Temperature relaxation in strongly-coupled binary ionic mixtures

In shallow-water downward-refracting ocean environments, hydrophone measurements of shipping noise encode information about the seabed. In this study, neural networks are trained on synthetic data to predict seabed classes from multichannel hydrophone spectrograms of shipping noise. Specifically, ResNet-18 networks are trained on different combinations of synthetic inputs from one, two, four, and eight channels. The trained networks are then applied to measured ship spectrograms from the Seabed Characterization Experiment 2017 (SBCEX 2017) to obtain an effective seabed class for the area. Data preprocessing techniques and ensemble modeling are leveraged to improve performance over previous studies. The results showcase the predictive capability of the trained networks; the seabed predictions from the measured ship spectrograms tend towards two seabed classes that share similarities in the upper few meters of sediment and are consistent with geoacoustic inversion results from SBCEX 2017. This work also demonstrates how ensemble modeling yields a measure of precision and confidence in the predicted results. Furthermore, the impact of using data from multiple hydrophone channels is quantified. While the water sound speed in this experiment was only slightly upward refracting, we anticipate increased advantages of using multiple channels to train neural networks for more varied sound speed profiles.

The coupling between structural, electronic and magnetic degrees of freedom across the metal-insulator transition in V₂O₃ makes it hard to determine the main driving mechanism behind the transition. Specifically, the role of magnetism is debated and its interplay with the other transitions has not been established. To address this issue, this work uses a combination of muon spin relaxation/rotation, electrical transport and reciprocal space mapping which allows to correlate magnetic, electronic and structural degrees of freedom in strain-engineered V₂O₃ thin films. Evidence is found for a magnetic instability in the vicinity of the structural transition. This is manifested as a decrease in the antiferromagnetic moment in proximity to the structural and electronic transitions. Moreover, this work finds evidence for an onset of antiferromagnetic (AF) fluctuations in the rhombohedral phase even without a structural transition to the monoclinic phase. In samples where the transition is most strongly suppressed by strain, a depth-dependent magnetic state is observed. These results reveal the importance of an AF instability in the paramagnetic phase in triggering the metal-insulator transition and the crucial role of the structural transition in allowing for the formation of an ordered AF state.

Time Reversal (TR) is a signal processing technique that can be used to focus acoustic waves to a specific location in space, with most applications aiming to create an impulsive focus. This study instead aims to focus long-duration noise signals using TR. This paper seeks to generate higher amplitude noise at a desired location over an existing method of broadcasting equalized noise. Additionally, this paper explores various characteristics associated with focusing long duration noise using TR. The dependence of the focal amplitude on the duration of the focused signal is explored as well as the implications of using multiple sources when focusing noise. The focal amplitude decreases with longer duration and then levels off when the duration exceeds a few seconds. Coherent addition of focused noise is observed if all loudspeakers have coherent noise signals convolved with their reversed impulse responses. Lastly, focusing noise with a desired spectrum is explored.

We present an undergraduate optics instructional laboratory designed to teach skills relevant to a broad range of modern scientific and technical careers. In this laboratory project, students image a custom aperture using coherent diffraction imaging, while learning principles and skills related to digital image processing and computational imaging, including multidimensional Fourier analysis, iterative phase retrieval, noise reduction, finite dynamic range, and sampling considerations. After briefly reviewing these imaging principles, we describe the required experimental materials and setup for this project. Our experimental apparatus is both inexpensive and portable, and a software application we developed for interactive data analysis is freely available.

A sound power spectrum analysis has been conducted on a T-7A-installed F404 engine, for operating conditions spanning intermediate thrust to afterburner. From free-field pressure spectra at microphone arc arrays with radii of 38 and 76 m, sound power level spectra are calculated from surface integrals and assumed axisymmetric radiation. The spectral peak-frequency region, from ∼100–500 Hz, broadens with increasing engine conditions. When the power level spectra are plotted with Strouhal number, the spectral peak decreases with engine condition. Comparing this decrease with rocket data suggests that military jet noise radiation is becoming more rocket-like, especially at afterburner conditions.

Understanding the atomic structure of precipitate phases in shape memory alloys is critical to determining their structure–property relationships and developing high-performance shape memory alloys. However, experimental methods are limited in determining atomic configurations in cases where the number of atoms per unit cell is very high, or the phase is small (few nms). While density functional theory (DFT) can aid in the accurate determination of a phase’s crystallography, this is challenged by the number of candidate structures. Recently, a cubic phase was discovered during the heat treatment of a Hf-Ni-Ti alloy developed with improved tribological applications and rolling contact fatigue. We use DFT, machine learned interatomic potentials (MLIPs), and a genetic algorithm to identify likely configurations for the cubic phase. Likely candidate structures consistent with experimentally determined structural information were identified. Limitations of experimental microscopy methods, crystal simulation, and DFT-MLIP techniques are discussed.