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All sources NASA NTRS DOE OSTI

DOE OSTI2025

Ultrasonic characterization of material heterogeneities in stainless steel components produced by laser powder bed fusion

We introduce pulse-echo ultrasound as a method for characterizing the impact of powder bed fusion parameters on the properties of additively manufactured stainless-steel components, their material anisotropy, and location-dependent heterogeneity. Our results indicate that accurate characterization requires careful selection of ultrasonic propagation paths, which must consider the direction of additive layering, variations in processing parameters, and the component's geometry. We employed two distinct methods to estimate material properties from ultrasonic data: One assumes isotropy, while the other accounts for anisotropic interactions during the propagation of elastic waves. When applied to samples fabricated with laser energy densities ranging from 24 to 42 J/mm³ , these methods revealed transverse isotropy and weak anisotropy (quantified by small Thomsen parameters, ε = 0.0651 and γ = 0.0092) and less than a ∼6 % change in acoustic impedance. The assumption of isotropy, in this case, leads to small errors (less than 4 % or 1 % for Young's modulus in the build or transverse directions) when estimating orthotropic material properties using ultrasonic data measured along just two orthogonal directions, one of which must align with the build direction. By comparing ultrasonic measurements — which aggregate the spatial variability in material properties along the length of elastic wave propagation into a single value — with localized measurements obtained from surface nanoindentation, we uncovered and spatially profiled significant differences between the surface and interior properties. Specifically, the surface Young's modulus decreased from approximately 210 GPa to 180 GPa within a depth of about 3 mm. We attribute this surface-localized heterogeneity in PBF-fabricated components to distinct thermal histories experienced by the surface and interior regions. Collectively, the results of this study establish a framework for the ultrasonic characterization of material heterogeneity and anisotropy in material properties and demonstrate its application in additively manufactured metal components.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Analytical modeling of the evolution of the nonlinearity parameter of sensitized stainless steel

Austenitic stainless steels are subject to the precipitation of chromium carbides (M 23 C 6 ) during exposure to high temperatures, causing these alloys to be susceptible to intergranular corrosion due to chromium depletion along grain boundaries. The acoustic nonlinearity parameter, β, shows sensitivity to the formation of carbides in these alloys. The Thermo-Calc TC-PRISMA module was used to model the nucleation and growth of grain boundary M 23 C 6 carbides. The model was verified with scanning transmission electron microscopy analysis that allowed measurements of the grain boundary precipitates. The paper introduces a reduced-order model of the acoustic nonlinearity based on the formation of misfit dislocations at the interface of the grain boundary precipitate and matrix to explain the change in β during isothermal aging. Furthermore, a direct relationship between the radius of the M 23 C 6 grain boundary carbides and β was observed and verified with nonlinear ultrasound measurements on 304L and 316L stainless steels.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Thermodynamic insights into the intricate magnetic phase diagram of EuAl 4

The tetragonal intermetallic compound EuAl 4 hosts an exciting variety of low-temperature phases. In addition to a charge density wave below 140 K, four ordered magnetic phases are observed below 15.4 K. Recently, a skyrmion phase was proposed based on Hall effect measurements under a c-axis magnetic field. Here, we present a detailed investigation of the phase transitions in EuAl 4 under c-axis magnetic field. Our dilatometry, heat-capacity, DC magnetometry, AC magnetic susceptibility, and resonant ultrasound spectroscopy measurements reveal three magnetic phase transitions not previously reported. The first key result is a detailed H ∥ [001] magnetic phase diagram mapping the seven phases we observe. Second, we identify a high-field phase, phase VII, which directly corresponds to the region were skyrmions have been previously suggested. Our results provide guidance for future studies exploring the complex magnetic interactions and spin structures in EuAl 4 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Domain wall dynamics in tungsten trioxide: Evidence for polar domain walls

Domain walls have distinct properties from the bulk, and tailoring them to suit the needs for device applications is critical. Tungsten trioxide, WO 3 , is of great interest for device applications that make use of domain wall properties; it exhibits a phenomenologically rich sequence of phase transitions, virtually all of which are ferroelastic in character, resulting in many sets of domain walls at low temperatures, each with their own unique properties. Domain wall motion and its contribution to the piezoelectric response have been investigated in WO 3 from 300 to 180 K using resonant ultrasound spectroscopy (RUS) and resonant piezoelectric spectroscopy (RPS), which showed that the P 2 1 / n , P 1 ¯ , and P 2 1 / c phases give a piezoelectric response despite the bulk being nominally centrosymmetric. Second harmonic generation (SHG) confirmed that polarity was strongest within the domain walls, and additional weak signals were found in the domains. Domain wall mobility was investigated in the P b c n , P 2 1 / n , and P 2 1 / c phases from 685 to 5 K. Domain walls in the P 2 1 / n and P 1 ¯ were more mobile than those in the P b c n and P 2 1 / c structures, and soon after the P 1 ¯ → P 2 1 / c transition the walls become pinned at ∼ 140 K . Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

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↗

DOE OSTI2026

Ultrasonic Resonance Techniques for Materials Research

Mechanical resonances are directly related to the physical behavior of a system at the bulk and microscopic levels. In materials science, resonant ultrasound spectroscopy (RUS) has long been a preferred nondestructive method to study mechanical resonances of solids and precisely measure quantitative material properties, namely elasticity. In recent years, advances in computational power and hardware have enabled RUS to be relevant for an increasing range of applications, such as advanced manufacturing. An extension of this technique, nonlinear RUS (NRUS), has been demonstrated to provide unmatched sensitivity to early-stage damage. NRUS was originally developed to probe geologic materials but has become a vital tool in nondestructive evaluation and materials research, offering a powerful means of quantifying and characterizing microstructural nonlinearity in a broad range of materials. This review summarizes recent developments and growth opportunities in RUS and NRUS techniques, modeling, and applications across a wide range of material systems including metals, composites, geomaterials, and explosives.

36 MATERIALS SCIENCE↗

DOE OSTI2021

A Biomimetic Ultrasonic Whistle for Use as a Bat Deterrent on Wind Turbines

Our project goal was to design a novel mechanical ultrasonic deterrent for use on wind turbines in order to reduce bat fatalities around these structures. Our proposed deterrent design would be composed of a series of ultrasonic pulse generators, or whistles, affixed to a wind turbine blade, which produce ultrasound through mechanical means. The whistles would produce sounds mimicking the spectrotemporal patterns of bat echolocation pulses, thereby enhancing the bats’ ability to detect, localize and avoid the moving blades. These whistles are intended to be operated passively, blown by the wind, and to be positioned at intervals along a turbine blade. Because the source of sound generation will be mechanical in nature, these devices will require no external power source, should require little maintenance, and will be small and cost-effective.

17 WIND ENERGY↗

DOE OSTI2021

Development of NDE/NDT Tools for High-Volume & High-Speed Inspection of CFRP Structures in Automotive Manufacturing

Main advantages of the air-coupled ultrasound testing (ACUT) and electromagnetic testing (EMT) techniques for NDE of CFRP composites were non-contact sensing, scalability for high-speed inspection, cost-effectiveness, and non-hazardous operation. Despite these advantages, no systems that would satisfy the project requirements were commercially available. Hence, one of the major efforts of the Michigan State University (MSU) team at the initial stage of the project was to close this technological gap by developing, optimizing, and validating array sensors that would provide sufficient sensitivity, spatial coverage, and resolution for robust defect detection. Optimization of the ACUT and EMT sensor designs was performed using experimentally validated finite element models. Initial experiments using array probes were conducted on relatively flat CFRP samples. In parallel, the MSU team designed and assembled a portable platform with two robotic arms. The robots were equipped with newly designed sensors that enabled high-speed NDE of curved CFRP parts. Presently, the developed robotic platform can be used as a demo/template NDE system, which is easily adaptable to manufacturing environments and in-line NDE. The ACUT NDE system developed by the MSU team used a high-power 4-channel pulser receiver for parallel data acquisition. The array probes were designed by stacking commercially available ACUT transducers, which operated in the frequency range between 100 kHz and 500 kHz. MSU optimized the excitation procedure and developed wave focusing cones so as to reduce the crosstalk between the transducers and to provide higher pulse repletion frequency (PRF). The through-transmission (TT) and single-side access (SSA) inspection modes were successfully implemented. In the TT-ACUT, structural defects in CFRP were detected by passing ultrasonic waves through the test part. Hence, the ACUT transmitters and receivers needed to be placed on the opposite sides of the test part. In the SSA-ACUT, guided waves (GW) were excited in the test part using the transmitters and were sensed by the receivers from the same side. Multi-channel TT-ACUT and SSA-ACUT provided high-speed NDE, and were successfully validated on CFRP test samples with interlaminar delaminations and other embedded defects The EM techniques developed by the MSU team included: 1) eddy current testing (ECT), 2) capacitive imaging (CI) and hybrid dual-mode imaging. In ECT, structural damage was detected in CFRP using coils sensor arrays. In ECT, the excitation magnetic field is generated by passing an alternating current through a coil, which is placed above the test sample. The excitation field penetrates the conductive sample and induces the eddy currents in its transect. In turn, the eddy currents generate the reaction field, which affects the total field sensed by a coil. Hence, the presence of structural flaws will alter the eddy current flow and the picked-up signal. ECT is mostly sensitive to local changes of the electric conductivity of the test sample, and CFRPs are mostly conductive in the direction of carbon fibers. Hence, ECT was well suited for the detection of fiber damage/fiber irregularities. The MSU team developed printed circuit boards (PCB) with coil sensor arrays optimized for NDE of CFRP. Unlike most commercial probes designed for ECT of metallic structures, the MSU array probes were designed for operation in [1-10] MHz frequency range, which was optimal for low-conductive CFRP. Multiple sensing topologies (coil groups excitation/sensing arrangements) were implemented and successfully validated. Capacitive Imaging (CI) technique developed by MSU was complementary to ECT. In contrast to ECT, which was sensitive to local changes of the electrical conductivity, the CI was sensitive to local changes of the dielectric constant. Therefore, CI could provide information about matrix damage/matrix irregularities in CFRP. The MSU CI sensor arrays were made of multiple circular or rectangular open-plate capacitors printed on PCB. Sensors of this type are not commercially available. In addition to ECT and CI, the MSU team developed a hybrid (dual-mode) inductive/capacitive measurement technique that synergistically combined the benefits of inductive and capacitive sensing for rapid NDE of fiber reinforced polymer (FRP) composite structures. Fiber damage and fiber irregularities in FRPs were detected by configuring hybrid sensors as coil sensors. Similarly, matrix damage, matrix irregularities and interlaminar delaminations were detected by configuring hybrid sensors as capacitive sensors. ECT and CI were performed sequentially by means of electronic switching. Hence, eliminating the need for mounting two separate sensor arrays on the probe. Portable robotic platform was developed by MSU for multi-technique high-speed NDE of CFRP test parts. The platform had two 6-axis robots, which enabled inspection of curved parts in approximately a 6×6×6 ft 3 active scan area. On the software side, the MSU team integrated scripts for NDE hardware control with scripts for robot motion control. MSU also implemented automated path planning for the robots, reconstruction of part’s surfaces via stereovision, 3D rendering of inspection data, and image processing algorithms for enhanced defect detection. Automotive composite parts manufactured by Plasan Composites from Phase I were used to validate the ACUT and EMT techniques on representative testbeds. Among those parts were three X-braces for a Dodge Viper, one composite calibration plaque with known defects at known locations, and four other test sections, including sections from a front splitter, a corner section from a composite hood, and a high-pressure RTM panel made using non crimp fabric. Other test samples included CFRP and GFRP calibration plates with fiber/matrix defects fabricated at MSU/CVRC.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Stress‐Induced Domain Wall Motion in a Ferroelastic Mn 3+ Spin Crossover Complex

Abstract Domain wall motion is detected for the first time during the transition to a ferroelastic and spin state ordered phase of a spin crossover complex. Single‐crystal X‐ray diffraction and resonant ultrasound spectroscopy (RUS) revealed two distinct symmetry‐breaking phase transitions in the mononuclear Mn 3+ compound [Mn(3,5‐diBr‐sal 2 (323))]BPh 4 , 1. The first at 250 K, involves the space group change Cc → Pc and is thermodynamically continuous, while the second, Pc → P 1 at 85 K, is discontinuous and related to spin crossover and spin state ordering. Stress‐induced domain wall mobility was interpreted on the basis of a steep increase in acoustic loss immediately below the the Pc ‐ P 1 transition

Jakobsen, Vibe B.↗

DOE OSTI2023

Beyond Solvothermal: Alternative Synthetic Methods for Covalent Organic Frameworks

Abstract Covalent organic frameworks (COFs) are crystalline porous organic materials that hold a wealth of potential applications across various fields. The development of COFs, however, is significantly impeded by the dearth of efficient synthetic methods. The traditional solvothermal approach, while prevalent, is fraught with challenges such as complicated processes, excessive energy consumption, long reaction times, and limited scalability, rendering it unsuitable for practical applications. The quest for simpler, quicker, more energy‐efficient, and environmentally benign synthetic strategies is thus paramount for bridging the gap between academic COF chemistry and industrial application. This Review provides an overview of the recent advances in alternative COF synthetic methods, with a particular emphasis on energy input. We discuss representative examples of COF synthesis facilitated by microwave, ultrasound, mechanic force, light, plasma, electric field, and electron beam. Perspectives on the advantages and limitations of these methods against the traditional solvothermal approach are highlighted.

Hu, Jiyun↗

DOE OSTI2023

Beyond Solvothermal: Alternative Synthetic Methods for Covalent Organic Frameworks

Hu, Jiyun↗

DOE OSTI2023

Breast tumor-targeted drug delivery via polymer nanocarriers: Endogenous and exogenous strategies

Breast cancer, one of the most common types of cancer worldwide, has a high degree of malignancy while lacking efficient treatments. The off-target events frequently occurring in drug administration have been a major obstacle, which causes severe side effects to patients and reduces the therapeutic efficacy. An ideal medication should precisely target the specific site with precise control over concentration and duration. In recent years, there has been immense progress in polymer nanocarriers that demonstrate great potential in the targeted delivery. These nanocarriers are constructed from materials sensitive to a wide range of endogenous (e.g., pH, enzyme, redox) and exogenous stimuli (e.g., light, ultrasound, magnetic waves), driving cargo release to the targeted tissue or cells. Here, we elucidate the mechanism of current targeting strategies and the engineering methods to construct these targeting systems or to improve their targeting efficiency. Here we capture the recent progress in the targeted nanocarriers derived from polymers which span hydrogels and micelles, demonstrating their design and applications in chemo, hyperthermia, immuno, and gene therapies.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Recurrent and convolutional neural networks for sequential multispectral optoacoustic tomography ( MSOT ) imaging

Abstract Multispectral optoacoustic tomography (MSOT) is a beneficial technique for diagnosing and analyzing biological samples since it provides meticulous details in anatomy and physiology. However, acquiring high through‐plane resolution volumetric MSOT is time‐consuming. Here, we propose a deep learning model based on hybrid recurrent and convolutional neural networks to generate sequential cross‐sectional images for an MSOT system. This system provides three modalities (MSOT, ultrasound, and optoacoustic imaging of a specific exogenous contrast agent) in a single scan. This study used ICG‐conjugated nanoworms particles (NWs‐ICG) as the contrast agent. Instead of acquiring seven images with a step size of 0.1 mm, we can receive two images with a step size of 0.6 mm as input for the proposed deep learning model. The deep learning model can generate five other images with a step size of 0.1 mm between these two input images meaning we can reduce acquisition time by approximately 71%.

Juhong, Aniwat↗

DOE OSTI2021

Novel compound heterozygous CPLANE1 variants identified in a Chinese family with Joubert syndrome

Abstract Joubert syndrome (JS) and JS‐related disorders (JSRD) are a group of neurodevelopmental diseases that share the “molar tooth sign” on axial brain magnetic resonance imaging (MRI), accompanied by cerebellar vermis hypoplasia, ataxia, hypotonia, and developmental delay. To identify variants responsible for the clinical symptoms of a Chinese family with JS and to explore the genotype–phenotype associations, we conducted a series of clinical examinations, including blood tests, brain MRI scans, ultrasound imaging, and ophthalmologic examination. Genomic DNA was extracted from the peripheral blood of the six‐person family, and the pathogenic variants were detected by whole‐exome sequencing (WES) and verified by Sanger sequencing. WES revealed two novel compound heterozygous variants in CPLANE1 : c.1270C>T (p.Arg424*) in exon 10 and c.8901C>A (p.Tyr2967*) in exon 48 of one child, inherited from each parent. Both variants were absent in ethnically matched Chinese control individuals and were either absent or present at very low frequencies in public databases, suggesting that these variants could be the pathogenic triggers of the JS phenotype. Notably, these CPLANE1 sequence variants were related to the pathogenesis of autosomal recessive JS in this study. The newly discovered variants expand the mutation spectrum of CPLANE1 , which assists in understanding the molecular mechanism underlying JS and improving the recognition of genetic counseling, particularly for families with a history of autosomal recessive JS.

Zhang, Cheng↗

DOE OSTI2023

A combination interferometric and morphological image processing approach to rapid quality assessment of additively manufactured cellular truss core components

Advanced manufacturing (AM) processes such as laser powder bed fusion (LPBF) are increasingly capable of fabricating components with useful and unprecedented mechanical properties by incorporating complex internal bracing structures. From the standpoint of quality control and assessment, however, internally complex assemblies present significant build-verification challenges. Here we propose a hybrid approach to the inspection involving the application of computer-aided speckle interferometry (CASI) and morphological image processing as a rapid, inexpensive, and facile method for AM quality control. The described methodology has low capital equipment costs, is full-field and non-contact, can be used in an industrial setting, and has very low requirements in terms of operator training and expertise. Consisting primarily of the combination of image processing software with a simple optical system of variable sensitivity, the method is shown to be effective for inspection of a titanium honeycomb component subjected to differential pressure. Results are compared to those achieved with computed tomography (CT), immersion ultrasound testing (UT), and optical holographic interferometry. Here we propose several possible processing strategies for automated quality assessment based on this powerful hybrid approach.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Ultrasonic degradation of GenX (HFPO-DA) – Performance comparison to PFOA and PFOS at high frequencies

Sonolytic degradation kinetics of hexafluoropropylene oxide-dimer acid (HFPO-DA or GenX) were studied for the first time at four high ultrasonic frequencies (375, 580, 860 and 1,140kHz) and three power densities (200, 300 and 400W/L), and compared to the degradation of previously studied perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS). The frequency of 580kHz displayed the highest degradation of all three PFAS tested. Within each frequency, the degradation performance increased consistently with increasing power density. Degradation rates were highest for GenX over PFOA to PFOS (k GenX = 0.0501 min -1 , k PFOA = 0.0444 min -1 , k PFOS 0.0153 min -1 ), which is in direct agreement with their reported thermal stability (PFOS > PFOA > GenX). No known by-product formation as expected from the literature on truncation mechanism was detected in the samples (i.e. shorter chain carboxylic acid PFAS). Further, fluorine mass balance experiments at 580kHz and 400W/ L confirmed that GenX defluorinated fastest among the three tested PFAS and had lowest loss of fluorine in the mass balance. Degradation experiments with a mixture of all three PFAS displayed lower degradation rates than the individual experiments, where PFOA exhibited the largest reduction in degradation rate (by 31%), followed by GenX (by 19%), and finally by PFOS (by 17%). Overall, our study demonstrates that ultrasound can provide effective destruction of different PFAS (70-90% fluorine from mitigated PFAS was detected as inorganic fluoride) with a similar energy demand to alternative PFAS treatment methods reported in literature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Experimental evidence for the acceleration of slag hydration in blended cements by the addition of CaCl2

Cements with high substitution rates of ground granulated blast furnace slags (GGBS) have the potential to significantly lower CO{sub 2} emissions of concrete, but their early age strength is often below those of traditional OPC cements. One way of mitigating this drawback is to use accelerating admixtures. In this study, the effect of CaCl{sub 2} additions on the hydration of blended cements was investigated by measuring compressive strength, porosity, heat release and propagation of ultrasound in blends containing 70 wt% of GGBS. The onset of formation of aluminate phases was monitored using in-situ XRD. The effect of CaCl{sub 2} on slag hydration was isolated by replacing GGBS by an inert quartz filler. Results showed that compressive strength values at one, two and seven days were increased by 50% by the CaCl{sub 2} addition. The increases in compressive strength corresponded to a reduction in pore space. GGBS hydration contributed to the heat development, structuration and compressive strength of the blended cements from 15 h. The addition of CaCl{sub 2} led to an earlier onset of the GGBS reaction, at around 10 h, and increased the rate of GGBS hydration during the first seven days. The time of onset of the GGBS contribution was also the moment when AFm precipitation started. In CaCl{sub 2}-containing blends, Cl was incorporated in AFm.

36 MATERIALS SCIENCE↗

DOE OSTI2025

A Computational Framework to design 3D stiffness gradient acoustic metamaterials for impedance matching

Acoustic waves play a crucial role in various applications, including medical imaging, non-destructive testing, and sonar systems. One of the significant challenges in these applications is impedance matching, which is essential for minimizing reflections and maximizing the transfer of acoustic energy between different media. Acoustic metamaterials offer a promising solution to this challenge. In addition to impedance control, gradient stiffness can enhance structural efficiency and enable spatial control of wave propagation, making it a valuable feature in acoustic metamaterial design. In this pa- per, we present our developed computational method to design 3D stiffness gradient acoustic metamaterials for impedance matching. The key steps in our approach include generating initial designs using a periodic covariance function to provide unit cells that are both periodic on the boundaries and randomly formed inside the unit cell. Furthermore, we integrated manufacturing constraints into the design process, ensuring that the structures are interconnected for fabrication. We propose two computational optimization algorithms: GenUnit, based on a non-dominated sorting genetic algorithm (NSGA-II), and MLMatch, which leverages differentiable machine learning. The two approaches are not separate contributions but complementary com- ponents of a unified framework. GenUnit requires no training data and directly interfaces with physics-based simulations, making it highly accurate but slower for large-scale exploration. In contrast, MLMatch is data-hungry during training but, once trained, enables near-instantaneous inference and broad design-space coverage. Together, they form a hybrid strategy: ML- Match rapidly explores the global design space, and GenUnit provides local refinement with high-fidelity accuracy. This balance between training cost, inference time, and precision is the motivation for including both methods in the same study. We applied this dual-algorithm framework to generate two metallic-based metamaterial designs that match the acoustic impedance of water while exhibiting a controlled gradient in stiffness (from stiff to soft). The stiffness gradient is particularly advantageous in applications where one side of the structure must interface with soft or sensitive surfaces, such as human tissue or delicate components. Here, this work paves the way for improved materials in various acoustic applications, particularly in ultrasound devices, by providing better impedance.

Metamaterial↗