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Phase transitions in high-purity zirconium under dynamic compression

Physical Review B

Greeff, C.W.; Brown, Justin L.; Velisavljevic, N.; Rigg, P.A.

We present results from ramp compression experiments on high-purity Zr that show the α→ω, ω→β, as well as reverse β→ω phase transitions. Simulations with a multiphase equation of state and phenomenological kinetic model match the experimental wave profiles well. While the dynamic α→ω transition occurs ∼9GPa above the equilibrium phase boundary, the ω→β transition occurs within 0.9 GPa of equilibrium. We estimate that the dynamic compression path intersects the equilibrium ω-β line at P=29.2GPa, and T=490K. The thermodynamic path in the interior of the sample lies ∼100K above the isentrope at the point of the ω→β transition. Approximately half of this dissipative temperature rise is due to plastic work, and half is due to the nonequilibrium α→ω transition. The inferred rate of the α→ω transition is several orders of magnitude higher than that measured in dynamic diamond anvil cell (DDAC) experiments in an overlapping pressure range. We discuss a model for the influence of shear stress on the nucleation rate. We find that the shear stress sji has the same effect on the nucleation rate as a pressure increase δP=cϵijsji/(ΔV/V), where c is a geometric constant ∼1 and ϵij are the transformation shear strains. The small fractional volume change ΔV/V≈0.1 at the α→ω transition amplifies the effect of shear stress, and we estimate that for this case δP is in the range of several GPa. Correcting our transition rate to a hydrostatic rate brings it approximately into line with the DDAC results, suggesting that shear stress plays a significant role in the transformation rate.

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TYPE Journal Article YEAR 2022
DOIOSTIScopus

Federated Learning and Differential Privacy: What might AI-Enhanced co-design of microelectronics learn?

Eugenio, Evercita

Data is a valuable commodity, and it is often dispersed over multiple entities. Sharing data or models created from the data is not simple due to concerns regarding security, privacy, ownership, and model inversion. This limitation in sharing can hinder model training and development. Federated learning can enable data or model sharing across multiple entities that control local data without having to share or exchange the data themselves. Differential privacy is a conceptual framework that brings strong mathematical guarantee for privacy protection and helps provide a quantifiable privacy guarantee to any data or models shared. The concepts of federated learning and differential privacy are introduced along with possible connections. Lastly, some open discussion topics on how federated learning and differential privacy can tied to AI-Enhanced co-design of microelectronics are highlighted.

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TYPE Other Report YEAR 2022
DOIOSTI

Front-End Design for SiPM-Based Monolithic Neutron Double Scatter Imagers

Sensors

Cates, Joshua W.; Steele, John T.; Balajthy, Jon A.; Negut, Victor; Hausladen, Paul; Ziock, Klaus; Brubaker, Erik B.

Neutron double scatter imaging exploits the kinematics of neutron elastic scattering to enable emission imaging of neutron sources. Due to the relatively low coincidence detection efficiency of fast neutrons in organic scintillator arrays, imaging efficiency for double scatter cameras can also be low. One method to realize significant gains in neutron coincidence detection efficiency is to develop neutron double scatter detectors which employ monolithic blocks of organic scintillator, instrumented with photosensor arrays on multiple faces to enable 3D position and multi-interaction time pickoff. Silicon photomultipliers (SiPMs) have several advantageous characteristics for this approach, including high photon detection efficiency (PDE), good single photon time resolution (SPTR), high gain that translates to single photon counting capabilities, and ability to be tiled into large arrays with high packing fraction and photosensitive area fill factor. However, they also have a tradeoff in high uncorrelated and correlated noise rates (dark counts from thermionic emissions and optical photon crosstalk generated during avalanche) which may complicate event positioning algorithms. We have evaluated the noise characteristics and SPTR of Hamamatsu S13360-6075 SiPMs with low noise, fast electronic readout for integration into a monolithic neutron scatter camera prototype. The sensors and electronic readout were implemented in a small-scale prototype detector in order to estimate expected noise performance for a monolithic neutron scatter camera and perform proof-of-concept measurements for scintillation photon counting and three-dimensional event positioning.

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TYPE Journal Article YEAR 2022
DOIOSTIScopus

Electrical-Discharge-Machining Contamination Removal from Metal Additively Manufactured Components

Banga, Dhego O.; Chames, Jeffery M.; Yee, Joshua K.; Jankowski, Alan F.

The use of an electrochemical dissolution process is shown to remove the recast layer contamination from the surfaces of electrical-discharge-machining cut components, as well as the interior exposed surfaces of the structure. The solution chemistry, cell potential, and exposure time are all relevant interdependent variables. Optimization of the electrode geometry should be made for each type of component. For the case of Cu-Zn recast contamination of 300-series alloy components, surface composition analysis indicates that complete electrochemical dissolution is achieved using a dilute solution of nitric acid (HNO3). For example, electrochemical dissolution of the Cu-Zn recast is accomplished at 1.2 V cell potential using a 20% nitric solution and an exposure time of 4 h. The use of a nitric acid bath was specifically chosen since it’s chemically compatible and will not degrade the host alloy or the component. In sum, an electrochemically driven dissolution process can be tailored to remove of the recast contamination without affecting the integrity of the host component structure and its dimensional tolerances.

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TYPE SAND Report YEAR 2022
DOIOSTI

Molecular Inclusion of Small Aging Products into the Hexanitrohexaazaisowurtzitane (CL-20) Lattice: Part I, Infrared Spectra

Propellants, Explosives, Pyrotechnics

Beste, Ariana B.; Alam, Mary K.

Accelerated aging studies of β CL-20 thin films deposited on glass surfaces in different environments (N2, air, air/water) were conducted. Samples were analyzed with attenuated total reflectance infrared (ATR-IR) spectroscopy. Spectral features of molecular lattice inclusions in CL-20 films aged in an air/water environment were observed. The features occurred after β CL-20 polymorph transformation to α CL-20 and were accompanied by the appearance of lattice water peaks. To assist ATR-IR peak assignment, density functional theory studies were performed, and IR spectra of α CL-20 lattice inclusions of small molecules that were identified as degradation products of CL-20 were computed. Simulated spectra of NO2, HNCO, N2O, and CO2 incorporated into partially hydrated α CL-20 matched the experimental spectrum of β CL-20 thin films aged in air/water.

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TYPE Journal Article YEAR 2022
DOIOSTIScopus

Graph theory and nighttime imagery based microgrid design

Journal of Renewable and Sustainable Energy

Lugo-Alvarez, Melvin; Kleissl, Jan; Khurram, Adil; Lave, Matthew S.; Jones, Christian B.

Reducing the duration and frequency of blackouts in remote communities poses an engineering challenge for grid operators. Outage effects can also be mitigated locally through microgrids. This paper develops a systematic procedure to account for these challenges by creating microgrids prioritizing high value assets within vulnerable communities. Nighttime satellite imagery is used to identify vulnerable communities. Using an asset classification and rating system, multi-Asset clusters within these communities are prioritized. Infrastructure data, geographic information systems, satellite imagery, and spectral clustering are used to form and rank microgrid candidates. A microgrid sizing algorithm is included to guide through the microgrid design process. An application of the methodology is presented using real event, location, and asset data.

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TYPE Journal Article YEAR 2022
DOIOSTIScopus

A Tanks-in-Series Approach to Estimate Parameters for Lithium-Ion Battery Models

Journal of the Electrochemical Society

Kolluri, Suryanarayana; Mittal, Prateek; Subramaniam, Akshay; Preger, Yuliya P.; De Angelis, Valerio D.; Ramadesigan, Venkatasailanathan; Subramanian, Venkat R.

Advanced Battery Management Systems (BMS) play a vital role in monitoring, predicting, and controlling the performance of lithium-ion batteries. BMS employing sophisticated electrochemical models can help increase battery cycle life and minimize charging time. However, in order to realize the full potential of electrochemical model-based BMS, it is critical to ensure accurate predictions and proper model parameterization. The accuracy of the predictions of an electrochemical model is dependent on the accuracy of its parameters, the values of which might change with battery cycling and aging. Parameter estimation for an electrochemical model is generally challenging due to the nonlinear nature and computational complexity of the model equations. To this end, this work utilizes the recently proposed Tanks-in-Series model for Li-ion batteries (J.Electrochem. Soc., 167, 013534 (2020)) to perform parameter estimation. The Tanks-in-Series approach allows for substantially faster parameter estimation compared to the original pseudo two-dimensional (p2D) model. The objective of this work is thus to demonstrate the gain in computational efficiency from the Tanks-in-Series approach. A sensitivity analysis of model parameters is also performed to benchmark the fidelity of the Tanks-in-Series model.

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TYPE Journal Article YEAR 2022
DOIOSTIScopus
Results 5401–5500 of 96,771
Results 5401–5500 of 96,771