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At least 523 records · Page 29

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DOE OSTI2024

Avalanche statistics of fluctuation-induced fluxes from the SLPM and the W7-AS stellarator

Measurements of fluctuating floating potentials and ion saturation currents at different radial locations in the Santander Linear Plasma Machine (Castellanos et al 2005 Plasma Phys. Control. Fusion47 2067) and at the edge of the W7-AS stellarator by means of radially movable Langmuir probes allow to infer the corresponding fluctuation-induced radial flux temporal series. Avalanche-like transport events are identified in the time series and statistically characterized in terms of avalanche size/duration/quiet-time distributions and size-duration scaling relations. Transport is diffusive in the inner and intermediate radial region of the SLPM r < r tr ≈ 2.6 cm, undergoing a transition at r tr , becoming non-diffusive in the outermost region of the device, r > r tr . Here, the results obtained at the edge of the W7-AS stellarator are similar to those found in SLPM for r > r tr , i.e. consistent with what would be expected for scale-free, self-similar plasma transport dynamics near a critical state.

Avalanches↗

DOE OSTI2025

Integrated modeling of RF-induced tungsten erosion at ICRH antenna structures in the WEST tokamak *

This paper introduces STRIPE (Simulated Transport of RF Impurity Production and Emission), an advanced modeling framework developed to analyze material erosion and the global transport of eroded impurities originating from radio-frequency (RF) antenna structures in magnetic confinement fusion devices. STRIPE integrates multiple physics modules: SolEdge3x for scrape-off-layer plasma profiles, COMSOL for 3D RF rectified sheath potentials, RustBCA for erosion yields and surface interactions, and global impurity transport for 3D ion energy-angle distributions and impurity transport. The framework is applied to an ion cyclotron RF-heated L-mode discharge (#57877) in the WEST tokamak, where it predicts a thirty-fold increase in gross tungsten erosion at antenna limiters during the transition from ohmic to ICRH operation. Additionally, under ICRH conditions, a tenfold enhancement in erosion is observed when comparing RF sheath effects to purely thermal sheath conditions. High-charge-state oxygen ions ($\mathrm{O}$ 6+ and above) are identified as the dominant contributors to tungsten sputtering. To validate the model, a synthetic diagnostic tool based on inverse photon efficiency (S/XB coefficients) from the ColRadPy collisional-radiative model enables direct comparison with spectroscopic measurements. Model predictions using a plasma composition of 1% oxygen and 99% deuterium show good agreement with observed W − I (400.9 nm) emission for discharge #57877, supporting the accuracy of the STRIPE framework. This study focuses specifically on gross erosion calculations to demonstrate STRIPE’s capabilities. Future extensions of this work will incorporate net erosion, re-deposition, self-sputtering effects, and whole-device modeling of sputtered tungsten impurity transport. STRIPE is also being applied to other RF-heated linear and toroidal devices, offering valuable insights for antenna design, impurity control, and performance optimization in next-generation fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Prediction of transport in the JET DTE2 discharges with TGLF and NEO models using the TGYRO transport code

Abstract The JET Deuterium-Tritium-Experiment Campaign 2 (DTE2) has demonstrated the highest-ever fusion energy production. To forecast the transport dynamics within these discharges, the TGLF and NEO models within the TGYRO transport code were employed. A critical development in this study is the new quasilinear transport model, TGLF-SAT2, specifically designed to resolve discrepancies identified in JET deuterium discharges. This model accurately describes the saturated three-dimensional (3D) fluctuation spectrum, aligning closely with a database of nonlinear CGYRO turbulence simulations, thereby enhancing the predictive accuracy of TGYRO simulations. In validating against the JET DTE2 discharges across two primary operating scenarios, TGYRO effectively predicted the temperature profiles within a broad radial window ( ρ ∼ 0.2–0.85), though with minor ion temperature discrepancies near the core. However, a consistent underprediction of electron density profiles by 20% across the simulation domain was noted, indicating areas for future refinement. To achieve a self-consistent steady-state solution based on the JET DTE2 discharges, an integrated modeling workflow TGYRO-STEP within the OMFIT framework was introduced. This workflow iterates among the core transport, the pedestal pressure and the MHD equilibrium, ultimately yielding a converged solution that significantly reduces dependence on experimental boundary conditions for temperature and density profiles. The integrated simulation results show negligible differences in electron density and temperature profiles compared to standalone TGYRO modeling, while the ion temperature profile is lower due to the updated boundary condition in TGYRO-STEP. The application of the TGYRO-STEP workflow to JET DTE2 discharges serves as a crucial test to validate its robustness and highlights its limitations, providing valuable insights for its potential future application in ITER and Fusion Power Plant deuterium and tritium prediction modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Surfactant-Specific AI-Driven Molecular Design: Integrating Generative Models, Predictive Modeling, and Reinforcement Learning for Tailored Surfactant Synthesis

Molecular design is a critical aspect of various scientific and industrial fields, where the properties of molecules hold significant importance. In this study, a 3-fold methodology design is presented that leverages the power of generative artificial intelligence (AI), predictive modeling, and reinforcement learning to create tailored molecules with desired properties. This model synergistically combines deep learning techniques with Self-Referencing Embedded Strings (SELFIES) molecular representation to build a generative model that generates valid molecules and a graphical neural network model that accurately forecasts molecular properties. The Variational Autoencoder (VAE) coupled with reinforcement learning helps refine molecule generation based on targeted attributes. Data from an experimental study involving surfactants were used to test the framework. A validation of the structural integrity of the molecules generated was conducted, and Tanimoto similarities were used to quantify the similarity and diversity between the original and generated molecular structures. Also, saliency maps for the generated surfactants were produced to identify the features explaining the property values. Lastly, molecular dynamics simulations were used to validate the stability of the generated molecules. The results showed that the proposed framework can effectively produce valid molecules within the set property threshold value.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Decagonal Sn clathrate on d-Al-Ni-Co

Decagonal quasiperiodic ordering of Sn thin films on d-Al-Ni-Co is shown based on scanning tunneling microscopy (STM), low-energy electron diffraction, and density functional theory (DFT). Interestingly, the decagonal structural correlations are partially retained even up to a large film thickness of 10 nm grown at 165±10K. The nucleation centers called “Sn white flowers” identified by STM at submonolayer thickness are recognized as valid patches of the decagonal clathrate structure with low adsorption energies of these motifs. Due to the excellent lattice matching (to within 1%) between columns of Sn dodecahedra in the clathrate structure and pentagonal motifs at the d-Al-Ni-Co surface, the interfacial energy favors clathrate over the competing Sn crystalline forms. DFT study of the Sn/Al-Ni-Co composite model shows good mechanical stability, as shown by the work of separation of Sn from Al-Ni-Co slab that is comparable to the clathrate self-separation energy. Finally, the relaxed surface terminations of the R 2 T 4 clathrate approximant are in self-similarity correspondence with the motifs observed in the STM images from monolayer to the thickest Sn film.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

On the statistical theory of self-gravitating collisionless dark matter flow: Scale and redshift variation of velocity and density distributions

The statistics of velocity and density fields are crucial for cosmic structure formation and evolution. Here, this paper extends our previous work on the two-point second-order statistics for the velocity field [Phys. Fluids 35, 077105 (2023)] to one-point probability distributions for both density and velocity fields. The scale and redshift variation of density and velocity distributions are studied by a halo-based non-projection approach. First, all particles are divided into halo and out-of-halo particles so that the redshift variation can be studied via generalized kurtosis of distributions for halo and out-of-halo particles, respectively. Second, without projecting particle fields onto a structured grid, the scale variation is analyzed by identifying all particle pairs on different scales $r$. We demonstrate that: (i) Delaunay tessellation can be used to reconstruct the density field. The density correlation, spectrum, and dispersion functions were obtained, modeled, and compared with the N-body simulation; (ii) the velocity distributions are symmetric on both small and large scales and are non-symmetric with a negative skewness on intermediate scales due to the inverse energy cascade on small scales with a constant rate $\varepsilon_u$; (iii) On small scales, the even order moments of pairwise velocity $\Delta u_L$ follow a two-thirds law $\propto{(-\varepsilon_ur)}^{2/3}$, while the odd order moments follow a linear scaling $\langle(\Delta u_L)^{2n+1}\rangle=(2n+1)\langle(\Delta u_L)^{2n}\rangle\langle\Delta u_L\rangle\propto{r}$; (iv) The scale variation of the velocity distributions was studied for longitudinal velocities $u_L$ or $u_L^{'}$, pairwise velocity (velocity difference) $\Delta u_L$=$u_L^{'}$-$u_L$ and velocity sum $\Sigma u_L$=$u^{'}_L$+$u_L$. Fully developed velocity fields are never Gaussian on any scale, despite that they can initially be Gaussian; (v) On small scales, $u_L$ and $\Sigma u_L$ can be modeled by a $X$ distribution to maximize the entropy of the system. The distribution of $\Delta u_L$ can be different; (vi) On large scales, $\Delta u_L$ and $\Sigma u_L$ can be modeled by a logistic or a $X$ distribution, while $u_L$ has a different distribution; (vii) the redshift variation of the velocity distributions follows the evolution of the $X$ distribution involving a shape parameter $\alpha(z)$ decreasing with time.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Exhibit D Scope of Work and Technical Specifications MOX Rod Reduction

PROJECT/PROGRAM GOALS AND OBJECTIVES: The Los Alamos National Laboratory (LANL), here after referred to as the CONTRACTOR, plans to provide NQA-1 service and support for the disposition of PF-4 basement inventory of Areva fuel rods. These fuel rods need to be reduced in length for proper shipping and disposition. The objective of this acquisition is to enter into an agreement with a SUBCONTRACTOR that shall provide expertise, materials, input for procurement of specialized tooling to be identified, and mockups for size reduction and FS65 disposition. Handling and size reduction of the Areva rods would take place at LANL. Physical work at LANL will be performed by the CONTRACTOR’s field execution team, portions of this work will have expertise provided by the SUBCONTRACTOR. As cited below via an add alternative and supplemental site visit(s) to LANL the CONTRACTOR may request the SUBCONTRACTOR to ship the necessary transportation, handling and packaging equipment at the SUBCONTRACTOR’s location to the CONTRACTOR’s facility for size reduction activities at LANL by the CONTRACTOR’s self-perform field execution team. In addition, the SUBCONTRACTOR shall provide subject matter expertise to CONTRACTOR personnel cutting the mockup Areva Fuel Rod at LANL as a rehearsal prior to CONTRACTOR cutting the actual MOX Fuel Rod if this add alternative is exercised.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

3D simulations of spinlike flames in Co/Al multilayers with enhanced conduction losses

Reactive Co/Al multilayers are uniformly structured materials that may be ignited to produce rapid and localized heating. Prior studies varying the bilayer thickness (i.e., sum of two individual layers of Co and Al) have revealed different types of flame morphologies, including: (a) steady/planar, (b) wavy/periodic, and (c) transverse bands, originating in the flame front. These instabilities resemble the “spin waves” first observed in the early studies of solid combustion (i.e., Ti cylinder in a N 2 atmosphere), and are likewise thought to be due to the balance of heat released by reaction and heat conduction forward into the unreacted multilayer. However, the multilayer geometry and three-dimensional (3D) edge effects are relatively unexplored. In this work, a new diffusion-limited reaction model for Co/Al multilayers was implemented in large, novel 3D finite element analysis (FEA) simulations, in order to study the origins of these spinlike flames. This reaction model builds upon previous work by introducing three new phase-dependent property models for: (1) the diffusion coefficient, (2) anisotropic thermal conductivity tensor, and (3) bulk heat capacity, as well as one additional model for the bilayer-dependent heat of reaction. These novel 3D simulations are the first to predict both steady and unsteady flames in Co/Al multilayers. Moreover, two unsteady modes of flame propagation are identified, which depend on the enhanced conduction losses with slower flames, as well as flame propagation around notched edges. Finally, future work will consider the generality of the current modeling approach and also seek to define a more generalized set of stability criteria for additional multilayer systems.

42 ENGINEERING↗

DOE OSTI2025

New Era Towards Autonomous Additive Manufacturing: A Review of Recent Trends and Future Perspectives

Abstract The Additive Manufacturing (AM) landscape has significantly transformed in alignment with Industry 4.0 principles, primarily driven by the integration of Artificial Intelligence (AI) and Digital Twin (DT). However, current Intelligent Additive Manufacturing (IAM) systems face limitations such as fragmented AI tool usage and suboptimal human-machine interaction (HMI). This paper reviews existing IAM solutions, emphasizing control, monitoring, process autonomy, and end-to-end integration, and identifies key limitations, such as the absence of a high-level controller for global decision-making. To address these gaps, we propose a transition from IAM to Autonomous Additive Manufacturing (AAM), featuring a hierarchical framework with four integrated layers: knowledge, generative solution, operational, and cognitive. In the cognitive layer, AI agents notably enable machines to independently observe, analyze, plan, and execute operations that traditionally require human intervention. These capabilities streamline production processes and expand the possibilities for innovation, particularly in sectors like in-space manufacturing (ISM). Additionally, this paper discusses the role of AI in self-optimization and lifelong learning, positing that the future of AM will be characterized by a symbiotic relationship between human expertise and advanced autonomy, fostering a more adaptive, resilient manufacturing ecosystem.

Fan, Haolin↗

DOE OSTI2022

Colossal phonon drag enhanced thermopower in lightly doped diamond

Diamond is one of the most studied materials because of its unique combination of remarkable electrical, mechanical, thermal and optical properties. Using a fully self-consistent ab initio theory of coupled electron-phonon transport, we reveal another striking behavior: a huge drag enhancement of the thermopower of lightly doped diamond. Thermopower values of around 100,000 μV K –1 are found at 100 K, significantly exceeding the highest previously measured value in the correlated metal FeSb 2 , and occurring at much higher temperatures. The enormous thermopower in diamond arises primarily from exceptionally weak anharmonic phonon decay around and below 100 K that facilitates efficient momentum exchange between charge carriers and phonons through electron-phonon interactions. Exceedingly large thermoelectric power factors are also identified. Furthermore, this work gives insights into the physics of the coupled electron-phonon system in solids and advances our understanding of thermoelectric transport in the regime of strong drag.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Balancing growth amidst salt stress – lifestyle perspectives from the extremophyte model Schrenkiella parvula

Schrenkiella parvula, a leading extremophyte model in Brassicaceae, can grow and complete its lifecycle under multiple environmental stresses, including high salinity. Yet, the key physiological and structural traits underlying its stress-adapted lifestyle are unknown along with trade-offs when surviving salt stress at the expense of growth and reproduction. We aimed to identify the influential adaptive trait responses that lead to stress-resilient and uncompromised growth across developmental stages when treated with salt at levels known to inhibit growth in Arabidopsis and most crops. Its resilient growth was promoted by traits that synergistically allowed primary root growth in seedlings, the expansion of xylem vessels across the root-shoot continuum, and a high capacity to maintain tissue water levels by developing thicker succulent leaves while enabling photosynthesis during salt stress. A successful transition from vegetative to reproductive phase was initiated by salt-induced early flowering, resulting in viable seeds. Self-fertilization in salt-induced early flowering was dependent upon filament elongation in flowers otherwise aborted in the absence of salt during comparable plant ages. Furthermore, the maintenance of leaf water status promoting growth, and early flowering to ensure reproductive success in a changing environment, were among the most influential traits that contributed to the extremophytic lifestyle of S. parvula.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Uranium Bed Design Parameters for Tritium Plants Supporting Fusion Reactors

Uranium hydride is commonly used to store hydrogen or its isotopes in a solid state. The Self-Assaying Tritium Accountancy and Containment Unit for ITER (STACI) is a 5.2-kg bed of depleted uranium (dU) capable of holding up to 33 mol of hydrogen or its isotopes. Here we summarize the data analysis of past experimental campaigns with STACI, with the aim of describing the kinetics and thermodynamics of the hydriding process. Computed tomography imaging was performed on STACI both before and after its experimental campaign, and a high degree of swelling was observed in the dU. Literature on studies in regard to the swelling of large (multikilogram) quantities of uranium hydride for storage applications was not identified during this study. Data from the experimental campaign, as well as data on the formation reaction, are presented. The authors hope to create an analytical model of STACI based on these data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Stand and environmental conditions drive functional shifts associated with mesophication in eastern US forests

There is a growing body of evidence that mesic tree species are increasing in importance across much of the eastern US. This increase is often observed in tandem with a decrease in the abundance and importance of species considered to be better adapted to disturbance and drier conditions (e.g., Quercus species). Concern over this transition is related to several factors, including the potential that this transition is self-reinforcing (termed “mesophication”), will result in decreased resiliency of forests to a variety of disturbances, and may negatively impact ecosystem functioning, timber value, and wildlife habitat. Evidence for shifts in composition provide broad-scale support for mesophication, but we lack information on the fine-scale factors that drive the associated functional changes. Understanding this variability is particularly important as managers work to develop site-and condition-specific management practices to target stands or portions of the landscape where this transition is occurring or is likely to occur in the future. To address this knowledge gap and identify forests that are most susceptible to mesophication (which we evaluate as a functional shift to less drought or fire tolerant, or more shade tolerant, forests), we used data from the USDA Forest Service Forest Inventory and Analysis program to determine what fine-scale factors impact the rate (change through time) and degree (difference between the overstory and midstory) of change in eastern US forests. We found that mesophication varies along stand and environmental gradients, but this relationship depended on the functional trait examined. For example, shade and drought tolerance suggest mesophication is greatest at sites with more acidic soils, while fire tolerance suggests mesophication increases with soil pH. Mesophication was also generally more pronounced in older stands, stands with more variable diameters, and in wetter sites, but plots categorized as “hydric” were often highly variable. Our results provide evidence that stand-scale conditions impact current and potential future changes in trait conditions and composition across eastern US forests. We provide a starting point for managers looking to prioritize portions of the landscape most at risk and developing treatments to address the compositional and functional changes associated with mesophication.

Woodbridge, Margaret↗

DOE OSTI2022

Image transformers for classifying acute lymphoblastic leukemia

Cancer is the leading cause of death by disease in American children. Each year, nearly 16,000 children in the United States and over 300,000 children globally are diagnosed with cancer. Leukemia is a form of blood cancer that originates in the bone marrow and accounts for one-third of pediatric cancers. This disease occurs when the bone marrow contains 20% or more immature white blood cell blasts. Acute lymphoblastic leukemia is the most prevalent leukemia type found in children, with half of all annual cases in the U.S. diagnosed for subjects under 20 years of age. To diagnose acute lymphoblastic leukemia, pathologists often conduct a morphological bone marrow assessment. This assessment determines whether the immature white blood cell blasts in bone marrow display the correct morphological characteristics, such as size and appearance of nuclei. Pathologists also use immunophenotyping via multi-channel flow cytometry to test whether certain antigens are present on the surface of blast cells; the antigens are used to identify the cell lineage of acute lymphoblastic leukemia. These manual processes require well-trained personnel and medical professionals, thus being costly in time and expenses. Computerized decision support via machine learning can accelerate the diagnosis process and reduce the cost. Training a reliable classification model to distinguish between mature and immature white blood cells is essential to the decision support system. Here, we adopted the Vision Transformer model to classify white blood cells. The Vision Transformer achieved superb classification performance compared to state-of-the-art convolutional neural networks while requiring less computational resources for training. Additionally, the latent self-attention architecture provided attention maps for a given image, providing clues as to which portion(s) of the image were significant in decision-making. We applied the Vision Transformer model and a convolutional neural network model to an acute lymphoblastic leukemia classification dataset of 12,528 samples and achieved accuracies of 88.4% and 86.2%.

Cho, Priscilla↗

DOE OSTI2020

Tunable structural color of bottlebrush block copolymers through direct-write 3D printing from solution

Additive manufacturing of functional materials is limited by control of microstructure and assembly at the nanoscale. In this work, we integrate nonequilibrium self-assembly with direct-write three-dimensional (3D) printing to prepare bottlebrush block copolymer (BBCP) photonic crystals (PCs) with tunable structure color. After varying deposition conditions during printing of a single ink solution, peak reflected wavelength for BBCP PCs span a range of 403 to 626 nm (blue to red), corresponding to an estimated change in d-spacing of >70 nm (Bragg- Snell equation). Physical characterization confirms that these vivid optical effects are underpinned by tuning of lamellar domain spacing, which we attribute to modulation of polymer conformation. Using in situ optical microscopy and solvent-vapor annealing, we identify kinetic trapping of metastable microstructures during printing as the mechanism for domain size control. More generally, we present a robust processing scheme with potential for on-the-fly property tuning of a variety of functional materials.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Injection mechanisms in a III -nitride light-emitting diode as seen by self-emissive electron microscopy

Here, we report on the investigation of an electrically biased high efficiency green III-nitride light-emitting diode (LED) by electron emission microscopy (EEM) using a low-energy electron microscope (LEEM). The surface of the LED was activated to negative electron affinity via deposition of a submonolayer of Cs. With the illumination column of the LEEM turned off, upon electrical injection of the LED, we directly image the hot electrons generated by eeh Auger-Meitner nonradiative processes that diffuse through the top p-Ga N layer and emit out the surface of the biased LED. By determining the source of emitted electrons using complementary electron emission spectroscopy measurements, EEM allows us to effectively map the carrier density within the LED. Using EEM, we observed nonelectron emitting regions with a density of approximately 3 × 10 8 cm -2 , identified as V-shaped defects (V-defects). This is confirmed through the corresponding dark spots of panchromatic cathodoluminescence measurements of the same sample and by plan-view transmission electron microscopy. The absence of electron emission at the sidewall of the V-defects can be attributed to several factors, including reduced carrier density in the sidewall quantum wells due to carriers traveling fast through the semipolar sidewalls before being injected into the planar quantum wells, the reduced population of hot electrons surviving diffusion through the thicker p-GaN filling in the V-defect before emission onto vacuum, and a smaller Auger-Meitner coefficient for the low In content semipolar sidewall quantum wells. The stronger electron emission observed at the ridges of most V-defects compared to the planar quantum well regions indicates larger local injected carrier densities, confirming that V-defect sidewalls allow for strong lateral carrier injection when compared to the weaker vertical injection away from the V-defect as evidenced by the weaker electron emission intensity away from the V-defects.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Intrinsic even-odd thickness-driven anomalous Hall effect in epitaxial MnBi2⁢Te4 thin films

We demonstrate precise control of magnetism in MnBi2⁢Te4 thin films through careful synthesis by molecular beam epitaxy, achieving minimal defects and accurate layer thickness control. By optimizing Mn-Bi-Te ratios and growth temperatures, we minimize detrimental self-doping effects and accurately target integer-layer films. X-ray diffraction and reflectivity provide quantitative measures of film quality and thickness. When these macroscale probes of structure and thickness are integrated with magnetotransport measurements, a striking even-odd layer dependence of the anomalous Hall effect is revealed. Odd-layer films exhibit a large hysteresis up to the Néel temperature (∼25K), consistent with noncompensated antiferromagnetism, while even-layer films show minimal response, as expected for an antiferromagnet. The sign of the anomalous Hall effect exhibits a sign reversal for intrinsic magnetism versus magnetism associated with defects. This work identifies critical factors for inducing pure, noncompensated ferromagnetism and reveals the characteristics of the intrinsic anomalous Hall effect in MnBi2⁢Te4, which together is a step toward realizing the zero-field quantum anomalous Hall effect in topological materials.

Mallick, Deb [ORNL] (ORCID:000900005806411X)↗

DOE OSTI2023

Galvanic corrosion of AZ31B joined to dual-phase steel with and without Zn layer by ultrasonic and friction stir welding

Galvanic corrosion of AZ31B joined with bare or Zn-coated DP590 steel by ultrasonic spot welding or linear friction stir welding was quantitatively studied by pre-defining anode and cathode in the lap joint samples. Corrosion volume and depth from Mg anode surfaces exposed to 0.1 M sodium chloride solution was analyzed as functions of cathode surface type and welding method. Characterization of as-welded joints was performed to identify any microstructural feature of the bonding zone that could impact galvanic corrosion behavior. COMSOL modeling with modified user subroutine was conducted to simulate the progression of Mg corrosion in the same joint and electrode configurations used for the corrosion experiments. The experimental results indicated that Zn-coated cathode surface can reduce Mg galvanic corrosion significantly as galvanic polarization and cathodic current on Zn-coated surface remained relatively low for Mg in the weld joints. COMSOL modeling described the growth of Mg galvanic corrosion in a reasonable manner but showed limitation by underestimating the corrosion volume as it did not capture self-corrosion.

36 MATERIALS SCIENCE↗