casings.

Neuromodulatory transcranial magnetic stimulation (TMS) changes functional connectivity proportional to the electric-field induced by the TMS pulse

ObjectiveTranscranial magnetic stimulation (TMS) can efficiently and robustly modulate synaptic plasticity, but little is known about how TMS affects functional connectivity (rs-fMRI). Accordingly, this project characterized TMS-induced rsFC changes in depressed patients who received 3 days of left prefrontal intermittent theta burst stimulation (iTBS). Methodsrs-fMRI was collected from 16 subjects before and after iTBS. Correlation matrices were constructed from the cleaned rs-fMRI data. Electric-field models were conducted and used to predict pre-post changes in rs-fMRI. Site by orientation heatmaps were created for vectors centered on the stimulation site and a control site (contralateral motor cortex). ResultsFor the stimulation site, there was a clear relationship between both site and coil orientation, and connectivity changes. As distance from the stimulation site increased, prediction accuracy decreased. Similarly, as eccentricity from the optimal orientation increased, prediction accuracy decreased. The systematic effects described above were not apparent in the heatmap centered on the control site. ConclusionsThese results suggest that rs-fMRI following iTBS changes systematically as a function of the distribution of electrical energy delivered from the TMS pulse, as represented by the e-field model. SignificanceThis finding lays the groundwork for future studies to individualize TMS targeting based on how predicted rs-fMRI changes might impact psychiatric symptoms.

The analytical model of time-harmonic electric field and impedance spectrum in the multilayered interdigital electrode structure

Accurately determining the time-harmonic electric field and impedance spectrum in the multilayered interdigital electrode (IDE) transducers with lossy dielectrics is essential for the design of the structure, the property estimation of the dielectric, and performance optimization. This paper presents an analytical model of the electric field and impedance within a multilayered interdigitated electrode (IDE) when subjected to alternating excitation through the method of separation of variables (MSV). The equivalent circuit of IDE is established, where the impedance is the parallel of capacitive coupling and resistive coupling between electrodes. The general solutions for the electric field and impedance involving arbitrary numbers and complex permittivities of the dielectric layers are analytically derived. However, due to the approximation of boundary conditions, these physical quantities cannot be accurately obtained by the conventional analytical method using conformal mapping technique (CMT) and partial capacitance technique (PCT). The proposed model exhibits proficiency in generating precise electric field images and impedance values that closely correspond with simulated data, even when accounting for the frequency-dependent characteristics of permittivity and conductivity in lossy dielectrics. Moreover, the approaches to improve the sensitivity of a traditional three-layered IDE-based sensor are demonstrated. For a three-layered IDE-based capacitive sensor, improving the sensitivity can be accomplished through the incorporation of a ground plane at the substrate's bottom and increasing the metallization rate. Conversely, it is recommended to reduce the metallization rate, increase substrate thickness, and remove the ground plane in order to enhance the sensitivity of the IDE-based impedance sensor. The experimental results demonstrate that the proposed model generates outstanding impedance spectra (involving capacitance spectra and resistance spectra) results for various metallization ratios and top layers. This exemplifies the model's potential for predicting, designing, and enhancing a complex multilayered IDE-based transducer to achieve precise and sensitive detection.

P‐167: A simulation model for charged particle motion in INK system

This paper provides a simulation model for the electronic paper display device, the model can quickly and efficiently simulate the initial steady state of the electronic ink system, thus improving the efficiency of device development. It mainly includes the following contents: Obtaining the parameters of the model, then the built‐in electric field strength is calculated through the model parameter information and the pre‐ constructed built‐in electric field model. The motion of each charged particle is simulated to obtain the simulation relationship between the display gray scale and the applied electric field force. Finally, it make various charged particles reach the force equilibrium state, so as to realize the simulation of the voltage‐gray scale relationship of electronic ink system.

Study on space charge accumulation characteristics of silicone elastomer under DC voltage

AbstractThe electric field distortion caused by the accumulation of space charge in the insulating dielectric is easy to lead to accelerated ageing and even breakdown. In this paper, the space charge characteristics and the interfacial electric field change with time of silicone elastomer under different polarity DC voltages are studied. The results show that the homopolar charge injection is dominant in the silicone elastomer, and the electric field threshold is less than 4 kV/mm. The accumulation of homopolar charge weakens the interfacial electric field, resulting in the reduction of charge injection, and the interfacial electric field and spatial charge distribution gradually stabilise over time. In addition, the electric field at the interface does not decrease to the charge injection field threshold when it reaches stability. A time‐varying electric field model of the metal‐dielectric interface under a direct current field is derived and a calculation method for the time of charge accumulation to stabilise is proposed, based on the Schottky injection model and the relation between current density and volume charge density. The accuracy of the model is verified by comparing it with the experimental results of the stability time of silicone elastomer. This model is used to estimate the time when space charge accumulation reaches stability by means of the electric field threshold and the interface barrier, which can provide reference for the experimental measurement of space charge.

Perspectives on Optimized Transcranial Electrical Stimulation Based on Spatial Electric Field Modeling in Humans.

Background: Transcranial electrical stimulation (tES) generates an electric field (or current density) in the brain through surface electrodes attached to the scalp. Clinical significance has been demonstrated, although with moderate and heterogeneous results partly due to a lack of control of the delivered electric currents. In the last decade, computational electric field analysis has allowed the estimation and optimization of the electric field using accurate anatomical head models. This review examines recent tES computational studies, providing a comprehensive background on the technical aspects of adopting computational electric field analysis as a standardized procedure in medical applications. Methods: Specific search strategies were designed to retrieve papers from the Web of Science database. The papers were initially screened based on the soundness of the title and abstract and then on their full contents, resulting in a total of 57 studies. Results: Recent trends were identified in individual- and population-level analysis of the electric field, including head models from non-neurotypical individuals. Advanced optimization techniques that allow a high degree of control with the required focality and direction of the electric field were also summarized. There is also growing evidence of a correlation between the computationally estimated electric field and the observed responses in real experiments. Conclusions: Computational pipelines and optimization algorithms have reached a degree of maturity that provides a rationale to improve tES experimental design and a posteriori analysis of the responses for supporting clinical studies.

A semi-automated pipeline for finite element modeling of electric field induced in nonhuman primates by transcranial magnetic stimulation

BackgroundTranscranial magnetic stimulation (TMS) is used to treat a range of brain disorders by inducing an electric field (E-field) in the brain. However, the precise neural effects of TMS are not well understood. Nonhuman primates (NHPs) are used to model the impact of TMS on neural activity, but a systematic method of quantifying the induced E-field in the cortex of NHPs has not been developed. New methodThe pipeline uses statistical parametric mapping (SPM) to automatically segment a structural MRI image of a rhesus macaque into five tissue compartments. Manual corrections are necessary around implants. The segmented tissues are tessellated into 3D meshes used in finite element method (FEM) software to compute the TMS induced E-field in the brain. The gray matter can be further segmented into cortical laminae using a volume preserving method for defining layers. ResultsModels of three NHPs were generated with TMS coils placed over the precentral gyrus. Two coil configurations, active and sham, were simulated and compared. The results demonstrated a large difference in E-fields at the target. Additionally, the simulations were calculated using two different E-field solvers and were found to not significantly differ. Comparison with existing methodsCurrent methods segment NHP tissues manually or use automated methods for only the brain tissue. Existing methods also do not stratify the gray matter into layers. ConclusionThe pipeline calculates the induced E-field in NHP models by TMS and can be used to plan implant surgeries and determine approximate E-field values around neuron recording sites.

Experimental Research of Ultrasonic Cavitation Evolution Mechanism and Model Optimization of RUREMM on Cylindrical Surface

Micro-pits are widely used in the aerospace and tribology sectors on cylindrical surfaces and electrochemical micromachining which are of great significance for the high material removal rate, absence of tool wear, and mechanical stress, while facing significant challenges such as stray corrosion and low machining efficiency. Aiming at the above problems, this paper proposes a comprehensive method called radial ultrasonic rolling electrochemical micromachining (RUREMM) in which an ultrasonic field has been added onto the cylindrical surface. First, a theoretical model was created to gain the rules of the formation and collapse of bubbles in the liquid medium. Second, to analyze the optimal size of the cathode electrode, the COMSOL5.2 simulation software was proposed to research the influence of the electric field on the different dimensions, and the influences of different parameters in RUREMM on material depth/diameter ratio and roughness are explored through processing experiments. Research results found that the cavitation bubble undergoes expansion, compression, collapse and oscillation, where the max deviation is less than 12.5%. The optimized size was chosen as 200 × 200 μm2 and an electrode spacing of 800 μm through a series of electric field model simulation analyses. Relevant experiments show that the minimum pits with a width of 212.4 μm, a depth of 21.8 μm, and a surface roughness (Ra) of 0.253 μm were formed due to the optimized parameters. The research results can offer theoretical references for fabricating micro-pits with enhanced surface quality and processing precision on cylindrical surfaces.