Characterizing the Relationship Between Coating Structure and Properties: Acoustic and Elastic Properties in Controlled Atmosphere Plasma Sprayed Metals
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Peleg, Emma Esther↗
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Acoustic Properties of Aerogels: Current Status and Prospects
Noise reduction remains an important priority in the modern society, in particular, for urban areas and highly populated cities. Insulation of buildings and transport systems such as cars, trains, and airplanes has accelerated the need to develop advanced materials. Various porous materials, such as commercially available foams and granular and fibrous materials, are commonly used for sound mitigating applications. In this review, a special class of advanced porous materials, aerogels, is examined, and an overview of the current experimental and theoretical status of their acoustic properties is provided. Aerogels can be composed of inorganic matter, synthetic or natural polymers, as well as organic/inorganic composites and hybrids. Aerogels are highly porous nanostructured materials with a large number of meso‐ and small macropores; the mechanisms of sound absorption partly differ from those of traditional porous absorbers possessing large macropores. The understanding of the acoustic properties of aerogels is far from being complete, and experimental results remain scattered. It is demonstrated that the structure of the aerogel provides a complex three‐dimensional architecture ideally suited for promising high‐performance materials for acoustic mitigation systems. This is in addition to the numerous other desirable properties that include low density, low thermal conductivity, and low refractive index.
36 MATERIALS SCIENCE↗
Noninvasive acoustical property measurement of fluids
Methods for noninvasive determination of acoustical properties of flowing in pipes having a large ratio (>10) of pipe diameter to wall thickness, and in highly attenuating fluids are described. When vibrations are excited on the outer surface of the wall of a pipe, the resulting vibrations propagate directly through the wall in a normal direction and through the pipe wall as guided waves, appearing on the opposite side of the pipe. This dual path propagation through pipes, where guided waves take the circumferential path in the wall of the pipe and may interfere with the time of-flight measurement obtained from the direct path through the fluid, is at least in part resolved by subtracting the signal from the guided wave from the combined signal, thereby permitting improved observation of the direct path propagation through the fluid.
Sinha, Dipen N.↗
Synthesis and acoustic properties study of castor‐oil‐based polyurethane foams with the addition of graphene‐oxide‐modified straw fibers
Abstract Polyurethane foam (PUF) can absorb sound by air friction and structural vibrations of cell walls. It is widely used as acoustic material in the automotive industry. According to existing studies, graphene oxide (GO) can improve the acoustic properties of PUF. However, GO tends to coalesce inside PUF. In this paper, straw fibers were modified with different concentrations of GO solution to embed GO on the surface of plant fibers. The GO was dispersed in the PUF using straw fibers. In addition, some studies show that the wrinkled morphology of the GO surface is believed to play a mechanical interlocking role in improving interfacial bonding, thus enhancing the stress transfer between the plant fibers and the polyurethane (PU) matrix and improving the mechanical properties of the PU composites. The acoustic and mechanical properties of the modified PU materials were observed by treating plant fibers with appropriate amounts of GO solution. The experimental study shows that the sample modified with 1 g L −1 GO solution reaches a maximum average sound absorption coefficient of 0.5838 when the straw fiber content reaches 0.5 g, and the sample modified with 2 g L −1 GO solution reaches a maximum transmission loss of 10.5333 when the straw fiber content reaches 1 g. © 2022 Society of Industrial Chemistry.
Yang, Keyao↗
Acoustic properties, elasticity, and equation of state of glycerol under pressure
Herein we employed high-pressure Brillouin scattering to study the pressure dependencies of acoustic modes of glycerol up to 14 GPa at 300 K. We observed longitudinal acoustic velocities and transverse acoustic velocities for the first time from 5 to 14 GPa. The results allow the determination of a complete set of elastic properties and an accurate determination of the pressure–volume (P–V) equation of state (EOS). EOS parameters, K 0 = 14.9 ± 1.8 GPa and K' 0 = 5.6 ± 0.5, were determined from fits to the data from ambient pressure to 14 GPa. Direct volume measurements of the P–V EOS are consistent with those determined by Brillouin scattering. A deviation from a Cauchy-like relationship for elastic properties was observed, and the pressure dependencies of the photoelastic constants and relaxation times were documented from 5 to 14 GPa. These results have broad implications for glass-forming liquids, viscoelastic theory, and mode coupling theory.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Establishing an acoustic-property relationship in laser powder bed fusion with machine learning
Quality control of Laser Powder Bed Fusion (PBF-LB) additively manufactured parts is an important hurdle inhibiting the technology’s use structural applications. Acoustic monitoring of the laser powder bed fusion process can detect defects in-situ that are known to degrade mechanical properties. However, processing-structure-property (PSP) relationships are required to extrapolate from detected defects to part performance. Here, this study explores how acoustics may be a suitable signature linking processing conditions to properties, thus effectively substituting for structure in the PSP relationship. Establishing such a relationship would enable a part’s mechanical performance to be directly predicted from its acoustic signature, reducing the need for destructive testing or microstructural analysis to ensure a part will meet performance requirements. One hundred CoCrFeMnNi high entropy alloy tensile bars were printed across 13 process conditions in a series of 6 prints. The acoustic signatures of these tensile bars were used to train machine learning models to predict each part’s mechanical properties. By using both process information and acoustic information to predict mechanical properties, yield strength was predicted 18% more accurately and ductility to failure was predicted 10% more accurately than is achieved when using duplicate parts to predict part performance. Finally, individual acoustic frequencies were investigated to determine why acoustic signatures improve mechanical property predictions and the potential physical origins of these signatures. This work demonstrates how blending acoustics, process information, and machine learning can provide in-situ diagnostics of mechanical properties and improve the reliability of the PBF-LB process.
Acoustic emission↗
Tailoring the Thermal Mechanical and Acoustic Properties through Ion Beam Modification.
Abstract not provided.
Hattar, Khalid Mikhiel↗
Environmental cell for in situ X-ray synchrotron micro-CT imaging with simultaneous acoustic measurements
Synchrotron radiation provides the necessary spatial and temporal resolution for non-invasive operando studies of dynamic processes under complex environmental conditions. Here a new environmental cell for simultaneous in situ dynamic X-ray imaging and measuring acoustic properties of geological samples is presented. The primary purpose of this cell is to study gas-hydrate formation in porous geo-materials and its influence on their acoustic properties. The cell is designed for cylindrical samples of 9 mm in diameter, confining and pore pressures up to 12 MPa, and temperatures from –20°C to room temperature. The cell is portable and can be easily assembled and operated at different X-ray sources. This cell enables a wide range of experiments studying physical/chemical processes in the Earth subsurface that change the mechanical properties of rocks (geochemical reactions, phase transitions, etc.).
47 OTHER INSTRUMENTATION↗
Probing the role of solids loading and mix procedure on the properties of acoustically mixed materials for additive manufacturing
We report resonant acoustic mixing has been of particular interest for use in additive manufacturing since viscous, solids-loaded materials can be difficult to mix and inhomogeneity has adverse effects on print quality. In this study, we detail a method to iterate through different formulations and mix procedures and assess mixture quality. The approach utilizes a constant pressure-driven flow test to collect statistics on flow rate through a standard geometry. This test is first applied to well mixed formulations containing particulate solids and find that the results are sensitive to viscosity produced by solids content. We then consider the formulations at various stages of mixing and find that the spread in the volume measurements is indicative of the mixing quality; poorly mixed material yields measurements with wide distributions. We believe this testing approach can be useful when screening new formulations, developing mixing processes, or for quality control.
36 MATERIALS SCIENCE↗
Ultrafast low-temperature metal–insulator interface phonon dynamics and heat transport in a Pt/Gd 3 Fe 5 O 12 heterostructure
Interfacial thermal and acoustic phenomena have an important role in quantum science and technology, including in spintronic and spincaloritronic materials and devices. Simultaneous measurements of the low-temperature thermal and acoustic properties of a metal/insulator heterostructure reveal distinct dynamics in the characteristic phonon frequency ranges of acoustic and thermal transport. The measurements probed a heterostructure consisting of a thin film of Pt on the ferrimagnetic insulator gadolinium iron garnet (Gd 3 Fe 5 O 12 , GdIG) grown epitaxially on a gadolinium gallium garnet substrate. Ultrafast structural dynamics within the Pt layer were tracked using time-resolved ultrafast x-ray diffraction and analyzed to probe interfacial acoustic and thermal properties. The rapid heating of the Pt layer by a 400 nm wavelength femtosecond-duration optical pulse produced transient structural changes that provided the stimulus for these measurements. Rapid heating produced a broadband acoustic pulse that was partially reflected by the Pt/GdIG interface. Temporal frequencies up to 740 GHz, corresponding to angular frequencies of several THz, were detected in a wavelet analysis of the acoustic oscillations of the strain in the Pt layer. The structural results were analyzed to determine (i) the acoustic damping coefficient and phonon mean free path in Pt at frequencies of hundreds of GHz and (ii) the Grüneisen anharmonicity parameter. The thermal conductance of the Pt/GdIG interface was tracked using the slower, tens-of-picosecond-scale, dynamics of the initial cooling of the heated Pt layer. Analysis using a model based on the Boltzmann transport equation shows that the phonon transmission is lower at the phonon frequencies relevant to thermal transport than for subterahertz regime acoustics.
Acoustic phenomena↗
Shockwave dissipation by interface-dominated porous structures
The advent of additive manufacturing (AM) has enabled topological control of structures at the micrometer scale, transforming the properties of polymers for a variety of applications. Examples include tailored mechanical responses, acoustic properties, and thermal properties. Porous polymer materials are a class of materials used for shock and blast mitigation, yet they frequently possess a lack of structural order and are largely developed and evaluated via trial-and-error. Here, we demonstrate control of shockwave dissipation through interface-dominated structures prepared by AM using 2-photon polymerization. A fractal structure with voids, or free surfaces, arranged less than 100 μm apart, allows for rarefaction interactions on the timescale of the shockwave loading. Simulations and dynamic x-ray phase contrast imaging experiments show that fractal structures with interfaces assembled within a “critical” volume reduce shockwave stress and wave velocity by over an order of magnitude within the first unit cell.
36 MATERIALS SCIENCE↗
Dynamic Behavior of Natural Seep Vents: Analysis of Field and Laboratory Observations and Modeling (Final Scientific/Technical Report)
In this project, we have analyzed data collected by the U.S. Department of Energy (DOE), National Energy Technology Laboratory (NETL) in a high pressure water tunnel (HPWT) and data from two research cruises to natural seeps in the Gulf of Mexico to adapt and validate a numerical model to predict the dynamics of natural seeps in the deep oceans. The HPWT data include video observations of the shrinkage rate of individual methane and natural gas bubbles under simulated deep-water conditions. Field data were collected during two cruises by the Gulf Integrated Spill Research (GISR) Consortium led by Texas A&M University and funded by the Gulf of Mexico Research Initiative (GoMRI). These data included in situ observations from a remotely operated vehicle (ROV) of gas bubbles at two natural seep sites in the Gulf and acoustic observations of the natural seep bubble flares in the ocean water column. The acoustic data were from multibeam echosounders, one mounted in a forward-looking orientation on the ROV and another mounted down-looking in the haul of the ship. All of these laboratory and field data were focused on the dynamics of natural gas bubbles at temperatures and pressures favorable for clathrate hydrate formation between the gas and water. Our analyses of this data focused on understanding the mechanisms responsible for gas bubble dissolution within the hydrate stability zone (HSZ) of the oceans. Ice-like hydrate shells may form on the bubble-water interface under these conditions, and it was unknown how this might affect the mass transfer of gas into the ocean. We were able to extract bubble shrinkage rates from the HPWT datasets. Using this data we determined that mass transfer coefficients with and without a hydrate shell match empirical values for bubbles in contaminated systems (so-called dirty bubbles contaminated by naturally occurring surfactants). We also showed that free gas, and not gas hydrate, is the dominant dissolving phase when the hydrate sub-cooling is below 11 degree Celsius (temperature difference between hydrate the hydrate formation temperature and ambient temperator) or the pressure is reducing as bubbles rise through the ocean water column. Using this mass transfer model, our numerical model of bubble dissolution matched the over 200 HPWT experiments with an average error of 10% for predicting the bubble size at the end of an experiment. From field data in the literature, we also observed that gas bubbles dissolve faster when they are initially released, following mass transfer coefficients for so-called clean-bubbles (those not yet contaminated by surfactants). Shortly after release within the HSZ, a hydrate shell forms on the bubble-water interface, and the mass transfer reduces to rates matching those of dirty bubbles. We correlated this transition time from clean to dirty bubble behavior with the initial bubble surface area and the hydrate sub-cooling. With this model for hydrate formation time and using the mass transfer coefficients deduced from the HPWT data, we validated our numerical model for predicting the rise heights of natural seep flares in the oceans. Flare heights are commonly observed in haul-mounted acoustic multibeam data. The numerical model predicts bubbles to rise high in the ocean water column owing to the slower mass transfer rates for dirty bubbles that accompany the majority of their rise time. We found that the numerical model predictions matched the observed flare heights within 5% to 10% accuracy when we compared the rise heights of the largest bubbles released from the seafloor with the bubbles acoustically visible in the multibeam data. Bubbles become acoustically transparent as they shrink to sizes of order 1 mm in diameter for the multibeam frequencies used in the field. The forward-looking multibeam on the ROV also provided data on the lateral spreading of bubbles in natural seep flares. Our analysis of this data showed that spreading follows a diffusion process, with the effective diffusivity correlating with the wobbling length scale of these ellipsoidal bubbles. When we apply this diffusivity in a random displacement model of bubble spreading, our numerical simulations match closely the lateral spread observed by the M3 in the ocean water column. Finally, we compared the seep model predictions for the acoustic properties of these natural seep plumes with that observed by the acoustic instruments in the field. The M3 and EM 302 observations were converted to relative values of target strength using a calibration we obtained in the laboratory for the M3 and using an algorithm from the manufacturer for the EM 302. Comparing the numerical seep model to these data, we obtain good agreement over the whole height of rise of these bubble flares. This further validates the numerical model. Overall, our validated seep model captures the key dynamics of gas bubbles released from natural seeps in the oceans and helps to predict the fate of methane in the water column.
03 NATURAL GAS↗
Survey of Deep Learning and Physics-Based Approaches in Computational Wave Imaging
Computational wave imaging (CWI) extracts hidden structure and physical properties of a volume of material by analyzing wave signals that traverse that volume. Applications include seismic exploration of the Earth’s subsurface, acoustic imaging and nondestructive testing (NDT) in material science, and ultrasound computed tomography (USCT) in medicine. Current approaches for solving CWI problems can be divided into two categories: those rooted in traditional physics and those based on deep learning. Physics-based methods stand out for their ability to provide high-resolution and quantitatively accurate estimates of acoustic properties within the medium. However, they can be computationally intensive and are susceptible to ill-posedness and nonconvexity typical of CWI problems. Machine learning (ML)-based computational methods have recently emerged, offering a different perspective to address these challenges. Diverse scientific communities have independently pursued the integration of deep learning in CWI. This review discusses how contemporary scientific ML techniques, and deep neural networks in particular, have been developed to enhance and integrate with traditional physics-based methods for solving CWI problems. We present a structured framework that consolidates existing research spanning multiple domains, including computational imaging, wave physics, and data science. This study concludes with important lessons learned from existing ML-based methods and identifies technical hurdles and emerging trends through a systematic analysis of the extensive literature on this topic.
42 ENGINEERING↗
FAIR Data and Interpretable AI Framework for Architectured Metamaterials
Our interdisciplinary effort successfully generated FAIR (Findable, Accessible, Interoperable, and Reusable) benchmark datasets for mechanical metamaterials while introducing a novel Artificial Intelligence (AI) framework known as Learning Refined Compositional Rules (LRCR). This framework was specifically designed to bridge the gap across varying computational length scales and extract the underlying physical mechanisms that connect a material's structural geometry to its bulk acoustic properties. Historically, the discovery of such structured materials relied heavily on human intuition or opaque, black-box optimization algorithms that were difficult to generalize. By combining interpretable machine learning techniques with rigorous experimental validation, this project established clear, generalizable design guidelines for tuning wave dispersion and controlling vibrations. Ultimately, the public availability of these structured datasets and algorithms will significantly reduce computational costs and accelerate the design of advanced multi-functional acoustic devices, offering broad societal impacts across fields like aerospace engineering, telecommunications, and biomedical implant design.
36 MATERIALS SCIENCE↗
Materials Engineering of Violin Soundboards by Stradivari and Guarneri
Abstract We investigated the material properties of Cremonese soundboards using a wide range of spectroscopic, microscopic, and chemical techniques. We found similar types of spruce in Cremonese soundboards as in modern instruments, but Cremonese spruces exhibit unnatural elemental compositions and oxidation patterns that suggest artificial manipulation. Combining analytical data and historical information, we may deduce the minerals being added and their potential functions—borax and metal sulfates for fungal suppression, table salt for moisture control, alum for molecular crosslinking, and potash or quicklime for alkaline treatment. The overall purpose may have been wood preservation or acoustic tuning. Hemicellulose fragmentation and altered cellulose nanostructures are observed in heavily treated Stradivari specimens, which show diminished second‐harmonic generation signals. Guarneri's practice of crosslinking wood fibers via aluminum coordination may also affect mechanical and acoustic properties. Our data suggest that old masters undertook materials engineering experiments to produce soundboards with unique properties.
Su, Cheng‐Kuan↗
Materials Engineering of Violin Soundboards by Stradivari and Guarneri
Abstract We investigated the material properties of Cremonese soundboards using a wide range of spectroscopic, microscopic, and chemical techniques. We found similar types of spruce in Cremonese soundboards as in modern instruments, but Cremonese spruces exhibit unnatural elemental compositions and oxidation patterns that suggest artificial manipulation. Combining analytical data and historical information, we may deduce the minerals being added and their potential functions—borax and metal sulfates for fungal suppression, table salt for moisture control, alum for molecular crosslinking, and potash or quicklime for alkaline treatment. The overall purpose may have been wood preservation or acoustic tuning. Hemicellulose fragmentation and altered cellulose nanostructures are observed in heavily treated Stradivari specimens, which show diminished second‐harmonic generation signals. Guarneri's practice of crosslinking wood fibers via aluminum coordination may also affect mechanical and acoustic properties. Our data suggest that old masters undertook materials engineering experiments to produce soundboards with unique properties.
36 MATERIALS SCIENCE↗
Subspace Methods in Multi-Parameter Seismic Full Waveform Inversion
In full waveform inversion (FWI) high-resolution subsurface model parameters are sought. FWI is normally treated as a nonlinear least-squares inverse problem, in which the minimum of the corresponding misfit function is found by updating the model parameters. When multiple elastic or acoustic properties are solved for, simple gradient methods tend to confuse parameter classes. This is referred to as parameter cross-talk; it leads to incorrect model solutions, poor convergence and strong dependence on the scaling of the different parameter types. Determining step lengths in a subspace domain, rather than directly in terms of gradients of different parameters, is a potentially valuable approach to address this problem. The particular subspace used can be defined over a span of different sets of data or different parameter classes, provided it involves a small number of vectors compared to those contained in the whole model space. Additionally, in a subspace method, the basis vectors are defined first, and a local minimum is found in the space spanned by these. We examine the application of the subspace method within acoustic FWI in determining simultaneously updates for velocity and density. We first discuss the choice of basis vectors to construct the spanned space, from linear updates by distinguishing only the contributions of different parameter classes towards nonlinear updates by adding the contributions of higher-order perturbations of each parameter class. The numerical character of FWI solutions generated via subspace methods involving different basis vectors is then analyzed and compared with traditional FWI methods. The subspace methods can provide better reconstructions of the model, especially for the velocity, as well as improved convergence rates, while the computational costs are still comparable with the traditional FWI methods.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Spin-strain interactions under hydrostatic pressure in α-RuCl 3
We investigate the effects of hydrostatic pressure on 𝛼−RuCl 3 , a prototypical material for the Kitaev spin model on a honeycomb lattice with a possible spin-liquid ground state. Using ultrasound measurements at pressures up to 1.16 GPa, we reveal significant modifications of the acoustic properties and the 𝐻−𝑇 phase diagram of this material. Hydrostatic pressure suppresses the three-dimensional magnetic order and induces a dimerization transition at higher pressures. At low pressures, the sound attenuation exhibits a linear temperature dependence, while above 0.28 GPa, it becomes nearly temperature independent, suggesting a shift in the phonon scattering regime dominated by Majorana fermions. These findings provide new insights into spin-strain interactions in Kitaev magnets and deliver a detailed characterization of the 𝐻−𝑇 phase diagram of 𝛼−RuCl 3 under hydrostatic pressure.
Focused ion beam↗