Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “plastic work”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

880 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Transition in helium bubble strengthening of copper from quasi-static to dynamic deformation

Damage from low-temperature irradiation and the subsequent degradation of materials performance pose significant challenges for the storage of radioactive materials and for peripheral components in some nuclear reactor designs. Fully understanding the mechanical behavior of such materials requires test data for strain rates in both the quasi-static (< 10/s) and dynamic (>> 10/s) regimes. While dynamic testing has generally been avoided in the past for neutron irradiated (contamination concerns) and ion irradiated (insufficient volume) materials, surface-sensitive Richtmyer-Meshkov instability (RMI) tests were used in the present work to overcome these limitations. Here, nanopillar compression, nanoindentation, and RMI testing data from a helium implanted surface layer (~10 µm thick) were compiled to explore the effects of helium bubbles on the materials strength of high-purity copper at strain rates of 0.001/s – 10 8 /s. While nano-mechanical testing revealed increases in yield strength and hardness with increasing helium dose from 1000 to 4000 appm He, RMI indicated no significant changes in strength as compared to unimplanted copper. Here, this discrepancy in behavior was rationalized through a combination of recent literature and follow-on molecular dynamics (MD) simulations, leading to the conclusion that the nanoscale helium bubbles acting as dispersed barriers to dislocation motion at quasi-static strain rates collapse under shock loading and cease to be effective barriers at high strain rates.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Elucidating texture and grain morphology contributions to the micromechanical response of additively manufactured Inconel 625

Microstructural variation of additively manufactured (AM) metal components in comparison to wrought counterparts makes certification for critical applications a challenge. Microscale simulations leveraging modern computational tools may be used to supplement testing of AM microstructures, thus accelerating certification by reducing the number of experiments needed. However, as micromechanical response is closely tied to critical properties like fatigue-life and fracture, utilization of these simulations with macroscale experimental data alone is insufficient. One means to attain microscale experimental data is in situ diffraction data collected from synchrotron X-ray sources. In this work, such data were collected during in situ compression of AM Inconel 625 superalloy. Interpretation of experimental results was assisted by massive (8M element) complementary micromechanical simulations performed on sets of virtual microstructures generated using cellular automata. Together, micromechanical data from diffraction experiments and simulations were used to probe the effects of textured “track” microstructures generated during laser powder bed fusion and directional strength-to-stiffness on micromechanical response. Though fiber-averaged directional strength-to-stiffness ratios were expected to dominate given the high elastic anisotropy of the material, the combination of small variations in texture and specific grain configurations unique to AM microstructures lead to significant variability in micromechanical response after yield. The findings emphasize the importance of high-fidelity microstructural representation that captures key texture components and AM-specific morphology for property prediction of AM metals.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A fast and robust computational modeling approach for density and shape predictions in powder metallurgy hot isostatic pressing

Powder metallurgy hot isostatic pressing (PM-HIP) is an advanced manufacturing process that produces near-net-shape parts with high material utilization and uniform microstructures. PM-HIP is frequently used for producing small-scale parts with complicated geometries and is potentially economical for producing large-scale parts. However, excessive post-HIP shape distortions can reduce its effectiveness and economic advantage, especially for larger parts. A PM-HIP computational model can predict and help mitigate these distortions. However, due to complex deformation mechanisms and thermo-mechanical coupling present in PM-HIP processes, these non-linear computational models sometimes become numerically unstable. The numerical instabilities in these models can lead to very slow convergence or no convergence at all, which often translates to slow and unreliable models. These limitations are more pronounced in large models with complicated geometries. Hence, in this work, an alternative modeling approach is presented that improves numerical stability and computational performance. The presented approach achieves these improvements through approximating the fully coupled thermo-mechanical PM-HIP model as a decoupled model and adding inertial damping to the model’s mechanical part. In conclusion, a comparison with the fully coupled model indicated a slight dip in prediction accuracy (<5% error) but significant improvements in numerical stability (>20 times larger time step size) and computational performance (5-10 times speed-up with less computational resource usage) when using the presented approach.

Hot isostatic pressing↗
DOE OSTI2023

Thermally Induced Structural Transitions in Epoxy Thermoset Polymer Networks and Their Spectroscopic Responses

The polymer network structure of epoxy thermosets plays a significant role in its final material properties. However, the effects of mild thermal exposure on these network structures are poorly studied. In this work, wide-angle X-ray scattering was used to investigate the polymer network structure of two epoxy thermosets: homopolymerized bisphenol A (BPA) epoxy resin and BPA epoxy resin cured with a polyether amine hardener (BPA/T-403). Using density functional theory and wide-angle X-ray scattering, insights into the polymer network structure were obtained. Diffraction features were determined to originate from hardener-to-hardener molecular distance, perpendicular π–π stacking of aromatic p-phenylene rings, and the average carbon–carbon distance in the polymer. Thermal exposure was found to permanently alter these structural features for both thermosets, with an increase in the π–π stacking distance. Homopolymerized BPA had an additional decrease in the hardener-to-hardener distance. These structural alterations were found to be detectable using Fourier transform infrared spectroscopy and Raman spectroscopy, with changes in the hardener-to-hardener distance having the largest variations in the resulting spectra specifically at the aromatic and ether frequencies.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Development of a Printable Prill Formulation Technique and Demonstration of Monomodal Prill Size on Compaction Density and Compressive Strength

Polymer-bonded explosive molding powder, or “prills,” are relied on for the fabrication of pressed high explosives since the 1950's. The wet granulation technique, also known as “slurry coating,” that is used to formulate prills, is a complex process that results in polydisperse and variable yields. This makes it difficult to study the mesoscale effect that prills have on the microstructure of a pressed article. The following study introduces a novel approach to energetic granulation that leverages techniques used in the additive manufacturing of paste-like energetic materials. This extrusion granulation, or prill printing technique, makes it possible to tailor the sizes and shapes of prills, allowing for their morphological influences to be studied in a controlled manner. The following work details the fabrication and characterization of four monomodal size lots of prills using an inert formulation (95 wt.% melamine, 5 wt.% polymer binder). Prills from each size lot were die-pressed using a fixed recipe to investigate how prill size impacts compaction density and therefore compressive strength. It was found that larger prills influence the pressing density by creating larger defects within the microstructure of a pressed article, resulting in a decrease in compressive strength.

direct ink write↗
DOE OSTI2021

Synthesis of High-Performance Lignin-Based Inverse Thermoplastic Vulcanizates with Tailored Morphology and Properties

In this work, we report synthesis of a high-strength renewable phenolic composition with linear large deformation strain without a thermoplastic-like yielding while retaining thermal processability. Small molecule carboxylic acid derivatives with varying molecular architectures act as esterifying crosslinkers in an equal mass mixture of lignin and acrylonitrile–butadiene copolymers in a highly scalable, solvent-free process. These “inverse thermoplastic vulcanizates” (iTPVs)—unique in their approach of crosslinking the rigid lignin phase rather than the soft phase—exhibit ordered self-assembly, tunable nanoscale morphology, and processability. The first of its kind iTPV compositions exhibit engineering stress–strain curves with two- to sixfold linear extensibility, a twofold rise in strength, and an order of magnitude enhanced modulus compared to a simple lignin-rubber blend. Viscoelastic properties correlate well with crosslinker architecture and the resulting morphology, allowing competing properties of toughness and stiffness to be tuned. This research finds a path for identifying the potential of lignin as a sustainable feedstock.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Calibration of RAFM Micromechanical Model for Creep Using Bayesian Optimization for Functional Output

A Bayesian optimization procedure is presented for calibrating a multimechanism micromechanical model for creep to experimental data of F82H steel. Reduced activation ferritic martensitic (RAFM) steels based on Fe(8–9)%Cr are the most promising candidates for some fusion reactor structures. Although there are indications that RAFM steel could be viable for fusion applications at temperatures up to 600°C, the maximum operating temperature will be determined by the creep properties of the structural material and the breeder material compatibility with the structural material. Due to the relative paucity of available creep data on F82H steel compared to other alloys such as Grade 91 steel, micromechanical models are sought for simulating creep based on relevant deformation mechanisms. As a point of departure, this work recalibrates a model form that was previously proposed for Grade 91 steel to match creep curves for F82H steel. Due to the large number of parameters (9) and cost of the nonlinear simulations, an automated approach for tuning the parameters is pursued using a recently developed Bayesian optimization for functional output (BOFO) framework (Huang et al., 2021, “Bayesian optimization of functional output in inverse problems,” Optim. Eng., 22, pp. 2553–2574). Incorporating extensions such as batch sequencing and weighted experimental load cases into BOFO, a reasonably small error between experimental and simulated creep curves at two load levels is achieved in a reasonable number of iterations. In conclusion, validation with an additional creep curve provides confidence in the fitted parameters obtained from the automated calibration procedure to describe the creep behavior of F82H steel.

42 ENGINEERING↗
DOE OSTI2020

Topologically derived dislocation theory for twist and stretch moiré superlattices in bilayer graphene

In this work, we develop a continuum dislocation description of twist and stretch moiré superlattices in two-dimensional material bilayers. The continuum formulation is based on the topological constraints introduced by the periodic dislocation network associated with the moiré structure. The approach is based on solving analytically for the structural distortion and displacement fields that satisfy the topological constraints and that minimize the total energy. The total energy is described by both the strain energy of each individual distorted layer and a Peierls-Nabarro-like interfacial contribution arising from stacking disregistry. The dislocation core emerges naturally within the formalism as a result of the competition between the two contributions. The approach presented here captures the structure and energetics of twist and stretch moiré superlattices of dislocations with arbitrary direction and character, without assuming an analytical solution a priori and while accounting naturally for dislocation-dislocation image interactions. In comparisons to atomistic simulations using classical potentials, the maximum structure deviation is 6%, while the maximum line energy deviation is 0.019 eV/Å. Several applications of our model are shown, including predicting the variation of structure with twist angle and describing dislocation line tension and junction energies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Measuring representative volume elements from high-resolution grain-scale strain fields

Most crystalline materials present a highly heterogeneous response at the microscale, which can be affected by both internal factors (such as microstructural parameters) and external factors (such as loading). Relating microscale inhomogeneities to the macroscale response of a material requires the use of homogenisation techniques, usually based on the concept of a representative volume element (RVE)—the smallest volume of material that represents the global average response. Here, in this work, we present a new and robust experimental method of measuring the size of a strain-based RVE from high-resolution grain-scale strain fields obtained using digital image correlation (DIC). The proposed method is based on the statistical (stereological) nature of the RVE, which has been widely adopted in numerical studies, and involves dividing a strain field into randomly selected regions of varying sizes and statistically analysing the distributions of average strains within them. To validate the new method, we generate a large number of synthetic strain fields from a fractional Gaussian noise algorithm. The proposed stereological method is shown to be capable of producing reliable RVE measurements from a very large range of possible microscale strain fields while at the same time being robust in that it can produce RVE measurement results even in cases where other existing methods may be unable to do so. The proposed method has a low field-of-view requirement, only needing a field-of-view about 1.2 times as large as the RVE to produce reliable measurements. In addition, the stereological method offers significant flexibility since its statistical nature allows for control over how strict the RVE measurement should be in each case.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The influence of thermomechanical treatment pathways on texture and mechanical properties in ARB Cu/Nb nanolaminates

Accumulative roll-bonded Cu/Nb nanolaminates (ARB Cu/Nb) possess high strength, thermal stability, and radiation tolerance arising from a high content of heterophase interfaces at fine layer thicknesses. These properties can be tailored by processing parameters used in the ARB Cu/Nb fabrication process, in which layer thickness, thermal history, and strain pathway determine the interface types and resultant properties found in the material. In this work, we subject ARB Cu/Nb to annealing, and then two different rolling pathways – one where rolling direction is held constant (longitudinal rolling, or LR), and one where rolling direction is rotated by 90º and held constant thereafter (cross rolling, or CR). Rolling is performed on ARB Cu/Nb over a targeted range of layer thicknesses from 193 to 25 nm and resultant bulk textures measured by neutron diffraction are correlated with mechanical properties measured by miniaturized tensile tests. The annealing procedure sharpens texture in both phases. We find that Cu mostly develops the same texture in LR and CR. In contrast, Nb develops a distinct texture along the CR pathway that is distinct from the LR texture. The composite texture of Cu/Nb is thus distinct between LR and CR pathways. This difference in texture development between Cu and Nb as a function of strain after change in rolling direction demonstrates the viability for deliberate pairing of Cu LR and Nb CR textures at a desired layer thickness. For mechanical properties, we find that differences in texture do not result in yield or flow stress differences above a layer thickness of 25 nm. Below a layer thickness of 25 nm, despite similar Taylor factors, yield and flow stress and are significantly different. In conclusion, this indicates texture only influences mechanical behavior at low layer thickness, where interface structure dominates mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Inverse design of hypoeutectoid pearlite steel microstructures using a deep learning and genetic algorithm optimization framework

Goal-oriented microstructure design in metallic materials is a challenging task due to complex structure-property relationships. Traditional experimental and computational approaches are time-intensive and economically inefficient, limiting their applicability for large-scale design space exploration. Here, in this work, we propose an end-to-end framework that integrates deep learning models with genetic optimization to design microstructures with targeted mechanical properties. Deep learning models enable accurate forward design, while their integration with genetic optimization enables efficient inverse design within a few hours, compared to days or weeks using conventional finite element simulations. The framework combines experimental characterization and finite element modeling to analyze the influence of microstructural features on the mechanical behavior of hypoeutectoid steels. Data from both experiments and simulations are used to train the deep learning models. To demonstrate its effectiveness, we apply the framework to 0.63% carbon steel with proeutectoid ferrite and pearlite phases, commonly used in industrial applications. In this study, 2D microstructures were used for modeling, selected primarily for computational efficiency and to establish proof of concept. The framework successfully optimizes microstructures for targeted yield strength, ultimate strength, and stress concentration factors while significantly reducing computational time. Beyond hypoeutectoid steels, this scalable framework can be extended to other material systems and integrated with additive manufacturing, offering an efficient approach for accelerating microstructure design for specific engineering applications.

ConvLSTM↗
DOE OSTI2024

Upcycling linear low-density polyethylene waste to turbostratic graphene for high mass loading supercapacitors

Linear low-density polyethylene (LLDPE) waste is difficult to upcycle into more valuable carbon materials because it tends to completely decompose into small molecules during thermal processing. In this work, LLDPE is upcycled into a high quality turbostratic graphene using a pre-treatment step to oxidatively crosslink the polymer with the assistance of solid additives (KCl and K 2 CO 3 ) that improve crosslinking by increasing the effective surface area of the polymer melt during processing. After this pretreatment step, the crosslinked polymer could then be carbonized and catalytically graphenized between 400–950°C without decomposition of the polymer feedstock. The LLDPE derived graphene (LLDPE-G) obtained from this process has a Brunauer–Emmett–Teller (BET) specific surface area, up to 1800m 2 g -1 and average Raman I D /I G and I 2D /I G ratios of 0.85 and 0.57, respectively, indicating high quality graphene. When used as an electrode material in symmetric supercapacitors, LLDPE-G possesses a specific capacitance up to 175Fg -1 at a mass loading of 20mgcm -2 , which is two times the commercial requirement, yielding an areal capacitance of 3.5 Fcm -2 . Moreover, LLDPE-G exhibits exceptional cycling stability with a capacitance retention of 95.8 % after 100,000 cycles at a current density of 4.0 Ag -1 . Additionally, the KCl and K 2 CO 3 solids are recycled and reused over 3 complete reaction cycles to make new LLDPE-G with the material quality and electrocapacitive performance retained and verified after each cycle. Our approach creates new opportunities for upcycling waste LLDPE and other varieties of polyethylene into a higher value graphene used for electrochemical energy storage applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Multitask graph neural networks for elastoplastic response prediction in dual-phase polycrystals

Microstructure-sensitive prediction of elastoplastic response remains a recurring bottleneck in multiscale damage and fatigue modeling, where large ensembles of statistically distinct polycrystals are required to quantify variability and extreme-value behavior. In this work, we develop a multitask graph neural network (GNN) surrogate that maps dual-phase ferrite–martensite polycrystal microstructures to Statistical Volume Element (SVE)-level elastoplastic Quantities of Interest (QoIs). Each SVE is represented as a grain-adjacency graph, with node features encoding phase, geometry, and crystallographic orientation, and edge features encoding relative misorientation. A message-passing graph convolution generates node embeddings, which are pooled into a graph representation and passed to a multitask regression head that jointly predicts 10 scalar QoIs and vector-valued stress–strain responses in orthogonal loading directions across multiple martensite volume fractions and SVE sizes. Results show high accuracy for scalar QoIs and strong agreement for full stress–strain trajectories, with population envelopes reproducing both median behavior and finite-SVE variability across compositions and partition scales. A unified model trained on pooled volume-fraction data preserves most within-regime accuracy relative to regime-specific models while also capturing the broader cross-regime variation reflected in the pooled test set. Distributional comparisons further demonstrate that the surrogate preserves heterogeneity under SVE partitioning, enabling statistically consistent block-wise random-field construction for mesoscale analyses. Overall, the proposed grain-graph surrogate provides a practical pathway to accelerate ensemble-based studies of SVE-level constitutive variability in dual-phase polycrystals.

Crystal plasticity↗
DOE OSTI2024

Interconnected Nanoporous Polysulfone by the Self-Assembly of Randomly Linked Copolymer Networks and Linear Multiblocks

Porous materials have attracted considerable attention due to their versatile applications, especially in water purification. Interconnected nanoporous structures are distinguished by their high degree of porosity and resistance to clogging, as well as their insensitivity to nanostructural orientation. Previous works on randomly linked copolymer systems have shown that they can effectively produce disordered cocontinuous nanostructures, which upon removal of one component yield interconnected nanoporous materials. However, the cocontinuous nanomaterials previously developed using polystyrene (PS) and poly(d,l-lactic acid) (PLA) strands, and the resulting interconnected nanoporous PS monoliths, were far too brittle to enable practical use as membranes. Here, we study the self-assembly of randomly linked copolymer networks prepared using blocks of the engineering polymer polysulfone (PSU). A wide cocontinuous regime (spanning 40 wt %) was found for randomly end-linked copolymer networks (RECNs) constructed from PSU and PLA strands, via a combination of mechanical testing, gravimetry, small-angle X-ray scattering, and scanning electron microscopy. The PSU/PLA cocontinuous nanomaterial with symmetric composition showed 2.4 times higher Young’s modulus and ~100 times greater toughness than the corresponding PS/PLA sample. The interconnected nanoporous PSU fabricated after etching of PLA even exhibited 1.6 times greater toughness than PS/PLA prior to PLA removal. To facilitate the production of thin films of cocontinuous nanomaterials, we applied solution-processable randomly linked linear PSU/PLA multiblock polymers onto ultrafiltration membranes. Here, the interconnected nanoporous PSU thin film generated by etching PLA was found to effectively reject 50 nm diameter particles without significantly compromising permeability. This discovery presents a valuable addition to the existing techniques used to fabricate PSU membranes. In contrast to traditional methods, which are sensitive to processing conditions, produce a wide range of pore sizes, and offer limited adjustability of pore size, the current technique is anticipated to enable interconnected PSU membranes with more uniform and tailorable porosity.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Energetics of the nucleation and glide of disconnection modes in symmetric tilt grain boundaries

Grain boundaries (GBs) evolve by the nucleation and glide of disconnections, which are dislocations with a step character. In this work, motivated by recent success in predicting GB properties such as the shear coupling factor and mobility from the intrinsic properties of disconnections, we develop a systematic method to calculate the energy barriers for the nucleation and glide of individual disconnection modes under arbitrary driving forces and a quasi-2D setting. This method combines tools from bicrystallography to enumerate disconnection modes and the Nudged elastic band (NEB) method to calculate their energetics, yielding minimum energy paths and atomistic mechanisms for the nucleation and glide of each disconnection mode. We apply the method to accurately predict shear coupling factors of $[001]$ symmetric tilt grain boundaries in Cu. Particular attention is paid to the boundaries where the dislocation-based disconnection nucleation model produces incorrect nucleation barriers. We demonstrate that the method can accurately compute energy barriers and predict shear-coupling factors in the low-temperature regime. For certain disconnection modes in which the assumptions underlying our method do not hold, we report upper bounds on the energy barriers for disconnection nucleation and glide. In addition, the NEB trajectories reveal interesting phenomena such as the dissociation of a higher energy mode into lower energy modes, and in some cases, shear coupling being mediated by partial disconnections, wherein the GB structure temporarily changes to a metastable state before reverting back to its original structure. Graphical abstract

36 MATERIALS SCIENCE↗
DOE OSTI2025

Evolved Gas Analysis–Mass Spectrometry Exposes Polymer Network Structures

Polymer network structures in epoxy thermosets play an important role in the final thermoset material properties. However, analytical characterization of these network structures is difficult due to their amorphous nature. In this work, the application of evolved gas analysis–mass spectrometry (EGA-MS) to characterize the polymer network structures of bisphenol A (BPA)-based thermosets is demonstrated. Analytical characterization of the polymer network structures is accomplished by monitoring the Product-Specific Kinetics (PSK) of BPA monomer formation during thermal degradation investigations. We relate observed differences in the activation energy (E a ) of BPA monomer formation to the local packing environment around the BPA monomer units within the polymer network. Variations in the local environment related to the polymer networks manifest qualitatively as broadening in the thermal profile of the BPA monomer evolution and quantitatively as changes in the activation energy (E a ). Three BPA thermoset formulations were investigated; two amine-cured thermoset with 4,4′-diaminodiphenylmethane (DDM) or poly(propylene glycol) bis(2-amino-propyl ether) (PPG400) and a homopolymerized thermoset via curing with Epikure 3253 catalyst (3253). Results revealed that the 3253 thermoset contained two distinct packing densities in the polymer network, while DDM and PPG400 thermosets had uniform distributions of packing densities. Results from the DDM thermoset revealed a gradually decreasing E a , while the apparent E a of PPG400 was consistent over the entire degradation. Furthermore, these differences in E a were concluded to stem from the flexibility of the corresponding polymer networks and the ability of the network components to rearrange and occupy formed voids. Due to the minimal sample required for analysis (100–200 μg), this EGA-MS technique has great potential for postproduction evaluation of composite parts to identify changes in the polymer networks from use and aging, which could signal compromised performance.

Degradation↗