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Escobar, Julian D.

Publications and source records attributed to Escobar, Julian D..

Structural uniformity and compositional homogeneity of solid-phase alloyed rod

Solid-phase processes have emerged as an alternative to fusion-based alloying to avoid coarse microstructures, undesirable phase formation, and high energy consumption. However, achieving uniform distribution of alloying elements during friction-based processing remains challenging due to highly heterogeneous thermomechanical conditions. This work evaluates the structural uniformity and compositional homogeneity of Al–Cu–Zn alloyed rods produced by friction extrusion (FE) and establishes the role of the rotational speed to feed rate ratio (N/V) on alloying effectiveness. A systematic matrix of FE experiments was conducted at constant extrusion ratio with N/V values ranging from 3.7 to 300. Compositional uniformity was assessed along the rod length (ICP-OES), in three dimensions (X-ray computed tomography), and at the microscale (SEM–EDS), supported by a gray-level co-occurrence matrix (GLCM)–based homogeneity metric. Smoothed particle hydrodynamics (SPH) simulations were used to reveal material flow and thermomechanical fields. Results show that N/V = 100 produces a high-shear mixing zone that eliminates the unmixed core and enables near-full dissolution and dispersion of Cu and Zn. At lower N/V, a laminar flow region persists at the rod center, causing segregation and large composition gradients. The combined experimental–computational analysis provides mechanistic insight into the transition from fragmented particle dispersion to thermomechanically assisted metallurgical mixing. This study establishes processing–structure relationships for solid-phase alloying and provides guidance for achieving homogenized compositions comparable to wrought alloys via rapid, scalable FE processing.

Aluminum↗

Generalizable Image Segmentation for Microstructure Characterization Through Integrated SEM and EBSD Analysis

We demonstrate generalizable semantic segmentation using minimal ground truth data. Correlated scanning electron microscopy (SEM) images and electron backscatter diffraction (EBSD) measurements of frictionstir processed 316L stainless steel plates were used to train deep learning models for grain boundary segmentation. Secondary electron (SE) imaging taken at an accelerating voltage of 10 keV correlated to EBSD-derived grain boundaries produced the best performing model. Notably, an ensemble of three models trained on a single SE image produced accurate segmentation over a series of BSE images of samples manufactured under different processing parameters, with a resultant mean absolute error in grain size of 0.34 µm. The striking generalizability of the models likely results from the similar escape depths of the SE training input and the EBSD training output and the reduced probability of dislocation artifacts appearing in the image. This finding highlights the importance of considering the physical principles behind imaging in the development of robust segmentation models for microstructure characterization.

Taufique, Mohammad Fuad Nur↗

Materials Characterization, Prediction and Control Project: Summary Report on Data Analytics Framework

This report summarizes the activities performed under the data analytics Vertex in the Materials Characterization, Prediction and Control Project funded under laboratory directed research and development at Pacific Northwest National Laboratory. The data analytics Vertex developed models for associating global or local process parameters, microstructural features, and performance properties of friction-stir-processed 316L stainless steel plates. Statistical, machine learning, and deep learning models, as well as generative artificial intelligence approaches, were used to develop the associations between the process-structure-property data streams. These associations formed the basis for predicting global properties of parts manufactured under different process envelopes, providing a basis for predicting performance using data driven as well as physics-informed and physics-constrained approaches. Additionally, the associations were used to predict local process parameters and microstructural features of the product, predictive relationships that have the potential to form the basis of a control framework that could eventually modulate a friction-stir process to maintain product quality.

316L stainless steel↗

Preliminary Characterization and Evaluation on ShAPE Manufactured 316H and ODS Steels

This study provides the first- of- a- kind results of direct tube formation through shear assisted processing and extrusion (ShAPE) for oxide dispersion strengthened (ODS) steel material; previously only bar was successfully made. The Advanced Materials and Manufacturing Technology (AMMT) program develops cross-cutting technologies in support of a broad range of nuclear reactor technologies and maintains U.S. leadership in materials and manufacturing technologies for nuclear energy applications. The overarching vision of AMMT is to accelerate the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy. Solid-state advanced manufacturing techniques can overcome some of the challenges in liquid-based additive manufacturing processes and should therefore be considered in material design and manufacturing as well. The work presented in this report forms part of a study on solid-state additive manufacturing techniques of 316 stainless steels and ODS steel components and supports the vision and goals of the AMMT program relevant to accelerate the development and deployment of advanced manufacturing processes. Achieving this can provide a safety improvement through larger safety margins, economic benefit for higher efficiency during operation, and a cost reduction through more effective manufacturing processes and less waste.

36 MATERIALS SCIENCE↗

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 4

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024).

36 MATERIALS SCIENCE↗

Materials Characterization, Prediction, and Control Project: Characterization of 316L Stainless Steel after Solid Phase Processing using Ultrasonic NDE Method

The Pacific Northwest National Laboratory undertook the Materials Characterization, Prediction, and Control Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems produced via advanced manufacturing methods, such as solid phase processing, for use in national security and advanced energy applications (Smith 2021). A motivation of the Materials Characterization, Prediction, and Control Project was to demonstrate ultrasonic testing as a nondestructive evaluation method to complement traditional destructive methods for characterizing material microstructure with emphasis on grain size determination using a method that may have future applications for real-time inline process monitoring. The objective of the work described in this report is to establish the process and an analysis method for measuring grain sizes of polycrystalline metals with ultrafine grains using ultrasonic shear wave backscattering, building on prior studies on coarser-grained material. The work involves five tasks: Measured ultrasonic backscattering experimentally for a series of 316L stainless steel specimens with various grain sizes made by friction stir processing. Calculated ultrasonic backscattering coefficients from experimental data based on a physical measurement model. Measured ground truth grain sizes of the specimens from electron backscatter diffraction grain boundary images using a generalization of the ASTM E112 (ASTM 2021) intercept method. Built a curve of ultrasonic backscattering coefficients versus the ground truth intercept-based grain sizes to determine the correlation between mean grain sizes and ultrasonic measurements. Demonstrated the ability of using the correlation curve to deduce grain sizes with measured ultrasonic backscattering coefficients for a few 316L stainless steel specimens whose grain sizes were unknown beforehand but were targeted to be an extrapolation to larger grain sizes than used to formulate the correlation curves. Experimental procedures and computational algorithms are developed and validated for these tasks. This work establishes an ultrasonic technique for characterizing material microstructure with ultrafine grains that are often resulted by solid-phase processing. The technique is nondestructive, and it has the potential to be used for real time inline process monitoring. This work successfully demonstrates the viability of an ultrasonic nondestructive evaluation method for microstructural characterization of material having ultrafine grain structure (as small as 1?mm) and produced by an advanced manufacturing method. This includes a demonstration of the method to extrapolate to other conditions. While not demonstrated here, the method is expected to be viable for in-line, or near-inline, process monitoring in advanced manufacturing applications with suitable consideration for access of instrumentation to the material being manufactured.

316 L Stainless Steel↗

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 2

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024).

36 MATERIALS SCIENCE↗

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 3

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024).

36 MATERIALS SCIENCE↗

Mechanisms for high creep resistance in alumina forming austenitic (AFA) alloys

Castable alumina forming austenitic (AFA) alloys have demonstrated superior creep life and oxidation resistance at temperatures exceeding 800⁰C. Despite the success in the applicability of these alloys in extreme environments, there is a limited understanding of the deformation modes and the influence of each alloying element guiding the alloy design strategies that could further enhance the creep strength of these AFA alloys, particularly at temperatures at and above 900⁰C. In this study, we reveal the mechanism underpinning the superior creep performance of castable AFA alloys that involves suppressing primary carbide formation through minor compositional modification. This approach results in a three-fold increase in creep strength at 900⁰C and 50 MPa. Here, by employing integrated characterization techniques, we analyzed the microstructures of two AFA alloys, both before and after the creep process. We discovered that the suppression of primary carbides permits the in-situ clustering of now-available interstitial elements such as C, Si, and O during high-temperature creep. This improved solid solution strengthening and reduced stacking fault energy of the alloy. Moreover, it also enabled controlled secondary carbide formation during testing, further improving the creep resistance. These findings underline the important interplay between alloy composition, microstructure, and creep properties, and offer a promising design strategy for developing economical high-temperature Fe-based alloys suitable for advanced applications.

36 MATERIALS SCIENCE↗

Role of phosphorus impurities in decomposition of La 2 NiO 4 –La 0.5 Ce 0.5 O 2-δ oxygen electrode in a solid oxide electrolysis cell

This study explored the decomposition mechanism of a La 2 NiO 4 (LNO) phase in the La 2 NiO 4 –La 0.5 Ce 0.5 O 2-δ (LNO-LDC) oxygen electrode in a solid oxide electrolysis cell (SOEC) after testing at 800 °C. Scanning electron microscopy and scanning transmission electron microscopy examinations of the LNO-LDC oxygen electrode before and after testing were undertaken. Other than phosphorus contamination in the form of P-rich grains and P-rich deposits along all grain boundaries (GBs), LNO and LDC phases were intact without degradation in the as-fabricated electrode. However, mild to aggressive LNO phase decomposition triggered by the phosphorus poisoned GBs was observed after testing at 800 °C for 900 h. The evolution of the LNO phase decomposition was noted beginning with the exsolution of Ni into the surrounding LNO matrix and GBs, forming La-rich and Ni-rich phases correspondingly, in the LNO. Importantly, this study illustrates a detailed decomposition progress of the LNO phase at the atomic level under an SOEC operation condition, and sheds light on how to ameliorate the fabrication process of SOECs to enhance their performance and durability.

25 ENERGY STORAGE↗

Sensing and Control During Bulk SPP

In this work, we use the thermoelectricity to directly measure the temperature at different radial positions within instrumented Al1100 billets during friction extrusion. Site-specific and uninterrupted temperature measurements were possible by measuring the local voltages at several thermoelectric junctions consisting of aluminum-nickel pairs during extrusion. Measurements were conducted for a constant die rotation speed of 150 RPM and different extrusion feed rates of 2, 8, 32, and 80 mm.min-1. X-ray computed tomography was used to locate the positions of the thermoelectric junctions inside the processed billet, thus allowing for site-specific microstructural characterization at the precise measurement points. Smooth particle hydrodynamic modeling allowed to determine the thermal, strain, and strain rate fields developing during FE. The applicability and limitations of this temperature measurement approach are discussed as a function of the peak extrusion and torsion stresses relative to the matrix of extrusion feed rates.

42 ENGINEERING↗

Microstructural evolution in shear-punch tests: A comparative study of pure Cu and Cu-Cr alloy

Understanding the mechanisms behind microstructural evolution during shear deformation has been a long-standing area of interest. However, establishing a connection between microstructure, mechanical properties, and extent of shear deformation is challenging and requires refined experimental approaches. Shear-punch testing (SPT) provides a controlled method to introduce shear into small volumes of material that later can be subjected to detailed microstructural characterization. In this study, we utilize an SPT device to induce shear deformation to pure copper and a binary copper-chromium alloy. Electron backscatter diffraction and transmission electron microscopy were used to study the mechanisms of plastic deformation after SPT. Our results indicate that shear deformation of pure Cu produces a dense network of intercepting microshear bands upon sustained deformation. Twin boundaries undergo degradation into high angle grain boundaries due to simultaneous deviation from the axis-angle pair condition of 60° misorientation on [111] direction. The presence of 50% volume Cr particles in the soft Cu matrix fundamentally altered the shear deformation mechanism. Preferential deformation of the Cu matrix led to accelerated shear-induced formation of low and high angle grain boundaries, and subsequent grain refinement. Comparatively, no grain refinement occurred in pure Cu at a strain ~10 times larger (ϵ = 4.73) than that of the copper-chromium case (ϵ = 0.42). Overall, our study sheds light on the microstructural evolution during shear deformation and highlights the significant influence of particle reinforcements on the shear deformation mechanisms of metals.

36 MATERIALS SCIENCE↗

Temperature-dependent formation of gradient structures with anomalous hardening in an Al–Si alloy

The temperature effect on forming gradient structure in an Al-Si alloy during surface severe deformation is studied in this report. The intermediate temperature (473 K) produces the steepest gradient structure by an anomalous hardening on the top layer compared to lower (300 K) and higher temperature (673 K) counterparts. Our analysis shows profuse aluminum oxide particles in the top layer of the gradient structure under 473 K and thus lead to anomalous hardening by oxide-dispersion strengthening. Here, the counterintuitive enhancement of strengthening at the intermediate temperature is explained by the dynamic interplay between thermal-driven, mechanical-aided oxidation and the wear-induced loss of surface materials as a function of temperature, which yields a critical processing temperature to achieve the steepest gradient structure.

36 MATERIALS SCIENCE↗

Heterogenous activation of dynamic recrystallization and twinning during friction stir processing of a Cu-4Nb alloy

An interplay between high degree of shear deformation and deformation-induced heating occurs during friction stir processing (FSP) of metals. In medium-to-low stacking fault energy Cu alloys, this can lead to a complex spatially heterogenous activation of dynamic recrystallization (DRX) and twinning mechanisms. Within the Cu-Nb system, the presence of Nb is further expected to influence the DRX mechanism of the Cu matrix. However, the microstructural changes induced by the co-deformation of Nb during FSP are still not well understood. So, this study uses a combination of multimodal microstructural characterization, solution thermodynamics-based predictions, and computational crystal plasticity simulation to reveal the various microstructural evolution mechanisms that can occur during FSP of a Cu-4at.%Nb binary model alloy. The formation of softer DRX zones, and harder shear localization regions are revealed using electron backscatter diffraction, transmission electron microscopy, atom probe tomography, and crystal plasticity modeling.

36 MATERIALS SCIENCE↗