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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 91 records · Page 5

Making ultrastrong steel tough by grain-boundary delamination

Developing ultrahigh-strength steels that are ductile, fracture resistant, and cost effective would be attractive for a variety of structural applications. We show that improved fracture resistance in a steel with an ultrahigh yield strength of nearly 2 gigapascals can be achieved by activating delamination toughening coupled with transformation-induced plasticity. Delamination toughening associated with intensive but controlled cracking at manganese-enriched prior-austenite grain boundaries normal to the primary fracture surface dramatically improves the overall fracture resistance. As a result, fracture under plane-strain conditions is automatically transformed into a series of fracture processes in “parallel” plane-stress conditions through the thickness. The present “high-strength induced multidelamination” strategy offers a different pathway to develop engineering materials with ultrahigh strength and superior toughness at economical materials cost.

36 MATERIALS SCIENCE↗

Chemically circular, mechanically tough, and melt-processable polyhydroxyalkanoates

Polyhydroxyalkanoates (PHAs) have attracted increasing interest as sustainable plastics because of their biorenewability and biodegradability in the ambient environment. However, current semicrystalline PHAs face three long-standing challenges to broad commercial implementation and application: lack of melt processability, mechanical brittleness, and unrealized recyclability, the last of which is essential for achieving a circular plastics economy. Here we report a synthetic PHA platform that addresses the origin of thermal instability by eliminating α-hydrogens in the PHA repeat units and thus precluding facile cis-elimination during thermal degradation. This simple α,α-disubstitution in PHAs enhances the thermal stability so substantially that the PHAs become melt-processable. Synergistically, this structural modification also endows the PHAs with the mechanical toughness, intrinsic crystallinity, and closed-loop chemical recyclability.

Science & Technology - Other Topics↗

In-situ, nanoscale fracture toughness measurements for improved mechanical interfaces

In this project, we demonstrated stable nanoscale fracture in single-crystal silicon using an in-situ wedge-loaded double cantilever beam (DCB) specimen. The fracture toughness KIC was calculated directly from instrumented measurement of force and displacement via finite element analysis with frictional corrections. Measurements on multiple test specimens were used to show K IC = 0.72 ± 0.07 MPa m 1/2 on {111} planes and observe the crack-growth resistance curve in <500 nm increments. The exquisite stability of crack growth, instrumented measurement of material response, and direct visual access to observe nanoscale fracture processes in an ideally brittle material differentiate this approach from prior DCB methods.

36 MATERIALS SCIENCE↗

Tough Errors Are no Match (TEAM): Optimizing the Quantum Compiler for Noise Resilience

This report summarizes research performed under the Tough Errors Are no Match (TEAM) project. The primary focus of TEAM has been to research and develop a compilation toolbox leveraging techniques from quantum characterization and control, probabilistic programming, and approximate computing. Our goal was to develop robust protocols that can be integrated into quantum compilers to optimize and enhance the robustness of noisy computation. Here, we provide a summary of TEAM work focused on characterization and control of quantum systems.

97 MATHEMATICS AND COMPUTING↗

Tough Errors are no Match (TEAM): Optimizing the Quantum Compiler for Noise Resilience

This report summarizes our contributions to the Department of Energy’s Tough Errors are no Match (TEAM) project (DE-SC0020377) under Thrust 2: Quantum Programming and Compilation. The central outcomes of this work included a novel efficient quantum compiling algorithm which works without requiring the quantum computer to exactly invert its operations, answering a longstanding open problem in quantum compiling. Additional results include the implementation of zero-noise extrapolation error mitigation in collaboration with the Unitary Fund, as well as novel quantum algorithms for entanglement detection and pseudorandomness.

Bouland, Adam [Stanford Univ., CA (United States)]↗

Testing Protocol Development for the Fracture Toughness of Parts Built with Big Area Additive Manufacturing

The mechanical testing of additively manufactured parts has largely relied on the existing standards developed for traditional manufacturing. While this approach leverages the investment made in current standards development, it inaccurately assumes that the mechanical response of additive manufacturing (AM) parts is identical to that of parts manufactured through traditional processes. When considering thermoplastic, material extrusion AM, the differences in response can be attributed to an AM part’s inherent inhomogeneity caused by porosity, interlayer zones, and surface texture. Additionally, the interlayer bonding of parts printed with large-scale AM is difficult to adequately assess, as much testing is performed such that stress is distributed across many layer interfaces; therefore, the lack of AM-specific standards to assess interlayer bonding is a significant research gap. To quantify interlayer bonding via fracture toughness, double cantilever beam (DCB) testing has been used for some AM materials, and DCB has been generally used for a variety of materials including metal, wood, and laminates. Mode I DCB testing was performed on thermoplastic matrix composites printed with Big Area Additive Manufacturing (BAAM). Of particular interest was the notch shape and deflection speed during testing. The results examine the differences when using two notch types and three deflection speeds. The testing method introduced by the following paper differentiates itself from the ones described in the standards used by modernizing the methodology. This was conducted with the introduction of Digital Image Correlation (DIC) to gather displacement and load data simultaneously without human intervention.

Polymer Science↗

Machine Learning Prediction of Fracture Toughness in Hydrogen-charged Stainless Steels

Austenitic stainless steels are structural materials utilized in tritium gas pressure boundaries since they are resistant to hydrogen isotope embrittlement [1-3]. However, exposure to tritium over long periods of time leads to tritium uptake which decays to result in helium ingrowth. This helium ingrowth results in further embrittlement effects which are synergistic with that from the hydrogen isotope [4]. Therefore, it is important for tritium facilities to understand the material limitations of stainless steel in this environment. The Savannah River National Laboratory (SRNL) has available a large experimental data set of austenitic stainless steels which have been exposed to tritium environments for various lengths of time. With the availability of this data set, machine learning (ML) algorithms provide an opportunity to model the embrittlement of stainless steel due to the algorithm’s ability to identify patterns in data sets that are difficult and costly to identify in other manners [5]. Ultimately, the amount and quality of the available data is one defining force in the ability of a ML model to accurately predict the desired outputs. The models developed herein will illustrate the ability for the various algorithms to predict the change in fracture toughness in stainless steels due to hydrogen-isotope embrittlement.

Hoar, Eric T.↗

Elasto-viscoplastic fast Fourier transform modeling framework for assessing microstructural effects on stress intensity factors characterizing fracture toughness

A large-strain elasto-viscoplastic fast Fourier transform (LS-EVPFFT) model with non-periodic (NP) velocity-based boundary conditions is adapted to simulate the sensitivity of stress intensity factors on microstructure for 304L stainless steel. The material was characterized via electron backscattered diffraction (EBSD) serial-sectioning to obtain a measured 3-D microstructural cell to perform simulations. The NP-LS-EVPFFT model, including the simulation setup and boundary conditions, was verified using a crystal plasticity finite element (CPFE) model. To this end, the generation of meshes of notched specimens was developed, which involved creating Python scripts for mesh “cutting” in Abaqus, and Sculpt scripts in Cubit for meshing of the measured microstructural cell processed with DREAM.3D. The complexity of the mesh preparation highlighted the advantages of the FFT-based model, which circumvents the mesh generation process. Given the efficiency of the FFT-based model, statistical distribution of stress intensity factors in function of crystal orientation at the crack tip, grain structure, and crystallographic texture surrounding the crack tip were predicted. Further, the distributions reveal about 10% variation of stress intensity factors with microstructure with the most significant sensitivity found to be the crystal orientation at the crack tip. The methodology developed in this work is discussed as a practical simulation tool for predicting the sensitivity of stress intensity factors on microstructural variability in metallic materials.

36 MATERIALS SCIENCE↗