Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “kinetic parameters”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Errors in Sounding of the Atmosphere Using Broadband Emission Radiometry (SABER) Kinetic Temperature Caused by Non-Local Thermodynamic Equilibrium Model Parameters

The vast set of near global and continuous atmospheric measurements made by the SABER instrument since 2002, including daytime and nighttime kinetic temperature (T(sub k)) from 20 to 105 km, is available to the scientific community. The temperature is retrieved from SABER measurements of the atmospheric 15 micron CO2 limb emission. This emission separates from local thermodynamic equilibrium (LTE) conditions in the rarefied mesosphere and thermosphere, making it necessary to consider the CO2 vibrational state non-LTE populations in the retrieval algorithm above 70 km. Those populations depend on kinetic parameters describing the rate at which energy exchange between atmospheric molecules take place, but some of these collisional rates are not well known. We consider current uncertainties in the rates of quenching of CO2 (v2 ) by N2 , O2 and O, and the CO2 (v2 ) vibrational-vibrational exchange to estimate their impact on SABER T(sub k) for different atmospheric conditions. The T(sub k) is more sensitive to the uncertainty in the latter two and their effects depend on altitude. The T(sub k) combined systematic error due to non-LTE kinetic parameters does not exceed +/- 1.5 K below 95 km and +/- 4-5 K at 100 km for most latitudes and seasons (except for polar summer) if the Tk profile does not have pronounced vertical structure. The error is +/- 3 K at 80 km, +/- 6 K at 84 km and +/- 18 K at 100 km under the less favourable polar summer conditions. For strong temperature inversion layers, the errors reach +/- 3 K at 82 km and +/- 8 K at 90 km. This particularly affects tide amplitude estimates, with errors of up to +/- 3 K.

Garcia-Comas, Maya↗
DOE OSTI2022

Reorganization Energies for Interfacial Proton-Coupled Electron Transfer to a Water Oxidation Catalyst

The reorganization energy (λ) for interfacial electron transfer (ET) and proton-coupled electron transfer (PCET) from a conductive metal oxide (In 2 O 3 :Sn, ITO) to a surface-bound water oxidation catalyst were extracted from kinetic data measured as a function of the thermodynamic driving force. Visible light excitation resulted in rapid excited-state injection (k inj > 10 8 s -1 ) to the ITO, which photo-initiated the two interfacial reactions of interest. The rate constants for both reactions increased with the driving force, −ΔG°, to a saturating limit, k max , with rate constants consistently larger for ET than for PCET. Marcus-Gerischer analysis of the kinetic data provided the reorganization energy for interfacial PCET (0.90 ± 0.02 eV) and ET (0.40 ± 0.02 eV), respectively. The magnitude of k max for PCET was found to decrease with pH, behavior that was absent for ET. Both the decrease in k max and the larger reorganization energy for an unwanted competing PCET reaction from the ITO to the oxidized catalyst showcases a significant kinetic advantage for driving solar water oxidation at high pH. Computational analysis revealed a larger inner-sphere reorganization energy contribution for PCET than for ET arising from a more significant change in the Ru–O bond length for PCET. Extending Marcus-Gerischer theory to PCET by including the excited electron-proton vibronic states and the proton donor-acceptor motion provided an apparent reorganization energy of 1.01 eV. Furthermore, this study demonstrates that the Marcus-Gerischer theory initially developed for ET can be reliably extended to PCET for quantifying and interpreting reorganization energies observed experimentally.

Catalysts Kinetic parameters↗
DOE OSTI2021

Dark Higgs dark matter

A new U(1) dark gauge group coupled to the Standard Model (SM) via the kinetic mixing portal provides a natural dark matter candidate in the form of the Higgs field, hd, responsible for generating the mass of the dark photon, γ d . We show that the condition m h d ≤m γ d , together with smallness of the kinetic mixing parameter, ϵ, and/or dark gauge coupling, g d , leads the dark Higgs to be sufficiently metastable to constitute dark matter. We analyze the Universe's thermal history and show that both freeze-in, SM→{γ d ,h d }, and freeze-out, {γ d ,h d }→SM, processes can lead to viable dark Higgs dark matter with a sub-GeV mass and a kinetic mixing parameter in the range 10 –13 ≲ϵ≲10 –6 . Observable signals in astrophysics and cosmology include modifications to primordial elemental abundances, altered energetics of supernovae explosions, dark Higgs decays in the late Universe, and dark matter self-interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Investigating Kinetic Mechanisms of Soot Formation in Plasma Pyrolysis of Methane via Active Learning (Final Technical Report)

Plasma pyrolysis of methane is an effective route for zero-carbon hydrogen production. Yet, soot generated from pyrolysis of hydrocarbons is detrimental to the climate and human health. There is ample experimental and theoretical evidence that suggests polycyclic aromatic hydrocarbons (PAHs) are the molecular precursors to soot particles. The reaction pathways of PAH formation are intricately dependent on a multitude of process parameters, whose kinetic mechanisms are not well-understood in plasma pyrolysis. This project aims to leverage advances in the kinetic modeling of soot formation in combustion, as well as in surrogate modeling and active learning, to systematically investigate the effects of process parameter on the kinetics of PAH formation in plasma pyrolysis of methane. To this end, we propose to use the PAH formation kinetics model developed by the PPPL/PU group based on the well-established ABF and HACA mechanisms, coupled with low-temperature plasma models. We will develop an active learning (AL) framework based on Bayesian optimization to systematically and data-efficiently explore the complex and multivariable parameter space of plasma pyrolysis in order to quantify the effects of plasma and feed parameters on the ABF and HACA kinetic pathways. AL is the branch of machine learning concerned with systematically querying samples from a system (experimental or computational) to train a data-driven model that maps design parameters to a performance criterion. We will use the data generated via AL to perform global sensitivity analysis, combined with uncertainty quantification, to elucidate the impact of different reaction pathways on minimizing formation of soot precursors. This study will result in an improved understanding of kinetics of PAH formation in plasma pyrolysis and can pave the way for more advanced mechanistic studies (e.g., soot nucleation mechanisms). Additionally, the findings will be useful for establishing practical strategies for increasing the pyrolysis efficiency and producing high-grade carbon for synthesis of nanomaterials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Uncertainty Quantification and Error Propagation in the Enthalpy and Entropy of Surface Reactions Arising from a Single DFT Functional

Accounting for parametric uncertainty in models is essential for quantifying the models’ predictive ability. Recently, approaches have been introduced to estimate parametric uncertainty in kinetic models while accounting for correlations among energy parameters. However, correlations have been estimated indirectly and correlations in entropies have not been accounted for. For surface-catalyzed microkinetic models of >C2 (more than two carbon-containing) molecules, which consist of thousands of reaction steps and intermediate surface species, first-principles density functional theory (DFT) is costly, and thus, estimation of thermochemistry and reaction barriers requires surrogate methods of DFT, such as group additivity and Brønsted–Evans–Polanyi relationships, respectively. For such parametrization, model uncertainty is unclear. This work develops a framework to overcome these gaps using group additivity and a single DFT functional. We estimate correlations in parameters of kinetic models and quantify uncertainty for thermochemistry, reaction barriers, reaction paths, and ultimately reaction rates, accounting also for the contribution of entropic uncertainty. Furthermore, the approach is illustrated on propane combustion and ethane oxidative dehydrogenation reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Comprehensive uncertainty quantification (UQ) for full engineering models by solving probability density function (PDF) equation

This report details a new method for propagating parameter uncertainty (forward uncertainty quantification) in partial differential equations (PDE) based computational mechanics applications. The method provides full-field quantities of interest by solving for the joint probability density function (PDF) equations which are implied by the PDEs with uncertain parameters. Full-field uncertainty quantification enables the design of complex systems where quantities of interest, such as failure points, are not known apriori. The method, motivated by the well-known probability density function (PDF) propagation method of turbulence modeling, uses an ensemble of solutions to provide the joint PDF of desired quantities at every point in the domain. A small subset of the ensemble is computed exactly, and the remainder of the samples are computed with approximation of the driving (dynamics) term of the PDEs based on those exact solutions. Although the proposed method has commonalities with traditional interpolatory stochastic collocation methods applied directly to quantities of interest, it is distinct and exploits the parameter dependence and smoothness of the dynamics term of the governing PDEs. The efficacy of the method is demonstrated by applying it to two target problems: solid mechanics explicit dynamics with uncertain material model parameters, and reacting hypersonic fluid mechanics with uncertain chemical kinetic rate parameters. A minimally invasive implementation of the method for representative codes SPARC (reacting hypersonics) and NimbleSM (finite- element solid mechanics) and associated software details are described. For solid mechanics demonstration problems the method shows order of magnitudes improvement in accuracy over traditional stochastic collocation. For the reacting hypersonics problem, the method is implemented as a streamline integration and results show very good accuracy for the approximate sample solutions of re-entry flow past the Apollo capsule geometry at Mach 30.

42 ENGINEERING↗
DOE OSTI2021

Kinetic and temperature sensitivity properties of soil exoenzymes through the soil profile down to one-meter depth at a temperate coniferous forest (Blodgett, CA)

This dataset contains data on kinetic and temperature sensitivity parameters of the exoenzymes β-glucosidase (BG), leucine/leucyl aminopeptidase (LAP) and acid phosphatase (AP) across a soil profile down to 90 cm depth at Blodgett forest, CA, USA. These data were generated to determine if kinetic and thermal properties of microbial exoenzymes involved in organic matter decomposition varied with soil depth, following variation in soil properties and microbial communities, as part of the study: Alves et al. (2021). Kinetic Properties of Microbial Exoenzymes Vary with Soil Depth but Have Similar Temperature Sensitivities Through the Soil Profile. Frontiers in Microbiology 12:3618. https://doi.org/10.3389/fmicb.2021.735282. This research was performed within the framework of the TES Belowground Biogeochemistry SFA project, in particular association with a long-term field warming experiment of the whole soil profile at Blodgett forest. Samples for this work were collected from locations representative of the field experimental plots. Potential enzyme activity rates were measured using laboratory fluorometric assays with soils collected at 0-10, 10-20, 30-40, 50-60, 60-70 and 80-90 cm deep in biological triplicates (i.e., three soil cores collected at different representative locations). Assays with each soil were conducted over a gradient of eight substrate concentrations per enzyme, and incubated at 4, 10, 16, 25, 35 or 50°C. Enzyme Michaelis-Menten kinetics were modeled over the eight substrate concentrations at each temperature, and the temperature sensitivity of the kinetic parameters was modeled over the six temperatures using linear Arrhenius/Q10 and non-linear Macromolecular Rate Theory (MMRT) models. The dataset includes the fully processed enzyme activity rate data used to model Michaelis-Menten kinetics, calculated kinetic and temperature sensitivity parameters, and basic soil and microbial biomass chemistry for each sample. All data is provided for each individual biological replicate, and kinetic and temperature sensitivity parameters are also provided as means of the biological replicates. The dataset also includes all raw measurement data and code used to parse, combine and perform the analyses described by Alves et al. (2021). For file descriptions, see the file-level metadata files: “enzymes_dataProcessed_flmd.xlsx” (processed data); “enzymes_dataRaw_flmd.xlsx” (compressed raw data and metadata); and “enzymes_code_flmd.xlsx” (compressed code). The experimental design, list of parameters measured, soil and microbial biomass chemistry data, and means of biological replicates for kinetic and temperature sensitivity parameters are also provided as human-readable tables in file “enzymeTraits_design_results_tables.xlsx”.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Biomass char gasification kinetic rates compared to data, including ash effects

This investigation provides both experimental and theoretical analyses of biomass char gasification kinetics over 1150–1350 °C in the environment of CO 2 , H 2 O and combinations of these reactants. The experimental data include continuous measurements of particle mass, external and internal temperatures, shape, and size with periodic but not continuous measurements of char porosity, pore size distribution, and pore surface area. The model describes heterogeneous char gasification for poplar wood, corn stover and switchgrass in different shapes and industrially relevant sizes (12.5 mm and smaller). Nonlinear least-squares regression produces optimized power-law model parameters for global kinetics that describe biomass char gasification with respect to both CO 2 and H 2 O separately and in combination. A single set of kinetic parameters describes reaction rates for all three fuels. Model simulations agree with measured data at all stages of char conversion even though the observed mass loss rates change significantly with conversion. In conclusion, the change in rate with conversion depends strongly on ash content, and this investigation provides a simple and theoretically based reaction rate expression that includes the effect of inert ash occupying an increasing portion of the reactive surface with increased conversion.

09 BIOMASS FUELS↗
NASA NTRS2000

Mechanisms for the Crystallization of ZBLAN

A number of research teams have observed that glass forming melts that are solidified in low-g exhibit enhanced glass formation. This project will examine one of these glasses, the heavy metal fluoride glass ZBLAN. A four year ground based research program has been approved to examine the crystallization of ZBLAN glasses with the purpose of testing a theory for the crystallization of ZBLAN glass. The theory could explain the general observations of enhanced glass formation of other glasses melted and solidified in low-g. Fluid flow in 1-g results from buoyancy forces and surface tension driven convection. This fluid flow can introduce shear in undercooled liquids in 1-g. In low-g it is known that fluid flows are greatly reduced so that the shear rate in fluids in low-g are extremely low. It is believed that fluids may have some weak structure in the absence of flow. Even very small shear rates could cause this structure to collapse in response to the shear. A general result would be shear thinning of the fluid. The hypothesis of this research is that: Shear thinning in undercooled liquids increases the rate of nucleation and crystallization of glass forming melts. Shear of the melt can be reduced in low-g enhancing undercooling and glass formation. Samples will be melted and quenched in 1-g under quiescent conditions at a number of controlled cooling rates to determine times and temperatures of crystallization and heated at controlled heating rates to determine kinetic crystallization parameters. Experiments will also be performed on the materials while under controlled vibration conditions and compared with the quiescent experiments in order to evaluate the effect of shear in the liquid on crystallization kinetics. After the experimental parameters are well known, experiments will be repeated under low-g (and 2-g) conditions on the KC-135 aircraft during low-g parabolic maneuvers. The results will determine the effects of shear on crystallization. Our experimental setups will be designed with low-g experiments in mind and will be tested as breadboard low-g experiments. It is very likely that the thermal analysis instrumentation can be adapted to be run in the microgravity glovebox facilities. Critical space experiments may result to test the theory at longer low-g time experiments in space.

Ethridge, Edwin C.↗
DOE OSTI2023

Parameter Identification for Battery Abuse Reaction Kinetics Models Using DSC Analysis [SWR-23-87]

This code estimates the parameters as inputs for NREL’s abuse reaction kinetics model using Differential scanning calorimetry (DSC) experimental data. The parameters for calculating the rates of abuse reactions among battery cell components at elevated temperatures include frequency factor, activation energy, and reaction orders. The least-squared method is employed to fit the reaction model to DSC data. The code is implemented in MATLAB.

Yang, Chuanbo↗
DOE OSTI2021

Effect of operating parameters on H 2 /CO 2 conversion to methanol over Cu-Zn oxide supported on ZrO 2 polymorph catalysts: Characterization and kinetics

Kinetic aspects of the operating parameters for the catalytic conversion of H 2 /CO 2 to methanol over two novel catalysts were evaluated to understand the effect of the polymorphic ZrO 2 phase composed of Cu 0/+ -ZnO sites at the atomic level and its impact on the reaction mechanism. The catalysts were characterized by in situ and ex-situ XRD, N 2 adsorption/desorption isotherms, FRX, TPR, TPD-N 2 O, in situ XANES, TPD-CO 2 , and in situ DRIFTS techniques. The influence of different reaction variables such as the GHSV, temperature, pressure, and H 2 /CO 2 ratio were studied using a fixed bed continuous plug flow reactor. The Cu-ZnO catalyst supported on the tetragonal zirconia polymorph exhibited the highest methanol yield due to the lower activation energy when compared to the catalyst with a greater amount of the monoclinic phase. In addition, the catalysts were reused for 8 cycles of 6 hours to evaluate their stability, which can translate into lower costs for large-scale methanol production. As a result, the estimation of the kinetic parameters over Cu-Zn oxide supported on ZrO 2 polymorphs was significant for understanding the reaction mechanism, as well as to provide a pathway for scaling-up of the process.

36 MATERIALS SCIENCE↗
NASA NTRS1974

Microbial metabolism and dynamic changes in the electrical conductivity of soil solutions - A method for detecting extraterrestrial life

Experiments are reported which show that measuring metabolic activity in soil solutions by means of dynamic changes in electrical conductivity, water-soluble Ca, or water-soluble Mg is a feasible life detection method. The addition of 0.5% glucose solutions to 12 different air-dried soils always resulted in increases in all three of these parameters. The kinetics and magnitude of these changes for at least two and usually all three of the parameters over a 14-day period were clearly distinguishable from the changes in heat-sterilized controls or unsterilized controls without added glucose. In general, maximal values were achieved more rapidly under aerobic than under anaerobic incubation.

Silverman, M. P.↗
DOE OSTI2025

Role of the Mobile Active Site Flap in IMP Dehydrogenase Inhibitor Binding

Inosine 5′-monophosphate dehydrogenase (IMPDH) is a promising antibiotic target. This enzyme catalyzes the NAD-dependent oxidation of inosine 5′-monophosphate (IMP) to xanthosine 5′-monophosphate (XMP), which is the rate-limiting step in guanine nucleotide biosynthesis. Bacterial IMPDH-specific inhibitors have been developed that bind to the NAD + site. These inhibitors display varied affinities to different bacterial IMPDHs that are not easily rationalized by X-ray crystal structures of enzyme–inhibitor complexes. Inspection of X-ray crystal structures of 25 enzyme–inhibitor complexes, including 10 newly described, suggested that a mobile active site flap may be a structural determinant of inhibitor potency. Saturation transfer difference NMR experiments also suggested that the flap may contact the inhibitors to varying extents in different IMPDHs. Flap residue Leu413 contacted some inhibitors but was not structured in the crystal structures of other inhibitor complexes. The substitution of Leu413 with Phe or Ala in Bacillus anthracis IMPDH had inhibitor-selective effects, suggesting residue 413 could be a structural determinant of affinity. Curiously, the Ala substitution increased the potency of most inhibitors, even those that contacted Leu413 in the crystal structures. Presteady-state and steady-state kinetics experiments showed that the Leu413Ala substitution had comparable effects on inhibitor binding to the noncovalent E·IMP complex and the covalent intermediate E-XMP*, suggesting that the flap had similar interactions in both complexes. These results demonstrate that contacts do not necessarily indicate favorable interactions, and poorly structured mobile regions should not be discounted when assessing binding determinants.

Conformation↗
DOE OSTI2025

Toward a Unified Kinetic Model of Nitrogenase Catalysis

The microbial enzyme nitrogenase catalyzes the MgATP-dependent reduction of N 2 to 2NH 3 , a transformation central to the global nitrogen cycle. While the canonical Thorneley−Lowe (TL) kinetic model has long served as a mechanistic framework, it does not incorporate several recent insights. Here, we present an updated kinetic model for Monitrogenase that incorporates these new findings. A significant insight is that electron transfer (ET) from the reduced Fe protein to the FeMo-cofactor is gated by MgATP-dependent conformational transitions and can be described as a probabilistic event that is dependent on the ligand bound to the active-site metallocofactor. The updated kinetic model quantitatively reproduces steady-state product formation rates across a broad range of experimental conditions, yielding revised estimates for key rate constants. It is demonstrated that under N 2 turnover, the probability of productive ET to the active site decreases by ∼60%, resulting in a significant fraction of Fe protein cycles that are unproductive for electron delivery. This mechanistic feature explains the observed rate limitation in N 2 reduction and implies a revised minimum energetic cost of approximately 25 MgATP per N 2 reduced. Integrating these new features into the revised kinetic model provides a more complete and usable foundation for understanding nitrogenase catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Energy-angle distribution of the ions in the RF sheath of ICRH antennas

Radio-frequency sheaths forming at the surface of ion cyclotron resonance heating (ICRH) actuators in fusion experiments are associated with enhanced impurity sputtering from ICRH plasma-facing components (PFCs). The minimization of impurity fluxes from the ICRH PFC is a vital task for the usage of ICRH systems. Capturing the ion kinetics is important for an accurate description of plasma–material interactions, because the ion dynamics plays a crucial role in RF sheaths. Here, we present a hybrid particle-in-cell (hPIC) model able to capture the kinetic behavior of the ions. We analyze the kinetic ion energy-angle distributions (IEADs) impacting the RF antenna and its dependence on different plasma and RF sheath parameters. In particular, the IEAD dependence on RF frequency and magnetic field alignment is investigated. Using hPIC, we simulated a case emulating the latest experimental campaign from JET. The simulation showed that under specific plasma and RF parameters, the kinetic motion of ions results in a cusp formation in the IEAD.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

H 2 Evolution at an Electrochemical “Underpotential” with an Iridium-Based Molecular Photoelectrocatalyst

Molecular platforms capable of both photochemical H 2 evolution and electrochemical catalyst regeneration hold promise for the efficient generation of solar fuels. Systems studied to date require a significant electrochemical overpotential (η), so no photon energy is being chemically stored. A detailed study of the parameters that govern the electrochemical overpotential of molecular photoelectrocatalysts is presented. By understanding how tuning the solvent, catalyst structure, and acid pK a affect the kinetics and thermodynamics of the potential- and light-driven H 2 evolution reaction, conditions were identified wherein the solvento complex [Cp*Ir(bpy)(NCCH 3 )][PF 6 ] 2 (Cp* is pentamethylcyclopentadienyl; bpy is 2,2'-bipyridine) mediates photoelectrocatalytic H 2 formation at an electrochemical “underpotential” (η < 0) driven by visible light. Under 460 nm illumination and in the presence of the weak organic acid H-PhTMG + (2-phenyl-1,1,3,3- tetramethylguanidinium), the catalyst facilitates H 2 evolution with Faradaic efficiencies up to 90% and overpotentials as low as –90 mV. As a result, mechanistic studies enabled the construction of graphical “maps” that can guide the choice of catalyst and conditions to minimize overpotential, applicable to both photoelectrocatalysts and dark electrocatalysts.

14 SOLAR ENERGY↗
DOE OSTI2022

Development of a Flotation Simulator That Can Predict Grade vs. Recovery Curves from Mineral Liberation Data

Flotation is a kinetic process designed to separate mineral fines by control of hydrophobicity. In general, both the recovery and selectivity of a flotation process increase with contact angle. It is difficult, however, to model flotation kinetics using the thermodynamic parameter. In the present work, we consider flotation as heterocoagulation so that the bubble-particle interactions occurring in the pulp phase of a flotation cell can be modeled using the hydrophobic force as a kinetic parameter that can represent the role of contact angles in flotation. Here, the pulp-phase model developed in this manner has been combined with a froth-phase model developed earlier by considering the effect of particles in film thinning kinetics and bubble coarsening (Park et al, 2018). The combined model has been used to develop a flotation simulator that can be used to construct grade vs. recovery curves from feed characteristics (e.g., mineral liberation and particle size) and various operating parameters. The simulator has been tested successfully against a set of bench-scale continuous flotation test results reported in the literature (dos Santos and Galery, 2018).

58 GEOSCIENCES↗
DOE OSTI2024

Wire directed energy deposition of steel-aluminum structures using cold metal transfer process

In this study, a sharp transition from 316L stainless steel to 4043 aluminum alloy was fabricated using wire directed energy deposition (DED) via the cold metal transfer (CMT) process. The CMT process with its inherently low heat input, led to a significant reduction in intermetallic thickness at the bi-metallic interface compared to blown powder DED technique reported in the literature resulting in superior properties when compared to those of dissimilar steel-aluminum welds. Thermo-kinetic modeling confirmed that the intermetallic formation is through a classical nucleation and growth mechanism, and the fraction and thickness can be controlled by adjusting CMT process parameters to kinetically arrest or minimize the intermetallic formation. These findings underscore the efficacy of CMT-based wire DED for fabrication of steel-aluminum bi-metallic structures.

36 MATERIALS SCIENCE↗