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All sources NASA NTRS DOE OSTI

DOE OSTI2023

Design and simulation of multilayer coatings for a multi-channel Wolter-like x-ray imager with large field of view and high resolution

X-ray diagnostics are key instruments for understanding the physics behind inertial confinement fusion experiments. We report on the multilayer design optimization for the Toroidal X-ray Imager (TXI), a hard x-rays microscope instrument designed by Commissariat à l’énergie atomique (CEA) and Laboratoire Charles Fabry (LCF) to be installed on the National Ignition Facility. TXI includes six channels designed for three different energy bands centered on 8.7, 13, and 17.5 keV. Each channel is made up of two toroidal mirrors arranged in a Wolter-like configuration. The required field of view is 800 × 400 µm2, and the resolution should be better than 5 µm. In addition, we seek to estimate the spatial distribution of the temperature, which requires no spectral overlap of the different energy bands and a good spectral homogeneity of the image produced. The development of the multilayer coatings was performed in a two-step method. First, the coatings were optimized to obtain proper energy bands. Then, an x-ray tracing code was used to calculate the integrated optical response of each channel and adjust the response of the mirror to fulfill the requirements. To fulfill all the specifications, we propose an original design using a combination of two aperiodic coatings, one with a narrow bandwidth and the other one with a larger bandwidth.

hard x-rays↗

DOE OSTI2023

Efficient multi-scale representation of visual objects using a biologically plausible spike-latency code and winner-take-all inhibition

Deep neural networks have surpassed human performance in key visual challenges such as object recognition, but require a large amount of energy, computation, and memory. In contrast, spiking neural networks (SNNs) have the potential to improve both the efficiency and biological plausibility of object recognition systems. Here we present a SNN model that uses spike-latency coding and winner-take-all inhibition (WTA-I) to efficiently represent visual stimuli using multi-scale parallel processing. Mimicking neuronal response properties in early visual cortex, images were preprocessed with three different spatial frequency (SF) channels, before they were fed to a layer of spiking neurons whose synaptic weights were updated using spike-timing-dependent-plasticity. We investigate how the quality of the represented objects changes under different SF bands and WTA-I schemes. We demonstrate that a network of 200 spiking neurons tuned to three SFs can efficiently represent objects with as little as 15 spikes per neuron. Furthermore, studying how core object recognition may be implemented using biologically plausible learning rules in SNNs may not only further our understanding of the brain, but also lead to novel and efficient artificial vision systems.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1993

Voyager Photometry of Saturn's A Ring

Saturn's A Ring samples a wide range of dynamical environments, from the relatively unperturbed, optically thick inner region to the outer part of the ring, which contains numerous density waves. We analyze Voyager images of the A Ring to determine how the reflectivity of different radial regions varies with lighting and viewing geometry. We model our data with a classical radiative transfer code that includes the illumination of the rings by the Sun and Saturn. The particles in the inner and mid-A Ring have Bond albedos near 0.5 and are more backscattering than satellites of comparable albedo. The region outside the Encke Gap becomes progressively less backscattering with increasing radius. Particle properties change abruptly outside the Keeler Gap; particles here have an albedo near 0.6 and a Lambert-like phase function. In contrast with previous suggestions, the abundance of free, submicrometer "dust" is small throughout the entire A Ring; this conclusion holds even in the outermost A Ring, which is strongly perturbed by density waves. Models derived from low-phase data, assuming only macroscopic particles, correctly predict the highphase reflectivity of the outer A Ring and individual strong density waves in the mid-A Ring. However, the inner and mid-A Ring are typically darker at high phase by a factor of two than our models predict. This discrepancy may be due to the reduced multiple scattering from a layer in which the particles are more closely packed. We have also studied the quadrupole azimuthal brightness asymmetry of the A Ring. The asymmetry has a full amplitude of 35% in the mid-A Ring in low-phase Voyager 2 images. We present results on its behavior and possible implications for the structure of the rings. Finally, we compare our results with studies using other data sets to synthesize our current understanding of the nature of the A Ring.

Dones, Luke↗

DOE OSTI2023

TDCOSMO. X. Automated modeling of nine strongly lensed quasars and comparison between lens-modeling software

When strong gravitational lenses are to be used as an astrophysical or cosmological probe, models of their mass distributions are often needed. We present a new, time-efficient automation code for the uniform modeling of strongly lensed quasars with GLEE, a lens-modeling software for multiband data. By using the observed positions of the lensed quasars and the spatially extended surface brightness distribution of the host galaxy of the lensed quasar, we obtain a model of the mass distribution of the lens galaxy. We applied this uniform modeling pipeline to a sample of nine strongly lensed quasars for which images were obtained with the Wide Field Camera 3 of the Hubble Space Telescope. The models show well-reconstructed light components and a good alignment between mass and light centroids in most cases. We find that the automated modeling code significantly reduces the input time during the modeling process for the user. The time for preparing the required input files is reduced by a factor of 3 from ~3 h to about one hour. The active input time during the modeling process for the user is reduced by a factor of 10 from ~ 10 h to about one hour per lens system. This automated uniform modeling pipeline can efficiently produce uniform models of extensive lens-system samples that can be used for further cosmological analysis. A blind test that compared our results with those of an independent automated modeling pipeline based on the modeling software Lenstronomy revealed important lessons. Quantities such as Einstein radius, astrometry, mass flattening, and position angle are generally robustly determined. Other quantities, such as the radial slope of the mass density profile and predicted time delays, depend crucially on the quality of the data and on the accuracy with which the point spread function is reconstructed. Better data and/or a more detailed analysis are necessary to elevate our automated models to cosmography grade. Nevertheless, our pipeline enables the quick selection of lenses for follow-up and further modeling, which significantly speeds up the construction of cosmography-grade models. This important step forward will help us to take advantage of the increase in the number of lenses that is expected in the coming decade, which is an increase of several orders of magnitude.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Octofitter: Fast, Flexible, and Accurate Orbit Modeling to Detect Exoplanets

As next-generation imaging instruments and interferometers search for planets closer to their stars, they must contend with increasing orbital motion and longer integration times. These compounding effects make it difficult to detect faint planets but also present an opportunity. Increased orbital motion makes it possible to move the search for planets into the orbital domain, where direct images can be freely combined with the radial velocity and proper motion anomaly, even without a confirmed detection in any single epoch. In this paper, we present a fast and differentiable multimethod orbit-modeling and planet detection code called Octofitter. This code is designed to be highly modular and allows users to easily adjust priors, change parameterizations, and specify arbitrary function relations between the parameters of one or more planets. Octofitter further supplies tools for examining model outputs including prior and posterior predictive checks and simulation-based calibration. We demonstrate the capabilities of Octofitter on real and simulated data from different instruments and methods, including HD 91312, simulated JWST/NIRISS aperture masking interferometry observations, radial velocity curves, and grids of images from the Gemini Planet Imager. We show that Octofitter can reliably recover faint planets in long sequences of images with arbitrary orbital motion. This publicly available tool will enable the broad application of multiepoch and multimethod exoplanet detection, which could improve how future targeted ground- and space-based surveys are performed. Finally, its rapid convergence makes it a useful addition to the existing ecosystem of tools for modeling the orbits of directly imaged planets.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Root responses to warming and hurricane disturbances in a wet tropical forest of Puerto Rico: R code and data

The purpose of this data was to generate a scientific article that describes the responses of tropical roots to a warming experiment and to the effect of two consecutive hurricanes in Puerto Rico (Yaffar et al. in review). This data is from 10 months of minirhizotron images taken every 2 weeks at the experimental warming Tropical Responses to Altered Climate Experiment (TRACE) plots in Puerto Rico before and after Hurricanes Irma and Maria. This project has 3 warmed plots (plot 2,4,6) and 3 control plots (plot 1,3,5) with 2 minirhizotron tubes at each plot. As part of the data, there is also root data taken from cores and in-growth cores. Additionally, there is soil nutrient concentration data, soil microclimate, total leaf area, and canopy openness taken by Reed et al. 2020, and the TRACE census. Data files are in CSV format and the R code included in this package can be used with R 3.4.4 (R Core Team and contributors worldwide).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

4D Imaging of ZnO-Coated Nanoporous Al 2 O 3 Aerogels by Chemically Sensitive Ptychographic Tomography: Implications for Designer Catalysts

The 3D chemical structure (4D spectromicroscopy) of nanoporous Al 2 O 3 aerogels coated with ZnO by atomic layer deposition (ALD) was studied by multienergy scanning transmission X-ray microscopy. These materials are representative of a class of designer catalysts in which the nanoporous support is prepared separately from the active catalyst material, which is subsequently introduced by ALD, thereby allowing independent optimization of the morphology, chemistry, and spatial distribution of the support and catalyst. The samples studied were prepared by Ga ion and Xe plasma focused ion beam (FIB) milling as well as drop casting from water suspension. Zn L and Al K edge spectra of six samples with three different ZnO loadings were measured to investigate how loading and different sample preparation methods affect the 3D distribution of the ZnO and Al 2 O 3 . Scanning transmission X-ray microscopy (STXM) and ptychographic imaging at two energies each at the Zn L 3 and Al K edge were measured. The ptychography data were analyzed by using the SHARP reconstruction code to generate quantitative 2D chemical maps of the Al 2 O 3 and the ZnO. The STXM and ptychography maps were then measured at a sequence of tilt angles, covering up to 160° of rotation. The 3D structure of the ZnO and Al 2 O 3 was derived from the tilt series data by tomographic reconstruction using a compressed sensing algorithm. A twodimensional spatial resolution (half-period) of 6 nm, measured by Fourier ring correlation, and a 3D spatial resolution (half-period) of 9 nm, measured by Fourier shell correlation, were achieved when using the COSMIC beamline at the Advanced Light Source (ALS). The results show that for all of the ZnO loadings studied there is nonuniform coverage of the ZnO on the Al 2 O 3 aerogel framework. In addition, we found that both FIB methods create sample artifacts, although the distortion was less with Xe plasma than Ga ion FIB.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Simulations of coherent scattering experiments at storage ring synchrotron radiation sources in the hard x-ray range

Detailed simulations of experiments carried out at modern light sources are directly related to the most efficient and productive use of these facilities for research in multiple branches of science and technology. The “Synchrotron Radiation Workshop” computer code with its Python interface, and Sirepo web-browser-based graphical user interface, currently supports physical optics simulations of coherent X-ray scattering and imaging experiments on user-defined virtual samples. We present examples of simulations of coherent scattering experiments that are typically performed at the Coherent Hard X-ray beamline at Brookhaven National Laboratory’s (BNL) National Synchrotron Light Source II. We also present several comparisons of the simulations with the results of actual coherent X-ray scattering experiments with nano-fabricated test samples produced at BNL’s Center for Functional Nanomaterials.

36 MATERIALS SCIENCE↗

NASA NTRS1989

Simulations of light scattering in planetary rings

The current status of efforts to model light scattering in the Uranian and Saturnian rings is briefly reviewed, with an emphasis on the treatment of thin, vertically warped, or clumpy rings. Consideration is given to observations of an opposition surge in the rings (indicating that they are physically thick) and possible reasons for the failure of classical models to predict the forward-scattering characteristics of the B and inner A rings of Saturn, the quadrupole brightness variations in the A ring, the increase in reflectivity with optical depth in the A and B rings, the increase in brightness with solar and observer angle in the B ring, and systematic brightness variations in images of the inner Cassini division. It is pointed out that some of these discrepancies are eliminated by the use of a ray-tracing simulation code which determines the singly scattered light from a layer one or many particles thick.

Dones, L.↗

NASA NTRS2011

Multipoint Observations of Coronal Mass Ejection and Solar Energetic Particle Events on Mars and Earth During November 2001

Multipoint spacecraft observations provide unique opportunities to constrain the propagation and evolution of interplanetary coronal mass ejections (ICMEs) throughout the heliosphere. Using Mars Global Surveyor (MGS) data to study both ICME and solar energetic particle (SEP) events at Mars and OMNI and Geostationary Operational Environmental Satellite (GOES) data to study ICMEs and SEPs at Earth, we present a detailed study of three CMEs and flares in late November 2001. In this period, Mars trailed Earth by 56deg solar longitude so that the two planets occupied interplanetary magnetic field lines separated by only approx.25deg. We model the interplanetary propagation of CME events using the ENLIL version 2.6 3-D MHD code coupled with the Wang-Sheeley-Arge version 1.6 potential source surface model, using Solar and Heliospheric Observatory (SOHO) Large Angle and Spectrometric Coronagraph (LASCO) images to determine CME input parameters. We find that multipoint observations are essential to constrain the simulations of ICME propagation, as two very different ICMEs may look very similar in only one observational location. The direction and width of the CME as parameters essential to a correct estimation of arrival time and amplitude of the ICME signal. We find that these are problematic to extract from the analysis of SOHO/LASCO images commonly used for input to ICME propagation models. We further confirm that MGS magnetometer and electron reflectometer data can be used to study not only ICME events but also SEP events at Mars, with good results providing a consistent picture of the events when combined with near-Earth data.

Falkenberg, T. V.↗

NASA NTRS1990

Image recovery from edge primitives

A method for extracting edge primitives from Mach-band patterns is presented together with a method for recovering image representations of features outlined by the edge boundaries. The accuracy, stability, and resolution of these representations are assessed. Since these representations are most commonly used in characterizing targets, this method of low-level processing offers new opportunities for computer vision and high data-compressing coding. Two bandpass filters are considered, the spatially invariant Laplacian of Gaussian filter and spatially variant intensity-dependent spatial (IDS) summation. It is shown that the recovery from the IDS bandpass data is particularly advantageous in applications for which robustness to local and temporal variations in illumination is important. It is concluded that the edge primitives extracted from bandpassed images can be an efficient way to store, transmit, and represent images.

Alter-Gartenberg, Rachel↗

DOE OSTI2022

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components (Final Technical Report)

Metal Additive Manufacturing (AM) is a promising method for cost-efficient fabrication of complex shape structures for applications in harsh environment, such as in a nuclear reactor. However, internal defects (pores) occur in high-strength AM alloys, which are manufactured with Laser Powder Bed Fusion (LPBF) AM method. Pulsed Infrared Thermography (PIT) is an efficient nondestructive evaluation (NDE) method to examine actual structures, because this method offers one-sided non-contact measurements, and fast processing of large sample areas. However, imaging of material defects, particularly defects with sizes at microscopic level, is challenging. In this report, we benchmark the performance of several Unsupervised Learning (UL) algorithms designed to enhance imaging of microscopic defects in metals with PIT. UL aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Performance of Independent Component Analysis (ICA), Sparse Coding (SC), Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) was compared using F-score, UL model training time and defects reconstruction time. We obtained the average F-score of 0.75, and a highest F-score of 0.89 for the EFA algorithm. Overall, EFA outperforms other UL algorithms considered in this study. In another approach, we investigate Thermal Tomography (TT), which is a computational method for reconstruction of depth profile of internal material defects from PIT nondestructive evaluation (NDE). TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of subsurface internals defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. Performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shape imported from scanning electron microscopy (SEM) images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on TT images of elliptical defects is capable of classifying shape and orientation of irregular defects. Training the CNN on irregular defect shapes instead of on elliptical shapes would make the resulting classifications more descriptive of actual defect shapes. However, this requires a much higher volume of SEM images of material defects, which are difficult to obtain because of random occurrence of defects in LPBF. To address this challenge, we developed a generative adversarial network (GAN) to augment the existing dataset of SEM defect images. The GAN model is demonstrated to create novel yet realistic defect shapes that can be used as input for simulated PTT images to train CNN. We also investigate several approaches based on Gaussian Random Circle and Bezier Curves for constructing parametric models of irregular-shape defects.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Characterization of a 1D-imaging high-energy x-ray backlighter driven by the National Ignition Facility Advanced Radiographic Capability laser

Plastic deformation of samples compressed to Mbar pressures at high strain rates at the National Ignition Facility (NIF) forms the basis of ongoing material strength experiments in conditions relevant to meteor impacts, geophysics, armor development, and inertial confinement fusion. Hard x-ray radiography is the primary means of measuring the evolution of these samples, typically employing a slit-collimated high-Z microdot driven by the NIF laser to generate >40 keV x rays [E. Gumbrell et al., Rev. Sci. Instrum. 89, 10G118 (2018) and C. M. Huntington et al., Rev. Sci. Instrum. 89, 10G121 (2018)]. Alternatively, a dysprosium “micro-flag” target driven by the Advanced Radiographic Capability laser (~2 kJ, 10 ps) can deliver significantly higher spatiotemporal resolution [M. P. Hill et al., Rev. Sci. Instrum. 92, 033535 (2021)], especially in high-opacity samples. Here, initial experiments revealed problematic brightness and spectral gradients from this source, but by radiographing a set of diamond-turned, 105 µm-thick Pb test objects and supported by simulations using the 3D Monte Carlo code GEANT4, these geometry-dependent gradients across the field of view are quantified and mitigation strategies are assessed. In addition to significantly enhancing the modulation transfer function compared to the existing system, image stacking from multiple layers of image plate is shown to almost double the signal to noise ratio that will reduce uncertainties in future dynamic strength experiments.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

AesFA: An Aesthetic Feature-Aware Arbitrary Neural Style Transfer

Neural style transfer (NST) has evolved significantly in recent years. Yet, despite its rapid progress and advancement, existing NST methods either struggle to transfer aesthetic information from a style effectively or suffer from high computational costs and inefficiencies in feature disentanglement due to using pre-trained models. This work proposes a lightweight but effective model, AesFA---Aesthetic Feature-Aware NST. The primary idea is to decompose the image via its frequencies to better disentangle aesthetic styles from the reference image while training the entire model in an end-to-end manner to exclude pre-trained models at inference completely. Finally, to improve the network's ability to extract more distinct representations and further enhance the stylization quality, this work introduces a new aesthetic feature: contrastive loss. Extensive experiments and ablations show the approach not only outperforms recent NST methods in terms of stylization quality, but it also achieves faster inference. Codes are available at https://github.com/Sooyyoungg/AesFA.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1981

Applications of digital image acquisition in anthropometry

A description is given of a video kinesimeter, a device for the automatic real-time collection of kinematic and dynamic data. Based on the detection of a single bright spot by three TV cameras, the system provides automatic real-time recording of three-dimensional position and force data. It comprises three cameras, two incandescent lights, a voltage comparator circuit, a central control unit, and a mass storage device. The control unit determines the signal threshold for each camera before testing, sequences the lights, synchronizes and analyzes the scan voltages from the three cameras, digitizes force from a dynamometer, and codes the data for transmission to a floppy disk for recording. Two of the three cameras face each other along the 'X' axis; the third camera, which faces the center of the line between the first two, defines the 'Y' axis. An image from the 'Y' camera and either 'X' camera is necessary for determining the three-dimensional coordinates of the point.

Woolford, B.↗

NASA NTRS2018

Nozzle Plume/Shock Interaction Experimental and Computational Sonic Boom Analyses from the NASA Ames 9- by 7-Foot Supersonic Wind Tunnel

A wind tunnel test and a computational study were conducted to investigate the complex interactions between a supersonic nozzle plume and shock waves of differing strengths generated from various aft surfaces typical of supersonic aircraft. These analytically-defined aft surfaces were representative of horizontal tails of various sizes, and an aft deck. CFD simulations of many proposed model configurations allowed for assessments of the detailed flow interactions of components in close proximity to the nozzle, as well as assessments of the nozzle jet flow itself. The evaluation of the computational results for many candidate configurations guided the design of model components. The interactions of the waveforms from these surfaces with the jet exhaust plume can have significant adverse effects on the loudness of the sonic boom if the surfaces are not carefully integrated into an aircraft design. The greatest discrepancy in estimating sonic boom loudness for low-boom flight vehicles is currently in predicting the signatures from the aft part of an aircraft, including the interactions with the plume flow. The objectives of this test were to gain a better understanding of these interactions, and to provide a detailed experimental database from multiple sources for use as validation cases for CFD tool development. The subject test was run in the NASA Ames 9- by 7-Ft Supersonic Wind Tunnel in February 2016 at Mach numbers of 1.6 and 2.0, and was funded by the NASA Commercial Supersonics Technology (CST) Project. The nozzle flow was provided by high-pressure air (HPA) pumped through the model, and pressure signature data were acquired with the NASA 14-inch sonic boom pressure rail. The rail measured the locations of the shocks and expansions at various distances and off-track angles from the model. This enabled the impact of the nozzle plume/shock interactions on the near- and mid-field sonic boom pressure waveforms to be quantified. Schlieren images of the flow field around and behind the model were obtained with an RBOS (Retroreflective Background-Oriented Schlieren) technique to determine the origins of the shock and expansion waves, to identify the shape and boundaries of the plume, and to determine the changes in incoming and exiting waveforms within the plume. A total pressure rake was positioned closely behind the model nozzle in order to measure the total pressure profiles of the flow above, within, and below the nozzle exhaust. Model angles and positions in the tunnel were measured by photogrammetry using two cameras since the lack of a model force balance prevented the measurement of model deflections under load.Navier-Stokes computations using two different CFD codes were compared to the experimental sonic boom pressure signature data, and the rake total pressure data in the plume. A computational schlieren technique was used to compare the computed flow field with the RBOS images. The computational results were also used to complement the test data with flow field quantities that could not be measured, such as Mach number and pressure distributions to distinguish shock waves and expansion waves.

sonic boom↗

DOE OSTI2024

Real space iterative reconstruction for vector tomography (RESIRE-V)

Tomography has had an important impact on the physical, biological, and medical sciences. To date, most tomographic applications have been focused on 3D scalar reconstructions. However, in some crucial applications, vector tomography is required to reconstruct 3D vector fields such as the electric and magnetic fields. Over the years, several vector tomography methods have been developed. Here, we present the mathematical foundation and algorithmic implementation of REal Space Iterative REconstruction for Vector tomography, termed RESIRE-V. RESIRE-V uses multiple tilt series of projections and iterates between the projections and a 3D reconstruction. Each iteration consists of a forward step using the Radon transform and a backward step using its transpose, then updates the object via gradient descent. Incorporating with a 3D support constraint, the algorithm iteratively minimizes an error metric, defined as the difference between the measured and calculated projections. The algorithm can also be used to refine the tilt angles and further improve the 3D reconstruction. To validate RESIRE-V, we first apply it to a simulated data set of the 3D magnetization vector field, consisting of two orthogonal tilt series, each with a missing wedge. Our quantitative analysis shows that the three components of the reconstructed magnetization vector field agree well with the ground-truth counterparts. We then use RESIRE-V to reconstruct the 3D magnetization vector field of a ferromagnetic meta-lattice consisting of three tilt series. Our 3D vector reconstruction reveals the existence of topological magnetic defects with positive and negative charges. We expect that RESIRE-V can be incorporated into different imaging modalities as a general vector tomography method. To make the algorithm accessible to a broad user community, we have made our RESIRE-V MATLAB source codes and the data freely available at https://github.com/minhpham0309/RESIRE-V.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

A New Miniaturized Acoustic Transmitter for Marine Animal Tracking

Most marine renewable energy (MRE) technologies are still in their infancy. Many uncertainties remain regarding MRE systems’ impacts on the marine environment and species where they are deployed, which is one of the major hurdles for these systems to be widely adopted at a commercial scale. Currently, the primary technologies to monitor marine animals’ behavior around existing or potential MRE deployment sites are optical and acoustic imaging. However, these methods cannot identify individual animals and thus are less useful in identifying protected species and studying their behavior. Implantable acoustic transmitters with unique identification codes could serve as a complementary technology. To minimize potential bias introduced to the study results, the implanted transmitters must be sufficiently small and light to not affect the animals’ behavior while still having acceptable signal strengths and service life. Recently, we developed a new miniaturized acoustic transmitter that offers a significantly improved signal strength and service life (140 days [projected value] at a 5-s transmission interval) in a smaller and lighter package (0.45 g in the air), compared to the existing technologies. The detection range and detection efficiency of the new transmitter were tested in an actual marine environment and demonstrated a detection range of up to 330 m, a 65% improvement over the existing commercial counterparts operating at similar frequencies. Here, we report the design principles, performance, and manufacturing procedure of the transmitter. Finally, theoretical estimates of the detection range, the actual range, and detection efficiency results from the field testing are presented.

acoustic telemetry↗