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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Modeling supercritical CO2 injection induced rupture of a minor fault embedded in a poroelastic layered reservoir-caprock system

CO2 injection for geologic carbon sequestration involves hydromechanical processes that lead to changes in fluid pressure and stresses that can activate existing faults. This paper presents a new method and workflow of modeling fault activation considering more complex three-dimensional geometry of natural faults using the TOUGH-FLAC multiphase fluid flow and geomechanical simulator. In this method and workflow, FLAC3D mechanical interfaces and TOUGH3 finite volume elements are discretized using computer aided design and gridding software along with a tailored mesh translation routine. The method and workflow are demonstrated with a model of a curved minor fault embedded in a poro-elastic layered reservoir-caprock system. The model is used for a comprehensive sensitivity analysis of fault responses to fault length, injection mass rate, injection schedule, well-fault distance, and well locations versus fault location. Four metrics (CO2 plume, shear state of fault, pressure and stress path at fault monitoring points) are selected to assess CO2 migration, pressure change, and the reactivation of faults. The results reveal that CO2 can bypass around the tip of the minor impermeable fault, building up pressure and poro-elastic stress on both sides that tends to impede fault rupture. Our study shows the benefit of carefully designing the injection to achieve the targeted final storage volume, starting at a relatively low rate for considerable time, and then ramping up the injection rate to the full rate of injection. The initial low injection has two distinct benefits: (1) it allows for the formation of an extensive CO2 plume with a much higher mobility through a low viscosity that will result in a lower pressure for a given injection rate, and (2) it allows for gradual build-up of horizontal poro-elastic stress within the reservoir that will tend to impede activation of steeply dipping faults. The injection scenario starting at a low injection rate, denoted here as conservative injection, can significantly reduce the risk of fault activation as high fluid mobility and reservoir strengthening poro-elastic stress has been established long before reaching the peak injection rates. Moreover, simultaneous injection in two injection wells on both sides of fault can provide further reservoir strengthening through poro-elastic stress buildup acting on a fault under normal faulting stress regime. The findings presented in the paper can provide practical and effective guidance on long-term, safe, and reliable geological CO2 storage.

Cao, Meng↗
DOE OSTI2022

Evidence for nitrogen binding to surface defects for topological insulator Bi 2 Se 3

Using scanning tunneling spectroscopy and theoretical simulations we have studied the effects of nitrogen gas exposure on the electronic density of states of Bi 2 Se 3 , a well-studied topological insulator. In carefully controlled measurements, Bi 2 Se 3 crystals were initially cleaved in a helium gas environment and then exposed to a 22 SCFH flow of ultra-high purity N 2 gas. We observe a resulting change in the spectral curves, with the exposure effect saturating after approximately 50 min, ultimately bringing the Dirac point about 50 meV closer to the Fermi level. Furthermore, these results are compared to density functional theory calculations, which support a picture of N 2 molecules physisorbing near Se vacancies. Furthermore, ab initio molecular dynamics simulations aided by a Blue Moon ensemble method reveal the dissociative adsorption of N 2 molecules which then bind strongly to Se vacancies at the surface. In this scenario, the binding of the N atom to a Se vacancy site removes the surface defect state created by the vacancy and changes the position of the Fermi energy with respect to the Dirac point.

36 MATERIALS SCIENCE↗
DOE OSTI2020

On the ATLAS top mass measurements and the potential for stealth stop contamination

The discovery of the stop — the Supersymmetric partner of the top quark — is a key goal of the physics program enabled by the Large Hadron Collider. Although much of the accessible parameter space has already been probed, all current searches assume the top mass is known. This is relevant for the “stealth stop” regime, which is characterized by decay kinematics that force the final state top quark off its mass shell; such decays would contaminate the top mass measurements. We investigate the resulting bias imparted to the template method based ATLAS approach. A careful recasting of these results shows that effect can be as large as 2.0 GeV, comparable to the current quoted uncertainty on the top mass. Thus, a robust exploration of the stealth stop splinter requires the simultaneous consideration of the impact on the top mass. Additionally, we explore the robustness of the template technique, and point out a simple strategy for improving the methodology implemented for the semi-leptonic channel.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Neurons die with heightened but functional macro- and chaperone mediated autophagy upon increased amyloid-ß induced toxicity with region-specific protection in prolonged intermittent fasting

Highlights: • Macroautophagy (MA) is strongly engaged upon APP overexpression and remains high over time. • APP colocalization with macroautophagy components remains increased until late, promoting continuous recruitment to the autophagy machinery. • Robust chaperone-mediated autophagy (CMA) engagement is observed in late APP overexpression. • Macroautophagic flux during APP overexpression is preserved, even at late time points, suggesting functional autophagy in the face of apoptosis onset. • Macroautophagy impairment increases markers of amyloidogenesis and further exacerbates the onset of apoptotic cell death. Alzheimer's disease (AD) is a devastating neurodegenerative condition with significant socio-economic impact that is exacerbated by the rapid increase in population aging, particularly impacting already burdened health care systems of poorly resourced countries. Accumulation of the amyloid-β (Aβ) peptide, generated through amyloid precursor protein (APP) processing, manifesting in senile plaques, is a well-established neuropathological feature. Aβ plays a key role in driving synaptic dysfunction, neuronal cell loss, glial cell activation and oxidative stress associated with the pathogenesis of AD. Thus, the enhanced clearance of Aβ peptide though modulation of the mechanisms that regulate intracellular Aβ metabolism and clearance during AD progression have received major attention. Autophagy, a lysosome-based major proteolytic pathway, plays a crucial role in intracellular protein quality control and has been shown to contribute to the clearance of Aβ peptide. However, to what extent autophagy activity remains upregulated and functional in the process of increasing Aβ neurotoxicity is largely unclear. Here, we investigated the extent of neuronal toxicity in vitro by characterising autophagic flux, the expression profile of key amyloidogenic proteins, and proteins associated with prominent subtypes of the autophagy pathway to dissect the interplay between the engagement of proteolytic pathways and cell death onset in the context of APP overexpression. Moreover, we assessed the neuroprotective effects of a caloric restriction regime in vivo on the modulation of autophagy in specific brain regions. Our results reveal that autophagy is upregulated in the presence of high levels of APP and Aβ and remains heightened and functional despite concomitant apoptosis induction, suggestive of a mismatch between autophagy cargo generation and clearance capacity. These findings were confirmed when implementing a prolonged intermittent fasting (IF) intervention in a model of paraquat-induced neuronal toxicity, where markers of autophagic activity were increased, while apoptosis onset and lipid peroxidation were robustly decreased in brain regions associated with neurodegeneration. This work highlights that especially caloric restriction mimetics and controlled prolonged IF may indeed be a highly promising therapeutic strategy at all stages of AD-associated pathology progression, for a cell-inherent and cell specific augmentation of Aβ clearance through the powerful engagement of autophagy and thereby robustly contributing to neuronal protection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

iMaNGA: mock MaNGA galaxies based on IllustrisTNG and MaStar SSPs – I. Construction and analysis of the mock data cubes

ABSTRACT Galaxy formation and evolution simulations are essential tools to probe poorly known astrophysics processes, but particular care is needed to compare simulations with galaxy observations, as observed data need to be modelled as well. We present a method to generate mock galaxies from the hydro-dynamical IllustrisTNG simulations which are suited to compare with integral field spectroscopic observation of galaxies from the SDSS-IV/Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. First, we include the same instrumental effects and procedures as adopted in the acquisition and analysis of real data. Furthermore, we generate the galaxy spectra from the simulations using new stellar population models based on the MaNGA stellar library (MaStar). In this way, our mock data cubes have the same spatial sampling, cover the same wavelength range (3600–10 300 Å), and share the same spectral resolution (R ≈ 1800) and flux calibration of real MaNGA galaxy spectra. In this first paper, we demonstrate the method over an early- and a late-type simulated galaxy from TNG50. We analyse the correspondent mock MaNGA-like data cubes with the same full spectral fitting code, firefly, which was used for the observed spectra. We find that the intrinsic and recovered age and metallicity gradients are consistent within 1σ, with residuals over all tassels consistent with 0 at the 68 ${{\ \rm per\ cent}}$ confidence level. We also perform the challenging test at comparing intrinsic and recovered star formation histories, finding a close resemblance between input and output. In follow-up papers, we will present a full simulated MaNGA-like catalogue (≈10 000 galaxies) with a comprehensive comparison of TNG50 simulations to MaNGA observational results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Molecular beam epitaxy of PdO on MgO (001)

PdO, widely used in catalysis in powder form for decades, has been predicted recently to be a Dirac semimetal. Synthesis of high-quality single crystals of this material is thus of great interest. Here, by using ozone-assisted molecular beam epitaxy, PdO thin films were grown on a MgO (001) substrate. X-ray diffraction and transmission electron microscopy indicate the film is a / b axis oriented, with the c axis lying in plane. Fully oxygenated PdO films have a low density of holelike carriers, and are insulating at the lowest temperatures. Our density functional theory calculations using the Heyd-Scuseria-Ernzerhof exchange-correlation functional suggest a ~1.0 eV band gap at the M point, where the gap can be reduced by tensile strain along the c axis and the bands begin to invert when the tensile strain is as high as 18%. Although tensile strain of this magnitude is experimentally not viable using epitaxy, electrons can be doped by oxygen reduction. Finally, our results emphasize the need for careful consideration of electron correlation effects and stoichiometry in ab initio modeling of topological semimetals involving transition metal oxides.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Fabrication of Silicon Sensors Based on Low-Gain Avalanche Diodes

Low-Gain Avalanche Diodes are a recently-developed class of silicon sensors. Characterized by an internal moderate gain that enhances the signal amplitude and if built on thin silicon substrates of a few tens of microns, they feature fast signals and exhibit excellent timing performance. Thanks to their fast timing they are planned to be exploited in timing detectors in High-Energy Physics experiments, for example for the upgrades of the ATLAS and CMS detectors at the High Luminosity Large Hadron Collider (HL-LHC) at CERN. However, to achieve a spatially uniform multiplication a large pixel pitch is needed, preventing a fine spatial resolution. To overcome this limitation, the AC-coupled LGAD approach was introduced. In this type of device, metal electrodes are placed over an insulator at a fine pitch, and signals are capacitively induced on these electrodes. The fabrication technology is similar for the two LGAD families, although a fine tuning of a few process parameters needs to be carefully studied. Other R&D efforts towards detectors that can simultaneously provide good time and spatial resolution, based on the LGAD concept, are under way. These efforts aim also to mitigate the loss of performance at high irradiation fluences due to the acceptor removal within the gain layer. In this paper we describe the main points in the fabrication of LGADs and AC-LGADs in a clean-room. We also discuss novel efforts carried on related topics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Operator origin of anomalous dimensions in de Sitter space

The late-time limit of the power spectrum for heavy (principal series) fields in de Sitter (dS) space yields a series of polynomial terms with complex scaling dimensions. Such scaling behavior is expected to result from an associated operator with a complex dimension. In a free theory, these complex dimensions are known to match the constraints imposed by unitarity on the space of states. Yet, perturbative corrections to the scaling behavior of operators are naively inconsistent with unitary evolution of the quantum fields in dS space. This paper demonstrates how to compute one-loop corrections to the scaling dimensions that appear in the two-point function from the field theory description in terms of local operators. We first show how to evaluate these anomalous dimensions using Mellin space, which has the feature that it naturally accommodates a scaleless regulator. We then explore the consequences for the soft de Sitter effective theory (SdSET) description that emerges in the long wavelength limit. Carefully matching between the UV and SdSET descriptions requires the introduction of novel nondynamical “operators” in the effective theory. This is not only necessary to reproduce results extracted from the Källén-Lehmann representation (that use the space of unitary states directly), but it is also required by general arguments that invoke positivity. Published by the American Physical Society 2025

Cohen, Timothy↗
DOE OSTI2021

Extremely Overdoped Superconducting Cuprates via High Pressure Oxygenation Methods

Within the cuprate constellation, one fixed star has been the superconducting dome in the quantum phase diagram of transition temperature vs. the excess charge on the Cu in the CuO2-planes, p, resulting from O-doping or cation substitution. However, a more extensive search of the literature shows that the loss of the superconductivity in favor of a normal Fermi liquid on the overdoped side should not be assumed. Many experimental results from cuprates prepared by high-pressure oxygenation show Tc converging to a fixed value or continuing to slowly increase past the upper limit of the dome of p = 0.26–0.27, up to the maximum amounts of excess oxygen corresponding to p values of 0.3 to > 0.6. These reports have been met with disinterest or disregard. Our review shows that dome-breaking trends for Tc are, in fact, the result of careful, accurate experimental work on a large number of compounds. This behavior most likely mandates a revision of the theoretical basis for high-temperature superconductivity. That excess O atoms located in specific, metastable sites in the crystal, attainable only with extreme O chemical activity under HPO conditions, cause such a radical extension of the superconductivity points to a much more substantial role for the lattice in terms of internal chemistry and bonding.

Sederholm, Linda (ORCID:0000000172090509)↗
DOE OSTI2025

Acoustic misalignment mechanism for axion dark matter

A rotation in the field space of a complex scalar field corresponds to a Bose-Einstein condensation of U(1) charges. We point out that fluctuations in this rotating condensate exhibit sound-wave modes, which can be excited by cosmic perturbations and identified with axion fluctuations once the U(1) charge condensate has been sufficiently diluted by cosmic expansion. We consider the possibility that these axion fluctuations constitute dark matter and develop a formalism to compute its abundance. We carefully account for the growth of fluctuations during the epoch where the complex scalar field rotates on the body of the potential and possible nonlinear evolution when the fluctuations become non-relativistic. We find that the resultant dark matter abundance can exceed the conventional and kinetic misalignment contributions if the radial direction of the complex scalar field is sufficiently heavy. The axion dark matter may also be warm enough to leave imprints on structure formation. We discuss the implications of this novel dark matter production mechanism — acoustic misalignment mechanism — for the axion rotation cosmology, including kination domination and baryogenesis from axion rotation, as well as for axion searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Distributed Ledger Technology Preliminary Performance Assessment for Applications in Utilities Operational Technology

This paper provides descriptions of the key components of different distributed ledger technology platforms. Distributed ledger technology (DLT) allows for distribution of databases among different organizations and devices. The platforms use cryptographically linked “blocks” to store and verify transactional information between these organizations. DLT increases data security, data integrity, trust among its participants. Different organizations are looking to deploy this distributed and decentralized approach to avoid the single-point-of-failure vulnerabilities associated with centralized data repositories. In this study we examine twelve different DLT platforms. There is agreement within the community that of all the platforms considered here, Hyperledger and Ethereum are the most mature when it comes to privacy and permissions. These DLT platforms are being used for applications such as transactive energy, health care, and the food and goods supply chain. However, further development is required to realize the full promise of DLT. Our assessment includes a general description of each DLT and its key characteristics. Such characteristics include consensus protocol and cryptography used, public vs. private, and permissioned or permissionless. The selection and implementation of a DLT architecture depends heavily on the use case and performance requirements. During this research we found key parameters to measure performance and existing tools for assessment. Four different parameters were identified 1) consensus, 2) throughput, 3) latency, and 4) scalability. The architectures of Hyperledger Caliper and Blockbench are described as different performance assessment frameworks. From this preliminary study it is evident that there are dissimilarities on the performance assessments methods developers and users are characterizing DLT architectures. The purpose of this paper is to identify key parameters to test performance, tools that are being used and provide information on results from previous studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Effects of process intensification on homogeneity of an IgG1:κ monoclonal antibody during perfusion culture

The pharmaceutical industry employs various strategies to improve cell productivity. These strategies include process intensification, culture media improvement, clonal selection, media supplementation and genetic engineering of cells. However, improved cell productivity has inherent risk of impacting product quality attributes (PQA). PQAs may affect the products’ efficacy via stability, bioavailability, or in vivo bioactivity. Variations in manufacturing process may introduce heterogeneity in the products by altering the type and extent of N-glycosylation, which is a PQA of therapeutic proteins. We investigated the effect of different cell densities representing increasing process intensification in a perfusion cell culture on the production of an IgG1-κ monoclonal antibody from a CHO-K1 cell line. This antibody is glycosylated both on light chain and heavy chain. Our results showed that the contents of glycosylation of IgG1-κ mAb increased in G0F and fucosylated type glycans as a group, whereas sialylated type glycans decreased, for the mAb whole protein. Overall, significant differences were observed in amounts of G0F, G1F, G0, G2FS1, and G2FS2 type glycans across all process intensification levels. G2FS2 and G2 type N-glycans were predominantly quantifiable from light chain rather than heavy chain. It may be concluded that there is a potential impact to product quality attributes of therapeutic proteins during process intensification via perfusion cell culture that needs to be assessed. Since during perfusion cell culture the product is collected throughout the duration of the process, lot allocation needs careful attention to process parameters, as PQAs are affected by the critical process parameters (CPPs).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Research-Driven Radiation Oncology: A Narrative on the Ongoing Legacy of Henry S. Kaplan

In this rapidly evolving time of precision medicine and scientifically based cancer care, how radiation oncology became a strong research-based scientific discipline in the United States after its separation from diagnostic radiology might be lost. The importance of generational mentorship, “family trees,” and interpersonal relationships can be difficult or impossible to trace absent personal narrative recollections of those involved. Henry S. Kaplan is a central figure and the focal point for 3 generations of research-based academic department chairs. This report establishes a first draft of a living record of the radiation oncology history of the Kaplan legacy to serve as an example of how knowledge networks grow and flourish and as an impetus for others to trace the legacy of other radiation oncology academic “trees.”.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Collective coordinate fix in the path integral

Collective coordinates are frequently employed in path integrals to manage divergences caused by fluctuations around saddle points that align with classical symmetries. These coordinates parametrize a manifold of zero modes and more broadly provide judicious coordinates on the space of fields. However, changing from local coordinates around a saddle point to more global collective coordinates is remarkably subtle. The main complication is that the mapping from local coordinates to collective coordinates is generically multivalued. Consequently one is forced to either restrict the domain of path integral in a delicate way, or otherwise correct for the multivaluedness by dividing the path integral by certain intersection numbers. We provide a careful treatment of how to fix collective coordinates while accounting for these intersection numbers, and then demonstrate the importance of the fix for free theories. We also provide a detailed study of the fix for interacting theories and show that the contributions of higher intersections to the path integral can be nonperturbatively suppressed. Using a variety of examples ranging from single-particle quantum mechanics to quantum field theory, we explain and resolve various pitfalls in the implementation of collective coordinates. Published by the American Physical Society 2024

Bhattacharya, Arindam (ORCID:0000000244578926)↗
DOE OSTI2022

Preliminary Results for Using Uncertainty and Out-of-distribution Detection to Identify Unreliable Predictions.

As machine learning (ML) models are deployed into an ever-diversifying set of application spaces, ranging from self-driving cars to cybersecurity to climate modeling, the need to carefully evaluate model credibility becomes increasingly important. Uncertainty quantification (UQ) provides important information about the ability of a learned model to make sound predictions, often with respect to individual test cases. However, most UQ methods for ML are themselves data-driven and therefore susceptible to the same knowledge gaps as the models themselves. Specifically, UQ helps to identify points near decision boundaries where the models fit the data poorly, yet predictions can score as certain for points that are under-represented by the training data and thus out-of-distribution (OOD). One method for evaluating the quality of both ML models and their associated uncertainty estimates is out-of-distribution detection (OODD). We combine OODD with UQ to provide insights into the reliability of the individual predictions made by an ML model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Scalable statistical inference of photometric redshift via data subsampling

Handling big data has largely been a major bottleneck in traditional statistical models. Consequently, when accurate point prediction is the primary target, machine learning models are often preferred over their statistical counterparts for bigger problems. But full probabilistic statistical models often outperform other models in quantifying uncertainties associated with model predictions. We develop a data-driven statistical modeling framework that combines the uncertainties from an ensemble of statistical models learned on smaller subsets of data carefully chosen to account for imbalances in the input space. We demonstrate this method on a photometric redshift estimation problem in cosmology, which seeks to infer a distribution of the redshift—the stretching effect in observing the light of far-away galaxies—given multivariate color information observed for an object in the sky. Our proposed method performs balanced partitioning, graph-based data subsampling across the partitions, and training of an ensemble of Gaussian process models.

data subsampling↗
DOE OSTI2024

GPU-enabled extreme-scale turbulence simulations: Fourier pseudo-spectral algorithms at the exascale using OpenMP offloading

Fourier pseudo-spectral methods for nonlinear partial differential equations are of wide interest in many areas of advanced computational science, including direct numerical simulation of three-dimensional (3-D) turbulence governed by the Navier-Stokes equations in fluid dynamics. This paper presents a new capability for simulating turbulence at a new record resolution up to 35 trillion grid points, on the world's first exascale computer, Frontier, comprising AMD MI250x GPUs with HPE's Slingshot interconnect and operated by the US Department of Energy's Oak Ridge Leadership Computing Facility (OLCF). Key programming strategies designed to take maximum advantage of the machine architecture involve performing almost all computations on the GPU which has the same memory capacity as the CPU, performing all-to-all communication among sets of parallel processes directly on the GPU, and targeting GPUs efficiently using OpenMP offloading for intensive number-crunching including 1-D Fast Fourier Transforms (FFT) performed using AMD ROCm library calls. With 99% of computing power on Frontier being on the GPU, leaving the CPU idle leads to a net performance gain via avoiding the overhead of data movement between host and device except when needed for some I/O purposes. Memory footprint including the size of communication buffers for MPI_ALLTOALL is managed carefully to maximize the largest problem size possible for a given node count. Detailed performance data including separate contributions from different categories of operations to the elapsed wall time per step are reported for five grid resolutions, from 2048 3 on a single node to 32768 3 on 4096 or 8192 nodes out of 9408 on the system. Both 1D and 2D domain decompositions which divide a 3D periodic domain into slabs and pencils respectively are implemented. The present code suite (labeled by the acronym GESTS, GPUs for Extreme Scale Turbulence Simulations) achieves a figure of merit (in grid points per second) exceeding goals set in the Center for Accelerated Application Readiness (CAAR) program for Frontier. The performance attained is highly favorable in both weak scaling and strong scaling, with notable departures only for 2048 3 where communication is entirely intra-node, and for 32768 3 , where a challenge due to small message sizes does arise. Communication performance is addressed further using a lightweight test code that performs all-to-all communication in a manner matching the full turbulence simulation code. Performance at large problem sizes is affected by both small message size due to high node counts as well as dragonfly network topology features on the machine, but is consistent with official expectations of sustained performance on Frontier. Overall, although not perfect, the scalability achieved at the extreme problem size of 32768 3 (and up to 8192 nodes — which corresponds to hardware rated at just under 1 exaflop/sec of theoretical peak computational performance) is arguably better than the scalability observed using prior state-of-the-art algorithms on Frontier's predecessor machine (Summit) at OLCF. New science results for the study of intermittency in turbulence enabled by this code and its extensions are to be reported separately in the near future.

3D fast Fourier transform↗
DOE OSTI2020

Defects and Mechanical Behavior of Plutonium [Slides]

Defects are important because they heavily influence material properties (e.g. strength, ductility, elasticity, conductivity, phase transformation temperatures (melting point), corrosion resistance, etc.). At LANL defects in plutonium are being characterized using many different methods (e.g. EXAFS, XRD, microscopy, RUS, DSC, dilatometry, density, etc.) My goal is to introduce a complimentary method of understanding defects in δ-Pu using the mechanical microscope concept. Using well-developed theories of first principles strengthening mechanisms (i.e. how defects influence strength) and carefully designed experiments, mechanical testing can compliment other defect characterization tools.

36 MATERIALS SCIENCE↗