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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 487 records · Page 27

Hydrocarbon-Seeded Ignition System for Small Spacecraft Thrusters Using Ionic Liquid Propellants

"Green" propellants based on Ionic-liquids (ILs) like Ammonium DiNitramide and Hydroxyl Ammonium Nitrate have recently been developed as reduced-hazard replacements for hydrazine. Compared to hydrazine, ILs offer up to a 50% improvement in available density-specific impulse. These materials present minimal vapor hazard at room temperature, and this property makes IL's potentially advantageous for "ride-share" launch opportunities where hazards introduced by hydrazine servicing are cost-prohibitive. Even though ILs present a reduced hazard compared to hydrazine, in crystalline form they are potentially explosive and are mixed in aqueous solutions to buffer against explosion. Unfortunately, the high water content makes IL-propellants difficult to ignite and currently a reliable "coldstart" capability does not exist. For reliable ignition, IL-propellants catalyst beds must be pre-heated to greater than 350 C before firing. The required preheat power source is substantial and presents a significant disadvantage for SmallSats where power budgets are extremely limited. Design and development of a "micro-hybrid" igniter designed to act as a "drop-in" replacement for existing IL catalyst beds is presented. The design requires significantly lower input energy and offers a smaller overall form factor. Unlike single-use "squib" pyrotechnic igniters, the system allows the gas generation cycle to be terminated and reinitiated on demand.

Whitmore, Stephen A.↗

Machine learning-based ethylene and carbon monoxide estimation, real-time optimization, and multivariable feedback control of an experimental electrochemical reactor

Electrochemical reduction of CO 2 gas is a novel CO 2 utilization technique that has the potential to mitigate the global climate crisis caused by anthropogenic CO 2 emissions, and enable the large-scale storage of energy generated from renewable sources in the form of carbon-based chemicals and fuels. However, due to the complexity of the electrochemical reactions, the explicit first-principles models for CO2 reduction are not available yet, and there has been a limited effort to develop process modeling, optimization and control of CO 2 electrochemical reactors. To this end, a rotating cylinder electrode (RCE) reactor has been constructed at UCLA to understand the mass transfer and reaction kinetics effects separately on the productivity. In the RCE reactor, the applied potential strongly influences the reaction energetics and the electrode rotation speed affects the hydrodynamic boundary layer and modifies the film mass transfer coefficient, which involves convective and diffusive transport. Further, the present work aims to develop a multi-input multi-output (MIMO) control scheme for the RCE reactor that integrates techniques from artificial and recurrent neural network modeling, nonlinear optimization, and process controller design. Specifically, production rates of two products from the experimental reactor, ethylene and carbon monoxide, are controlled by manipulating two inputs, applied potential and catalyst rotation speed. Process dynamics and controllability are analyzed, a feedback control strategy is designed and the controllers are tuned accordingly. The experimental electrochemical cell is employed to gather data for process modeling and implement the multivariable control system. Finally, the experimental results are presented which demonstrate excellent closed-loop performance by the control system and regulation of the outputs at three different set-points including an economically-optimal set-point.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Non-Intrusive Appliance Identification with Appliance-Specific Networks

The problem of noninstrusive load monitoring (NILM) is usually formulated as a single-channel blind source separation task, whose successful solution enable fast and convenient load identification and energy disaggregation. When applied at test time, NILM algorithms aim to identify the operating characteristics of individual appliances from an aggregate power measurement of the entire house. Recent advances in deep learning gave rise to many methods that mostly focus on learning a direct mapping from aggregate measurement to individual appliance power. However, these methods are not only computationally expensive, but they often suffer from overfitting and do not generalize very well. In this article, we propose a novel NILM method that leverages advances in statistical learning that have not been properly applied in this domain before. The proposed method consists of three stages: first, a Bayesian nonparametric learning-based approach for appliance state extraction; second, synthetic minority oversampling technique for data augmentation and mitigating the heavy imbalance in switching events; and third, appliance-specific lightweight long short-term memory networks for status classification for each appliance. Here, we adopt a “differential” input (the difference before and after the switching event) to reduce the complexity of network training and make the proposed method robust to multiappliance switching events. Experiments are conducted to demonstrate the effectiveness of the proposed method, achieving superior performance when compared to recent methods. An ablation study is conducted to demonstrate the effectiveness of each module of our method. Finally, we investigate the quality of generated synthetic samples.

42 ENGINEERING↗

Ni coarsening under humid atmosphere in the electrode of solid oxide cells: A combined study of density-functional theory and phase-field modeling

Ni coarsening in solid oxide cell (SOC) electrodes is known to be significantly faster under a humid atmosphere. The underlying mechanisms, though, have not been fully understood. In this work, we examine the surface diffusion of Ni(OH) x by a combination of density-functional theory and phase-field modeling. Here, density-functional theory is used to evaluate the adsorption and diffusion of the Ni(OH) x species on Ni (111) surface, and the results are used to obtain the effective surface diffusivity of Ni versus steam and hydrogen gas partial pressures. This diffusivity is used as an input for a phase-field model to investigate the Ni coarsening in SOC electrodes. It is found that Ni(OH) x formed through chemical reaction cannot accelerate coarsening unless an extremely high steam to hydrogen ratio is reached. However, if Ni(OH) x is formed through electrochemical reactions near triple phase boundaries (TPBs), surface diffusion of Ni(OH) x may cause faster Ni coarsening in fuel cell mode under a large overpotential. Specifically, surface diffusion of Ni(OH) may be comparable to or faster than that of Ni under an overpotential that is large but still possible under fuel cell operating conditions.

25 ENERGY STORAGE↗

An uncertainty quantification method relevant to material test reactors

Within material test reactor calculations, energy dependent flux and reaction rate uncertainties are typically not quantified when performing as-run analyses to determine the neutron field experienced by the experiment. When high fidelity Monte-Carlo codes are used in such analyses, straight forward methods to calculate output uncertainties are not available, instead expert opinion is used to postulate computational uncertainties. New methods to propagate uncertainties through these high fidelity simulations are available when sufficient computational power is available. A tool is developed here for sampling any part of an MCNP input from random distributions to determine output uncertainties based on those inputs. Another tool is developed to sample nuclear data cross-section in ACE format using multi-group nuclear data covariances. The Total Monte-Carlo Method and Gesellschaft für Anlagen-und Reaktorsicherheit method (GRS) are implemented and compared to one another as well as MCNP sensitivity and uncertainty calculations. The methods were applied to the Godiva critical sphere k-eigenvalue, the UAM pin-cell benchmark energy dependent flux and reaction rates, and the Advanced Test Reactor energy dependent flux within an experimental location. Furthermore, the two methods agree well, with GRS allowing for an order of magnitude speedup for reaction rate uncertainty calculations and several orders of magnitude for eigenvalue uncertainty calculations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Exploring the Influence of Linker Substitution and Ratios on Cooperative Framework Flexibility through the Mixed-Linker Approach

Cooperatively flexible metal–organic frameworks that exhibit step-shaped, or Type V-like, adsorption–desorption profiles can lower requisite pressure–temperature swings and thus energy input, necessary for an array of gas storage, delivery, and separations applications. However, such benefits are lost if the pressure threshold of the adsorption and desorption steps at a given temperature does not match the conditions dictated by the application, such as H 2 storage and delivery or olefin–paraffin separations. Unfortunately, the discovery of cooperatively flexible frameworks remains wholly serendipitous and de novo design remains impossible. Accordingly, there is a great need to further our understanding of flexibility such that we can intuitively derivatize known frameworks and, ultimately, design entirely new ones to meet the requisite conditions of energy-consumptive processes. In this work, we demonstrate that the mixed-linker, or multivariate, approach is a powerful tool for the derivation of a known flexible framework, with variances in linker substitution and ratio giving rise to a family wherein significant changes to the step-shaped adsorption–desorption profiles for multiple adsorbates are observed. Specifically, we report 12 isostructural mixed-linker derivatives of CdIF-13 (sod–Cd(benzimidazolate) 2 ) with six point-modified benzimidazole linkers spontaneously synthesized through prototypical solvothermal conditions. Furthermore, each is shown by PXRD to exhibit similar reversible flexibility to CdIF-13 and by TGA and DSC to be similarly thermally stable. Isothermal gas adsorption measurements with N 2 at 77 K, CO 2 at 195 K, and propane at 298 K demonstrate the wide-ranging, adsorbate-dependent effects of linker substitution and ratio, including dramatic reductions in the adsorption threshold pressure, evolution of multiple steps, and complete absence of observable adsorption. Aided by prior crystallographic characterization of CdIF-13, the observed trends were analyzed in an attempt to resolve the influence of linker substitution and ratios on structural behavior. In total, this work illustrates how the mixed-linker approach enables the synthesis and study of a large catalog of functionally modified frameworks, which can help identify the variables that influence flexibility and sorption behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Efficient Reversible Operation and Stability of Novel Solid Oxide Cells

This project aims to develop and test novel Reversible Solid Oxide Cells (ReSOCs) specifically designed to yield low area specific resistance, as required to achieve high round trip efficiency in reversible operation at high current density. A key objective is to improve long-term reversible SOC durability; mechanistic degradation models will be used to predict long-term durability using input data from accelerated testing that combines electrochemical life testing with quantitative microstructural and chemical evaluation. The modeling tasks seek to design low-loss, low-cost ReSOC systems using input data from the experimental cell studies. A key challenge is to develop a thermal management strategy that maintains thermally self-sustaining operation while operating the stack at a potential lower than the thermo-neutral steam electrolysis voltage of ~1.3 V, to maintain high efficiency.

08 HYDROGEN↗

Risk Model for EM Decision Support Toolsets

The Government Office of Accountability (GAO) has published several reports identifying the need for the Department of Energy (DOE) Office of Environmental Management (EM) to address mounting costs for DoE's cleanup program. DOEEM could greatly benefit from independent decision tool-sets/models that would allow them to evaluate options and inform business decision at the enterprise level considering site-specific life cycle costs and system plans. Program goals: Develop a tool-set that enables EM to independently evaluate alternatives, assess outcomes from different contracting strategies, and inform critical decisions for the enterprise. Project goals: Adaption of a Risk Model for integration with complimentary tool-sets for project level decision making. Operational Events: Discrete event model that evaluates operational variables (e.g. capacity, throughput, maintenance constraints) and identify bottlenecks. Identifying and Bounding Project Risk: Identify risks that impact confidence in meeting goals (e.g. production). Life cycle Cost: Evaluate impacts of staffing levels, inventory, and capital investments on life cycle costs. Methods and approach: Monte Carlo Analysis is being executed to generate results: Input derives from Risk Register Data; Tied to Projected and Target Schedules; Incorporates float duration within the model. Assumes associated risk mitigation actions being completed within a timeline of five fiscal years. Metrics include: Confidence in Meeting Production Goal; Confidence in Safety Standards; Confidence in Continuous Operation; Other Metrics can be added as appropriate regarding specific site needs. The adapted risk model can be used as a stand alone decision tool or can be integrated complementary tool-sets (i.e. process and cost models) for project-specific decisions. These support tool-sets can then be integrated with others for site- and complex- level evaluations. Future work includes designing an adaptable and modular framework that would allow integration of multiple tool-sets for holistic and/or targeted evaluation of alternative strategies for decision making that could lead to risk and cost reduction across the enterprise.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

time-resolved spectroscopy fit (trspecfit) v0.01

Analyze 2D time- and energy-resolved data, such as from a pump-probe spectroscopy experiment. User can select and input different peak shapes/ functions and background types to first fit a ground state/ unperturbed spectrum. This would be similar to how standard spectroscopy data is fit. Subsequently, to describe the time domain, users can choose functions that describe the temporal dynamics of one or more spectral features, such as a peak amplitude, peak position, etc. These time dynamics functions can be added or convoluted (e.g. describing an instrument response function) with each other. Functionality to integrate implicit variables leading to distributions of certain parameters/ functions is in development. Alternatively, 2D data can be analyzed one time step at a time to get an idea of the time dynamics of the system before deploying the global 2D fit described above. Typically people write custom software for this purpose. During my PhD I've seen five internal LBL and external researchers write one-off code in different languages to analyze time- and energy-resolved spectra. While this was specifically was for a laser pump - X-ray probe spectroscopy experiment, I'm trying to write a general package for the time-resolved spectroscopy community.

Mahl, Johannes [Lawrence Berkeley National Laborat↗

Tropical Diabatic Heating and the Role of Convective Processes as Represented in Several Contemporary Climate Models

One of the most fundamental properties of the global heat balance is the net heat input into the tropical atmosphere that helps drive the planetary atmospheric circulation. Although broadly understood in terms of its gross structure and balance of source / sink terms, incorporation of the relevant processes in predictive models is still rather poor. The work reported here examines the tropical radiative and water cycle behavior as produced by four contemporary climate models. Among these are the NSIPP-2 (NASA Seasonal to Interannual Prediction Project) which uses the RAS convective parameterization; the FVCCM, a code using finite volume numerics and the CCM3.6 physics; FVCCM-MCRAS again having the finite volume numerics, but MCRAS convective parameterization and a different radiation treatment; and, finally, the NCEP GSM which uses the RAS. Using multi-decadal integrations with specified SSTs we examine the statistics of radiative / convective processes and associated energy transports, and then estimate model energy flux sensitivities to SST changes. In particular the behavior of the convective parameterizations is investigated. Additional model integrations are performed specifically to assess the importance representing convective inhibition in regulating convective cloud-top structure and moisture detrainment as well as controlling surface energy fluxes. To evaluate the results of these experiments, a number of satellite retrievals are used: TRMM retrievals of vertical reflectivity structure, rainfall rate, and inferred diabatic heating are analyzed to show both seasonal and interannual variations in vertical structure of latent heat release. Top-of-atmosphere radiative fluxes from ERBS and CERES are used to examine shortwave and longwave cloud forcing and to deduce required seasonal energy transports. Retrievals of cloud properties from ISCCP and water vapor variations from SSM/T-2 are also used to understand behavior of the humidity fields. These observations are supplemented with output form the DOE Reanalysis-2.

Robertson, Franklin R.↗

Lightweight Radiator for in Space Nuclear Electric Propulsion

Nuclear electric propulsion (NEP) is a promising option for high‐speed in‐space travel due to the high energy density of nuclear fission power sources and efficient electric thrusters. Advanced power conversion technologies may require high operating temperatures and would benefit from lightweight radiator materials. Radiator performance dictates power output for nuclear electric propulsion systems. Game‐changing propulsion systems are often enabled by novel designs using advanced materials. Pitch‐based carbon fiber materials have the potential to offer significant improvements in operating temperature, thermal conductivity, and mass. These properties combine to allow advances in operational efficiency and high temperature feasibility. An effort at the NASA Marshall Space Flight Center to show that woven high thermal conductivity carbon fiber mats can be used to replace standard metal and composite radiator fins to dissipate waste heat from NEP systems is ongoing. The goals of this effort are to demonstrate a proof of concept, to show that a significant improvement of specific power (power/mass) can be achieved, and to develop a thermal model with predictive capabilities making use of constrained input parameter space. A description of this effort is presented.

Craven, Paul↗

A review of water valuation metrics: Supporting sustainable water use in manufacturing

In the manufacturing sector, water has been often considered too cheap to conserve. Such thinking relies on water valuations that limit the value of water to the price paid. Using such simple methods, the share of water cost to total manufacturing cost is significantly small, <3%. As a result, conserving water and enabling technology uptake is difficult to justify economically and slow to advance, hindering progress toward sustainable water use. However, the value of water to a manufacturer is far greater than the price paid. Valuations such as the true cost of water consider the additional in-plant treatment and energy costs and have been gaining greater traction in the manufacturing sector. However, true cost alone still undervalues water by not accounting for economic and social costs related to scarcity and environmental externalities. This paper makes the case and presents a framework for valuing manufacturing water beyond the price paid and the true cost. The proposed fuller valuation of manufacturing water takes into account the internal and opportunity costs associated with the realization of water risks. The paper follows with a review of a wide range of water valuation metrics, both at the specific industry level and regional/economy-wide level. The use of various valuation metrics incorporating the relationship between the change in value with change in water use, such as marginal value of water, shadow price, and elasticity at the specific industry level, has been limited in the U.S. manufacturing sector. Further, a limited number of studies exist on data-intensive subjective evaluation techniques such as computable general equilibrium modeling and input-output modeling for regional water valuation. After reviewing water value metrics, several recent case studies from manufacturers from the literature are presented to illustrate both the promise and challenges of a fuller valuation of water as proposed here. Some large multinational corporations have moved toward assessing the value of water via supply chain sustainability initiatives, environmental profit and loss accounting, estimating risk-adjusted values of water, hydro-economic modeling, natural capital asset valuation, and developing value chain indices. This paper provides policymakers and technology developers a framework for monetizing water value beyond its true cost and current metrics. If adopted, such fuller water valuations can help make the business case for the development and deployment of cost-effective water-conserving technologies, thereby improving the sustainability of the manufacturing sector with respect to water.

54 ENVIRONMENTAL SCIENCES↗

A Tool for Model-Based Generation of Scenario-driven Electric Power Load Profiles

Power consumption during all phases of spacecraft flight is of great interest to the aerospace community. As a result, significant analysis effort is exerted to understand the rates of electrical energy generation and consumption under many operational scenarios of the system. Previously, no standard tool existed for creating and maintaining a power equipment list (PEL) of spacecraft components that consume power, and no standard tool existed for generating power load profiles based on this PEL information during mission design phases. This paper presents the Scenario Power Load Analysis Tool (SPLAT) as a model-based systems engineering tool aiming to solve those problems. SPLAT is a plugin for MagicDraw (No Magic, Inc.) that aids in creating and maintaining a PEL, and also generates a power and temporal variable constraint set, in Maple language syntax, based on specified operational scenarios. The constraint set can be solved in Maple to show electric load profiles (i.e. power consumption from loads over time). SPLAT creates these load profiles from three modeled inputs: 1) a list of system components and their respective power modes, 2) a decomposition hierarchy of the system into these components, and 3) the specification of at least one scenario, which consists of temporal constraints on component power modes. In order to demonstrate how this information is represented in a system model, a notional example of a spacecraft planetary flyby is introduced. This example is also used to explain the overall functionality of SPLAT, and how this is used to generate electric power load profiles. Lastly, a cursory review of the usage of SPLAT on the Cold Atom Laboratory project is presented to show how the tool was used in an actual space hardware design application.

power load profile↗

An Ab Initio Molecular Dynamics Study of Key Thermodynamic Input Parameters for Computer Simulation of U-6Nb Solidification

The key to metallic fuel development is the fabrication of uranium metal and alloys into fuel forms. U-Nb alloys are one of the best candidates for a metallic fuel alloy with high-temperature strength sufficient to support the core, acceptable nuclear properties, good fabricability, and compatibility with usable coolant media. Melt processing has been a key component of the metallic fuel cycle, and process models require thermophysical parameters at elevated temperatures, particularly above the melting temperatures, regarding which experimental data are scarce, for accurate simulations and process development. By means of ab initio density-functional theory (DFT) quantum molecular dynamics (QMD), we have calculated the main thermophysical parameters—the density, thermal expansion coefficient, specific heat, thermal conductivity, melting temperature, latent heat of fusion, and viscosity—used in the modeling of the U-6 wt.% Nb alloy casting. The melting temperature of the U-6 wt.% Nb alloy at ambient pressure is obtained by means of QMD simulations using the Z-method. The ambient volume change and latent heat of melting of U-6 wt.% Nb are also derived from QMD simulations in conjunction with analytical fitting for the energy and pressure. The thermal conductivity for the solid U-Nb alloy is calculated from the semi-classical Boltzmann transport equation combined with an estimate of the electron relaxation time obtained from DFT simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

HZETRN: Description of a free-space ion and nucleon transport and shielding computer program

The high-charge-and energy (HZE) transport computer program HZETRN is developed to address the problems of free-space radiation transport and shielding. The HZETRN program is intended specifically for the design engineer who is interested in obtaining fast and accurate dosimetric information for the design and construction of space modules and devices. The program is based on a one-dimensional space-marching formulation of the Boltzmann transport equation with a straight-ahead approximation. The effect of the long-range Coulomb force and electron interaction is treated as a continuous slowing-down process. Atomic (electronic) stopping power coefficients with energies above a few A MeV are calculated by using Bethe's theory including Bragg's rule, Ziegler's shell corrections, and effective charge. Nuclear absorption cross sections are obtained from fits to quantum calculations and total cross sections are obtained with a Ramsauer formalism. Nuclear fragmentation cross sections are calculated with a semiempirical abrasion-ablation fragmentation model. The relation of the final computer code to the Boltzmann equation is discussed in the context of simplifying assumptions. A detailed description of the flow of the computer code, input requirements, sample output, and compatibility requirements for non-VAX platforms are provided.

Wilson, John W.↗

TCR Input to NUREG-1537 Process for Advanced Nuclear Technologies Derived from Additive Manufacturing

There has been a renewed interest by several advanced reactor developers to use NUREG-1537 “Guidelines for Preparing and Reviewing Applications for the Licensing of Non-Power Reactors” as a basis for their safety analysis report content and organization. Recently, SHINE Medical Technologies, LLC (SHINE), which is a non-power, Aqueous Homogenous Reactor design radioisotope production facility, received a construction permit based around their NUREG-1537 safety evaluation report (ADAMS No. ML16229A140). Advanced reactor developers are interested in using NUREG-1537 as a basis for their safety analysis report content and organization because of its successful application towards research reactors, graded approach, and simplicity in structure and requirements. However, NUREG-1537 is still largely geared toward light water reactors (LWRs) and many improvements could be made or supported through guidance documents for advanced reactors. For nuclear power to play a role in the future zero-carbon energy portfolio, a supportive regulatory structure is needed to lower regulatory uncertainty and barriers to deployment. At the time of this report, no such document or pathway exists for advanced nuclear technologies, including those derived from nontraditional technology such as advanced manufacturing technology (AMT) and, specifically, additive manufacturing. This report will explore and provide recommendations as to how advanced nuclear technologies derived from additive manufacturing technologies could employ the use of an ISG, other guidance document, or revisions to NUREG-1537 to lower the regulatory uncertainty and barriers for adoption.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Simulation-Based Validation of An Open-Source, Scalable Framework for Building Energy Management in Small and Medium-Sized Commercial Buildings

Abstract: Small and medium-sized commercial buildings (SMCBs) represent 94% of U.S. commercial buildings but encounter substantial obstacles in adopting Building Energy Management (BEM) systems. Current approaches exhibit fundamental limitations: vendor-specific API platforms restrict interoperability through proprietary ecosystems; commercial automation software demands extensive technical expertise and licensing costs; open-source IoT solutions lack native support for building automation protocols and semantic models. This paper introduces a configuration-driven web interface framework addressing the gap between smart device advancements and accessible BEM software infrastructure for SMCBs. The framework leverages VOLTTRON middleware integrated with an automated converter that processes unified YAML configurations into heterogeneous system files, reducing required configuration artifacts from six separate files to a single unified specification. The system architecture enables vendor-agnostic operation through BACnet and Modbus protocols while supporting semantic building model integration via automated Brick Schema parsing. Configuration-driven interfaces automatically adapt to diverse HVAC types without custom development. Simulation-based validation using BOPTEST demonstrates automatic interface generation between fan coil and hydronic systems, with the automated converter successfully generating all platform-specific outputs from the single YAML input. The result demonstrates the framework's capability to streamline BEM system deployment through reduced configuration complexity. This work bridges simulation capabilities with operational deployment, demonstrating how virtual testbeds validate generalizable software frameworks for real-world building automation.

Chung, Jihoon [ORNL] (ORCID:0000000184880815)↗

Characterization of multi-material 316L-Hastelloy X fabricated via laser powder-bed fusion

The aim of this work is to provide firsthand knowledge of 316 L stainless steel (316 L) and Hastelloy X (HX) multi-material processing via laser powder bed fusion (PBF). Specifically, microstructure of the interface is studied using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and X-ray diffraction (XRD). Surface metrology is performed to characterize the resulting surface roughness at the interface followed by tensile and flexural testing of multi-material samples to characterize the mechanical properties of the interfaces. Results showed that use of proper process parameters for each individual material led to formation of a compositional gradient at the interface that stretched for 240 μm (10–12 layers) with no evidence of cracking or porosity. The interface exhibited higher surface roughness compared to 316 L or HX as measured by arithmetic mean height, Sa, and maximum valley depth, Sv, parameters. During tensile testing, samples failed in the 316 L region away from the interface, with comparable yield strength, ultimate strength, and ductility. Finally, it was concluded that the “naturally” formed interface created a compositional gradient which was defect free due to similar values of coefficient of thermal expansion, input energy density, and different Marangoni numbers of the materials.

316L stainless Steel↗