Speed Of Sound Values Research Articles

Source localization at low frequency using deconvolution of the waveguide impulse response

Matched-mode processing (MMP) methods have been widely investigated for source localization and geoacoustic inversion. For horizontal line arrays (HLA), it aims at retrieving the horizontal wavenumbers and thus at inferring source range and bearing. In this work, the matched-mode is performed by applying the deconvolution of the waveguide response in a narrowband context in order to improve the localization accuracy. Deconvolution usually refers to a sparse framework when the number of sources is smaller than the number of sensors of the HLA. The Orthogonal Matching Pursuit algorithm is then used in this work. First results from numerical simulations for Pekeris waveguide highlight better localization accuracy than MMP. The deconvolution shows as well stronger robustness to mismatch in the sound speed values of the seabed. Results from measurement campaign, involving large HLA, low to ultra-low frequency and water depth up to 1500 m are investigated as well.

Ultrasonic and volumetric investigation of aqueous disodium EDTA with PEG 400 and PEG 4000 at different temperatures

Polyethylene glycol (PEG) 400 and 4000 thermodynamic characteristics in water-based disodium ethylenediaminetetraacetic acid solutions provide important clues about the nature of the intermolecular interactions taking place in this liquid environment. In order to make these determinations, the present study reports data for density and sound velocity at a variety of temperatures and then analyses the volumetric-acoustic features of the solutions. The experimental data for PEG 400 and PEG 4000, which are polyethylene glycols, were recorded at a constant atmospheric pressure of 0.1 MPa and at temperatures ranging from 288.15 to 318.15 K. The values were 0.007, 0.008, and 0.009 mol·kg−1. From the experimental density and speed of sound values, the following are computed: apparent molar properties, partial molar properties, partial molar transfer properties, and the partial molar expansibility, along with its first derivative and thermal expansion coefficient. According to the co-sphere overlap model, the results are described using these generated parameters, these are thought of as the type of interactions taking place within the combination. This study also uses partial molar characteristics to assess the pair interaction coefficients and triplet interaction coefficients.

Constraining the variable generalized Chaplygin gas model in matter creation cosmology

We explore the variable generalized Chaplygin gas (VGCG) model in the theory of matter creation cosmology within the framework of a spatially homogeneous and isotropic flat Friedmann—Lemaître—Robertson—Walker space-time. Matter creation cosmology is based on reinterpretation of the energy–momentum tensor in Einstein’s field equations. This creation corresponds to an irreversible energy flow from the gravitational field to the created matter constituents. The variable Chaplygin gas (VCG) is also studied as a particular solution. We use the Markov chain Monte Carlo method to constrain the free parameters of three models, namely, Lambda-Cold-Dark matter (ΛCDM), VGCG and VCG models with and without matter creation from the latest observational data from baryon acoustic oscillations, cosmic chronometer, type Ia supernovae (Pantheon) including gamma-ray bursts, quasars and the local measurement of H 0 from R21 data. Two different combinations of dataset provide a fairly tight constraint on the parameters of the ΛCDM, VGCG and VCG models. The present values of various cosmological parameters are obtained, which are very close to the ΛCDM model. Furthermore, we perform stability analysis, Bayesian evidence analysis and information criteria analysis for these models through studying the sound speed, Bayes factor, and Akaike information criteria (AIC) and Bayesian information criteria (BIC) selection criteria. The values of sound speed for VGCG and VCG models shows that both the models are stable. According to AIC, it is observed that VGCG and VCG models with matter creation are supported considerably less by current observations, while BIC shows that these models are not favoured by observational data.

Real-Time Speed-of-Sound Estimation In Vivo via Steered Plane Wave Ultrasound.

Speed-of-sound (SoS) is an intrinsic acoustic property of human tissues and has been regarded as a potential biomarker of tissue health. To foster the clinical use of this emerging biomarker in medical diagnostics, it is important for SoS estimates to be derived and displayed in real time. Here, we demonstrate that concurrent global SoS estimation and B-mode imaging can be achieved live on a portable ultrasound scanner. Our innovation is hinged upon the design of a novel pulse-echo SoS estimation framework that is based on steered plane wave imaging. It has accounted for the effects of refraction and imaging depth when the medium SoS differs from the nominal value of 1540 m/s that is conventionally used in medical imaging. The accuracy of our SoS estimation framework was comparatively analyzed with through-transmit time-of-flight measurements in vitro on 15 custom agar phantoms with different SoS values (1508-1682 m/s) and in vivo on human calf muscles ( N = 9 ; SoS range: 1560-1586 m/s). Our SoS estimation framework has a mean signed difference (MSD) of - 0.6 ± 2.3 m/s in vitro and - 2.2 ± 11.2 m/s in vivo relative to the reference measurements. In addition, our real-time system prototype has yielded simultaneous SoS estimates and B-mode imaging at an average frame rate of 18.1 fps. Overall, by realizing real-time tissue SoS estimation with B-mode imaging, our innovation can foster the use of tissue SoS as a biomarker in medical ultrasound diagnostics.

Investigation of acoustical excess parameters and FTIR studies for binary liquid mixtures of tetrachloroethylene and cyclopentanone at different temperatures.

Abstract Speed of sound (U), Density (ρ), and viscosity (η) values of liquid mixtures of Tetrachloroethylene with Cyclopentanone and pure liquids were determined at regular intervals of molar range at different temperatures (303.15, 308.15, 313.15, 318.15) K. From the experimentally determined values, thermo-acoustic parameters such as excess molar volume (VE) and excess free length (Lf E), excess Gibb’s free energy (ΔGE) and excess enthalpy (HE) have been estimated. The variations of the above parameters discussed based on intermolecular interactions existing in this binary mixture. The computed values of sound speed in the mixture from various theories are compared with experimentally calculated values and have a clear check to validate the theories for the present system, and FTIR studies provide detailed analysis of molecular interactions.

Density, Speed of Sound and Derived Properties of Binary Mixtures Propiophenone + Butoxyethanol at T = (303.15, 308.15, 313.15 and 318.15) K

The current study reports the experimental density (ρ) and sound speed (u) values for binary mixes of liquids propiophenone + 2-butoxyethanol at atmospheric pressure (0.1 MPa) and T = (303.15, 308.15, 313.15 and 318.15) K for the full spectrum of composition. densities and sound speed measurements from experiments have been used to estimate excess isentropic compressibility (κsE), excess molar volume (VEm), excess molar isentropic compressibility (KEs,m), excess isobaric thermal expansivity (αEp) and excess sound speed (uE). The Redlich-Kister polynomials were used to correlate excess parameters. Excess partial molar volume quantities (VEm,1 and VEm,2) at infinite dilution and their limiting values (V0Em,1 and V0Em,2) have been analytically determined using Redlich-Kister polynomials from the experimental density data. The results have been analyzed in light of strength and interactions among molecular entities scope and extent prevalent in these mixtures.

Thermophysical insights and COSMO-RS study of triethylenetetramine-based protic ionic liquids with alkyl carboxylic acids

Protic ionic liquids (PILs) have increasing interest due to their potential application compared to conventional organic solvents. In the present study, new class of protic ionic liquids were developed by combining triethylenetetramine as cation and distinct carboxylic acids, specifically formic acid, butanoic acid, hexanoic acid, and octanoic acid employed as the anions. The products structures and purity were verified using 1H and 13C NMR as well as ESI-MS analysis. The structural variations effects on the thermophysical characteristics such as refractive index (nD), viscosity (η), density (ρ), and speed of sound (u) were evaluated throughout a broad temperature range. Temperatures between 293.15 and 333.15 K were used to calculate the viscosity and density values. It was also determined the thermal decomposition temperature (Td) and quantified the amount of water in the synthetic protic ionic liquids. Additional parameters such the expansion coefficient (α), standard entropy (S0), volume (V), lattice potential energy (UPOT), isentropic compressibility (βs), Intermolecular free length (Lf) of PILs were calculated using experimental values for sound speed and density. Furthermore, computation of activation energy employed the experimental viscosity values. In order to calculate the electronic polarizability and free volume present inside the ionic liquids, refractive indices of PILs were measured between the temperatures of 293.15 and 323.15 K. The study also explored the Conductor-like Screening Model for Real Solvents (COSMO-RS) computational approach to gain insights into the structural variation of TETA-based ionic liquids. The prepared PILs derived properties and linked with their structural moieties.

Clinical value of endoscopic ultrasound sound speed in differential diagnosis of pancreatic solid lesion and prognosis of pancreatic cancer.

Differential diagnosis of pancreatic solid lesion (PSL) and prognosis of pancreatic cancer (PC) is a clinical challenge. We aimed to explore the differential diagnostic value of sound speed (SS) obtained from endoscopic ultrasonography (EUS) in PSL and the prognostic value of SS in PC. Patients with PSL in The Third Xiangya Hospital of Central South University from March 2019 to October 2019 were prospectively enrolled, who obtained SS from PSL. Patients were divided into the PC group and the pancreatic benign lesion (PBL) group. SS1 is the SS of lesions and SS2 is the SS of normal tissues adjacent to lesions. Ratio1 is equal to SS1 divided by SS2 of PSL (ratio1 = SS1/SS2). Eighty patients were enrolled (24 PBL patients, 56 PC patients). SS1 and ratio1 in PC group were higher compared with PBL group (SS1:1568.00 vs. 1550.00, Z = -2.066, p = 0.039; ratio1: 1.0110 vs. 1.0051, Z = -3.391, p = 0.001). The SS1 in PC (Z = -6.503, p < 0.001) was higher compared to SS2. In the nonsurgical group of PC, low ratio1 predicted high overall survival (OS) (7.000 months vs. 4.000 months; p = 0.039). In the surgical group of PC, low SS1 was associated with low median OS (4.000 months vs. 12.000 months; p = 0.033). SS plays a vital role in distinguishing between PBL and PC. Higher SS1 and ratio1 obtained by EUS are more related to PC than PBL. In PC patients, high SS1 may predict pancreatic lesions. In the nonsurgical group of PC, low ratio1 may predict high OS. However, in the surgical group of PC, low SS1 may predict low OS.

Compression AutoEncoder for High-Resolution Ocean Sound Speed Profile Data

High-resolution ocean sound speed profile (HROSSP) data is essential for ocean acoustic modeling and sonar performance evaluation. However, the large volume and storage requirements of this data severely restrict its practical application in ocean acoustics. In this paper, we propose a compression autoencoder specifically designed for managing HROSSP data (CAE-HROSSP) and investigate the optimal network structure. Experimental results demonstrate that by using the min-max normalization method for input data and the corresponding inverse normalization for output data, along with employing the LeakyReLU function as the final activation layer, the accuracy of decompressed data reconstruction can be significantly improved. To tackle the challenges of fitting the distribution of surface sound speed data caused by significant variations and noise, we propose two loss functions: slice mean square error and elemental mean square error. These loss functions are combined with mean squared error through weighted summation to enhance CAE-HROSSP’s ability to fit the distribution of surface sound speed values and minimize the reconstruction errors of compressed data. Performance evaluation experiments reveal that CAE-HROSSP outperforms two existing methods in compressing HROSSP data, achieving superior performance with smaller data reconstruction errors at higher compression ratios. Furthermore, transfer learning is utilized to enhance the training of CAE-HROSSP, employing HROSSP data from the area where the mesoscale eddy is situated, as well as at the convergence of cold and warm ocean currents. The compression performance of both the training set and the validation set is comparable in the sea, where the structure of the sound speed profile varies greatly. This indicates that CAE-HROSSP can compress highly variable sound speed profile data in more sea areas using transfer learning, and has the potential to be extended globally. The findings and insights obtained from this study provide guidance for future endeavors in utilizing autoencoders to compress HROSSP data.

Deconvolution of the waveguide impulse response for source localization at low frequency

Matched-mode processing (MMP) methods have been widely investigated for source localization and geoacoustic inversion. For horizontal line arrays (HLA), it aims at retrieving the horizontal wavenumbers and thus at inferring source range and bearing. In this work, the matched-mode is performed by applying the deconvolution of the waveguide response in a narrowband context in order to improve the localization accuracy. Deconvolution usually refers to a sparse framework when the number of sources is smaller than the number of sensors of the HLA. The Orthogonal Matching Pursuit algorithm is then used in this work. First results from numerical simulations for Pekeris waveguide highlight better localization accuracy than MMP. The deconvolution shows as well stronger robustness to mismatch in the sound speed values of the seabed. Results from measurement campaign, involving large HLA, low to ultra-low frequency and water depth up to 1500 m are investigated as well.

Transcranial Phase Correction Using Pulse-Echo Ultrasound and Deep Learning: A 2-D Numerical Study.

Phase aberration caused by human skulls severely degrades the quality of transcranial ultrasound images, posing a major challenge in the practical application of transcranial ultrasound techniques in adults. Aberration can be corrected if the skull profile (i.e., thickness distribution) and speed of sound (SOS) are known. However, accurately estimating the skull profile and SOS using ultrasound with a physics-based approach is challenging due to the complexity of the interaction between ultrasound and the skull. A deep learning approach is proposed herein to estimate the skull profile and SOS using ultrasound radiofrequency (RF) signals backscattered from the skull. A numerical study was performed to test the approach's feasibility. Realistic numerical skull models were constructed from computed tomography (CT) scans of five ex vivo human skulls in this numerical study. Acoustic simulations were performed on 3595 skull segments to generate array-based ultrasound backscattered signals. A deep learning model was developed and trained to estimate skull thickness and SOS from RF channel data. The trained model was shown to be highly accurate. The mean absolute error (MAE) was 0.15 mm (2% error) for thickness estimation and 13 m/s (0.5% error) for SOS estimation. The Pearson correlation coefficient between the estimated and ground-truth values was 0.99 for thickness and 0.95 for SOS. Aberration correction performed using deep-learning-estimated skull thickness and SOS values yielded significantly improved beam focusing (e.g., narrower beams) and transcranial imaging quality (e.g., improved spatial resolution and reduced artifacts) compared with no aberration correction. The results demonstrate the feasibility of the proposed approach for transcranial phase aberration correction.

Learning the Imaging Model of Speed-of-Sound Reconstruction via a Convolutional Formulation.

Speed-of-sound (SoS) is an emerging ultrasound contrast modality, where pulse-echo techniques using conventional transducers offer multiple benefits. For estimating tissue SoS distributions, spatial domain reconstruction from relative speckle shifts between different beamforming sequences is a promising approach. This operates based on a forward model that relates the sought local values of SoS to observed speckle shifts, for which the associated image reconstruction inverse problem is solved. The reconstruction accuracy thus highly depends on the hand-crafted forward imaging model. In this work, we propose to learn the SoS imaging model based on data. We introduce a convolutional formulation of the pulse-echo SoS imaging problem such that the entire field-of-view requires a single unified kernel, the learning of which is then tractable and robust. We present least-squares estimation of such convolutional kernel, which can further be constrained and regularized for numerical stability. In experiments, we show that a forward model learned from k-Wave simulations reduces the contrast error of SoS reconstructions by 38%, compared to a conventional hand-crafted line-based wave-path model. This simulation-learned model generalizes successfully to acquired phantom data, reducing the contrast error compared to the conventional hand-crafted alternative. We successfully demonstrate the feasibility of learning machine-specific kernels as well as one-shot learning from a single image. On in-vivo data of a cancerous breast tumor, the phantom-learned model exhibits an SoS contrast of 34.6 m/s, as an impressive improvement over the conventional model contrast of merely 3.4 m/s.

The influence of bone model geometries on the determination of skull acoustic properties.

In this study, we investigated the impact of various simulated skull bone geometries on the determination of skull speed of sound and acoustic attenuation values via optimization using transmitted pressure amplitudes beyond the bone. Using the hybrid angular spectrum method (HAS), we simulated ultrasound transmission through four model sets of different geometries involving sandwiched layers of diploë and cortical bone in addition to three models generated from CT images of ex-vivo human skull-bones. We characterized cost-function solution spaces for each model and, using optimization, found that when a model possessed appreciable variations in resolvable layer thickness, the predefined attenuation coefficients could be found with low error (RMSE < 0.01 Np/cm). However, we identified a spatial frequency cutoff in the models' geometry beyond which the accuracy of the property determination begins to fail, depending on the frequency of the ultrasound source. There was a large increase in error of the attenuation coefficients determined by the optimization when the variations in layer thickness were above the identified spatial frequency cutoffs, or when the lateral variations across the model were relatively low in amplitude. For our limited sample of three CT-image derived bone models, the attenuation coefficients were determined successfully. The speed of sound values were determined with low error for all models (including the CT-image derived models) that were tested (RMSE < 0.4 m/s). These results illustrate that it is possible to determine the acoustic properties of two-component models when the internal bone structure is taken into account and the structure satisfies the spatial frequency constraints discussed.

Sound speed and attenuation of human pancreas and pancreatic tumors and their influence on focused ultrasound thermal and mechanical therapies.

There is increasing interest in using ultrasound for thermal ablation, histotripsy, and thermal or cavitational enhancement of drug delivery for the treatment of pancreatic cancer. Ultrasonic and thermal modelling conducted as part of the treatment planning process requires acoustic property values for all constituent tissues, but the literature contains no data for the human pancreas. This study presents the first acoustic property measurements of human pancreatic samples and provides examples of how these properties impact a broad range of ultrasound therapies. Data were collected on human pancreatic tissue samples at physiological temperature from 23 consented patients in cooperation with a hospital pathology laboratory. Propagation of ultrasound over the 2.1-4.5MHz frequency range through samples of various thicknesses and pathologies was measured using a set of custom-built ultrasonic calipers, with the data processed to estimate sound speed and attenuation. The results were used in acoustic and thermal simulations to illustrate the impacts on extracorporeal ultrasound therapies for mild hyperthermia, thermal ablation, and histotripsy implemented with a CE-marked clinical system operating at 0.96MHz. The mean sound speed and attenuation coefficient values for human samples were well below the range of values in the literature for non-human pancreata, while the human attenuation power law exponents were substantially higher. The simulated impacts on ultrasound mediated therapies for the pancreas indicated that when using the human data instead of the literature average, there was a 30% reduction in median temperature elevation in the treatment volume for mild hyperthermia and 43% smaller volume within a 60°C contour for thermal ablation, all driven by attenuation. By comparison, impacts on boiling and intrinsic threshold histotripsy were minor, with peak pressures changing by less than 15% (positive) and 1% (negative) as a consequence of the counteracting effects of attenuation and sound speed. This study provides the most complete set of speed of sound and attenuation data available for the human pancreas, and it reiterates the importance of acoustic material properties in the planning and conduct of ultrasound-mediated procedures, particularly thermal therapies.

Expliciting the interactions of tramadol hydrochloride + choline chloride-based deep eutectic solvent + water systems: Thermodynamic aspects

In recent years, a new class of environmentally friendly solvents called deep eutectic solvents (DESs) have been employed in a number of operations in both academia and industry. The study described herein offers an assessment of a green solvent in the preparation of Drug delivery systems (DDSs) as well as delivery vehicles made of a deep eutectic system (DES) constituted of Choline Chloride (ChCl) and Urea (U). For the designing of such processes, there is a need for an understanding of the molecular interaction of Tramadol hydrochloride with DES. In this regard, we have experimentally measured density and sound velocity for Tramadol hydrochloride in aqueous solutions and in different concentrations of aqueous DES (i.e., 0.25, 0.50, and 1.0)mol.kg−1 within the concentration range 0 to 0.15 mol.kg−1 at various temperatures (288.15, 298.15, 308.15 and 318.15) K. In order to interpret the view on solute–solvent and solute–solute interactions, several derived parameters chiefly apparent molar volume of solute (Vϕ), isentropic compressibility (κS), apparent molar isentropic compressibility of solute (KS,ϕ) for tramadol hydrochloride in aqueous and in an aqueous DES solutions have been calculated from experimental density and speed of sound values. The limiting apparent molar volume of solute (Vϕ0) and limiting apparent molar isentropic compressibility of solute (KS,ϕ0) for binary as well as ternary systems have been calculated from apparent molar volume and compressibility values. The thermal coefficient of expansion (α) and partial molar isobaric expansion (Eϕ0) have been derived from the temperature dependence of limiting apparent molar volume of solute. Transfer volume (ΔVϕtrans0) and transfer compressibility ΔKS,ϕtrans0 of tramadol hydrochloride from aqueous to aqueous DES solutions have been calculated.

Computation of thermodynamic and thermoacoustical properties of binary mixtures of ionic liquids – Applications of Flory’s statistical theory

For the first time, widely employed Flory’s statistical theory of binary liquid mixtures has been successfully applied to six binary ionic liquid mixtures. Only density and sound speed data have been used to compute a number of useful and important thermodynamic and thermoacoustical properties of DEAA + H2O, DEAS + H2O, TEAA + H2O, TEAS + H2O, TMAA + H2O and TMAS + H2O at 298.15 K. Experimental values of density and sound speed were taken from the recent work of Venkatesu et al [J P C 118B (2014) 5971].Their data are rare, very precise and accurate. The validity of FST for pure ionic liquids (RTIL’s) and their binary mixtures has been tested from the theoretical values of surface tension and sound speed. The magnitudes of sound speed, internal pressure, energy and heat of vaporization, cohesive energy density, solubility parameter and polarity factor obtained from FST demonstrate the excellent agreement with the available values of the experimental properties.

Numerical investigation of compressible cryogenic cavitating flows by a modified mass transport model

The objectives of this study are to propose exact numerical methods for the compressible cryogenic cavitating flows and investigate the cavitation behaviors and vortex structures. A numerical modeling framework including large eddy simulations, vapor–liquid equations of state, and a modified mass transport model is presented in this paper. The modified transport model is proposed based on the convective heat transfer in which the convective heat transfer coefficient is associated with the material properties and local temperature. To validate the applicability of the modified model, the liquid nitrogen cavitating flows in the inertial and thermal modes (σ ≈ 0.50, Tthroat = 77.24 K and Tthroat = 85.23 K) are simulated, respectively. Meanwhile, the influence of thermodynamic effects on compressibility is investigated. The numerical method is further utilized to visualize the detailed cavity and vortex structures in different cavitating flow patterns (Tthroat ≈ 77 K, σ = 0.58, 0.39, 0.18). The results show that the predicted cavity structures with the modified mass transport model agree better with the corresponding experimental data. For the thermal mode, since the significant thermal effects restrain the development of cavity, the area of the low sound speed region is smaller than that of the inertial model. The value of the minimum sound speed is larger, so that the Mach number in the cavitation region is reduced. Therefore, the compressibility of the liquid nitrogen cavitation in the thermal mode is weaker. For different cavitating flow patterns, the core region of attached cavities near the throat remains stable during an evolutionary cycle. Compared to the attached cavity region, since some hairpin vortices break into many small-scale discrete vortices, the multi-scale effect of vortex distribution is more remarkable in the shedding cavity region.

Computationally efficient deep learning-based image reconstruction for sound speed estimation in ultrasound computed tomography

Ultrasound computed tomography (USCT) has great potential for breast cancer imaging due to its ability to quantify acoustic tissue properties such as the speed of sound (SOS). Full-waveform inversion (FWI)-based image reconstruction methods can produce high spatial resolution SOS images, but these methods are computationally demanding, especially when formulated in the time-domain. Deep learning (DL)-based methods can be computationally efficient and provide high-quality object estimates as studied in various medical image reconstruction problems. However, there remains a further need to develop and assess the DL-based image reconstruction methods for USCT for use in medical imaging applications. Here, we present a supervised DL approach for USCT image reconstruction that is formulated as an image-to-image translation problem. Specifically, a low-resolution SOS image obtained via traveltime tomography and a high-resolution reflection tomography image are used as inputs to a U-Net, which is trained to estimate a high-resolution SOS map. These input images are complementary, providing both quantitative information about SOS values and information about tissue boundaries. Numerical studies that employ realistic numerical breast phantoms demonstrated that the proposed method produced high-quality SOS estimates based on image quality metrics such as NMSE, SSIM, and PSNR.

Introducing sound speed variability in laboratory water tank

The variation of temperature in the ocean causes changes in sound propagation. To simulate the naturally occurring variability in an ocean environment, this project quantified the sound speed variation achievable in a laboratory water tank. The rectangular tank (1.2 m × 3.6 m with 0.5 m depth) has anechoic paneling that minimizes lateral reflections. In this experiment, temperature was measured from four different temperature sensors. The temperature was used to calculate the sound speed in the tank as a function of time while the water was cooled and heated. Sound speed values were compared from four different empirical equations. We found that while the temperature varies in time, the temperature is relatively uniform at different locations in the tank. In experiments involving three hours of heating and adding 100 pounds of ice, there was a 10-degree Celsius difference in temperature, corresponding to a 20 m/s difference in water sound speed. By adding an additional degree of variability to the tank measurements, a portion of the variability seen in the ocean can be replicated. This sound speed variability can then be used to test the robustness of machine learning algorithms.

Holography-based measurement of sound speed and attenuation coefficient values for small samples of tissue phantoms

For therapeutic ultrasound applications, design and planning of treatments often involve simulations to predict the in situ acoustic field, and these simulations rely on estimates of the acoustic properties of soft tissues. As defined in simulation models, these properties describe how a plane wave propagates in a homogeneous medium. However, because soft tissues inherently contain inhomogeneities, measurements are most appropriately performed on small, relatively homogeneous samples. In addition, mostly small samples of human tissue, either autopsy or post-surgical, are typically available for characterization. As published in a recent paper [J. Acoust. Soc. Am. 2021, 149(1): 386–404], we have proposed a holography-based technique to extract plane-wave measurements from ultrasound beams passing through small (cm-sized) material samples. Here, we seek to adapt this technique for measuring small samples of deformable materials using an apparatus that holds such samples with two plane, parallel surfaces that can be interrogated by an incident ultrasound beam having a diameter smaller than that of the sample. Initial testing over a range of frequencies from 0.5 to 10MHz is performed utilizing well characterized materials, such as hydrogels and silicone rubber. [Work supported by NIH grant R01EB025187.]