Achieving controllable coupling of dopants in silicon is crucial for operating donor-based qubit devices, but it is difficult because of the small size of donor-bound electron wavefunctions. Here, we report the characterization of a quantum dot coupled to a localized electronic state and present evidence of controllable coupling between the quantum dot and the localized state. A set of measurements of transport through the device enable the determination that the most likely location of the localized state is consistent with a location in the quantum well near the edge of the quantum dot. Our results are consistent with a gate-voltage controllable tunnel coupling, which is an important building block for hybrid donor and gate-defined quantum dot devices.
The performance and reliability of many mechanical and electrical components depend on the integrity of po lymer - to - solid interfaces . Such interfaces are found in adhesively bonded joints, encapsulated or underfilled electronic modules, protective coatings, and laminates. The work described herein was aimed at improving Sandia's finite element - based capability to predict interfacial crack growth by 1) using a high fidelity nonlinear viscoelastic material model for the adhesive in fracture simulations, and 2) developing and implementing a novel cohesive zone fracture model that generates a mode - mixity dependent toughness as a natural consequence of its formulation (i.e., generates the observed increase in interfacial toughness wi th increasing crack - tip interfacial shear). Furthermore, molecular dynamics simulations were used to study fundamental material/interfa cial physics so as to develop a fuller understanding of the connection between molecular structure and failure . Also reported are test results that quantify how joint strength and interfacial toughness vary with temperature.
We want to organize a body of trajectories in order to identify, search for, classify and predict behavior among objects such as aircraft and ships. Existing compari- son functions such as the Fr'echet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as total distance traveled and distance be- tween start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally, these features can generally be mapped easily to behaviors of interest to humans that are searching large databases. Most of these geometric features are invariant under rigid transformation. We demonstrate the use of different subsets of these features to iden- tify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories, predict destination and apply unsupervised machine learning algorithms.
This report describes advances in electrolytes for lithium primary battery systems. Electrolytes were synthesized that utilize organosilane materials that include anion binding agent functionality. Numerous materials were synthesized and tested in lithium carbon monofluoride battery systems for conductivity, impedance, and capacity. Resulting electrolytes were shown to be completely non-flammable and showed promise as co-solvents for electrolyte systems, due to low dielectric strength.
Synthesis of ditopic imidazoliums was achieved using a modular step-wise procedure. The procedure itself is amenable to a wide array of functional groups that can be incorporated into the imidazolium architecture. The resulting compounds range from ditopic zwitterions to highly-soluble dicationic aromatics
Achieving practical exascale supercomputing will require massive increases in energy efficiency. The bulk of this improvement will likely be derived from hardware advances such as improved semiconductor device technologies and tighter integration, hopefully resulting in more energy efficient computer architectures. Still, software will have an important role to play. With every generation of new hardware, more power measurement and control capabilities are exposed. Many of these features require software involvement to maximize feature benefits. This trend will allow algorithm designers to add power and energy efficiency to their optimization criteria. Similarly, at the system level, opportunities now exist for energy-aware scheduling to meet external utility constraints such as time of day cost charging and power ramp rate limitations. Finally, future architectures might not be able to operate all components at full capability for a range of reasons including temperature considerations or power delivery limitations. Software will need to make appropriate choices about how to allocate the available power budget given many, sometimes conflicting considerations.
