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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Ultraviolet antireflection coatings for use in silicon detector design

We report on the development of coatings for a charged-coupled device (CCD) detector optimized for use in a fixed dispersion UV spectrograph. Because of the rapidly changing index of refraction of Si, single layer broadband antireflection (AR) coatings are not suitable to increase quantum efficiency at all wavelengths of interest. Instead, we describe a creative solution that provides excellent performance over UV wavelengths. We describe progress in the development of a coated CCD detector with theoretical quantum efficiencies (QEs) of greater than 60% at wavelengths from 120 to 300 nm. This high efficiency may be reached by coating a backside-illuminated, thinned, delta-doped CCD with a series of thin film AR coatings. The materials tested include MgF{sub 2} (optimized for highest performance from 120-150 nm), SiO{sub 2} (150-180 nm), Al{sub 2}O{sub 3} (180-240 nm), MgO (200-250 nm), and HfO{sub 2} (240-300 nm). A variety of deposition techniques were tested and a selection of coatings that minimized reflectance on a Si test wafer were applied to functional devices. We also discuss future uses and improvements, including graded and multilayer coatings.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Development of Novel Functionally Graded Transition Joints for Improving the Creep Strength of Dissimilar Metal Welds in Nuclear Applications

Steam generators of the small modular Very High Temperature Reactor (VHTR) will require use of Alloy 800 and 2.25Cr-1Mo steel in different regions depending on temperature and corrosion resistance requirements. As a result, Dissimilar Metal Welds (DMWs) between these two materials are critical for design, development, and manufacturing of the VHTR. DMWs are also used in many other applications in the power generation and petrochemical industries. Experience has demonstrated that failures of such DMWs can occur prematurely well below the expected creep life of either base metal, and these failures have significant consequences in terms of plant reliability, safety, and economic impact. These DMWs failures are caused by the abrupt change in composition that occurs at the weld interface between the two alloys. In this research, the concept of developing and optimizing Graded Transition Joints (GTJ) was developed through an integrated modeling and experimental approach. With GTJs, the composition is gradually graded between the two alloys, thus eliminating the sharp change in composition that causes failure. Microstructural modeling was first conducted to identify the optimum grade length required for improved resistance to carbon diffusion that is largely responsible for premature failure. Next, GTJs were fabricated and characterized in detail to understand how the microstructure evolves during fabrication and long term aging. Finally, the creep behavior of the GTJs was investigated and compared to that of conventional DMWs to demonstrate the superior creep strength of the GTJs. The results of this research provide significant insight into design, fabrication, microstructural evolution, and resultant performance of GTJs that can be used for reducing or eliminating DMW failures in a number of high temperature applications. The results also demonstrate that the GTJs can be readily fabricated with either conventional or additive manufacturing processes, and detailed guidelines are provided on the length of grades needed for optimal performance. The results of this research benefits the general public by improving the reliability of power generation and petrochemical plants that rely on DMWs for safe and reliable operation to deliver power and other products.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

A reaction–diffusion model for grayscale digital light processing 3D printing

We report that digital light processing (DLP) 3D printing is an additive manufacturing process that utilizes light patterns to photopolymerize a liquid resin into a solid. Due to the accuracy of modern digital micromirror devices (DMD) and recent advances in resin chemistry, it is now possible to create functionally graded structures using different light intensity values, also known as grayscale DLP (g-DLP). Different intensities of light lead to differences in the polymer crosslinking density after curing, which ultimately produces a part with gradients of material properties. However, g-DLP is a complicated process. First, the DLP printing is a highly coupled chemical and physical process that involves light propagation, chemical reactions, species diffusion, heat transfer, volume shrinkage, and changes in mechanical behaviors of the curing resin. Second, in g-DLP, light gradients create strong in plane gradients of chemical species concentrations in the curing liquid resin due to the strong dependence of light intensity on the rate of monomer crosslinking. Furthermore, light gradients through the depth create concentration gradients due to the degree of cure dependent light absorption and the use of photoabsorbers. These complex physical features of the printing process must be understood in order to properly control printing parameters such as light exposure time, printing speed, and grayscale variations to achieve accurate mechanical properties. In this paper, a photopolymerization reaction–diffusion model is developed and used in conjunction with experiments to investigate the coupled effects of light propagation, chemical reaction rates, and species diffusion during g-DLP 3D printing. The model is implemented numerically utilizing the finite difference method and simulation results are compared to experimental findings of simple printed structures. The agreement between experimental and model predictions of simple quantities of interest, such as geometric feature sizes, shows that the model can capture the overcure due to free-radical and other species diffusion during printing when grayscale patterns are employed. This model lays the groundwork for future extensions that can incorporate more complex coupled physics such as heat transfer, volume shrinkage, and material property evolution, which are critically important in utilizing g-DLP 3D printing for the fabrication of high-performance parts which excellent geometric and material property tolerances.

36 MATERIALS SCIENCE↗
NASA NTRS1997

SiC-Based Gas Sensors

Electronic grade Silicon Carbide (SiC) is a ceramic material which can operate as a semiconductor at temperatures above 600 C. Recently, SiC semiconductors have been used in Schottky diode gas sensor structures. These sensors have been shown to be functional at temperatures significantly above the normal operating range of Si-based devices. SiC sensor operation at these higher temperatures allows detection of gases such as hydrocarbons which are not detectable at lower temperatures. This paper discusses the development of SiC-based Schottky diode gas sensors for the detection of hydrogen, hydrocarbons, and nitrogen oxides (NO(x)). Sensor designs for these applications are discussed. High sensitivity is observed for the hydrogen and hydrocarbon sensors using Pd on SiC Schottky diodes while the NO(x) sensors are still under development. A prototype sensor package has been fabricated which allows high temperature operation in a room temperature ambient by minimizing heat loss to that ambient. It is concluded that SiC-based gas sensors have considerable potential in a variety of gas sensing applications.

Chen, Liang-Yu↗
DOE OSTI2018

Microstructural study and simulation of intrinsic two-way shape memory behavior of functionally graded Ni-rich/NiTiCu thin film

Highlights: • Ni-rich/Ti-rich bi-layer thin film was deposited on Si by using DC magnetron sputtering. • The bi-layer exhibits the gradient structure and mechanical properties through the thickness. • The bi-layer shows intrinsic two-way shape memory effect due to functionally graded structure. • The intrinsic two-way shape memory effect was confirmed by finite element simulation. - Abstract: In this research, the gradient structure and mechanical properties of an austenitic/martensitic (Ni{sub 50.8}Ti/Ni{sub 45}TiCu{sub 5} (at.%)) bi-layer thin film was investigated. The bi-layer was deposited on a Si substrate using DC magnetron sputtering. After crystallization of the film at 773 K for 60 min, the microstructure and mechanical properties of the bi-layer thin film were characterized using X-ray diffraction (XRD), transmission electron microscopy (STEM and HRTEM) and nanoindentation, respectively. The diffraction pattern illustrated that the crystallized bi-layer was combined of martensitic and austenitic layers while secondary ion mass spectroscopy (SIMS) and high resolution transmission electron microscopy analysis demonstrated the existence of a compositional gradient through the thickness and residual strain in the interface of the bi-layer, respectively. Furthermore, the compositional gradient in the bi-layer led to gradual variations in the structure, hardness and Young's modulus through the thickness of the bi-layer. The intrinsic two-way shape memory effect due to its functionally graded structure and the induced stress was confirmed by experimental test and finite element simulation.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Hoop Tensile Failure Stress of 500 µm-Diameter Ceramic Spheres

The tensile failure stress of a brittle-material sphere is important to the survival of the sphere itself but is particularly relevant to systems that employ such spheres for applications in which the sphere exterior is subjected to tension during system fabrication or operation. That maximum hoop or tangential stress can be measured by diametrally compressing a C-sphere specimen directly machined from such spheres. This combination of specimen geometry and test method was conceived at Oak Ridge National Laboratory around 20 years ago. Although the C-sphere geometry has been tested with larger spheres, the ease and efficacy of its testing are unknown for submillimeter sphere diameters. To consider this, C-sphere specimens were machined from yttria-stabilized zirconia (YSZ) spheres of ∼500 µm diameter. The maximum (hoop or tangential) tensile stress was determined as a function of compressive failure force and specimen dimensions using finite element analysis. Companion effective area and volume as a function of Weibull modulus were computed. Hoop tensile failure stresses were then measured and fractography conducted to examine flaw type and location and to estimate the mirror constant of this YSZ grade. This novel study demonstrates that hoop tensile failure stress can be determined with sub-millimeter brittle-material spheres.

Delia, Daniel [ORNL] (ORCID:0000000209023239)↗
DOE OSTI2018

Mesostructure and porosity effects on the thermal conductivity of additively manufactured interpenetrating phase composites

In this paper, we have investigated the relationship between structure and thermal conductivity in additively manufactured interpenetrating A356/316L composites. We used X-ray microcomputed tomography to characterize the pore structure in as-fabricated composites, finding microporosity in both constituents as well as a 50 μm thick layer of interfacial porosity separating the constituents. We measured the thermal conductivity of a 43 vol% 316L composite to be 53 Wm -1 K -1 , which is significantly less than that predicted by a simple rule-of-mixtures approximation, presumably because of the residual porosity. Motivated by these experimental results we used periodic homogenization theory to determine the combined effects of porosity and unit cell structure on the effective thermal conductivity. This analysis showed that in fully dense composites, the topology of the constituents has a weak effect on the thermal conductivity, whereas in composites with interfacial porosity, the size and structure of the unit cell strongly influence the thermal conductivity. Finally, we also found that an approximation formula of the strong contrast expansion method gives excellent estimates of the effective thermal conductivity of these composites, providing a powerful tool for designing functionally graded composites and for identifying mesostructures with optimal thermal conductivity values.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Achieving clean production with nanostructured coated milling tools dry machining low carbon steel

The advancement of clean production using nanostructured materials in subtractive manufacturing processes has focused on replacing the use of liquid lubrication with solid lubricants coated to conventional cutting tools machining low carbon steel (~ 0.2 wt. % carbon). However, little is known about the wear mechanisms that dominate such tools when coated with functional graded nanostructured coatings. The present study follows an international standard for characterizing such wear (ISO 8688) but uses advanced measurement techniques such as x-ray fluorescence technology to measure the diffusion of chemical species from tool to workpiece and vice versa, that contributes to tool wear with the view to enhance the principles of cleaner production. The results show that when commercially-available tools coated with the appropriate functionally graded industrial coating, diffusion does not take place and creates an effective chemical barrier during machining. The experimental methods used in the study include machining workpieces using a CNC milling machine, tachometer for measuring spindle speed, dynamometer for measuring cutting forces, infra-red camera for measuring cutting temperatures, chemical species diffusion wear using x-ray florescence detector, and an optical microscope for measuring tool wear. Coupled with the physical measurement of wear, it is concluded that mechanical wear dominates the milling of a low carbon steel and that thermal properties of the coatings do not correlate with such wear. It is also concluded that flank wear as a function of volume of workpiece removed and machining duration (machining index) is a sound method for assessing the transition of the stages of wear during clean machining operations. The present study not only has implication for the design of better cutting tools, but also advances dry machining processes that eliminate the use of liquid lubricants making subtractive production processes cleaner. The main conclusions drawn from this study show that coated tools have a longer life under dry conditions compared to uncoated tools and that there is no correlation between coating properties and tool wear. In conclusion, diffusion of chemical species into the cut chips did not occur because of the lack of thermally induced chemical wear of the cutting tool and that wear is caused by the gradual erosion of the flank face due to the chip abrading the cutting tool.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Online simulation powered learning modules for materials science

Simulation tools are playing a significant role in materials science and engineering and beyond their well established importance in research and development, these tools have a vital pedagogical potential. We describe a set of online simulation tools and learning modules designed to help students explore important concepts in materials science where hands-on activities with high-fidelity simulations can provide insight not easily acquired otherwise. The online tools, which involve density functional theory and molecular dynamics simulations, have been designed with non-expert end-users in mind and only a few clicks are required to perform most simulations, yet they are powered by research-grade codes and expert users can access advanced options. All tools and modules are available for online simulation in nanoHUB.org and access is open and free of charge. Importantly, instructors and students do not need to download or install any software. The learning modules cover a range of topics from electronic structure of crystals and doping, plastic deformation in metals, and physical properties of polymers. These modules have been utilized in several core undergraduate courses at Purdue’s School of Materials Engineering, they are self contained, and are easy to incorporate into existing classes.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Multijunction Solar Cells With Graded Buffer Bragg Reflectors

Metamorphic solar cells can have optimal bandgap combinations through the use of compositionally graded buffers, where the lattice constant is slowly varied over several microns of growth. Bragg reflectors consist of several microns of alternating layers with refractive index contrast and provide a useful internal reflection to multijunction solar cells with optically thin subcells. In this work, we implement distributed Bragg reflectors within the compositionally graded buffers of inverted metamorphic solar cells to add functionality to the buffer. The reflectance of this AlGaInAs 'graded buffer Bragg reflector' is very similar to the reflectance of a similar AlGaAs Bragg reflector external to a buffer as well as the reflectance predicted by the transfer matrix model, indicating that the roughness of the buffer does not drastically reduce the reflection. Reflectance of 72%, 91%, and 98% is achieved in 2, 4, and 8 um buffers using AlGaInAs layers that alternate between 30% and 70% aluminum content. Using a 2 um graded buffer Bragg reflector, the 1.0-eV mismatched subcell of a GaAs/GaInAs tandem has a minor increase in threading dislocation density compared to a standard graded buffer and a small, 20 mV, loss in voltage. As the buffer is thickened, the voltage loss is recuperated and excellent subcell voltages are achieved, indicating that the Bragg reflector is not severely hindering dislocation glide. We demonstrate that the benefits of the graded buffer Bragg reflector for optically thin subcells and subcells containing quantum wells, and conclude that Bragg reflectors can effectively be implemented within graded buffers, adding functionality without adding cost.

14 SOLAR ENERGY↗
DOE OSTI2019

Investigation of deep levels in CdZnTeSe crystal and their effect on the internal electric field of CdZnTeSe gamma-ray detector

A study of deep levels in CdZnTeSe radiationdetection materials is presented. The approach relies on electrical methods that combine time and temperature evolution of the electric field and electric current after switching on the bias voltage. Two optical methods were also applied to study the deep levels. The first method utilizes the temperature and temporal analysis of the electric-field evolution after switching off an additional light illuminating the sample at a wavelength of 940 nm. The second method involved measuring of the electric-field spectral dependence during near infrared illumination. The results are compared with those obtained with high-quality CdZnTe detector-grade material. We conclude that the introduction of Se into the lattice leads to a shift of the second ionization level of the Cd vacancy towards the conduction band, as predicted recently by first-principles calculations based on screened hybrid functionals.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Graphite Characterization: Baseline Variability Analysis Report

The Idaho National INL’s Baseline Material Property program provides many measurements of different material properties on a variety of nuclear graphite grades being investigated for irradiation-induced changes in material properties. The baseline material properties provide an unirradiated reference for comparison with measurements of those properties after irradiation. This study describes how uncertainty, or variance, in estimates of important material properties, like compressive strength, may depend on sample size, sample distribution and parameter estimation methods. Compressive strength data from two large collections of specimens from a billet of PCEA graphite (sample size = 230) and a billet of IG-110 graphite (sample size = 48) are used to illustrate these dependencies. The grades of graphite used represent approximate end members in terms of relative variability in strength measurements. Monte Carlo simulation and bootstrapping methods were used to examine variance in Weibull-parameter estimates as a function of sample size. Results were consistent with what previous statistical analyses have shown about the relationship between sample size and width of the confidence interval for maximum likelihood (ML) estimated parameters when samples are repeatedly drawn from a Weibull distribution. As a function of sample size, the precision of the modulus estimate increases faster than that of the characteristic strength. The modulus maximum likelihood estimates (MLEs) are biased for low sample sizes. The American Society for Testing and Materials document ASTM D7846-16 provides equations that describe the dependence of the variance of parameter MLEs on sample size. Using the same methodology, we show that the polynomials provided for variance dependence on sample size are inaccurate for sample sizes greater than ~120. We provide approximations to that relationship that illustrate relative constancy for sample size > ~10, in the logspace relationship of the modulus variance and the log transformed characteristic strength variance. Bootstrapping provided a means of comparing Weibull parameters obtained using ASME’s guidance for specimen collection to those obtained using different weighting in a case where strength is related to position in a billet and to grain orientation and a single distribution is used to characterize the billet. ASME specifies that samples be collected with equal representation in all locations and grain orientations. Parameter values obtained using ASME’s method were different from those obtained using random sampling of the complete data sets, and this was particularly true for the PCEA data. In addition, while the ASME approach yielded more conservative parameters for the PCEA data, the opposite was true for the IG-110 data. The difference observed for the PCEA data set likely reflects the larger number of against-grain specimens collected, which had generally higher strength than the with-grain specimens. This emphasizes the importance of the dependence of strength on location or grain orientation and suggests that it may be prudent to weight specimen collection toward the weaker subgroups if a conservative estimate as desired, as the equal weighting method recommended by ASME would will not always provide the most conservative Weibull parameters. Because spatial correlations commonly exist in certain grades of graphite, future work may involve developing a methodology for parameter inference that relaxes the assumption of independent specimens. ASTM and ASME codes recommend different parameter estimation methods and models of the Weibull distribution in different situations. Descriptions of the effects on parameter estimates for the example billets used in this study provide an example of how the method may affect the parameter estimate, and how—in this case—that compares to differences due to other factors, such as sample size and dependence on grain orientation or sample location.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Parametric reduced order models for graded lattice structures

Graded lattice structures, characterized by smoothly varying mechanical properties, hold significant promise for optimizing material distribution in advanced engineering applications. However, accurately modeling these structures poses substantial computational challenges due to the continuous geometric variations within their unit cells. Here, to address these challenges, this paper introduces a novel Efficient Reduced Order Model (EROM) that integrates the Matrix Discrete Empirical Interpolation Method (MDEIM) and Discrete Empirical Interpolation Method (DEIM) with polynomial regression to efficiently manage geometric parametrization in lattice structures. Unlike traditional reduced order models (ROMs) that require extensive precomputed libraries for each geometric configuration, our approach enables continuous geometric variations through a flexible algebraic formulation, significantly reducing computational costs while preserving high accuracy. The method constructs projection matrices for individual unit cells that can be efficiently assembled into global systems, leveraging the repetitive nature of lattice structures. Numerical studies demonstrate that our EROM achieves displacement errors below 1% and von Mises stress prediction errors below 4%, coupled with computational speedups exceeding two orders of magnitude compared to full-order simulations. The proposed method's modularity and scalability make it particularly suitable for design optimization and real-time simulation of functionally graded lattice structures, with applications spanning aerospace to biomedical engineering.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Ensemble cure kinetics network (ECK-Net): A method to derive cure kinetics of thermosetting resin

This paper introduces an Ensemble Cure Kinetics Network (ECK-Net), a neural network (NN)–based framework for modeling the cure kinetics of thermosetting resins within a phenomenological context. ECK-Net replaces traditional analytic models, which require extensive chemical insight and multiple isothermal/non-isothermal experiments, with a data-driven surrogate that maps nonlinear relationships between temperature, degree of cure, and reaction rate from differential scanning calorimetry data. The proposed approach predicts input-dependent kinetic coefficients of a generalized nth-order reaction equation rather than reaction rates directly, enabling a single unified model to represent various epoxy systems without relying on iso-conversional analysis or predefined functional forms. To ensure robustness, multiple independently trained networks under different random initializations are blended through an ensemble strategy, effectively mitigating the stochastic variability inherent to neural networks. The framework is validated using experimental datasets from multiple resin systems, including aerospace-grade materials (Toray 3900-2, Cycom 5320-1, and Hexcel 8552) and a windmill-grade resin (RIMR 035c). The model accurately reproduces the temporal evolution of the degree of cure under manufacturers’ recommended cure cycles across all tested resins systems, yielding Pearson’s correlation coefficients of 0.992, 0.994, 0.993, 0.997, respectively. To demonstrate process-level applicability, the trained network was implemented within the Abaqus environment to simulate out-of-autoclave (OOA) curing process of the CFRP panel composed of Toray T830H-6K/3900-2D prepreg. The simulation results showed excellent agreement with experimental temperature response (maximum peak temperature, simulation: 189.6 °C, experiment: 188.5 °C) and the final degree of cure (simulation: 0.948, experiment: 0.960 ± 0.013), confirming ECK-Net’s capability as a reliable alternative to conventional cure kinetics modeling methods.

Composite curing↗
DOE OSTI2022

Fragility Functions Resource Report: Documented Sources for Electricity and Water Resilience Valuation

Fragility curves provide the vulnerability between hazard intensity and an asset. Federal installations may include many different electricity and water infrastructure types (or assets) such as generators, wind turbines, solar PV, switch yards, substations and power lines as well as water distribution systems that could be affected by different hazards. The vulnerability of each asset is a function of its age, type of materials and maintenance. In addition, the vulnerability changes with the hazards intensity and has a probability distribution function associated with it. The fragility functions are used in conjunction with hazard probability and consequence valuations to determine the values at risk for examination of investment grade analyses of alternative mitigation strategies. This document provides examples of fragility functions and links to their sources for different electricity and water infrastructure assets by hazard type.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2008

Design and Field Test of a Mass Efficient Crane for Lunar Payload Handling and Inspection: The Lunar Surface Manipulation System

Devices for lifting, translating and precisely placing payloads are critical for efficient Earthbased construction operations. Both recent and past studies have demonstrated that devices with similar functionality will be needed to support lunar outpost operations. Lunar payloads include: a) prepackaged hardware and supplies which must be unloaded from landers and then accurately located at their operational site, b) sensor packages used for periodic inspection of landers, habitat surfaces, etc., and c) local materials such as regolith which require grading, excavation and placement. Although several designs have been developed for Earth based applications, these devices lack unique design characteristics necessary for transport to and use on the harsh lunar surface. These design characteristics include: a) composite components, b) compact packaging for launch, c) simple in-field reconfiguration and repair, and d) support for tele-operated or automated operations. Also, in contrast to Earth-based construction, where special purpose devices dominate a construction site, a lunar outpost will require versatile devices which provide operational benefit from initial construction through sustained operations. This paper will detail the design of a unique, high performance, versatile lifting device designed for operations on the lunar surface. The device is called the Lunar Surface Manipulation System to highlight the versatile nature of the device which supports conventional cable suspended crane operations as well as operations usually associated with a manipulator such as precise positioning where the payload is rigidly grappled by a tool attached to the tip of the device. A first generation test-bed to verify design methods and operational procedures is under development at the NASA Langley Research Center and recently completed field tests at Moses Lake Washington. The design relied on non-linear finite element analysis which is shown to correlate favorably with laboratory experiments. A key design objective, reviewed in this paper, is the device s simplicity, resulting from a focus on the minimum set of functions necessary to perform payload offload. Further development of the device has the potential for significant mass savings, with a high performance device incorporating composite elements estimated to have a mass less than 3% of the mass of the maximum lunar payload lifted at the tip. The paper will conclude with future plans for expanding the operational versatility of the device.

Doggett, William R.↗
DOE OSTI2024

Formation of functionally graded steel by laser powder bed fusion via in-situ carbon doping

Additive Manufacturing (AM) enables functional integration by combining multiple components into a single part to shorten assembly time, reduce weight, and improve performance. Laser Powder Bed Fusion (LPBF) is an important AM method due to excellent spatial resolution, surface finish, and material properties without the need for extensive post-processing. Functional integration could be enhanced by spatial tuning of properties, but LPBF cannot readily vary material composition. Here, this paper addresses a method to add spatial composition control by printing small quantities of dopants via liquid carrier prior to laser fusion. The impact of carbon black suspension added to select regions of a Stainless Steel 316 L powder bed on melt pool dimension, hardness, and porosity is reported. The distribution of the carbon between the doped and plain layers and the resulting spatial variation in hardness is measured. Optical microscopy and composition analysis show that the carbon dispersed uniformly within the layer of deposition and diffused as little as 50 μm in the build direction. Keyhole conditions dramatically increase the inter-layer transport of the dopant. The added carbon increased hardness by >50 %. Porosity increased in doped regions but remained below 1.5 % for the best processing parameters. These results demonstrate that the composition of LPBF parts could be controlled in 3-dimensions using a dopant that is soluble in the melt pool. Additional work will be required to evaluate different dopant materials and optimize processing conditions for full density, but microalloying with soluble dopants appears to be a plausible solution to enhance functional integration with LPBF.

36 MATERIALS SCIENCE↗