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At least 1,207 records · Page 67

Atomistic deformation mechanism of silicon under laser-driven shock compression

Abstract Silicon (Si) is one of the most abundant elements on Earth, and it is the most widely used semiconductor. Despite extensive study, some properties of Si, such as its behaviour under dynamic compression, remain elusive. A detailed understanding of Si deformation is crucial for various fields, ranging from planetary science to materials design. Simulations suggest that in Si the shear stress generated during shock compression is released via a high-pressure phase transition, challenging the classical picture of relaxation via defect-mediated plasticity. However, direct evidence supporting either deformation mechanism remains elusive. Here, we use sub-picosecond, highly-monochromatic x-ray diffraction to study (100)-oriented single-crystal Si under laser-driven shock compression. We provide the first unambiguous, time-resolved picture of Si deformation at ultra-high strain rates, demonstrating the predicted shear release via phase transition. Our results resolve the longstanding controversy on silicon deformation and provide direct proof of strain rate-dependent deformation mechanisms in a non-metallic system.

36 MATERIALS SCIENCE↗

The nonlinear mechanics of highly extensible plant epidermal cell walls

Plant epidermal cell walls maintain the mechanical integrity of plants and restrict organ growth. Mechanical analyses can give insights into wall structure and are inputs for mechanobiology models of plant growth. To better understand the intrinsic mechanics of epidermal cell walls and how they may accommodate large deformations during growth, we analyzed a geometrically simple material, onion epidermal strips consisting of only the outer (periclinal) cell wall, ~7 μm thick. With uniaxial stretching by >40%, the wall showed complex three-phase stress–strain responses while cyclic stretching revealed reversible and irreversible deformations and elastic hysteresis. Stretching at varying strain rates and temperatures indicated the wall behaved more like a network of flexible cellulose fibers capable of sliding than a viscoelastic composite with pectin viscosity. We developed an analytic framework to quantify nonlinear wall mechanics in terms of stiffness, deformation, and energy dissipation, finding that the wall stretches by combined elastic and plastic deformation without compromising its stiffness. We also analyzed mechanical changes in slightly dehydrated walls. Their extension became stiffer and more irreversible, highlighting the influence of water on cellulose stiffness and sliding. This study offers insights into the structure and deformation modes of primary cell walls and presents a framework that is also applicable to tissues and whole organs.

59 BASIC BIOLOGICAL SCIENCES↗

Upcycling of Mixed Aluminum Alloy Shredder Scrap using Shear Processing

Conservation of critical materials is an increasing area of focus in the Unites States. In 2023, aluminum was added to the US Department of Energy Final Critical Materials List which has spurred public and private research into sustainable management of these resources. Additionally, efficiency in manufacturing and conservation of natural resources are growing concerns with targets to lower global carbon emissions, as primary aluminum alloy production is energy intensive, requiring 14 MWh of electricity plus 0.4 tonnes of CO2 per tonne of Al. Due to these factors, is essential that more sustainable manufacturing methods for aluminum alloys are developed going forward. To this end, much research is ongoing on the topic of more efficient utilization and recovery. However, most of this research still requires primary aluminum in the production process. Here, it will be attempted to bypass the use of primary aluminum and produce useful material recycled from 100% post-consumer scrap. Even considering recent developments in recycling of Al scrap, there is still a large amount of post-consumer scrap that is underutilized due to high impurity content, and that amount will increase significantly as more and more aluminum alloys are utilized in vehicles. This “scrap wave” is expected to cover 80% of the demand for automotive aluminum alloys by 2050 . A challenge to be addressed before the coming scrap wave can be fully utilized is that the tolerance of manufacturing techniques to impurities or off-spec alloy compositions must be increased. Particularly, in 5000-and 6000-series alloys (the most common wrought alloys in durable products), excess iron, copper, and silicon create brittle intermetallics during casting that remain in the extruded microstructure which limit the formability, ductility, and corrosion resistance of the alloy. Concerningly, many of the highest-volume post-consumer aluminum scrap streams such as automotive shredder scrap contain a mix of alloys including both wrought and cast alloys. Their compositions can vary widely depending on geography and the time of year. Because they are mixed, they often contain high content of multiple alloying elements such as Si and Cu in higher concentrations than are found in typical wrought alloys. They may also be contaminated with non-Al alloys from fasteners that get mixed in and often have high content of unwanted elements such as Fe. As a method for utilizing these underused scrap streams that are high in tramp elements, an emerging extrusion technology is being developed at the Pacific Northwest National Laboratory (PNNL) that aims to upcycle 100% post-consumer aluminum scrap directly into extruded components without the addition of primary aluminum . This new technology, called Shear Assisted Processing and Extrusion (ShAPE), is enabling a shift away from today’s recycling paradigm by reaching deeper into lower-value scrap streams, using shredder scrap as the extrusion billet material. Sometimes referred to as Twitch or Tweak, these scrap streams result from shredding and sorting of automobiles, building materials, appliances, and consumer goods. ShAPE combines the linear axis of conventional extrusion with a rotating extrusion die. This rotating die applies large strain to the material during extrusion, which breaks up large impurity-containing intermetallic particles, reducing their deleterious effects. This has been demonstrated for 6063 machining scrap spiked with excess Fe, and Twitch scrap high in Fe, Si and Cu where strength and ductility were retained for both feedstock compositions. Additionally, the extreme plastic deformation during ShAPE enables extrusion of billets with high Si that are too brittle for processing by conventional extrusion. By using 100% post-consumer shedder scrap as feedstock, ShAPE has the potential to slash embodied energy and carbon in extruded components by >80% compared to conventional extrusion of primary aluminum alloys.

Milligan, Brian K.↗

Simulating the Structural Response of a Preloaded Bolted Joint

The present paper describes the structural analyses performed on a preloaded bolted-joint configuration. The joint modeled was comprised of two L-shaped structures connected together using a single bolt. Each L-shaped structure involved a vertical flat segment (or shell wall) welded to a horizontal segment (or flange). Parametric studies were performed using elasto-plastic, large-deformation nonlinear finite element analyses to determine the influence of several factors on the bolted-joint response. The factors considered included bolt preload, washer-surface-bearing size, edge boundary conditions, joint segment length, and loading history. Joint response is reported in terms of displacements, gap opening, and surface strains. Most of the factors studied were determined to have minimal effect on the bolted-joint response; however, the washer-bearing-surface size affected the response significantly.

Knight, Norman F., Jr.↗

Probing Fundamental Mechanisms of Plastic Deformation with High Energy X-rays (Final Progress Report)

Overall, substantial progress was made on developing BCDI techniques in the direction of imaging defects in multi-crystal samples. Section 2.1 describes a new method to reconstruct the 3D atomic displacement field within a grain from multiple coherently resolved diffraction peaks. The key development is the ability to recover a best fit to the grain shape at the same time as the internal displacement (strain) variation with no prior knowledge of the microstructure. This is complemented by the development of a method, Sec. 2.2, to separate out sets of Laue reflections that belong to a single grain (and thus be able to index its orientation) in the commonly encountered situation in which the beam illuminates several grains in a given location. This is essential for enabling collection of coherent diffraction data (at APS 34-ID-C) from neighboring grains. All experiments depend on the quality of samples used. Although good progress has been made with thin film samples, we are working with a broader range of geometries. A new sample design uses a high-Z metal (e.g., Pt) deposited in a sub-micron trench in a low-Z metal (e.g., Al) so that the grain size is prevented from exceeding the current limit for BCDI. We also report in section 3.1 on successfully applying NF-HEDM to a fine-grain Mg sample that would normally be considered out of scope for the method. This represents progress towards being able to map out polycrystalline samples in 3D before performing BCDI on individual grains. We further report in section 3.2 on preliminary NF-HEDM characterization of a sample of UO2 that has sub-micron grains; the data imply the capability of mapping fine-grain polycrystals at 1-ID-E, again for the purposes of BCDI in the bulk. Lastly, our plan is to load grains in polycrystalline samples by inducing thermal stress. We also report the experimental measurements of the Ti- 6Al-4V alloy obtained at the European Synchrotron Radiation Facility (ESRF), which had been indexed and mapped via HEDM at APS in section 9. As discussed below, however, technique development pre-occupied the team throughout the project which meant that we did not make any significant progress towards answering the original hypotheses as stated in the proposal. In summary, we assert that we have made good progress in methods and samples and future work taking advantage of this progress is likely to obtain and analyze BCDI data from multiple adjacent grains in 3D polycrystals. Obtaining such data depends on re-gaining access to the Advanced Photon Source, which is anticipated in late summer or the Fall. In all cases, work has involved close collaboration with faculty, staff, postdocs and students from Brigham Young University (BYU), the Los Alamos National Laboratory and APS beamlines 1-ID and 34-ID.

36 MATERIALS SCIENCE↗

Finite deformation of elasto-plastic solids

A theoretical basis is established for analysis of finite deformation of metals. The observation that finite deformation of such elastoplastic materials may be viewed as a process rather than an event leads to derivation of a complete initial and boundary value problem distinguished by its quasilinear nature. This feature of the formulation motivates adoption of an incremental approach to numerical problem solving. Numerical solution capability is established for problems of plane stress and plane strain. The validity of the theory and numerical analysis is demonstrated by consideration of a number of problems of homogeneous finite deformation for which analytic solutions are available. Subsequently the analysis is employed for the investigation of necking in flat metal tensile bars. The results of this investigation provide the first full numerical solutions for tensile necking in plane stress and plane strain. In addition a basis is provided for assessment of the validity of stress-strain relations inferred from tensile test data.

Osias, J. R.↗

Predicting fracture behavior in single crystal nickel using a coupled crystal plasticity phase field damage approach

Understanding the fracture behavior of single crystal metals is critical for predicting material performance under mechanical loading. Here, in this study, we investigate the fracture characteristics of single crystal nickel tensile bars using a crystal plasticity coupled phase field damage (CP-PFD) model. Experimental tensile tests were conducted on 15 specimens spanning five crystallographic orientations and three thickness variants per orientation. The results revealed two distinct fracture modes: brittle fractures with 45-degree angled surfaces and ductile fractures characterized by significant necking. The CP-PFD model successfully replicated these fracture behaviors, demonstrating strong agreement with experimental observations. The model effectively predicted the strain at which necking and fracture occurred, as well as the orientation-dependent fracture mechanisms. By comparing experimental and simulated fracture surfaces, we establish the CP-PFD model as a robust tool for predicting single crystal behavior and damage evolution. This work provides insight into the microstructural dependence of fracture behavior and establishes a predictive framework for modeling orientation-dependent damage evolution in single-crystal nickel.

Crystal plasticity↗

Converting plastic waste pyrolysis ash into flash graphene

Pyrolysis of plastic waste (PW), a commercial method of recycling, is currently economically challenging and produces up to 20% by mass valueless pyrolysis ash (PA) as a byproduct. Here, direct, facile upcycling of PW-derived PA into high purity turbostratic flash graphene (tFG) is demonstrated. The tFG displays excellent dispersibility, yielding a concentration of 2.84 mg/mL in aqueous surfactant solution. The tFG was used to fabricate tFG-PVA nanocomposites, and low doses of tFG (0.1%–1%) improve failure strain by 15%–30% when compared to the samples of neat PVA. Furthermore, the addition of tFG to PVA films showed decreased hydrophilic interactions, increasing the water contact angle by 235% and adsorbing 500% less water than neat PVA. The tFG was also added to Portland cement paste as well as concrete, and exhibited 43% and 25% increases in compressive strength, respectively. The tFG is used directly in both composite applications, requiring no purification or chemical functionalization, unlike many other products used in nanocomposites.

54 ENVIRONMENTAL SCIENCES↗

A Hybrid AI/ML and Computational Mechanics Based Approach for Time-Series State and Fatigue Life Estimation of Nuclear Reactor Components

Environmental fatigue modeling is a complex problem due to multiple failure modes and their intermixing. The failure modes are function of various underlying causes in addition to the corrosive effect of reactor coolant environment. Some of the major causes are time-dependence of material associated with cyclic loading, load sequence effect associated with random/variable amplitude loading, effect of strain amplitude and rates, effect of varying temperature (along both temporal and spatial directions) and the effect of mean strain and stress. The nonlinear intermixing of failure modes associated with above mentioned causing parameters makes the environmental fatigue modeling is a challenging task. Because of this challenge, fatigue is traditionally being modeled based on experimental data. However, test based empirical approach often requires hundreds of fatigue tests to model the above-mentioned intermixing failure causes even for a single material system. The problem is further exaggerated for reactor component made from multi-material systems such as made from both carbon and stainless-steel base metals and their similar and dissimilar metal welds. With the difficulty of conducting hundreds of fatigue tests to capture the above-mentioned intermixing failure causes, fatigue modeling approaches often depends on empirical models based on limited available test data such as available through ASME code and NUREG 6909. However, these limited test-data-based models may not be enough to accurately predict the life of reactor components. Accurate prediction of life of reactor component would become a necessity, particularly when the license of the reactors to be extended for long-term-operation (LTO) that is for well beyond its original design life of 40 years. The requirement of extending the license of reactor under LTO requires hundreds of fatigue tests to be conducted to understand the mechanism associated with the above-mentioned interdependent failure causes. However, conducting large number of fatigue tests is not a feasibility due to the cost involved. To address this issues Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program trying to develop a hybrid predictive modeling approach. This is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics based modeling tools. The hybrid approach not-only can improve the accuracy of the existing stress analysis and fatigue modeling approach but also can reduce the over-dependency on test-based approach. Towards this goal following are some of the major contributions based on ANL’s FY-20 environmental fatigue modeling activities: 1) A cyclic plasticity material model database for 82/182 dissimilar metal weld, which can be readily shared with US nuclear industry and regulatory agency on request. 2) A well validated analytical modeling methodology to perform cycle-by-cycle stress prediction under both constant amplitude fatigue loading and variable amplitude fatigue loading (with load-sequence effect). 3) An AI/ML/DL based methodology to predict unmeasurable cyclic strain based on other available sensor signals. This type of approach can be used for estimating strain in real reactor components from other sensor readings. 4) An AI/ML based approach to improve the US capability on environmental fatigue testing. This is by improving ANL’s existing environmental fatigue testing capacity to conduct ASME required strain-controlled tests (by controlling strain amplitudes and its rate), while not measuring the strain (due to the difficulty of placing an extensometer in a narrow autoclave in a PWR-water-test system). 5) A simulation and experiment based probabilistic modeling methodology for time-series fatigue state and life estimation of reactor metal such as dissimilar metal weld.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Observations on the fourth-power scaling of high-pressure shock waves in solids

This paper is concerned with the bounds and approximations that are found in the original derivation of the fourth-power scaling of shock waves in solids [D. Grady, Appl. Phys. Lett. 38, 825 (1981)]. The analysis is focused on the framework of the derivation and is independent of constitutive assumption, such as visco-plastic behavior. Results include an upper bound for the shock pressure and a restriction on the range of power coefficient for materials having a power-type function for the shock velocity–particle velocity relation. Relaxation of this restriction is proposed based on the idea that the rise time along the Rayleigh line is strain dependent. The idea led to the application of the Onsager relation to strain rate calculation that in turn resulted in a quadratic function for the strain rate–shock pressure relation. The fourth-power relation is obtained by generalizing the Onsager relation through the introduction of a quadratic dissipative potential in analogy to Rayleigh's dissipative potential.

Horie, Yasuyuki (ORCID:0000000245207246)↗

1100 to 1300 K slow plastic compression properties of Ni-38.5Al composites

Compressive properties of Ni-38.5Al (in at. pct) composites containing 4, 7.5, and 15 vol pct Al2O3 whiskers or 20 vol pct TiB2 particles were investigated in samples compacted to full density by vacuum hot pressing at 20.7 MPa and 1725 K, followed by HIP at 207 MPa and 1725 K. Constant-velocity compression tests were conducted in air at 1100, 1200, and 1300 K to 8 percent strain. It was found that the elevated-temperature compressive properties of Ni-38.5Al+Al2O3 whisker composites were only marginally better than those of the matrix, and that the composite containing 20 vol pct TiB2 particles was only slightly stronger than unreinforced Ni-38.5Al.

Whittenberger, J. Daniel↗

Identification of a specific exporter that enables high production of aconitic acid in Aspergillus pseudoterreus

Aconitic acid is an unsaturated tricarboxylic acid that is attractive for its potential use in the manufacture of biodegradable and biocompatible polymers, plasticizers, and surfactants. Previously Aspergillus pseudoterreus was engineered as a platform to produce aconitic acid by deleting the cadA (cis-aconitic acid decarboxylase) gene in the itaconic acid biosynthetic pathway. In this study aconitic acid transporter gene (aexA) was identified using comparative global discovery proteomics analysis between the wild-type and cadA deletion strains. Deletion of aexA almost eliminated aconitic acid secretion, while its overexpression led to a significant increase in aconitic acid production. Transportation of aconitic acid across the plasma membrane is a key limiting step. In vitro proteoliposome transport assay further validated AexA’s function and its substrate specificity. This research provides new approaches to efficiently pinpoint and characterize exporters of fungal organic acids and accelerate the metabolic engineering to improve secretion capability and lower cost for bioproduction.

59 BASIC BIOLOGICAL SCIENCES↗

EVPSC modeling of 316 stainless steel with and without observed phase transformation

The following is a description of modeling the constitutive behavior of the transforming and non-transforming 316 stainless steel measured in-situ at APS. Details of the elasto-viscoplastic self-consistent (EVPSC) polycrystal deformation model are described in the literature and only the salient information is given here. The EVPSC model is a general rate-sensitive self-consistent polycrystal plasticity model valid at arbitrary large deformations. The homogenizing method used is the self-consistent approach, originally proposed by Kröner, assuming that each grain is an ellipsoidal inclusion embedded in an infinite homogeneous equivalent medium (HEM), where the interaction is determined using Eshelby's solution. The hardening behavior is described by a Voce type strain hardening law, and the phase transformation uses a strain energy criterion for choosing a single daughter grain for each parent grain that reaches a critical value of the Von Mises equivalent strain. The orientation relationship between parent and daughter grains is determined based upon a rotation matrix that preserves an invariant line between the parent and daughter. The evolution law for the growth of the martensite phase is based on an empirical accumulated shear strain law proposed by Olson and Cohen. The single crystal elastic constants for the austenite phase are as reported for 316 stainless steel and the single crystal elastic constants of the martensite are taken from hardened SAE 1050 plain-carbon steel.

36 MATERIALS SCIENCE↗

Toughening mechanisms in elastomer-modified epoxies. I - Mechanical studies. II - Microscopy studies

Tensile dilatometry at constant displacement rates is presently used to ascertain whether voiding, crazing or shear banding are the deformation mechanisms at work in the toughening of brittle epoxies through the addition of an elastomeric phase. The results obtained for epoxies toughened by various levels of several types of carbonyl-terminated butadiene nitrile liquid rubber indicate that, at low strain rates, the rubber particles simply enhance shear deformation; at sufficiently high strain rates, the particles cavitate and promote further shear deformation. Examinations of these materials are conducted by means of SEM, TEM, and optical microscopy in the second part of this study. Toughening is hypothesized to involve cavitation's relieving of triaxial tension at the crack tip, as well as shear band formation, which creates a plastic zone.

Yee, A. F.↗

Strong‐Yet‐Ductile Eutectic Alloys Employing Cocoon‐Like Nanometer‐Sized Dislocation Cells

Abstract Eutectic alloys (EAs) with superior fluidity are known to be the easiest to cast into high‐quality ingots, making them the alloys of choice for making large‐sized structural parts. However, conventional EAs (CEAs) have never reached strength–ductility combinations on par with the best in other alloy categories. Via thermomechanical processing of cast Ni‐32.88wt%Fe‐9.53wt%Al CEAs, a cocoon‐like nano‐meshed (as fine as 26 nm) network of dislocations (CNN‐D) is produced via recovery annealing, through the rearrangement of cold‐work‐accumulated dislocations anchored by dense pre‐existing nanoprecipitates. In lieu of traditional plasticity mechanisms, such as TWIP and TRIP, the CNN‐D is particularly effective in eutectic lamellae with alternating phases, as it instigates nanometer‐spaced planar slip bands that not only dynamically refine the microstructure but also transmit from the FCC (face‐centered‐cubic) layers into the otherwise brittle B2 layers. These additional mechanisms for strengthening and strain hardening sustain stable tensile flow, resulting in a striking elevation of both strength and ductility to outrank not only all previous CEAs, but also the state of the art—additively manufactured eutectic high‐entropy alloys. The CNN‐D thus adds a novel microstructural strategy for performance enhancement, especially for compositionally complex alloys that increasingly make use of nanoprecipitates or local chemical order.

Chemistry↗

Modeling plasticity-mediated void growth at the single crystal scale: A physics-informed machine learning approach

Modeling the evolution of voids during plastic flow as well as their effects on plastic dissipation is critical for both component manufacturing and lifetime estimation purposes. To this end, we propose a rate-dependent constitutive model to homogenize the effects of semi-randomly distributed voids on single crystal plasticity whilst capturing void interaction and plastic anisotropy. Here, this present work focuses on the case of face centered cubic crystals to introduce an anisotropic gauge function applicable within the crystal plasticity formalism. The approach combines analytical methods to describe the micromechanics of the system in combination with symbolic regression to capture analytically intractable mechanisms from data. The hybrid framework uses a physics-informed genetic programming-based symbolic regression algorithm to solve a multiform optimization problem simultaneously producing a new gauge function and a new strain rate equation. This is also a multi-objective optimization problem with many competing objectives. A new search and selection step is introduced to the genetic algorithm that promotes convergence toward a global solution that better satisfies all the objectives. Overall, the symbolic equations produced leverage data-driven methods to achieve greater accuracy than comparable alternatives on an analytically intractable problem while maintaining model transparency.

36 MATERIALS SCIENCE↗

A stable numerical solution method in-plane loading of nonlinear viscoelastic laminated orthotropic materials

In response to the tremendous growth in the development of advanced materials, such as fiber-reinforced plastic (FRP) composite materials, a new numerical method is developed to analyze and predict the time-dependent properties of these materials. Basic concepts in viscoelasticity, laminated composites, and previous viscoelastic numerical methods are presented. A stable numerical method, called the nonlinear differential equation method (NDEM), is developed to calculate the in-plane stresses and strains over any time period for a general laminate constructed from nonlinear viscoelastic orthotropic plies. The method is implemented in an in-plane stress analysis computer program, called VCAP, to demonstrate its usefulness and to verify its accuracy. A number of actual experimental test results performed on Kevlar/epoxy composite laminates are compared to predictions calculated from the numerical method.

Gramoll, K. C.↗

Predicting the reliability of an additively-manufactured metal part for the third Sandia fracture challenge by accounting for random material defects

We describe an approach to predict failure in a complex, additively-manufactured stainless steel part as defined by the third Sandia Fracture Challenge. A viscoplastic internal state variable constitutive model was calibrated to fit experimental tension curves in order to capture plasticity, necking, and damage evolution leading to failure. Defects such as gas porosity and lack of fusion voids were represented by overlaying a synthetic porosity distribution onto the finite element mesh and computing the elementwise ratio between pore volume and element volume to initialize the damage internal state variables. These void volume fraction values were then used in a damage formulation accounting for growth of these existing voids, while new voids were allowed to nucleate based on a nucleation rule. Blind predictions of failure are compared to experimental results. The comparisons indicate that crack initiation and propagation were correctly predicted, and that an initial porosity field superimposed as higher initial damage may provide a path forward for capturing material strength uncertainty. Here, the latter conclusion was supported by predicted crack face tortuosity beyond the usual mesh sensitivity and variability in predicted strain to failure; however, it bears further inquiry and a more conclusive result is pending compressive testing of challenge-built coupons to de-convolute materials behavior from the geometric influence of significant porosity.

36 MATERIALS SCIENCE↗