Breakdown Model Research Articles

Transferring Decomposed Tensors for Scalable Energy Breakdown Across Regions

Homes constitute roughly one-third of the total energy usage worldwide. Providing an energy breakdown – energy consumption per appliance, can help save up to 15% energy. Given the vast differences in energy consumption patterns across different regions, existing energy breakdown solutions require instrumentation and model training for each geographical region, which is prohibitively expensive and limits the scalability. In this paper, we propose a novel region independent energy breakdown model via statistical transfer learning. Our key intuition is that the heterogeneity in homes and weather across different regions most significantly impacts the energy consumption across regions; and if we can factor out such heterogeneity, we can learn region independent models or the homogeneous energy breakdown components for each individual appliance. Thus, the model learnt in one region can be transferred to another region. We evaluate our approach on two U.S. cities having distinct weather from a publicly available dataset. We find that our approach gives better energy breakdown estimates requiring the least amount of instrumented homes from the target region, when compared to the state-of-the-art.

On Polymers Nanocomposites: Electrical Treeing, Breakdown models and Related Simulations

On Polymers Nanocomposites: Electrical Treeing, Breakdown models and Related Simulations

On Polymers Nanocomposites: Electrical Treeing, Breakdown models and Related Simulations

This paper deals with polymer nanocomposites and their related breakdown mechanisms. Polymer nanocomposites seem to be a very promising alternative to conventional polymers regarding high voltage applications. Some developed breakdown models are discussed as well as the mechanism of treeing in such materials. Treeing simulation results are presented.

Phase‐Field Model of Electrothermal Breakdown in Flexible High‐Temperature Nanocomposites under Extreme Conditions

AbstractPolymer‐based dielectrics are attracting increasing attention due to their high‐density energy storage. However, mitigating the heat generation in real capacitors has been a challenge. Here an electrothermal breakdown phase‐field model is developed to fundamentally understand the thermal effects on the dielectric breakdown of polymer‐based dielectrics in real capacitor configurations including the increase in the dielectric loss and the decrease in the breakdown strength. While both enhancing the thermal conductivity and reducing the electrical conductivity of the polymer nanocomposites can reduce the thermal effects, it is found that reducing the electrical conductivity is more effective. This work is expected to not only stimulate attention to the thermal effects in polymer‐based dielectrics but also provide a fundamental guidance to mitigate the heat‐induced deterioration of breakdown strength.

Secondary electron emission influenced by oxidation on the aluminum surface: the roles of the chemisorbed oxygen and the oxide layer

A relationship between the apparent secondary electron yield () and the oxygen coverage/oxide layer thickness on an aluminum cathode is obtained in an experiment under a controlled environment. The apparent secondary electron yield () is deduced from the breakdown voltage between two parallel plate electrodes in a 360 mTorr argon environment using a simple Townsend breakdown model with the assumption that the variation of the apparent secondary electron yield is dominated by the variation of the argon ion induced processes. The oxygen coverage/oxide layer thickness on the aluminum cathode is measured by a semi in situ x-ray photoemission spectroscopy equipment which is directly attached to the discharge chamber. It is found that three phases exist: (1) in the monomonolayer regime, as the oxygen coverage increases from 0 to 0.3, decreases by nearly , (2) as the oxygen coverage increases from 0.3 to 1, keeps nearly constant, (3) as the oxide layer thickness increases from about 0.3 nm to about 1.1 nm, increases by . We propose that, in the submonolayer regime, the chemisorbed oxygen on the aluminum surface causes the decrease of by creating a local potential barrier, which reduces the Auger neutralization rate and the energy gained by the Auger electrons. In the multilayer regime, as the oxide layer grows in thickness, there are three proposed mechanisms which cause the increase of : (1) the work function decreases; (2) resonance neutralization and Auger de-excitation may exist. This is served as another channel for secondary electron production; (3) the kinetic energy of Auger electrons is increased on average, leading to a higher probability for electrons to overcome the surface potential barrier.

Magnetic susceptibility increases as diamagnetic molecules breakdown: Myelin digestion during multiple sclerosis lesion formation contributes to increase on QSM.

The pathological processes in the first weeks of multiple sclerosis (MS) lesion formation include myelin digestion that breaks chemical bonds in myelin lipid layers. This can increase lesion magnetic susceptibility, which is a potentially useful biomarker in MS patient management, but not yet investigated. To understand and quantify the effects of myelin digestion on quantitative susceptibility mapping (QSM) of MS lesions. Histological and QSM analyses on in vitro models of myelin breakdown and MS lesion formation in vivo. Acutely demyelinating white matter lesions from MS autopsy tissue were stained with the lipid dye oil red O. Myelin basic protein (MBP), a major membrane protein of myelin, was digested with trypsin. Purified human myelin was denatured with sodium dodecyl sulfate (SDS). QSM was performed on phantoms containing digestion products and untreated controls. In vivo QSM was performed on five MS patients with newly enhancing lesions, and then repeated within 2 weeks. 3D -weighted spoiled multiecho gradient echo scans performed at 3T. Region of interest analyses were performed by a biochemist and a neuroradiologist to determine susceptibility changes on in vitro and in vivo QSM images. Not applicable. MBP degradation by trypsin increased the QSM measurement by an average of 112 ± 37 ppb, in excellent agreement with a theoretical estimate of 111 ppb. Degradation of human myelin by SDS increased the QSM measurement by 23 ppb. As MS lesions changed from gadolinium enhancing to nonenhancing over an average of 15.8 ± 3.7 days, their susceptibility increased by an average of 7.5 ± 6.3 ppb. Myelin digestion in the early stages of MS lesion formation contributes to an increase in tissue susceptibility, detectable by QSM, as a lesion evolves from gadolinium enhancing to nonenhancing. 1 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1281-1287.

Two-dimensional nanowires on homoepitaxial interfaces: Atomic-scale mechanism of breakdown and disintegration

We present a model for hole-mediated spontaneous breakdown of ahomoepitaxial two-dimensional (2D) flat nanowire based exclusively on random, thermally-activated motion of atoms. The model suggests a consecutive three-step mechanism driving the rupture and complete disintegration of the nanowire on a crystalline surface. The breakdown scenario includes: (i) local narrowing of a part of the stripe to a monatomic chain, (ii) formation of a recoverable single vacancy or a 2D vacancy cluster that causes temporary nanowire rupture, (iii) formation of a non-recoverable 2D hole leading to permanent nanowire breakdown. These successive events in the temporal evolution of the nanowire morphology bring the nanowire stripe into an irreversible unstable state, leading to a dramatic change in its peculiar physical properties and conductivity. The atomistic simulations also reveal a strong increase of the nanowire lifetime with an enlargement of its width and open up a way for a fine atomic-scale control of the nanowire lifetime and structural, morphological and thermodynamic stability.

Pressure evolution and deformation of confined granular media during pneumatic fracturing.

By means of digital image correlation, we experimentally characterize the deformation of a dry granular medium confined inside a Hele-Shaw cell due to air injection at a constant overpressure high enough to deform it (from 50 to 250 kPa). Air injection at these overpressures leads to the formation of so-called pneumatic fractures, i.e., channels empty of beads, and we discuss the typical deformations of the medium surrounding these structures. In addition we simulate the diffusion of the fluid overpressure into the medium, comparing it with the Laplacian solution over time and relating pressure gradients with corresponding granular displacements. In the compacting medium we show that the diffusing pressure field becomes similar to the Laplace solution on the order of a characteristic time given by the properties of the pore fluid, the granular medium, and the system size. However, before the diffusing pressure approaches the Laplace solution on the system scale, we find that it resembles the Laplacian field near the channels, with the highest pressure gradients on the most advanced channel tips and a screened pressure gradient behind them. We show that the granular displacements more or less always move in the direction against the local pressure gradients, and when comparing granular velocities with pressure gradients in the zone ahead of channels, we observe a Bingham type of rheology for the granular paste (the mix of air and beads), with an effective viscosity μ_{B} and displacement thresholds ∇[over ⃗]P_{c} evolving during mobilization and compaction of the medium. Such a rheology, with disorder in the displacement thresholds, could be responsible for placing the pattern growth at moderate injection pressures in a universality class like the dielectric breakdown model with η=2, where fractal dimensions are found between 1.5 and 1.6 for the patterns.

Effects of the injected plasma on the breakdown process of the trigatron gas switch under low working coefficient

Based on the surface flashover discharge, the injected plasma was generated, and the effects on the breakdown process of the trigatron gas switch were studied in this paper. The breakdown model caused by the injected plasma under the low working coefficient (<0.7) was established. The captured framing images showed that the injected plasma distorted the electrical field of the gap between the frontier of the injected plasma and the opposite electrode, making it easier to achieve the breakdown critical criterion. The calculation results indicated that the breakdown delay time was mainly decided by the development of the injected plasma, as without considering the effects of the photo-ionization and the invisible expansion process, the breakdown delay time of the calculation results was 20% higher than the experimental results. The morphology of the injected plasma generated by polyethylene surface flashover was more stable and regular than ceramic, leading to a 30% lower breakdown delay time when the working coefficient is larger than 0.2, and the difference increased sharply when the working coefficient is lower than 0.2. This was significant for improving the trigger performance of the trigatron gas switch under low working coefficient.

Patterns of Regime Breakdown Since the French Revolution

We present a new dataset comprising more than 1900 regimes in 197 polities over the time period 1789-2016. We use this dataset to describe dierent historical patterns of regime duration globally, leveraging ne-grained measures on when regimes started and ended and a nuanced scheme of dierent modes of regime breakdown. To mention a few patterns, we display how the frequency of regime breakdown, and particular modes of breakdown, have followed cyclical rather than linear patterns across modern history and that the most common modes, overall, are coups d'etat and incumbent-guided transformations of regimes. Further, we evaluate whether selected economic and political-institutional features are systematically associated with breakdown. We nd robust evidence that low income levels, slow or negative economic growth, and having intermediate levels of democracy predict higher chances of regime breakdown, although these factors are more clearly related to regime breakdown during some periods of modern history than others. When disaggregating dierent models of breakdown, we nd notable dierences for these predictors, with low income levels, for example, being strongly related to regime breakdowns due to popular uprisings, whereas intermediate levels of democracy clearly predict regime breakdowns due to coups and incumbent-guided regime transitions.

Pattern transition from dense branching morphology to fractal for copper and β′ brass electrodeposition in thin gap geometry

Copper and β′ brass are electrodeposited in thin gap geometry and a clear transition from dense branching to fractal like pattern is observed with the variation of electric potential and concentration. The transition electric potential is 6V – 5V for copper and 25V for β′ brass. The explanation of the pattern transition is done first using the Laplacian growth as in the Di-electric Breakdown Model (DBM) and then on the basis of ion dynamics in terms of viscosity, ionic mobility, drift and thermal velocity. The fractal growth is more likely at higher electric potential as the electric field dominates and more likely to be dense branched at lower electric field when thermal motion dominates. This work inspires for further studies on modification of our model for the two ions electrodeposition and their compositional variation with different deposition parameters.

Linking “Micro” to “Macro” Models of State Breakdown to Improve Methods for Political Forecasting

Author(s): Turchin, Peter; Gavrilets, Sergey; Goldstone, Jack A. | Abstract: Three predictive problems bedevil our ability to foresee political crises and state breakdown: (1) how to tell when a previously stable state falls into a situation of hidden but dangerous instability; (2) how to tell, once a certain level of instability has appeared in the form of protests, riots, or regional rebellions, whether chaos will grow and accelerate into revolution or civil war, or if the protests are likely to be contained and dampen out; and (3) how to tell which individuals and groups are likely to be the main source of mobilization for radical movements, and whether opposition networks will link up, grow and spread, or be isolated and contained. Prior work has focused on each of these problems separately. However, all three issues are crucial to understanding and foreseeing conflict dynamics. These issues operate on different time-scales and require separate models. In this article we discuss how better models of each process could be developed and, crucially, integrated with data for a more effective prediction system. A major theoretical challenge for us is to link these different approaches in order to increase their predictive power. A major empirical challenge is to identify data (direct or proxy) that can be used to parameterize, validate, and test our models.

A Combined Electro-Thermal Breakdown Model for Oil-Impregnated Paper

The breakdown property of oil-impregnated paper is a key factor for converter transformer design and operation, but it is not well understood. In this paper, breakdown voltages of oil-impregnated paper were measured at different temperatures. The results showed that with the increase of temperature, electrical, electro-thermal and thermal breakdown occurred successively. An electro-thermal breakdown model was proposed based on the heat equilibrium and space charge transport, and negative differential mobility was introduced to the model. It was shown that carrier mobility determined whether it was electrical or thermal breakdown, and the model can effectively explain the temperature-dependent breakdown.

Stochastic modeling of breakdown at freeway merge bottleneck and traffic control method using connected automated vehicle

This paper proposes a novel breakdown probability model based on microscopic driver behavior for a freeway merge bottleneck. Extending Newell's car following model to describe the transition from free-flow to congested regimes, two elements of breakdown, trigger and propagation, are derived in terms of vehicle headway. Combining these elements, a general breakdown probability is derived in terms of various parameters related to driver behavior and traffic conditions – other than flow – that can be treated as constants or stochastic with probability distributions. The proposed model is validated with real data. It was found that the theoretical breakdown probability distribution accords well with the empirical counterpart within reasonable ranges of parameter values. Our model suggests that the breakdown probability (i) increases with flow (both mainline and merging) as expected, and the merging spacing, (ii) decreases with the merging speed and aggressive driver characteristics, and interestingly, (iii) increases with the deviation in headway. A proactive traffic control method to achieve uniform headway is developed considering low penetration rates of connected automated vehicle technologies.

Numerical simulation of turbulent spots generated by unstable wave packets in a hypersonic boundary layer

The generation of a turbulent spot by an unstable wave packet propagating in a Mach-6 flat-plate boundary layer is considered. The asymptotic shape of the wave packet is obtained in the far field from the excitation point using linear stability theory. Unsteady boundary conditions are formulated for direct numerical simulation. They allow for excitation of a well-developed wave packet with specified amplitude, skipping the linear growth stage. Robustness of these boundary conditions for modeling of the nonlinear breakdown of unstable wave packets into turbulent spots is examined.

Identifying models of dielectric breakdown strength from high-throughput data via genetic programming

The identification of models capable of rapidly predicting material properties enables rapid screening of large numbers of materials and facilitates the design of new materials. One of the leading challenges for computational researchers is determining the best ways to analyze large material data sets to identify models that can rapidly predict a given property. In this paper, we demonstrate the use of genetic programming to generate simple models of dielectric breakdown based on 82 representative dielectric materials. We identified the band gap Eg and phonon cut-off frequency ωmax as the two most relevant features, and new classes of models featuring functions of Eg and ωmax were uncovered. The genetic programming approach was found to outperform other approaches for generating models, and we discuss some of the advantages of this approach.

Modeling of gas breakdown and early transients of plasma evolution in cylindrical all-dielectric resonators

We report on the computational modeling of gas break down and evolution of plasma in an all-dielectric resonator structure. Two cylindrical dielectric resonators (DR) of diameter 25 mm with material relative permittivity of 172.5 separated by a 1 mm gap are observed to resonate in a strong constructive interference mode (CIM) at 1.47 GHz. The electric fields in the gap between the DRs are amplified to about 30 times the incident wave strength which leads to gas breakdown in argon at 10 Torr. The species densities in the bulk of plasma rise primarily due to the wave power addition into the plasma. As the species densities rise above 1017 m−3, the bulk plasma acts as a lossy material and the wave experiences significant damping through collisional losses. As plasma densities in the bulk rise to around 1018 m−3, the wave is damped significantly in the bulk, and a surface plasmon polariton (SPP) wave mode develops at the interface of plasma sheath and the DR surfaces. These surface waves are initiated due to a thin negative permittivity region of the plasma in the vicinity of the DR surface. The quasi-steady state operation of the resonator system depends on the propagation of the damped CIM in the bulk regions of the plasma, the SPP waves in the sheath region and the slower ambipolar diffusion process in plasma. Gas temperature rise in plasma is found to be small throughout the time scales considered and electrostatic fields are found to play an equally important role for large plasma densities in the sheath regions.

TDDB modeling depending on interfacial conditions in magnetic tunnel junctions

We investigated time-dependent dielectric breakdown (TDDB) modeling for MgO dielectrics with/without Mg insertion of MgO-based magnetic tunnel junctions (MTJs). The number of permanent trap sites at the no-Mg insertion interface was much larger than that at the Mg-inserted interface as determined by interval voltage stress (IVS) tests. The interfacial conditions related to trap sites at MgO dielectrics give rise to the different TDDB modeling. Here, we confirmed that the TDDB curves obtained from the constant voltage stress (CVS) tests for the Mg inserted interface case were well fitted by the power-law voltage V model, while the case of no-Mg inserted interface showed a good correlation to the 1/E model. The difference in the TDDB models related to interfacial conditions was understood based on theoretical and experimental results. Finally, we concluded that it is necessary to select an appropriate reliability model depending upon the presence or absence of the trap sites at dielectric interfaces.

Electron energy dissipation model of gate dielectric progressive breakdown in n- and p-channel field effect transistors

We report the data and a model showing that the energy loss experienced by the carriers flowing through breakdown spots is the primary cause of progressive breakdown spot growth. The experiments are performed in gate dielectrics of metal-oxide-semiconductor (MOS) devices subjected to accelerated high electric field constant voltage stress under inversion conditions. The model is analytical and contains few free parameters of clear physical meaning. This is compared to a large set of data on breakdown transients at various oxide thicknesses, stress voltages, and temperatures, both in cases of n-channel and p-channel transistors and polycrystalline Si/oxynitride/Si and metal gate/high k dielectric/Si gate stacks. The basic idea is that the breakdown transient is due to the growth of one or more filaments in the dielectric promoted by electromigration driven by the energy lost by the electrons traveling through the breakdown spots. Both cases of polycrystalline Si/oxynitride/Si and metal gate/high-k dielectric/Si MOS structures are investigated. The best fit values of the model to the data, reported and discussed in the paper, consistently describe a large set of data. The case of simultaneous growth of multiple progressive breakdown spots in the same device is also discussed in detail.

Negative Bias Temperature Instability and Gate Oxide Breakdown Modeling in Circuits With Die-to-Die Calibration Through Power Supply and Ground Signal Measurements

With the scaling of CMOS technology, negative bias temperature instability (NBTI) and gate oxide breakdown (GOBD) are serious issues for transistors. Normally, degradation due to NBTI and GOBD are modeled based on test structure data during process development and monitored with embedded test structures in product die. In this paper, we present a method to determine NBTI and GOBD model parameters through I/O measurements. This work targets products that do not include embedded test structures for wearout monitoring. The ground and power supply bounce signals are used for the calculation of delay and amplitude shifts, which in turn estimate threshold voltage shifts due to NBTI and leakage resistance decreases from gate dielectric degradation. From this data, the NBTI and GOBD parameters are estimated. We calculate the lifetime for each chip individually using calibrated NBTI and GOBD models. The methodology enables the extraction of NBTI and GOBD model parameters for individual chips, not just for the manufacturing process, and hence it becomes possible to differentiate chips that are more or less vulnerable to NBTI and GOBD.