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At least 793 records · Page 44

Measuring Shock Stage of ltokawa Regolith Grains by Electron Back-Scattered Diffraction and Synchrotron X-Ray Diffraction

We have been analyzing Itokawa samples in order to definitively establish the degree of shock experienced by the regolith of asteroid Itokawa, and to devise a bridge between shock determinations by standard light optical petrography, crystal structures as determined by electron and X-ray diffraction techniques. We are making measurements of olivine crystal structures and using these to elucidate critical regolith impact processes. We use electron back-scattered diffraction (EBSD) and synchrotron X-ray diffraction (SXRD). We are comparing the Itokawa samples to L and LL chondrite meteorites chosen to span the shock scale experienced by Itokawa, specifically Chainpur (LL3.4, Shock Stage 1), Semarkona (LL3.00, S2), Kilabo (LL6, S3), NWA100 (L6, S4) and Chelyabinsk (LL5, S4). In SXRD we measure the line broadening of olivine reflections as a measure of shock stage. In this presentation we concentrate on the EBSD work. We employed JSC's Supra 55 variable pressure FEG-SEM and Bruker EBSD system. We are not seeking actual strain values, but rather indirect strain-related measurements such as extent of intra-grain lattice rotation, and determining whether shock state "standards" (meteorite samples of accepted shock state, and appropriate small grain size) show strain measurements that may be statistically differentiated, using a sampling of particles (number and size range) typical of asteroid regoliths. Using our system we determined that a column pressure of 9 Pa and no C-coating on the sample was optimal. We varied camera exposure time and gain to optimize mapping performance, concluding that 320x240 pattern pixilation, frame averaging of 3, 15 kV, and low extractor voltage yielded an acceptable balance of hit rate (>90%), speed (11 fps) and map quality using an exposure time of 30 ms (gain 650). We found that there was no strong effect of step size on Grain Orientation Spread (GOS) and Grain Reference Orientation Deviation angle (GROD-a) distribution; there was some effect on grain average Kernel Average Misorientation (KAM) (reduced with smaller step size for the same grain), as expected. We monitored GOS, Maximum Orientation Spread (MOS) and GROD-a differences between whole olivine grains and sub-sampled areas, and found that there were significant differences between the whole grain dataset and subsets, as well as between subsets, likely due to sampling-related "noise". Also, in general (and logically) whole grains exhibit greater degrees of cumulative lattice rotation. Sampling size affects the apparent strain character of the grain, at least as measured by GOS, MOS and GROD-a. There were differences in the distribution frequencies of GOS and MOS between shock stages, and in plots of MOS and GOS vs. grain diameter. These results are generally consistent with those reported this year. However, it is unknown whether the differences between samples of different shock states exceeds the clustering of these values to the extent that shock stage determinations can still be made with confidence. We are investigating this by examination of meteorites with higher shock stage 4 to 5. Our research will improve our understanding of how small, primitive solar system bodies formed and evolved, and improve understanding of the processes that determine the history and future of habitability of environments on other solar system bodies. The results will directly enrich the ongoing asteroid and comet exploration missions by NASA and JAXA, and broaden our understanding of the origin and evolution of small bodies in the early solar system, and elucidate the nature of asteroid and comet regolith.

Zolensky, Michael↗

Advanced Modeling of Beam Physics and Performance Optimization for Nuclear Physics Colliders

High energy colliders provide a critical tool in nuclear physics study by probing the fundamental structure and dynamics of matter. To maximize the potential of scientific discovery in nuclear physics study, it is important to optimize the parameters of these colliders to attain the best performance. The performance of a collider is typically measured by its integrated luminosity of colliding beams since the probability of a new event is proportional to the integrated luminosity. However, the achievable luminosity is limited by the electromagnetic interactions (beam-beam effects) of two colliding beams at higher energy, and the interplay between the space-charge effects and the beam-beam effects at lower energy. To achieve the best performance of a collider means to attain the highest luminosity of the collider with optimized collider parameters. Optimizing the collider’s machine parameters is both computationally and experimentally expensive. A fast and robust computational framework including beam-beam and space-charge effects will be critical to attaining the best performance of the collider. In this project, we will study the beam dynamics challenges, specifically the interplay of the space-charge and the beam-beam effects, and the machine tuning models for maximizing the performance of RHIC experiments. We will develop an advanced modeling framework based on first-principles physical simulations, lattice models and the state-of-the-art machine learning methods and apply this framework to performance improvement of the RHIC in operation. We will build data manipulation packages to connect the simulation data and the experimental data with the framework, develop a self-consistent hybrid model of space-charge and beam-beam effects, study underlying physics mechanisms, build surrogate models using the labeled data, integrate the models into the advanced modeling framework, and apply the framework to RHIC luminosity (STAR and sPHENIX) optimization. The success of this project would substantially improve the performance of existing and future colliders and increase the opportunity for scientific discovery.

43 PARTICLE ACCELERATORS↗

Understanding Structural and Compositional Evolution during NMC Cathode Direct Recycling via Solid-State NMR

Recycling end-of-life lithium-ion batteries (LIBs) to recover high-value cathode materials such as LiNixMnyCozO2 (NMC) is driven by economical, geopolitical, and sustainability needs. There has been recent interest in direct recycling methods to improve efficiency and recovery of materials, including ionothermal, hydothermal, solid-state, or redox mediator methods. In conjunction with recycling process development, detailed structural characterization is necessary in order to understand the mechanisms and efficacy of cathode recycling steps. Solid-state nuclear magnetic resonance (NMR) spectroscopy is a unique tool that can probe Li coordination, bulk and surface environments, and transition metal ordering in recycled and upcycled NMC cathodes. Here, 6,7Li, 1H, and 19F NMR spectroscopy to probe structural and compositional changes as well as surface impurities that may form during each step in NMC direct recycling is utilized. During relithiation, Li reinsertion into the NMC lattice is observed. During upcycling, where the goal is to increase the Ni content in the NMC, incorporation of Ni-rich phases into the bulk Li environment is observed. Surface impurities formed during processing were also identified. These studies provide valuable information for optimizing recycling processes to reach targeted cathode composition and structure that can enable electrochemical performance comparable to or better than pristine materials.

36 MATERIALS SCIENCE↗

Lattice dynamics and thermoelectric properties of diamondoid materials

Abstract The diamondoid compounds are a large family of important semiconductors, which possess various unique transport properties and had been widely investigated in the fields of photoelectricity and nonlinear optics. For a significantly long period of time, diamondoid materials were not given much attention in the field of thermoelectricity. However, this changed when a series of diamondoid compounds showed a thermoelectric figure of merit ( ZT ) greater than 1.0. This discovery sparked considerable interest in further exploring the thermoelectric properties of diamondoid materials. This review aims to provide a comprehensive view of our current understanding of thermal and electronic transport in diamondoid materials and stimulate their development in thermoelectric applications. We present a collection of recent discoveries concerning the lattice dynamics and electronic structure of diamondoid materials. We review the underlying physics responsible for their unique electrical and phonon transport behaviors. Moreover, we provide insights into the advancements made in the field of thermoelectricity for diamondoid materials and the corresponding strategies employed to optimize their performance. Lastly, we emphasize the challenges that lie ahead and outline potential avenues for future research in the domain of diamondoid thermoelectric materials.

Xie, Hongyao↗

Partial completion of post-irradiation examination of the ORNL samples

A total of six Grade 92 and two 800H samples were identified and secured as the selected ORNL samples, which were irradiated in the High Flux Isotope Reactor (HFIR) of ORNL to 0.46–14.66 dpa at 400 to ~720°C. The Grade 92 is an optimized heat and named as G92-2b. The two 800H samples have one sample as the standard solution-annealed condition and the other sample as a thermos-mechanically processed (TMP) condition with a maximized fraction of low-Σ coincidence site lattice (CSL) boundaries. Tensile tests were completed for the selected ORNL samples using the Irradiated Materials Examination and Testing (IMET) hot cell facility at ORNL. The G92-2b samples were tested at room temperature. The lower temperature irradiation at 400–496.7°C to 0.52–14.66 dpa resulted in minimal changes in tensile properties. However, the higher temperature irradiation at ~683.3–720°C to 0.46–14.63 dpa tended to reduce yield and tensile strength by about –136 to –311 MPa and plastic elongation with the increasing dose. The 800H and 800H-TMP samples were tensile-tested at their irradiation temperature 580°C, which showed >40% increase in yield and tensile strength with nearly 9% reduction in elongation for 800H-TMP compared with 800H.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Deformation and Phase Transformation Processes in Polycrystalline NiTi and NiTiHf High Temperature Shape Memory Alloys

The deformation and transformation mechanisms of polycrystalline Ni49.9Ti50.1 and Ni50.3Ti29.7Hf20 (in at.%) shape memory alloys were investigated by combined experimental and modeling efforts aided by an in situ neutron diffraction technique at stress and temperature. The thermomechanical response of the low temperature martensite, the high temperature austenite phases, and changes between these two states during thermomechanical cycling were probed and reported. In the cubic austenite phase, stress-induced martensite, deformation twinning and slip processes were observed which helped in constructing a deformation map that contained the limits over which each of the identified mechanisms was dominant. Deformation of the monoclinic martensitic phase was also investigated where the microstructural changes (texture, lattice strains, and phase fractions) during room-temperature deformation and subsequent thermal cycling were compared to the bulk macroscopic response. When cycling between these two phases, the evolution of inelastic strains, along with the shape setting procedures were examined and used for the optimization of the transformation properties as a function of deformation levels and temperatures. Finally, this work was extended to the development of multiaxial capabilities at elevated temperatures for the in situ neutron diffraction measurements of shape memory alloys on the VULCAN Diffractometer at Oak Ridge National Laboratory.

Benafan, Othmane↗

Lattice cell and full core physics of internally cooled annular fuel in heavy water moderated reactors

A program is underway at Atomic Energy of Canada Limited (AECL) to develop a new fuel bundle concept to enable greater burnups for PT-HWR (pressure tube heavy water reactor) cores. One option that AECL is investigating is an internally cooled annular fuel (ICAF) element concept. ICAF contains annular cylindrical pellets with cladding on the inner and outer diameters. Coolant flows along the outside of the element and through the centre. With such a concept, the maximum fuel temperature as a function of linear element rating is significantly reduced compared to conventional, solid-rod type fuel. The preliminary ICAF bundle concept considered in this study contains 24 half-metre long internally cooled annular fuel elements and one non-fuelled centre pin. The introduction of the non-fuelled centre pin reduces the coolant void reactivity (CVR), which is the increase in reactivity that occurs on voiding the coolant in accident scenarios. Lattice cell and full core physics calculations of the preliminary ICAF fuel bundle concept have been performed for medium burnups of approximately 18 GWd/tU using WIMS-AECL and reactor fuel simulation program (RFSP). The results will be used to assist in concept configuration optimization. The effects of radial and axial core power distributions, linear element power ratings, refuelling rates and operational power ramps have been analyzed. The results suggest that burnups of greater than 18 GWd/tU can be achieved in current reactor designs. At approximately 18 GWd/tU, expected maximum linear element ratings in a PT-HWR with online-refuelling are approximately 90 kW/m. These conditions would be prohibitive for solid-rod fuel, but may be possible in ICAF fuel given the reduced maximum fuel temperature as a function of linear element rating. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Understanding the Role of Temperature and Cathode Composition on Interface and Bulk: Optimizing Aluminum Oxide Coatings for Li-Ion Cathodes

Here, surface coating of cathode materials with Al 2 O 3 has been shown to be a promising method for cathode stabilization and improved cycling performance at high operating voltages. However, a detailed understanding on how coating process and cathode composition changes the chemical composition, morphology and distribution of coating within cathode interface and bulk lattice, is still missing. In this study, we use a wet-chemical method to synthesize a series of Al 2 O 3 -coated LiNi 0.5 Co 0.2 Mn 0.3 O 2 and LiCoO 2 cathodes treated under various annealing temperatures and a combination of structural characterization techniques to understand the composition, homogeneity and morphology of coating layer and the bulk cathode. Nuclear magnetic resonance and electron microscopy results reveal that the nature of the interface is highly depended on the annealing temperature and cathode composition. For Al 2 O 3 -coated LiNi 0.5 Co 0.2 Mn 0.3 O 2 , higher annealing temperature leads to more homogeneous and more closely attached coating on cathode materials, corresponding to better electrochemical performance. Lower Al 2 O 3 coating content is found to be helpful to further improve the initial capacity and cyclability, which can greatly outperform the pristine cathode material. For Al 2 O 3 -coated LiCoO 2 , the incorporation of Al into the cathode lattice is observed after annealing at high temperatures, implying the transformation from “surface coatings” to “dopants”, which is not observed for LiNi 0.5 Co 0.2 Mn 0.3 O 2 . As a result, Al 2 O 3 -coated LiCoO 2 annealed at higher temperature shows similar initial capacity but lower retention compared to that annealed at a lower temperature, due to the intercalation of surface alumina into the bulk layered structure forming a solid solution.

25 ENERGY STORAGE↗

Accelerating the Discovery of New, Single Phase High Entropy Ceramics via Active Learning

High-entropy ceramics have garnered interest due to their remarkable hardness, compressive strength, thermal stability, and fracture toughness; yet the discovery of new high-entropy ceramics (out of a tremendous number of possible elemental permutations) still largely requires costly, inefficient, trial-and-error experimental and computational approaches. The entropy forming ability (EFA) factor was recently proposed as a computational descriptor that positively correlates with the likelihood that a 5-metal high-entropy carbide (HECs) will form the desired single phase, homogeneous solid solution; however, discovery of new compositions is computationally expensive. If you consider 8 candidate metals, the HEC EFA approach uses 49 optimizations for each of the 56 unique 5-metal carbides, requiring a total of 2744 costly density functional theory calculations. Here, we describe an orders-of-magnitude more efficient active learning (AL) approach for identifying novel HECs. To begin, we compared numerous methods for generating composition-based feature vectors (e.g., magpie and mat2vec), deployed an ensemble of machine learning (ML) models to generate an average and distribution of predictions, and then utilized the distribution as an uncertainty. Here we then deployed an AL approach to extract new training data points where the ensemble of ML models predicted a high EFA value or was uncertain of the prediction. Our approach has the combined benefit of decreasing the amount of training data required to reach acceptable prediction qualities and biases the predictions toward identifying HECs with the desired high EFA values, which are tentatively correlated with the formation of single phase HECs. Using this approach, we increased the number of 5-metal carbides screened from 56 to 15,504, revealing 4 compositions with record-high EFA values that were previously unreported in the literature. Our AL framework is also generalizable and could be modified to rationally predict optimized candidate materials/combinations with a wide range of desired properties (e.g., mechanical stability, thermal conductivity).

36 MATERIALS SCIENCE↗

Epitaxial growth and physical properties of Bi 2 Ru 2 O 7 thin films on YSZ(111) substrates

We systematically investigated the growth of Bi 2 Ru 2 O 7 thin films on a Y-stabilized ZrO 2 (111) substrate using pulsed laser deposition by mapping the influence of growth temperature and oxygen partial pressure on phase stability, lattice parameters, and cation ratio. The results show that the epitaxial stabilization requires a minimum growth temperature, which is rather insensitive to the pressure. Meanwhile, the Bi:Ru ratio decreases when increasing growth temperature or decreasing pressure. By constructing the temperature–pressure phase diagram, an optimal growth window within the epitaxial phase was established. On the other hand, the electrical resistivity remains at a similar level within the epitaxial phase with only subtle changes to the temperature dependence, indicative of the robustness of the conductivity against composition variation. Our study provides a foundation for future investigations on thin films and heterostructures that utilize Bi 2 Ru 2 O 7 .

Crystallography↗

Investigation of dissimilar metal welds by energy-resolved neutron imaging

A nondestructive study of the internal structure and compositional gradient of dissimilar metal-alloy welds through energy-resolved neutron imaging is described in this paper. The ability of neutrons to penetrate thick metal objects (up to several cm) provides a unique possibility to examine samples which are opaque to other conventional techniques. The presence of Bragg edges in the measured neutron transmission spectra can be used to characterize the internal residual strain within the samples and some microstructural features, e.g. texture within the grains, while neutron resonance absorption provides the possibility to map the degree of uniformity in mixing of the participating alloys and intermetallic formation within the welds. In addition, voids and other defects can be revealed by the variation of neutron attenuation across the samples. This paper demonstrates the potential of neutron energy-resolved imaging to measure all these characteristics simultaneously in a single experiment with sub-mm spatial resolution. Two dissimilar alloy welds are used in this study: Al autogenously laser welded to steel, and Ti gas metal arc welded (GMAW) to stainless steel using Cu as a filler alloy. The cold metal transfer variant of the GMAW process was used in joining the Ti to the stainless steel in order to minimize the heat input. The distributions of the lattice parameter and texture variation in these welds as well as the presence of voids and defects in the melt region are mapped across the welds. The depth of the thermal front in the Al–steel weld is clearly resolved and could be used to optimize the welding process. As a result, a highly textured structure is revealed in the Ti to stainless steel joint where copper was used as a filler wire. The limited diffusion of Ti into the weld region is also verified by the resonance absorption.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Towards Improving luminosity using optics tuning and data-driven methods

The results of Run 24 experiments at Relativistic Heavy Ion Collider (RHIC) for improving luminosity using optics tuning are presented in this study. In the first experiment, MADx matching was used to output magnet strengths corresponding to specific s star movements around Interaction Region 8 (IR8). The corresponding Zero Degree Calorimeter (ZDC) signal was measured in place of luminosity, and Bayesian Optimization aids search of optimal movements. It was found that values retrieved from matching were inaccurate, resulting in negative feedback loops. The second experiment focused on calculating accurate s star movements. The matching method was replaced with a linear sensitivity matrix, directly relating optics to power supply, and its null space was used to fit constraints such as hysteresis effects. At the experiment, beam losses were observed at collimators around boundary of IR8, which were fixed for the third experiment. Dynamic mode decomposition was also introduced to improve quality of turn-by-turn (TBT) data as well as accuracy and consistency of optics measurements at IR8. These improvements will be tested in the experiment of next RHIC run for luminosity optimization.

Accelerator Physics↗

RISMC Industry Application no. 1 (ECCS/LOCA) Core characterization automation: Reference PWR designs for IA no. 1

The U.S. NRC is currently proposing rulemaking '10 CFR 50.46c' to revise the loss-of-coolant-accident (LOCA) and emergency core cooling system (ECCS) acceptance criteria to include the effects of higher burn-up on cladding performance. The key implications of this proposition are that both cladding and ECCS performance need to be considered in a coupled manner. This implies that LOCA methodologies will need to be updated for regulatory purposes. The Risk-Informed Safety Margin Characterization (RISMC) Pathway, as part of the DOE Light Water Reactor Sustainability (LWRS) research and development program initialed several programs at the Idaho National Laboratory (INL) to support the industry by offering potential solutions to this new LOCA/ECCS analysis. One of these programs is the Industry Application no. 1 (IA1). It's goal is to develop an integrated evaluation model called LOCA Toolkit for the US (LOTUS) to revisit how risks are evaluated in a LOCA under 10 CFR 50.46c. The focus of LOTUS is to establish the automation interfaces among the physics disciplines involved, namely the core design automation, the fuels/clad performance, the system analysis, the risk assessment and the core design optimization. The risk-informed margins management approach for IA1 will provide a means of quantifying the impact on the key LOCA analysis figures-of-merit like peak cladding temperature (PCT), equivalent cladding reacted (ECR), etc. of a change in LOCA analysis inputs. The information obtained can then be used for decision-making and margin management. The modular approach for LOTUS will enable plant owners/vendors to further customize the LOTUS framework for use within their established codes and methods. One of the LOTUS modules deals with the core design automation (CD-A). The purpose of this module is to supply the LOCA analysis with initial conditions, i.e. assembly/pin power histories, power shapes, etc. to be employed by the Fuels/Clad Performance (EP) and System Analysis (SA) modules. In the CD-A module, the plant owner/operator will characterize his core design with the tools he has. For the current LOTUS demonstration, the tools used are the already coupled codes PHISICS and RELAP5-3D2,3. Cross section generation will be done using the Studsvik lattice code HELIOS-2.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Recent Advances in Understanding the Structure and Properties of Amorphous Oxide Semiconductors

Here, amorphous oxide semiconductors (AOSs)—ternary or quaternary oxides of post-transition metals such as In-Sn-O, Zn-Sn-O, or In-Ga-Zn-O—have been known for a decade and have attracted a great deal of attention as they pos-sess several technological advantages, including low-temperature large-area deposition, mechanical flexibility, smooth surfaces, and high carrier mobility that is an order of magnitude larger than that of amorphous silicon (a-Si:H). Compared to their crystalline counterparts, the structure of AOSs is extremely sensitive to deposition conditions, stoichiometry, and composition, giving rise to a wide range of tunable optical and electrical properties. The large parameter space and the resulting complex deposition–structure–property relationships in AOSs make the currently available theoretical and experimental research data rather scattered and the design of new materials difficult. In this work, the key properties of several In-based AOSs are studied as a function of cooling rates, oxygen stoichiometry, cation composition, or lattice strain. Based on a thor-ough comparison of the results of ab initio mode ling, comprehensive structural analysis, accurate property calculations, and systematic experimental measure-ments, a four-dimensional parameter space for AOSs is derived, serving as a solid foundation for property optimization in known AOSs and for design of next-generation transparent amorphous semiconductors.

36 MATERIALS SCIENCE↗

SCF Framework, HF Stability, and RPA Correlation for Jordan–Wigner-Transformed Spin Hamiltonians on Arbitrary Coupling Topologies

Mapping spins to fermions via the Jordan–Wigner (JW) transformation can render mean-field (Hartree–Fock, HF) descriptions effective for strongly correlated spin systems. As established in recent work, the application of such approaches is not limited by the nonlocal structure of JW strings or by site ordering because string operators can be absorbed into Thouless rotations of a Slater determinant, and the variational optimization of a unitary Lie-algebraic similarity transformation removes any ordering dependence. Leveraging these ideas, we develop a self-consistent field (SCF) scheme that expresses the mean-field energy as a functional of the single-particle density matrix, providing an alternative to gradient-based optimization of Thouless parameters. We derive the analytical orbital Hessian to diagnose HF stability and compute the ground-state correlation energy through the random-phase approximation (RPA). Benchmark results for the XXZ and J 1 –J 2 model on one- and two-dimensional lattices demonstrate that RPA significantly improves mean-field accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In-Situ Atomic-Scale Revelation of Amorphous Metallic Iron Formation during Hydrogen-Driven Reduction of Iron Oxides

The transition to hydrogen as a green reductant in metal production is critical for decarbonizing the metallurgical industry, yet atomic-scale mechanisms governing reduction pathways and phase evolution remain unresolved. Using in-situ environmental transmission electron microscopy, we identify a hidden pathway that reveals dynamic formation of amorphous metallic iron (Fe) during the hydrogen-driven reduction of ferrous oxides of Fe 3 O 4 and FeO. Real-time imaging uncovers three coexisting transformation routes: (i) Fe 3 O 4 → FeO, (ii) Fe 3 O 4 → amorphous Fe, and (iii) FeO → amorphous Fe. The resulting amorphous Fe exhibits fluid-like mobility, enabling its rapid aggregation and crystallization into core-shell nanostructures, with a crystalline core enveloped by an amorphous shell. Complementary ab initio molecular dynamics simulations trace the amorphous Fe formation to interfacial strain at the metal/oxide interfaces, where large lattice mismatches destabilize the metal lattice during initial metallization. This interplay between thermodynamics and kinetics governs phase evolution: thermodynamics favors a self-limiting amorphous Fe overlayer, while rapid oxide reduction kinetics drives amorphous overgrowth. Our findings demonstrate that amorphous intermediates bypass rate-limiting crystalline steps, providing mechanistic insights to optimize H 2 -based processes for sustainable steelmaking. In conclusion, these insights bridge the gap between macroscopic process engineering and atomic-scale dynamics, with broader implications for catalysis and nanostructured material synthesis, where oxide reduction pathways critically shape functional phases and microstructures.

36 MATERIALS SCIENCE↗

Machine-learning-guided descriptor selection for predicting corrosion resistance in multi-principal element alloys

More than $270 billion is spent on combatting corrosion annually in the USA alone. As such, we present a machine-learning (ML) approach to down select corrosion-resistant alloys. Our focus is on a non-traditional class of alloys called multi-principal element alloys (MPEAs). Given the vast search space due to the variety of compositions and descriptors to be considered, and based upon existing corrosion data for MPEAs, we demonstrate descriptor optimization to predict corrosion resistance of any given MPEA. Our ML model with descriptor optimization predicts the corrosion resistance of a given MPEA in the presence of an aqueous environment by down selecting two environmental descriptors (pH of the medium and halide concentration), one chemical composition descriptor (atomic % of element with minimum reduction potential), and two atomic descriptors (difference in lattice constant (Δa) and average reduction potential). Our findings show that, while it is possible to down select corrosion-resistant MPEAs by using ML from a large search space, a larger dataset and higher quality data are needed to accurately predict the corrosion rate of MPEAs. This study shows both the promise and the perils of ML when applied to a complex chemical phenomenon like corrosion of alloys.

36 MATERIALS SCIENCE↗