Engineering topics

Perez, G.

Publications and source records attributed to Perez, G..

3 records

DOE OSTI2024

Tuning the spontaneous exchange bias effect in La 1.5 Sr 0.5 CoMnO 6 with sintering temperature

Here, in this study, we present a study of the influence of microstructure on the magnetic properties of polycrystalline samples of the La 1.5 Sr 0.5 CoMnO 6 double perovskite, with primary attention to the spontaneous exchange bias effect, a fascinating recently discovered phenomena for which some materials exhibit unidirectional magnetic anisotropy after being cooled in zero magnetic fields. By sintering La 1.5 Sr 0.5 CoMnO 6 at different temperatures, we obtained samples with distinct average grain sizes, ranging from 1.54-6.65 μm. A detailed investigation of the material's structural, morphologic, electronic, and magnetic properties using x-ray powder diffraction, powder neutron diffraction, x-ray absorption near edge structure spectroscopy, scanning electron microscopy, and ac and dc magnetometry has revealed a systematic enhancement of the exchange bias effect with increasing the average grain size. This evolution is discussed in terms of changes in the material's porosity and grain morphology and its influence on the exchange couplings at the magnetic interfaces.

14 SOLAR ENERGY↗

DOE OSTI2022

New Horizons: Scalar and Vector Ultralight Dark Matter

The last decade has seen unprecedented effort in dark matter model building at all mass scales coupled with the design of numerous new detection strategies. Transformative advances in quantum technologies have led to a plethora of new high-precision quantum sensors and dark matter detection strategies for ultralight ($<10\,$eV) bosonic dark matter that can be described by an oscillating classical, largely coherent field. This white paper focuses on searches for wavelike scalar and vector dark matter candidates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

The Effect of Storm Direction on Flood Frequency Analysis

Abstract Storm direction modulates a hydrograph's magnitude and duration, thus having a potentially large effect on local flood risk. However, how changes in the preferential storm direction affect the probability distribution of peak flows remains unknown. We address this question with a novel Monte Carlo approach where stochastically transposed storms drive hydrologic simulations over medium and mesoscale watersheds in the Midwestern United States. Systematic rotations of these watersheds are used to emulate changes in the preferential storm direction. We found that the peak flow distribution impacts are scale‐dependent, with larger changes observed in the mesoscale watershed than in the medium‐scale watershed. We attribute this to the high diversity of storm patterns and the storms' scale relative to watershed size. This study highlights the potential of the proposed stochastic framework to address fundamental questions about hydrologic extremes when our ability to observe these events in nature is hindered by technical constraints and short time records.

Perez, G.↗