Publications

Abstract not provided.

Mathematical models of Redox Flow Batteries (RFBs) can be used to analyze cell performance, optimize battery operation, and control the energy storage system efficiently. Among many other models, physics-based electrochemical models are capable of predicting internal states of the battery, such as temperature, state-of-charge, and state-of-health. In the models, estimating parameters is an important step that can study, analyze, and validate the models using experimental data. A common practice is to determine these parameters either through conducting experiments or based on the information available in the literature. However, it is not easy to investigate all proper parameters for the models through this way, and there are occasions when important information, such as diffusion coefficients and rate constants of ions, has not been studied. Also, the parameters needed for modeling charge-discharge are not always available. In this paper, an efficient way to estimate parameters of physics-based redox battery models will be proposed. This paper also demonstrates that the proposed approach can study and analyze aspects of capacity loss/fade, kinetics, and transport phenomena of the RFB system.

In situ Raman microscopy was used to study polysulfide speciation in the bulk ether electrolyte during the discharge and charge of a Li-S electrochemical cell to assess the complex interplay between chemical and electrochemical reactions in solution. During discharge, long chain polysulfides and the S3− radical appear in the electrolyte at 2.4 V indicating a rapid equilibrium of the dissociation reaction to form S3−. When charging, however, an increase in the concentration of all polysulfide species was observed. This highlights the importance of the electrolyte to sulfur ratio and suggests a loss in the useful sulfur inventory from the cathode to the electrolyte.

Containerization, or OS-level virtualization has taken root within the computing industry. However, container utilization and its impact on performance and functionality within High Performance Computing (HPC) is still relatively undefined. This paper investigates the use of containers with advanced supercomputing and HPC system software. With this, we define a model for parallel MPI application DevOps and deployment using containers to enhance development effort and provide container portability from laptop to clouds or supercomputers. In this endeavor, we extend the use of Sin- gularity containers to a Cray XC-series supercomputer. We use the HPCG and IMB benchmarks to investigate potential points of overhead and scalability with containers on a Cray XC30 testbed system. Furthermore, we also deploy the same containers with Docker on Amazon's Elastic Compute Cloud (EC2), and compare against our Cray supercomputer testbed. Our results indicate that Singularity containers operate at native performance when dynamically linking Cray's MPI libraries on a Cray supercomputer testbed, and that while Amazon EC2 may be useful for initial DevOps and testing, scaling HPC applications better fits supercomputing resources like a Cray.

We report real-time observations of a phase transition in the ionic solid CaF2, a model AB2 structure in high-pressure physics. Synchrotron x-ray diffraction coupled with dynamic loading to 27.7 GPa, and separately with static compression, follows, in situ, the fluorite to cotunnite structural phase transition, both on nanosecond and on minute time scales. Using Rietveld refinement techniques, we examine the kinetics and hysteresis of the transition. Our results give insight into the kinetic time scale of the fluorite-cotunnite phase transition under shock compression, which is relevant to a number of isomorphic compounds.

Sophisticated cyber attacks by state-sponsored and criminal actors continue to plague government and industrial infrastructure. Intuitively, partitioning cyber systems into survivable, intrusion tolerant compartments is a good idea. This prevents witting and unwitting insiders from moving laterally and reaching back to their command and control (C2) servers. However, there is a lack of artifacts that can predict the effectiveness of this approach in a realistic setting. We extend earlier work by relaxing simplifying assumptions and providing a new attacker-facing metric. In this article, we propose new closed-form mathematical models and a discrete time simulation to predict three critical statistics: probability of compromise, probability of external host compromise and probability of reachback. The results of our new artifacts agree with one another and with previous work, which suggests they are internally valid and a viable method to evaluate the effectiveness of cyber zone defense.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Sandia National Laboratories is the largest of the Department of Energy national laboratories with more than 13,000 staff spread across its two main campuses in New Mexico and California. For more than 60 years, the Sandia National Laboratories campus in Livermore, California has delivered cutting-edge science and technology solutions to resolve the nation’s most challenging and complex problems. As a multidisciplinary laboratory, Sandia draws from virtually every science and engineering discipline to address challenges in energy, homeland security, cybersecurity, climate, and biosecurity. Today, collaboration is vital to ensuring that the Lab stays at the forefront of science and technology innovation. Partnerships with industry, state, and local governments, and California universities help drive innovation and economic growth in the region. Sandia contributed to California’s regional and statewide economy with more than $145 million in contracts to California companies, $92 million of which goes to California small businesses. In addition, Sandia engages the community directly by running robust STEM education programs for local schools and administering community giving programs. Meanwhile, investments like the Livermore Valley Open Campus (LVOC), an innovation hub supported by LLNL and Sandia, help catalyze the local economy.

Individual donors in silicon chips are used as quantum bits with extremely low error rates. However, physical realizations have been limited to one donor because their atomic size causes fabrication challenges. Quantum dot qubits, in contrast, are highly adjustable using electrical gate voltages. This adjustability could be leveraged to deterministically couple donors to quantum dots in arrays of qubits. In this work, we demonstrate the coherent interaction of a 31P donor electron with the electron of a metal-oxide-semiconductor quantum dot. We form a logical qubit encoded in the spin singlet and triplet states of the two-electron system. We show that the donor nuclear spin drives coherent rotations between the electronic qubit states through the contact hyperfine interaction. This provides every key element for compact two-electron spin qubits requiring only a single dot and no additional magnetic field gradients, as well as a means to interact with the nuclear spin qubit.

We describe an all-optical lithography process that can make electrical contact to nanometer-precision donor devices fabricated in silicon using scanning tunneling microscopy (STM). This is accomplished by implementing a cleaning procedure in the STM that allows the integration of metal alignment marks and ion-implanted contacts at the wafer level. Low-temperature transport measurements of a patterned device establish the viability of the process.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.