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DOE OSTI2020

Columnar-to-equiaxed transition in a laser scan for metal additive manufacturing

In laser powder bed fusion additive manufacturing (LPBFAM), different solidification conditions, e.g., thermal gradient and cooling rate, can be achieved by controlling the process parameters, such as laser power and laser speed. Tailoring the behaviour of the columnar to equiaxed transition (CET) of the printed alloy during fabrication can facilitate the production of highly customized microstructures. In this study, effective analytical solutions for both thermal conduction and solidification are employed to model solidifying melt pools. Microstructure textures and solidification conditions are evaluated for numerous combinations of laser power and laser speed under bead-on-plate conditions. This analytical-based high-throughput tool was demonstrated to select specific process parameters that lead to desired microstructures. Two selected process conditions were examined in detail by a highly parallelized microstructural solidification model to reveal both nucleation and grain growth. Both numerical solutions agree well with experiments that are performed based on bead-on-plate conditions, indicating that these numerical models aid evaluation of the nucleation parameters, providing insights for controlling CET during the LPBFAM processing.

Lang, Yuan↗

DOE OSTI2024

Efficient sensitivity analysis of the thermal profile in powder bed fusion of metals using hypercomplex automatic differentiation finite element method

Rapid cyclic temperature fluctuation occurring in powder bed fusion of metals using a laser beam (PBF-LB/M) influences the formation of flaws in printed parts. Consequently, there is a pressing need to enhance the quality of printed parts by developing innovative methodologies that can predict thermal histories and help uncover the intricate relationships between process parameters and thermal profiles. Sensitivity Analysis (SA) emerges as an essential tool for this, offering the potential for process optimization and enhanced quality control. Nonetheless, conventional SA methodologies often incur in excessive computational costs and potential numerical approximation errors. Here, to address this technical challenge, we present a novel method for SA that integrates the HYPercomplex-based Automatic Differentiation (HYPAD) technique with transient thermal simulations conducted via the finite element method (FEM). Leveraging this methodology, we efficiently and accurately perform SA for PBF-LB/M processes in a post-processing step. Compared to traditional methods like Finite Differences (FD), HYPAD-FEM required 96 % less computational time for obtaining sensitivities for 22 process parameters, under a comparative study conducted within the context of the 2018–02 AM benchmark of the National Institute of Standards and Technology. In summary, HYPAD-FEM offers superior efficiency and accuracy in SA over conventional methods, delivering the best sensitivity of a model without the need for step-size selection and problem or parameter-based implementations.

36 MATERIALS SCIENCE↗

NASA NTRS1977

Thick-film materials for silicon photovoltaic cell manufacture

Thick film technology is applicable to three areas of silicon solar cell fabrication; metallization, junction formation, and coating for protection of screened ohmic contacts, particularly wrap around contacts, interconnection and environmental protection. Both material and process parameters were investigated. Printed ohmic contacts on n- and p-type silicon are very sensitive to the processing parameters of firing time, temperature, and atmosphere. Wrap around contacts are easily achieved by first printing and firing a dielectric over the edge and subsequently applying a low firing temperature conductor. Interconnection of cells into arrays can be achieved by printing and cofiring thick film metal pastes, soldering, or with heat curing conductive epoxies on low cost substrates. Printed (thick) film vitreous protection coatings do not yet offer sufficient optical uniformity and transparency for use on silicon. A sprayed, heat curable SiO2 based resin shows promise of providing both optical matching and environmental protection.

Field, M. B.↗

DOE OSTI2024

Melt Pool characteristics on surface roughness and printability of 316L stainless steel in laser powder bed fusion

Purpose Surface quality and porosity significantly influence the structural and functional properties of the final product. This study aims to establish and explain the underlying relationships among processing parameters, top surface roughness and porosity level in additively manufactured 316L stainless steel. Design/methodology/approach A systematic variation of printing process parameters was conducted to print cubic samples based on laser power, speed and their combinations of energy density. Melt pool morphologies and dimensions, surface roughness quantified by arithmetic mean height (Sa) and porosity levels were characterized via optical confocal microscopy. Findings The study reveals that the laser power required to achieve optimal top surface quality increases with the volumetric energy density (VED) levels. A smooth top surface (Sa < 15 µm) or a rough surface with humps at high VEDs (VED > 133.3 J/mm 3 ) can serve as indicators for fully dense bulk samples, while rough top surfaces resulting from melt pool discontinuity correlate with high porosity levels. Under insufficient VED, melt pool discontinuity dominates the top surface. At high VEDs, surface quality improves with increased power as mitigation of melt pool discontinuity, followed by the deterioration with hump formation. Originality/value This study reveals and summarizes the formation mechanism of dominant features on top surface features and offers a potential method to predict the porosity by observing the top surface features with consideration of processing conditions.

Engineering↗

DOE OSTI2023

Microstructure and microchemistry changes at U-10Mo fuel/AA6061 cladding interfaces with varying hot isostatic pressing conditions

Monolithic uranium - 10 wt.% molybdenum (U-10Mo) is a promising high-assay low-enriched uranium fuel system for nuclear reactors used in research, medical isotope production, and remote power applications. During manufacturing, AA6061 cladding is bonded to the U-10Mo fuel plate via hot isostatic pressing, during which diffusion and fuel/cladding chemical interaction occurs at plate edges. Furthermore, the microstructure and microchemistry changes that occur at fuel/cladding interfaces are important to understand as a function of process parameters to develop a reliable fuel fabrication process and to meet the desired specifications. Here, microstructural and microchemical changes are studied using complementary electron microscopy and atom probe tomography for two manufactured fuel plates with varied hot isostatic pressing (HIP) parameters. Results highlight that modifying thermomechanical processing parameters significantly changed the interaction layer thickness between U-10Mo and AA6061 by an order of magnitude. In addition to this the distribution and concentration of elements (i.e., Al, Si, Mg) from cladding to fuel was also investigated.

36 MATERIALS SCIENCE↗

NASA NTRS1984

An investigation into the injection molding of PMR-15 polyimide

The chemorheological behavior of the PRM-15 molding compounds were characterized, the range of suitable processing parameters for injection molding in a reciprocating screw injection molding machine was determined, and the effects of the injection molding processing parameters on the mechanical properties of molded PMR-15 parts were studied. The apparatus and procedures for measuring viscosity and for determining the physical response of the material during heating are described. Results show that capillary rheometry can be effectively used with thermosets if the equipment is designed to overcome some of the inherent problems of these materials. A uniform temperature was provided in the barrel by using a circulating hot oil system. Standard capillary rheometry methods can provide the dependence of thermoset apparent viscosity on shear rate, temperature, and time. Process conditions resulting in complete imidization should be carefully defined. Specification of controlled oven temperature is inadequate and can result in incomplete imidization. For completely imidized PMR-15 heat at 15 C/min melt flow without gas evolution occurs in the temperature range of 325 C to 400 C.

Colaluca, M. A.↗

DOE OSTI2022

A probabilistic inverse prediction method for predicting plutonium processing conditions

In the past decade, nuclear chemists and physicists have been conducting studies to investigate the signatures associated with the production of special nuclear material (SNM). In particular, these studies aim to determine how various processing parameters impact the physical, chemical, and morphological properties of the resulting special nuclear material. By better understanding how these properties relate to the processing parameters, scientists can better contribute to nuclear forensics investigations by quantifying their results and ultimately shortening the forensic timeline. This paper aims to statistically analyze and quantify the relationships that exist between the processing conditions used in these experiments and the various properties of the nuclear end-product by invoking inverse methods. In particular, these methods make use of Bayesian Adaptive Spline Surface models in conjunction with Bayesian model calibration techniques to probabilistically determine processing conditions as an inverse function of morphological characteristics. Not only does the model presented in this paper allow for providing point estimates of a sample of special nuclear material, but it also incorporates uncertainty into these predictions. This model proves sufficient for predicting processing conditions within a standard deviation of the observed processing conditions, on average, provides a solid foundation for future work in predicting processing conditions of particles of special nuclear material using only their observed morphological characteristics, and is generalizable to the field of chemometrics for applicability across different materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Process and feedstock driven microstructure for laser powder bed fusion of 316L stainless steel

Here in the pursuit of improving additively manufactured (AM) component quality and reliability, fine-tuning critical process parameters such as laser power and scan speed is a great first step toward limiting defect formation and optimizing the microstructure. However, the synergistic effects between these process parameters, layer thickness, and feedstock attributes (e.g. powder size distribution) on part characteristics such as microstructure, density, hardness, and surface roughness are not as well-studied. In this work, we investigate 316L stainless steel density cubes built via laser powder bed fusion (L-PBF), emphasizing the significant microstructural changes that occur due to altering the volumetric energy density (VED) via laser power, scan speed, and layer thickness changes, coupled with different starting powder size distributions. This study demonstrates that there is not one ideal process set and powder size distribution for each machine. Instead, there are several combinations or feedstock/process parameter ‘recipes’ to achieve similar goals. This study also establishes that for equivalent VEDs, changing powder size can significantly alter part density, GND density, and hardness. Through proper parameter and feedstock control, part attributes such as density, grain size, texture, dislocation density, hardness, and surface roughness can be customized, thereby creating multiple high-performance regions in the AM process space.

316L stainless steel↗

NASA NTRS2016

Formation of Oxides in the Interior of Friction Stir Welds

In friction stir welding (FSWing) the actual solid state joining takes place between the faying surfaces which form the weld seam. Thus the seam trace is often investigated for clues when the strength of the weld is reduced. Aluminum and its alloys are known to form a native, protective oxide on the surface. If these native surface oxides are not sufficiently broken up during the FSW process, they are reported to remain in the FSW interior and weaken the bond strength. This type of weld defect has been referred to as a lazy "S", lazy "Z", joint line defect, kissing bond, or residual oxide defect. Usually these defects are mitigated by modification of the process parameters, such as increased tool rotation rate, which causes a finer breakup of the native oxide particles. This study proposes that there may be an alternative mechanism for formation of oxides found within the weld nugget. As the oxidation rate increases at elevated temperatures above 400ºC, it may be possible for enhanced oxidation to occur on the interior surfaces during the FSW process from entrained air entering the seam gap. Normally, FSWs of aluminum alloys are made without a purge gas and it is unknown how process parameters and initial fit up could affect a potential air path into the interior during the processing. In addition, variations in FSW parameters, such as the tool rotation, are known to have a strong influence on the FSW temperature which may affect the oxidation rate if internal surfaces are exposed to entrained air. A series of FSWs were made in 3 different thickness panels of AA2219 (0.95, 1.27 and 1.56 cm) at 2 different weld pitches. As the thickness of the panels increased, there was an increased tendency for a gap to form in advance of the weld tool. If sufficient air is able to enter the workpiece gap prior to consolidation, the weld temperature can increase the oxidation rate on the interior surfaces. These oxidation rates would also be accelerated in areas of localized liquation. Metallographs from the weld panels showed indications of liquation at the grain boundaries. In FSWs of thicker panels, these regions of liquation were found to be heavily oxidized. The quality of the FSWs was evaluated from tensile testing at room temperature. As the panel thickness increased, a slight decrease in tensile strength was observed which was attributed to the presence of oxides. No oxide formation was observed in the thinner workpieces, although there were indications of localized liquation at the grain boundaries. Results from this study will assist in a better understand of the mechanisms of oxide formation in FSW interiors and provide methodology for minimizing their occurrence.

Schneider, Judy↗

DOE OSTI2025

Machine Learning-Based Process Control for Injection Molding of Recycled Polypropylene

The increased interest in artificial intelligence in manufacturing has driven the adoption of machine learning to optimize processes and improve efficiency. A key challenge in injection molding is the variability of recycled materials, which affects part quality and processing stability. This study presents a novel closed-loop process control approach for injection molding, leveraging machine learning to adaptively predict processing inputs and quality outcomes. The methodology was tested on five blends of recycled polypropylene (rPP), using artificial neural networks (ANNs), linear regression, and polynomial regression to model the relationships between material properties and process parameters. The dataset was split 80/20 into training and testing sets. The ANN model was implemented using TensorFlow and Keras, with six hidden layers of 32 neurons per layer, ReLU activation, and an Adam optimizer. Empirical tuning and early stopping were used to optimize performance and prevent overfitting. Predictions were evaluated based on mean absolute error (MAE), mean squared error (MSE), and percentage error. The results showed that yield stress, ultimate elongation, and part weight were accurately predicted within a 5% error for linear and polynomial regression models and within a 10% error for the ANN. However, modulus predictions were less reliable, with errors of ~11% for ANN and linear regression and ~40% for polynomial regression, reflecting the inherent variability of this property in rPP blends. Predictions of processing inputs had errors ranging from 3% to 25%, depending on the model and response variable. No single modeling approach was consistently superior across all responses, highlighting the complexity of the relationship between material properties, process parameters, and quality metrics. Overall, the work demonstrates that closed-loop process control, powered by machine learning, can effectively predict key quality parameters in injection molding of recycled materials. The proposed approach can improve process stability and material utilization, facilitating increased adoption of sustainable materials.

Krantz, Joshua↗

NASA NTRS1982

Development and evaluation of polyvinyl-alcohol blend polymer films as battery separators

Several dialdehydes and epoxies were evaluated for their suitability as cross-linkers. Optium concentrations of several cross-linking reagents were determined. A two-step method of cross-linking, which involves treatment of the film in an acid or acid periodate bath, was investigated and dropped in favor of a one-step method in which the acid catalyst, which initiates cross-linking, is added to the PVA - cross-linker solution before casting. The cross-linking was thus achieved during the drying step. This one-step method was much more adaptable to commercial processing. Cross-linked films were characterized as alkaline battery separators. Films were prepared in the lab and tested in cells in order to evaluate the effect of film composition and a number of processing parameters on cell performance. These tests were conducted in order to provide a broader data base from which to select optimum processing parameters. Results of the separator screening tests and the cell tests are discussed.

Manzo, M. A.↗

DOE OSTI2021

Intelligent Agents for the Optimization of Atomic Layer Deposition

Atomic layer deposition (ALD) is a highly controllable thin film synthesis approach with applications in computing, energy, and separations. The flexibility of ALD means that it can access a massive chemical catalogue; however, this chemical and process diversity results in significant challenges in determining processing parameters that result in stable and uniform film growth with minimal precursor consumption. In situ measurements of the ALD growth per cycle (GPC) can accelerate process development but it still requires expert intuition and time-consuming trial and error to identify acceptable processing parameters. This procedure is made more difficult by the presence of experimental noise in the GPC values and the complexity of ALD surface chemistries. Here, a need exists for efficient optimization approaches capable of autonomously determining processing conditions resulting in optimal ALD film growth. In this work, we present the development of three optimization strategies and compare their performance in optimizing four simulated ALD processes. Furthermore, the effect of noise in the GPC measurements on optimization convergence is studied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2009

Stability of Detached Solidification

Bridgman crystal growth can be conducted in the so-called "detached" solidification regime, where the growing crystal is detached from the crucible wall. A small gap between the growing crystal and the crucible wall, of the order of 100 micrometers or less, can be maintained during the process. A meniscus is formed at the bottom of the melt between the crystal and crucible wall. Under proper conditions, growth can proceed without collapsing the meniscus. The meniscus shape plays a key role in stabilizing the process. Thermal and other process parameters can also affect the geometrical steady-state stability conditions of solidification. The dynamic stability theory of the shaped crystal growth process has been developed by Tatarchenko. It consists of finding a simplified autonomous set of differential equations for the radius, height, and possibly other process parameters. The problem then reduces to analyzing a system of first order linear differential equations for stability. Here we apply a modified version of this theory for a particular case of detached solidification. Approximate analytical formulas as well as accurate numerical values for the capillary stability coefficients are presented. They display an unexpected singularity as a function of pressure differential. A novel approach to study the thermal field effects on the crystal shape stability has been proposed. In essence, it rectifies the unphysical assumption of the model that utilizes a perturbation of the crystal radius along the axis as being instantaneous. It consists of introducing time delay effects into the mathematical description and leads, in general, to stability over a broader parameter range. We believe that this novel treatment can be advantageously implemented in stability analyses of other crystal growth techniques such as Czochralski and float zone methods.

Mazuruk, K.↗

DOE OSTI2020

Thermal Image Processing for Feature Extraction from Encapsulated Phase Change Materials

Encapsulated inorganic particles with high melting points (>300 °C) are desired as high-temperature Phase Change Materials (PCMs) for next-generation Latent Heat Thermal Energy Storage (LHTES) systems. One of the many challenges during the development of PCMs is to achieve a high throughput that in turn depends on accurately modeling the relation between process parameters and geometric & thermal properties of the PCMs particle. During the production of the PCMs, a high-speed infrared camera is used to acquire images of the encapsulated material under controlled illumination conditions. This research article focuses on the development of image processing techniques for both geometric and thermal feature extraction during the development of the PCMs. A user-friendly GUI has been designed in MATLAB and preliminary experimental results have demonstrated that the method is fast, accurate and reliable for a high throughput production. The extracted features will be used to develop Machine Learning (ML) models to predict the geometric and thermal properties of the PCM based on the process parameter settings. The ML model will accelerate the search for the optimized process settings to boost the throughput of the production.

25 ENERGY STORAGE↗

NASA NTRS2018

Numerical Simulation of AFP Nip Point Temperature Prediction for Complex Geometries

Material placement at the ideal nip point temperature over complex surfaces with uniformity across the width of the compaction rollers results in optimized part properties for Automated Fiber Placement (AFP) processes. However, current AFP systems utilize heat control models and methodologies, based on multiple process parameters such as feed-rate and orientation, that are mostly open-loop. Here, infrared (IR) heater input is calibrated as a function of process parameters during machine qualification. This work presents a numerical simulation to predict arrayed-infrared (AIR) emitter radiation onto a substrate that includes view factor implementation, IR radiative heat flow calculation, energy rate balance, and a transient heat transfer model. The purpose of this numerical model is to predict nip point temperature on complex surfaces, serving as a baseline for a new arrayed-infrared (AIR) thermoset heater to improve AFP process control. It is anticipated that this simulation will accurately control the temperature for high-speed AFP layup of complex geometries. An anticipated result of an AIR heater system is that material calibration and testing will be reduced as temperature is instantaneously monitored and controlled. Therefore, temperature across the roller width will be uniform during placement of complex parts, independent of their geometry.

Xia, Kaishu↗

DOE OSTI2026

Enhancing microsegregation during rapid directional solidification through ternary microalloying

The nano-cellular dendritic microstructure formed during rapid directional solidification in powder bed fusion additive manufacturing creates unique properties such as simultaneous improvement in strength and ductility. However, process control of microsegregation features remains challenging due to low sensitivity of critical solidification mechanisms to process parameters. This study leverages microalloying to achieve large changes in dendrite composition, microstructure, and interdendritic zone width during laser powder bed fusion without modifying process parameters. CALPHAD simulations predict that the addition of Zr significantly steepens the solidus line of the dilute Cu-Cr alloy system, leading to enhanced Cr rejection into the melt and greater than 95% reduction in solubility of Cr in the solidified Cu matrix. Experimental validation using time-of-flight secondary ion mass spectrometry and Kelvin probe force microscopy reveals that the ternary alloy containing 0.01 wt% Zr exhibited wider interdendritic regions compared to the binary, a significantly higher number of Cr-rich particles within interdendritic regions, near-complete ejection of oxygen impurities from the matrix, and greater nanoscale work function contrast. These features indicate more aggressive Cr segregation in the presence of Zr and a purer Cu matrix and provide a potentially robust method for engineering the nano-cellular dendritic solidification microstructure.

CALPHAD↗

DOE OSTI2023

Property-Graded Stainless Steel 316L by Selective Laser Melting: Characterization & Design

Abstract The purpose of this research work is to characterize and inform the design of (mechanical) property-graded bulk structures made from a single metallic alloy via a laser powder bed fusion (LPBF) process, with an end goal of creating repeatable/reproducible functionally-graded additively manufactured (FGAM) parts. This paper specifically investigates the manufacture of stainless steel (SS) 316L structures via a pulsed selective laser melting (SLM) process, and the underlying causes of property variations (within a functionally-acceptable range) through various material characterization techniques. For this, a design of experiments spanning the volumetric energy density (VED) based process parameter design space was utilized to investigate the range of functionally-acceptable physical/mechanical properties achievable in SS 316L. Five sample conditions (made via different process parameter combinations) were down-selected for in-depth microstructure analysis and mechanical/physical property characterization; these were suitably selected to impart a wide and controllable property range (209–318 HV hardness, 90–99.9% relative density, and 154–211 GPa modulus). It was observed that property variations resulted from combinations of porosity types/amounts, martensitic phase fractions, and grain sizes. Based on these findings, property-graded standard test specimens were designed and manufactured for further investigation—tensile specimens having a monotonic hardness change along its gauge length, four-point bending specimens with varying elastic moduli as a function of the distance from the neutral axis, and Moore’s rotating beam fatigue specimens with moduli variations based on the distance from the center. Altogether, this work lays the foundation for understanding and designing the local and global mechanical performance of FGAM bulk structures.

Engineering↗

DOE OSTI2023

Effect of Melt-Spinning Parameters on the Structure and Properties of Ni 55.5 Mn 18.8 Ga 24 Si 1.7 Heusler Alloy Ribbons

Ni–Mn-based Heusler alloys are known to demonstrate magnetic shape memory and giant magnetocaloric effect (MCE). These effects depend on the phases, crystallographic and magnetic phase transitions, and the crystallographic texture characteristics. These structural characteristics, in turn, are a function of the processing parameters. In the current work, Ni 55.5 Mn 18.8 Ga 24 Si 1.7 Heusler alloy was processed by melt-spinning under a helium atmosphere. This process results in a fine microstructure. The ribbon that was produced with a narrower nozzle width, faster wheel speed, and higher cast temperature, indicating a faster cooling rate, had double the magnetic entropy change close to room temperature. However, the other ribbon demonstrated a large entropy change over a broader temperature range, extending its usability. The effect of the melt-spinning process parameters on the developing microstructure, crystallographic structure and texture, transformation temperatures, and the magnetic entropy change were studied to explain the difference in magnetocaloric behavior.

36 MATERIALS SCIENCE↗