Analytical Model of Optical-Field-Driven Subcycle Electron Tunneling Pulses from Two-Dimensional Materials.

We develop analytical models of optical-field-driven electron tunneling from the edge and surface of free-standing two-dimensional (2D) materials. We discover a universal scaling between the tunneling current density (J) and the electric field near the barrier (F): In(J/|F|ß) ∝ 1/|F| with ß values of 3/2 and 1 for edge emission and vertical surface emission, respectively. At ultrahigh values of F, the current density exhibits an unexpected high-field saturation effect due to the reduced dimensionality of the 2D material, which is absent in the traditional bulk material. Our calculation reveals the dc bias as an efficient method for modulating the optical-field tunneling subcycle emission characteristics. Importantly, our model is in excellent agreement with a recent experiment on graphene. Our results offer a useful framework for understanding optical-field tunneling emission from 2D materials, which are helpful for the development of optoelectronics and emerging petahertz vacuum nanoelectronics.

Modeling programmable drug delivery in bioelectronics with electrochemical actuation.

Drug delivery systems featuring electrochemical actuation represent an emerging class of biomedical technology with programmable volume/flowrate capabilities for localized delivery. Recent work establishes applications in neuroscience experiments involving small animals in the context of pharmacological response. However, for programmable delivery, the available flowrate control and delivery time models fail to consider key variables of the drug delivery system--microfluidic resistance and membrane stiffness. Here we establish an analytical model that accounts for the missing variables and provides a scalable understanding of each variable influence in the physics of delivery process (i.e., maximum flowrate, delivery time). This analytical model accounts for the key parameters--initial environmental pressure, initial volume, microfluidic resistance, flexible membrane, current, and temperature--to control the delivery and bypasses numerical simulations allowing faster system optimization for different in vivo experiments. We show that the delivery process is controlled by three nondimensional parameters, and the volume/flowrate results from the proposed analytical model agree with the numerical results and experiments. These results have relevance to the many emerging applications of programmable delivery in clinical studies within the neuroscience and broader biomedical communities.

An Analytical Model of IaaS Architecture for Determining Resource Utilization.

Cloud computing has become a major component of the modern IT ecosystem. A key contributor to this has been the development of Infrastructure as a Service (IaaS) architecture, in which users' virtual machines (VMs) are run on the service provider's physical infrastructure, making it possible to become independent of the need to purchase one's own physical machines (PMs). One of the main aspects to consider when designing such systems is achieving the optimal utilization of individual resources, such as processor, RAM, disk, and available bandwidth. In response to these challenges, the authors developed an analytical model (the ARU method) to determine the average utilization levels of the aforementioned resources. The effectiveness of the proposed analytical model was evaluated by comparing the results obtained by utilizing the model with those obtained by conducting a digital simulation of the operation of a cloud system according to the IaaS paradigm. The results show the effectiveness of the model regardless of the structure of the emerging requests, the variability of the capacity of individual resources, and the number of physical machines in the system. This translates into the applicability of the model in the design process of cloud systems.

Design Optimization of Piezocomposites Using a Homogenization Model: From Analytical Model to Experimentation.

In the process of activating non-conductive smart-structures using piezoelectric patches, one possible method is to add a conductive layer to ensure electrical contact of both electrodes of the ceramic. Therefore, depending on the stiffness and the thickness of this layer, changes in the overall piezoelectric properties lead to a loss in the electromechanical coupling that can be implemented. The purpose of this work is to study the impact of this added electrode layer depending on its thickness. A model of the effect of this layer on the piezoelectrical coefficients has been derived from the previous approach of Hashimoto and Yamagushi and successfully compared to experimental data. This global model computes the variation of all the piezoelectric coefficients, and more precisely of k31 or d31 for various brass electrode volumes relative to the ceramic volume. A decrease in the lateral electromechanical coupling factor k31 was observed and quantified. NAVY II PZT piezoelectric transducers were characterized using IEEE standard methods, with brass electrode thicknesses ranging from 50 to 400 microns. The model fits very well as shown by the results, leading to good expectations for the use of this design approach for actuators or sensors embedded in smart-structures.

Design and Validation of Single-Axis 3D-Printed Force Sensor Based on Three Nested Flexible Rings.

Force measurement is crucial in numerous engineering applications, while traditional force sensors often face problems such as elevated expenses or significant measurement errors. To tackle this issue, we propose an innovative force sensor employing three nested flexible rings fabricated through 3D additive manufacturing, which detects external forces through the displacement variations of flexible rings. An analytical model on the basis of the minimal energy method is developed to elucidate the force-displacement correlation with nonlinearity. Both FEM simulations and experiments verify the sensor's effectiveness. This sensor has the advantages of low expenses and easy manufacture, indicating promising prospects in a range of applications, including robotics, the automotive industry, and iatrical equipment.

Numerical study supplemented with simplified model on electrophoresis of a hydrophobic colloid incorporating finite ion size effects and ion-solvent interactions.

We consider a modified electrokinetic model to study the electrophoresis of a hydrophobic particle by considering the finite sized ions. The mathematical model adopted in this study incorporates the ion steric repulsion, ion-solvent interactions as well as Maxwell stress on the electrolyte. The dielectric permittivity and viscosity of the electrolyte is considered to vary with the local ionic volume fraction. Based on this modified model for the electrokinetics we have analyzed the electrophoresis in a single as well as mixture of electrolytes of monovalent and non- z : z $z:z$ electrolytes. The dependence of viscosity on local ionic volume fraction modifies the hydrodynamic drag as well as diffusivity of ions, which are ignored in existing studies on electrophoresis. A simplified model for electrophoresis of a hydrophobic particle incorporating the ion steric repulsion and ion-solvent interactions is developed based on the first-order perturbation on applied electric field. This simplified model is established to be efficient for a Debye layer thinner than the particle size and a smaller range of slip length. This model can be implemented for any number of ionic species as well as non- z : z $z:z$ electrolytes. It is established that the ion steric interactions and dielectric decrement creates a counterion saturation in the Debye layer leading to an enhanced mobility compared to the standard model. However, experimental data for non-dilute cases often under predicts the theoretically determined mobility. The present modified model fills this lacuna and demonstrate that the consideration of finite ion size modifies the medium viscosity and hence, ionic mobility, which in combination lowers the mobility value.

Insights on the variability of Cu filament formation in the SiO2electrolyte of quantized-conductance conductive bridge random access memory devices.

Conductive bridge random access memory devices such as Cu/SiO2/W are promising candidates for applications in neuromorphic computing due to their fast, low-voltage switching, multiple-conductance states, scalability, low off-current, and full compatibility with advanced Si CMOS technologies. The conductance states, which can be quantized, originate from the formation of a Cu filament in the SiO2electrolyte due to cation-migration-based electrochemical processes. A major challenge related to the filamentary nature is the strong variability of the voltage required to switch the device to its conducting state. Here, based on a statistical analysis of more than hundred fifty Cu/SiO2/W devices, we point to the key role of the activation energy distribution for copper ion diffusion in the amorphous SiO2. The cycle-to-cycle variability is modeled well when considering the theoretical energy landscape for Cu diffusion paths to grow the filament. Perspectives of this work point to developing strategies to narrow the distribution of activation energies in amorphous SiO2.

Clutter Effect Investigation on Co-Polarized Chipless RFID Tags and Mitigation Using Cross-Polarized Tags, Analytical Model, Simulation, and Measurement.

Chipless radio frequency identification (RFID) technology is expected to replace barcode technology due to its ability to read in non-line-of-sight (NLOS) situations, long reading range, and low cost. Currently, there is extensive research being conducted on frequency-coded (FC) co-polarized radar cross-section (RCS)-based tags, which are widely used. However, detecting co-polarized chipless RFID tags in cluttered environments is still a challenge, as confirmed by measuring two co-polarized tags in front of a perfect metal reflector (30.5cm×22.5cm). To address this challenge, a realistic mathematical model for a chipless RFID system has been developed that takes into account the characteristics of the reader and the tag, as well as reflections from cluttered objects. This extensive mathematical model developed for linear chipless RFID systems in clutter scenarios holds the potential to greatly assist researchers in their exploration of RCS-based tags. By relying solely on simulations, this model provides a tool to effectively analyze and understand RCS-based tags, ultimately simplifying the process of generating more authentic tag designs. This model has been simulated and verified with measurement results by placing a single flat metal reflector behind two co-polarized one-bit designs: a dipole array tag and a square patch tag. The results showed that the interfering signal completely overlaps the ID of the co-polarized tag, severely limiting its detectability. To solve this issue, the proposed solution involves reading the tag in cross-polarization mode by etching a diagonal slot in the square patch tag. This proposed tag provides high immunity to the environment and can be detected in front of both dielectric and metallic objects.

Temperature Dependency Model in Pressure Measurement for the Motion-Capturing Pressure-Sensitive Paint Method.

Pressure-sensitive paint (PSP) has received significant attention for capturing surface pressure in recent years. One major source of uncertainty in PSP measurements, temperature dependency, stems from the fundamental photophysical process that allows PSP to extract pressure information. The motion-capturing PSP method, which involves two luminophores, is introduced as a method to reduce the measurement uncertainty due to temperature dependency. A theoretical model for the pressure uncertainty due to temperature dependency is proposed and demonstrated using a static pressure measurement with an applied temperature gradient. The experimental validation of the proposed model shows that the motion-capturing PSP method reduces the temperature dependency by 37.7% compared to the conventional PSP method. The proposed model also proves that a PSP with zero temperature dependency is theoretically possible.

On the Impact of Multiple Access Interference in LTE-V2X and NR-V2X Sidelink Communications.

Developing radio access technologies that enable reliable and low-latency vehicular communications have become of the utmost importance with the rise of interest in autonomous vehicles. The Third Generation Partnership Project (3GPP) has developed Vehicle to Everything (V2X) specifications based on the 5G New Radio Air Interface (NR-V2X) to support connected and automated driving use cases, with strict requirements to fulfill the constantly evolving vehicular applications, communication, and service demands of connected vehicles, such as ultra-low latency and ultra-high reliability. This paper presents an analytical model for evaluating the performance of NR-V2X communications, with particular reference to the sensing-based semi-persistent scheduling operation defined in the NR-V2X Mode 2, in comparison with legacy sidelink V2X over LTE, specified as LTE-V2X Mode 4. We consider a vehicle platooning scenario and evaluate the impact of multiple access interference on the packet success probability, by varying the available resources, the number of interfering vehicles, and their relative positions. The average packet success probability is determined analytically for LTE-V2X and NR-V2X, taking into account the different physical layer specifications, and the Moment Matching Approximation (MMA) is used to approximate the statistics of the signal-to-interference-plus-noise ratio (SINR) under the assumption of a Nakagami-lognormal composite channel model. The analytical approximation is validated against extensive Matlab simulations that a show good accuracy. The results confirm a boost in performance with NR-V2X against LTE-V2X, particularly for high inter-vehicle distance and a large number of vehicles, providing a concise yet accurate modeling rationale for planning and adaptation of the configuration and parameter setup of vehicle platoons, without having to resort to extensive computer simulation or experimental measurements.

Estimating rainfall interception loss of three dominant shrub species in an oasis-desert ecotone using in situ measurements and the revised Gash analytical model.

Canopy interception loss affects the local water budget by removing a non-negligible proportion of rainfall from the terrestrial surface. Thus, quantifying interception loss is essential for thoroughly understanding the role of vegetation in the local hydrological cycle, especially in dryland ecosystems. However, sparse shrubs in dryland ecosystems have not been sufficiently studied, owing to time- and labor-intensive field experiments and challenging model parameterization. In this work, 4-year growing season field experiments on rainfall partitioning were conducted for three dominant shrub species (Haloxylon ammodendron, Nitraria sphaerocarpa, and Calligonum mongolicum) in an oasis-desert ecotone in northwestern China. The revised Gash analytical model was well parameterized, which reliably simulated the cumulative interception loss for sparse shrubs, and the validated model performed better for H. ammodendron, followed by C. mongolicum and N. sphaerocarpa, with relative errors of 8.4%, 15.4%, and 23.9%, respectively. The mean individual interception loss percentage for H. ammodendron (28.4%) was significantly higher than that for C. mongolicum (11.0%) and N. sphaerocarpa (10.9%) (p < 0.05), which could be ascribed to the higher canopy storage capacity and wet-canopy evaporation rate of H. ammodendron. For all shrub species, the majority proportion of interception loss occurred during canopy saturation and drying-out periods, accounting for approximately 79-85% of the cumulative interception loss. Overall, the mean local interception loss of three dominant shrub species in the ecotone removed nearly 17% of the corresponding cumulative rainfall during the growing season. These results not only provide methodological references for estimating the interception loss of sparse vegetation in dryland ecosystems, but also provide scientific insights for water resource management and ecosystem restoration in water-limited regions similar to the experimental site.

A Model for Material Metrics in Thermoelectric Thomson Coolers.

Thomson heat absorption corresponding to changes in the Seebeck coefficient with respect to temperature enables the design of thermoelectric coolers wherein Thomson cooling is the dominant term, i.e., the Thomson coolers. Thomson coolers extend the working range of Peltier coolers to larger temperature differences and higher electrical currents. The Thomson coefficient is small in most materials. Recently, large Thomson coefficient values have been measured attributed to thermally induced phase change during magnetic and structural phase transitions. The large Thomson coefficient observed can result in the design of highly efficient Thomson coolers. This work analyzes the performance of Thomson coolers analytically and sets the metrics for evaluating the performance of materials as their constituent components. The maximum heat flux when the Thomson coefficient is constant is obtained and the performance is compared to Peltier coolers. Three dimensionless parameters are introduced which determine the performance of the Thomson coolers and can be used to analyze the coefficient of performance, the maximum heat flux, and the maximum temperature difference of a Thomson cooler.

Investigation on the Direct Transfer of SVOCs from Source to Settled Dust: Analytical Model and Key Parameter Determination.

Settled dust is an important medium for semivolatile organic compound (SVOC) transport indoors. Understanding the mechanism of interaction between SVOCs and settled dust can greatly improve the exposure assessment. This study develops an analytical model to elucidate the mechanism of direct contact between SVOC sources and settled dust. The model incorporates the adsorption of SVOCs onto indoor surfaces, which was ignored in previous numerical models. Based on this model, a hybrid optimization method is applied to determine the key parameters of SVOC transport, i.e., the diffusion coefficient in the dust, the dust-air partition coefficient, and the chamber surface-air partition coefficient. Experiments of direct contact between SVOC source materials containing organophosphorus flame retardants (OPFRs) and settled dust were conducted in chambers. The key parameters were determined by performing curve fitting using data collected from the OPFR chamber tests and from the literature on phthalates. The reliability and robustness of the model and measurement method are demonstrated by the high fitting accuracy and sensitivity analysis. The obtained key parameters are more accurate than those from correlations in prior studies. Further analysis indicates that dust-air partition coefficient plays an important role and the adsorption effect on surfaces cannot be neglected for SVOC transport.

Analysis and Design of Single-Ended Resonant Converter for Wireless Power Transfer Systems.

Single-ended resonant converters such as Class-E inverters have been widely considered as a potential topology for small- and medium-power wireless power transfer (WPT) applications, which feature compact circuits, low switching losses, and cost benefits, as they only use a low-side switch with a simple gate driver. However, there remains a practical challenge in the design of voltage stress, efficiency, and power density. In this paper, a single-ended resonant converter with a primary parallel resonant-matching network is investigated to absorb the bulky input-choke inductors of the Class-E inverters into the coil inductance. The analytical expressions for all the converter parameters are derived based on time-domain resonant waveforms, including: (1) analysis of critical zero-voltage switching (ZVS) conditions and (2) power transfer capabilities under the given maximum switch voltage stress. Furthermore, this paper elaborates on the design methodology of the proposed single-ended resonant converters, and an optimal operating point is chosen to ensure soft-switching operation and rated power. Finally, the accuracy of the proposed model is verified by simulation and experimental results.

An Engineering Model of Magnetic Flux Density and Electromagnetic Force Density at the Structural Discontinuity within Transformer Cores.

The structural discontinuities in the form of air gaps in transformer cores cause the concentration of electromagnetic force, which is an important source of transformer vibration and noise. In this paper, an engineering model of magnetic flux density and electromagnetic force density on transformer core discontinuities is analytically developed. Based on a reasonable structural simplification and assumptions, magnetic flux density and electromagnetic force density are deduced as explicit functions of the geometric, material, and electrical excitation characteristics of the gap region and the transformer core. The accuracy of the established model is validated by the finite element method (FEM) combined with a magnetic measurement experiment. According to this engineering model, the electromagnetic force density can be reduced by decreasing the gap ratio and increasing the gap thickness to a reasonable level. The outcome of this paper can help to understand the physical mechanism of the electromagnetic force generated by core air gap discontinuities, which is meaningful for noise control and the condition monitoring of transformers.

Research on the Analytical Model of Improved Magnetic Flux Leakage Signal for the Local Stress Concentration Zone of Pipelines.

Local stress concentrations pose a significant hazard to the safe operation of pipelines. However, the classical analytical model of the magnetic flux leakage (MFL) signal is still unable to effectively quantitatively analyze and accurately evaluate the local stress concentration zone of a pipeline. In this paper, based on the Jiles-Atherton model of the magnetomechanical effect, the mathematical relationship between stress and the magnetization of ferromagnetic material under hysteresis conditions is introduced, and an improved analytical model of the MFL signal based on the magnetomechanical model is established. The influence law of stress intensity on the MFL signal in the local stress concentration zone of the pipeline is calculated and analyzed, and the theoretical calculation results are verified through experiments. Simulation and experimental results show that, considering the hysteresis condition, the stress causes a change in the hysteresis loop of the ferromagnetic material, and the magnetization strength of the material decreases with increasing stress; the effect of stress on the magnetization strength of ferromagnetic materials is most obvious when the external magnetic field is approximately 5 KA/m. The MFL signal on the surface of the local stress concentration zone of the pipe changes abruptly, and the amount of change in the axial amplitude and radial peak-to-peak value of the leakage signal of the pipe tends to increase with the increase in the stress intensity of the local stress concentration zone. A comparison of the analysis with the classical analytical model of the MFL signal shows that the improved analytical model of the MFL signal is more suitable for the quantification study of the local stress concentration zone of the pipeline.

Pulse-Modulation Eddy Current Evaluation of Interlaminar Corrosion in Stratified Conductors: Semi-Analytical Modeling and Experiments.

Interlaminar corrosion (ILC) poses a severe threat to stratified conductors which are broadly employed in engineering fields including aerospace, energy, etc. Therefore, for the pressing concern regarding the safety and integrity of stratified conductors, it is imperative to non-intrusively and quantitatively interrogate ILC via non-destructive evaluation techniques. In this paper, pulse-modulation eddy current (PMEC) for imaging and assessment of ILC is intensively investigated through theoretical simulations and experiments. A semi-analytical model of PMEC evaluation of ILC occurring at the interlayer of two conductor layers is established based on the extended truncated region eigenfunction expansion (ETREE) along with the efficient algorithm for the numerical computation of eigenvalues for reflection coefficients of the stratified conductor under inspection. Based on theoretical investigation, PMEC evaluation of ILC in testing samples are further scrutinized by using the PMEC imaging system built up for the experimental study. The theoretical and experimental results have revealed the feasibility of PMEC for imaging and evaluation of ILC in stratified conductors.

Long-Term Cost-Effectiveness of Smoking Cessation Interventions in People With Mental Disorders: A Dynamic Decision Analytical Model.

OBJECTIVES: People with mental disorders are more likely to smoke than the general population. The objective of this study is to develop a decision analytical model that estimates long-term cost-effectiveness of smoking cessation interventions in this population. METHODS: A series of Markov models were constructed to estimate average lifetime smoking-attributable inpatient cost and expected quality-adjusted life-years. The model parameters were estimated using a variety of data sources. The model incorporated uncertainty through probabilistic sensitivity analysis using Monte Carlo simulations. It also generated tables presenting incremental cost-effectiveness ratios of the proposed interventions with varying incremental costs and incremental quit rates. We used data from 2 published trials to demonstrate the model's ability to make projections beyond the observational time frame. RESULTS: The average smoker's smoking-attributable inpatient cost was 3 times higher and health utility was 5% lower than ex-smokers. The intervention in the trial with a statistically insignificant difference in quit rate (19% vs 25%; P=.2) showed a 45% to 49% chance of being cost-effective compared with the control at willingness-to-pay thresholds of £20 000 to £30 000/quality-adjusted life-years. The second trial had a significant outcome (quit rate 35.9% vs 15.6%; P<.001), and the corresponding probability of the intervention being cost-effective was 65%. CONCLUSIONS: This model provides a consistent platform for clinical trials to estimate the potential lifetime cost-effectiveness of smoking cessation interventions for people with mental disorders and could help commissioners direct resources to the most cost-effective programs. However, direct comparisons of results between trials must be interpreted with caution owing to their different designs and settings.

Improved analytical model for the relaxation process of aeolian sand transport.

The process from the initial sand movement to sand flux saturation is described as the relaxation of aeolian sand transport. For this relaxation process, most existing models distinguish the conditions with and without upwind sand flux, therefore lacking in generality. An improved analytical model is proposed in this paper, which incorporates the phenomena of "overshoot" and "equilibrium" and the concept of the region of initiation by fluid, and is able to unify the cases with and without upwind sand flux. Within the proposed model, a new definition of the saturation length is proposed based on the analogy between two damping oscillation models, and its constancy is physically interpreted and verified with wind tunnel experimental data. In comparison with the existing models, the proposed model agrees better with the measurements of the process of sand transport, thereby shedding light on the understanding of aeolian sand transport under complex circumstances.

Development and validation of an analytical model allowing accurate predictions of gamma and electron beam dose distributions in a water medical phantom.

The aim of this work was to study photon and electron dose distributions in a phantom filled with water using the Monte Carlo Geant4 tool for electron energies ranging from 1 to 21 MeV and for photon energies ranging from 1.25 MeV to 25 MeV, corresponding to conventional radiotherapy Linac energies. The results of the Geant4 calculations were validated based on the relevant experimental data previously published. The results obtained were fitted and analytical models of dose distributions were developed for gamma radiation and electrons. For each of these models, one-dimensional (including dose depth profiles as a function of the depth inside the phantom) and two-dimensional (including the dose distribution as a function of depth and lateral position inside the phantom) dose distributions have been considered. Results are presented for photons and electrons of various energies. The coefficient of determination [Formula: see text] illustrates an excellent match between the developed analytical model and the Geant4 results. It is demonstrated that the analytical models developed in the present study can be applied in various fields such as those used for calibration applications and radiation therapy. It is concluded that the analytical models developed allow for quick, easy and reliable clinical dose estimates and offer promising alternatives to the standard tools and methods used in radiotherapy for treatment planning.