The galvanostatic intermittent titration technique (GITT) is widely used to evaluate solid-state diffusion coefficients in electrochemical systems. However, the existing analysis methods for GITT data require numerous assumptions, and the derived diffusion coefficients typically are not independently validated. To investigate the validity of the assumptions and derived diffusion coefficients, we employ a direct-pulse fitting method for interpreting the GITT data that involves numerically fitting an electrochemical pulse and subsequent relaxation to a one-dimensional, single-particle, electrochemical model coupled with non-ideal transport to directly evaluate diffusion coefficients. Our non-ideal diffusion coefficients, which are extracted from GITT measurements of the intercalation regime of FeS2 and independently verified through discharge predictions, prove to be 2 orders of magnitude more accurate than ideal diffusion coefficients extracted using conventional methods. We further extend our model to a polydisperse set of particles to show the validity of a single-particle approach when the modeled radius is proportional to the total volume-to-surface-area ratio of the system.
The rapidly increasing use of electronics in high-radiation environments and the continued evolution in transistor architectures and materials demand improved methods to characterize the potential damaging effects of radiation on device performance. Here, electron-beam-induced current is used to map hot-carrier transport in model metal-oxide semiconductor field-effect transistors irradiated with a 300 KeV focused He+ beam as a localized line spanning across the gate and bulk Si. By correlating the damage to the electronic properties and combining these results with simulations, the contribution of spatially localized radiation damage on the device characteristics is obtained. This identified damage, caused by the He+ beam, is attributed to localized interfacial Pb centers and delocalized positive fixed-charges, as surmised from simulations. Comprehension of the long-term interaction and mobility of radiation-induced damage are key for future design of rad-hard devices.
Bulk 14-nm FinFET technology was irradiated in a heavy-ion environment (42-MeV Si ions) to study the possibility of displacement damage (DD) in scaled technology devices, resulting in drive current degradation with increased cumulative fluence. These devices were also exposed to an electron beam, proton beam, and cobalt-60 source (gamma radiation) to further elucidate the physics of the device response. Annealing measurements show minimal to no 'rebound' in the ON-state current back to its initial high value; however, the OFF-state current 'rebound' was significant for gamma radiation environments. Low-temperature experiments of the heavy-ion-irradiated devices reveal increased defect concentration as the result for mobility degradation with increased fluence. Furthermore, the subthreshold slope (SS) temperature dependence uncovers a possible mechanism of increased defect bulk traps contributing to tunneling at low temperatures. Simulation work in Silvaco technology computer-aided design (TCAD) suggests that the increased OFF-state current is a total ionizing dose (TID) effect due to oxide traps in the shallow trench isolation (STI). The significant SS elongation and ON-state current degradation could only be produced when bulk traps in the channel were added. Heavy-ion irradiation on bulk 14-nm FinFETs was found to be a combination of TID and DD effects.
Digital computing is nearing its physical limits as computing needs and energy consumption rapidly increase. Analogue-memory-based neuromorphic computing can be orders of magnitude more energy efficient at data-intensive tasks like deep neural networks, but has been limited by the inaccurate and unpredictable switching of analogue resistive memory. Filamentary resistive random access memory (RRAM) suffers from stochastic switching due to the random kinetic motion of discrete defects in the nanometer-sized filament. In this work, this stochasticity is overcome by incorporating a solid electrolyte interlayer, in this case, yttria-stabilized zirconia (YSZ), toward eliminating filaments. Filament-free, bulk-RRAM cells instead store analogue states using the bulk point defect concentration, yielding predictable switching because the statistical ensemble behavior of oxygen vacancy defects is deterministic even when individual defects are stochastic. Both experiments and modeling show bulk-RRAM devices using TiO2-X switching layers and YSZ electrolytes yield deterministic and linear analogue switching for efficient inference and training. Bulk-RRAM solves many outstanding issues with memristor unpredictability that have inhibited commercialization, and can, therefore, enable unprecedented new applications for energy-efficient neuromorphic computing. Beyond RRAM, this work shows how harnessing bulk point defects in ionic materials can be used to engineer deterministic nanoelectronic materials and devices.
Ashby, David; Choi, Christopher S.; Edwards, Martin A.; Talin, A.A.; White, Henry S.; Dunn, Bruce S.
It is well established that the miniaturization of batteries has not kept pace with the miniaturization of electronics. Three-dimensional (3D) batteries, which were developed with the intent of improving microbattery performance, have had limited success because of fabrication challenges and material constraints. Solid-state, 3D batteries have been particularly susceptible to these shortcomings. In this paper, we demonstrate that the incorporation of a high-conductivity, solid electrolyte is the key to achieving a nonplanar solid-state battery with high areal capacity and high power density. The model 2.5D platform used in this study is a modification of the more typical 3D configuration in that it is comprised of a cathode array of pillars (3D) and a planar (two-dimensional, 2D) anode. This 2.5D geometry exploits the use of a high-conductivity, ionogel electrolyte (10-3 S cm-1), which interpenetrates the 3D electrode array. The 2.5D battery offers high areal energy densities from the post array, while the high-conductivity, solid electrolyte enables high power densities (3.7 mWh cm-2 at 2.8 mW cm-2). The reported solid-state 2.5D device exceeds the energy and power densities of any 3D solid-state system and the derived multiphysics model provides guidance for achieving significantly higher energy and power densities.