Study of drift-field solar cells damaged by low-energy protons Monthly report, Oct. 15 - Nov. 19, 1965
Low energy proton damage to drift field solar cells
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Low energy proton damage to drift field solar cells
Drift-field structure for fabrication of radiation resistant solar cells by use of epitaxial growth techniques
Statistical analysis of gyroscopic drift rate data for computer simulation of inertial navigator output error
Drift instabilities and electron cyclotron oscillations for arbitrary plasma pressure
Syncom-II satellite drift rate in equatorial orbit used to define longitudinal dependence of earth gravitational field
Drift of inclined-orbit 24-hour satellite in earth gravity field through fourth order
Fabrication methods for lithium drifted surface barrier silicon detectors, discussing lithium diffusion, stain etching, preparation for and final etch
Program to measure horizontal drifts in lower and upper ionospheres
Automatic measurement of gain and zero drift characteristics of dc amplifier
Excitation and damping of drift waves in stable regime of ionized plasma radially confined by axial magnetic field
Drift field, field gradient and diffused impurity effects on minority carriers and quantum efficiency in silicon photocells
The Neutron star Interior Composition ExploreR (NICER) is set to be deployed on the International Space Station (ISS) in early 2017. It will use an array of 56 Silicon Drift Detectors (SDDs) to detect soft X-rays (0.2 - 12 keV) with 100 nanosecond timing resolution. Here we describe the e ort to calibrate the detectors in the lab primarily using a Modulated X-ray Source (MXS). The MXS that was customized for NICER provides more than a dozen emission lines spread over the instrument bandwidth, providing calibration measurements for detector gain and spectral resolution. In addition, the fluorescence source in the MXS was pulsed at high frequency to enable measurement of the delay due to charge collection in the silicon and signal processing in the detector electronics. A second chamber, designed to illuminate detectors with either 55Fe, an optical LED, or neither, provided additional calibration of detector response, optical blocking, and effectiveness of background rejection techniques. The overall ground calibration achieved total operating time that was generally in the range of 500-1500 hours for each of the 56 detectors.
Partial shading of a solar module can induce a set of cells within the module to operate under reverse bias. Studies have shown that metal halide perovskite solar cells with a wide variety of compositions and contacts exhibit interesting behavior in reverse bias that includes both reversible performance loss and non-reversible degradation. In this paper, an advanced drift-diffusion approach incorporating an electrochemical term to explain the short-circuit, open circuit and fill factor losses that are experimentally measured after prolonged reverse bias is used. It is shown that holes can tunnel into the perovskite due to sharp band bending near the contact, accumulate within the bulk of the perovskite absorber, and trigger the oxidation of halides to form neutral halogens. The density of neutral halogens is much higher in reverse bias because there are hardly any electrons available to reduce the iodine. The resulting halogens act as bulk recombination centers. While the interstitial halogen density does decay when the cell is operated in forward bias, permanent degradation can occur if the iodine diffuses out of the perovskite layer. Finally, the ways in which changing parameters such as the mobile ion density or the series resistance at the contact can influence device performance and stability are discussed.
Recently the drift-reduced Landau fluid six-field turbulence model within the BOUT++ framework has been upgraded. In particular, this new model employs a new normalization, adds a volumetric flux-driven source option, the Landau fluid closure for parallel heat flux and a Laplacian inversion solver which is able to capture $n$ = 0 axisymmetric mode evolution in realistic tokamak configurations. As we report here, these improvements substantially extended model's capability to study a wider range of tokamak edge phenomena, and are essential to build a fully self-consistent edge turbulence model capable of both transient (e.g., ELM, disruption) and transport time-scale simulations.
We propose an asymptotic-preserving (AP), uniformly convergent numerical scheme for the relativistic collisional Drift-Kinetic Equation (rDKE) to simulate runaway electrons in axisymmetric toroidal magnetic field geometries typical of tokamak devices. The approach is derived from an exact Green's function solution with numerical approximations of quantifiable impact, and results in a simple, two-step operator-split algorithm, consisting of a collisional Eulerian step, and a Lagrangian orbit-integration step with analytically prescribed kernels. The AP character of the approach is demonstrated by analysis of the dominant numerical errors, as well as by numerical experiments. We demonstrate the ability of the algorithm to provide accurate answers regardless of plasma collisionality on a circular axisymmetric tokamak geometry.
Here we introduce fluctuating hydrodynamics approaches on surfaces for capturing the drift-diffusion dynamics of particles and microstructures immersed within curved fluid interfaces of spherical shape. We take into account the interfacial hydrodynamic coupling, traction coupling with the surrounding bulk fluid, and thermal fluctuations. For fluid-structure interactions, we introduce Immersed Boundary Methods (IBM) and related Stochastic Eulerian-Lagrangian Methods (SELM) for curved surfaces. We use these approaches to investigate the statistics of surface fluctuating hydrodynamics and microstructures. For velocity autocorrelations, we find characteristic power-law scalings $τ^{-1}, τ^{-2}$, and plateaus can emerge. This depends on the physical regime associated with the geometry, surface viscosity, and bulk viscosity. This differs from the characteristic $τ^{-3/2}$ scaling for bulk three dimensional fluids. We develop theory explaining these observed power-laws associated with time-scales for dissipation within the fluid interface and coupling to the surrounding fluid. We then use our introduced methods to investigate a few example systems and roles of hydrodynamic coupling and thermal fluctuations including for the kinetics of passive particles and active microswimmers in curved fluid interfaces.
In this work we consider a relativistic drift-kinetic model for runaway electrons along with a Fokker–Planck operator for small-angle Coulomb collisions, a radiation damping operator, and a secondary knock-on (Boltzmann) collision source. Here, we develop a new scalable fully implicit solver utilizing finite volume and conservative finite difference schemes and dynamic mesh adaptivity. A new data management framework in the PETSc library based on the p4est library is developed to enable simulations with dynamic adaptive mesh refinement (AMR), distributed memory parallelization, and dynamic load balancing of computational work. This framework and the runaway electron solver building on the framework are able to dynamically capture both bulk Maxwellian at the low-energy region and a runaway tail at the high-energy region. To effectively capture features via the AMR algorithm, a new AMR indicator prediction strategy is proposed that is performed alongside the implicit time evolution of the solution. This strategy is complemented by the introduction of computationally cheap feature-based AMR indicators that are analyzed theoretically. Numerical results quantify the advantages of the prediction strategy in better capturing features compared with nonpredictive strategies; and we demonstrate trade-offs regarding computational costs. The robustness with respect to model parameters, algorithmic scalability, and parallel scalability are demonstrated through several benchmark problems including manufactured solutions and solutions of different physics models. We focus on demonstrating the advantages of using implicit time stepping and AMR for runaway electron simulations.