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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 325 records · Page 18

MultiTaskDeltaNet: change detection-based image segmentation for operando ETEM with application to carbon gasification kinetics

Transforming in situ transmission electron microscopy (TEM) imaging into a tool for spatially-resolved operando characterization of solid-state reactions requires automated, high-precision semantic segmentation of dynamically evolving features. However, traditional deep learning methods for semantic segmentation often face limitations due to the scarcity of labeled data, visually ambiguous features of interest, and scenarios involving small objects. To tackle these challenges, we introduce MultiTaskDeltaNet (MTDN), a novel deep learning architecture that creatively reconceptualizes the segmentation task as a change detection problem. By implementing a unique Siamese network with a U-Net backbone and using paired images to capture feature changes, MTDN effectively leverages minimal data to produce high-quality segmentations. Furthermore, MTDN utilizes a multi-task learning strategy to exploit correlations between physical features of interest. In an evaluation using data from in situ environmental TEM (ETEM) videos of filamentous carbon gasification, MTDN demonstrated a significant advantage over conventional segmentation models, particularly in accurately delineating fine structural features. Notably, MTDN achieved a 10.22% performance improvement over conventional segmentation models in predicting small and visually ambiguous physical features. This work bridges key gaps between deep learning and practical TEM image analysis, advancing automated characterization of nanomaterials in complex experimental settings.

08 HYDROGEN↗

Report on FY 2020 Testing in Support of the Development and Extension of ASME Code Rules for Grade 91

This report summarizes the FY 2020 research and activities at Oak Ridge National Laboratory in support of the ASME code rule development and code extension for Grade 91 (Gr. 91) steel. Incorporation of the Gr. 91 temperature-dependent fatigue curves in Section III Division 5 was one major task, and the associated major aspects brought up during the course of the ASME balloting process are documented in this report. Experiments and analysis continued on the development of the alternative creep-fatigue evaluation based on elastic–perfectly plastic (EPP) plus simplified model test (SMT) methodology. The focus of the study in FY 2020 was the evaluation of the hold-time effect at high cycle and low strain range region. Baseline testing in support of the evaluation of hold time effects was started and will continue in FY 2021. Major on-going experiments and activities in support of the ASME code development and extension of Gr. 91 will be completed in FY 2021.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Defects go green: using defects in nanomaterials for renewable energy and environmental sustainability

Induction of point defects in nanomaterials can bestow upon them entirely new physics or augment their pre-existing physical properties, thereby expanding their potential use in green energy technology. Predicting structure-property relationships for defects a priori is challenging, and developing methods for precise control of defect type, density, or structural distribution during synthesis is an even more formidable task. Hence, tuning the defect structure to tailor nanomaterials for enhanced device performance remains an underutilized tool in materials design. We review here the state of nanomaterial design through the lens of computational prediction of defect properties for green energy technology, and synthesis methods to control defect formation for optimal performance. We illustrate the efficacy of defect-focused approaches for refining nanomaterial physics by describing several specific applications where these techniques hold potential. Most notably, we focus on quantum dots for reabsorption-free solar windows and net-zero emission buildings, oxide cathodes for high energy density lithium-ion batteries and electric vehicles, and transition metal dichalcogenides for electrocatalytic green hydrogen production and carbon-free fuels.

14 SOLAR ENERGY↗

STK Integrated Message Production List Editor (SIMPLE) for CEO Operations

Late in fiscal year 2011, the Crew Earth Observations (CEO) team was tasked to upgrade and replace its mission planning and mission operations software systems, which were developed in the Space Shuttle era of the 1980s and 1990s. The impetuses for this change were the planned transition of all workstations to the Windows 7 64-bit operating system and the desire for more efficient and effective use of Satellite Tool Kit (STK) software required for reliable International Space Station (ISS) Earth location tracking. An additional requirement of this new system was the use of the same SQL database of CEO science sites from the SMMS, which was also being developed. STK Integrated Message Production List Editor (SIMPLE) is the essential, all-in-one tool now used by CEO staff to perform daily ISS mission planning to meet its requirement to acquire astronaut photography of specific sites on Earth. The sites are part of a managed, long-term database that has been defined and developed for scientific, educational, and public interest. SIMPLE's end product is a set of basic time and location data computed for an operator-selected set of targets that the ISS crew will be asked to photograph (photography is typically planned 12 to 36 hours out). The CEO operator uses SIMPLE to (a) specify a payload operations planning period; (b) acquire and validate the best available ephemeris data (vectors) for the ISS during the planning period; (c) ingest and display mission-specific site information from the CEO database; (d) identify and display potential current dynamic event targets as map features; (e) compute and display time and location information for each target; (f) screen and select targets based on known crew availability constraints, obliquity constraints, and real-time evaluated constraints to target visibility due to illumination (sun elevation) and atmospheric conditions (weather); and finally (g) incorporate basic, computed time and location information for each selected target into the daily CEO Target List product (message) for submission to ISS payload planning and integration teams for their review and approval prior to uplink. SIMPLE requires and uses the following resources: an ISS mission planning period Greenwich Mean Time start date/time and end date/time), the best available ISS mission ephemeris data (vectors) for that planning period, the STK software package configured for the ISS, and an ISS mission-specific subset of the CEO sites database. The primary advantages realized by the development and implementation of SIMPLE into the CEO payload operations support activity are a smooth transition to the Windows 7 operating system upon scheduled workstation refresh; streamlining of the input and verification of the current ISS ephemeris (vector data); seamless incorporation of selected contents of the SQL database of science sites; the ability to tag and display potential dynamic event opportunities on orbit track maps; simplification of the display and selection of encountered sites based on crew availability, illumination, obliquity, and weather constraints; the incorporation of high-quality mapping of the Earth with various satellite-based datasets for use in describing targets; and the ability to encapsulate and export the essential selected target elements in XML format for use by onboard Earth-location systems, such as Worldmap. SIMPLE is a carefully designed and crafted in-house software package that includes detailed help files for the user and meticulous internal documentation for future modifications. It was delivered in February 2012 for test and evaluation. Following acceptance, it was implemented for CEO mission operations support in May 2012.

Trenchard, Mike↗

Multifunctional Metal–Oxide Nanocomposite Thin Film with Plasmonic Au Nanopillars Embedded in Magnetic La 0.67 Sr 0.33 MnO 3 Matrix

Searching for multifunctional materials with tunable magnetic and optical properties has been a critical task toward the implementation of future integrated optical devices. Vertically aligned nanocomposite (VAN) thin films provide a unique platform for multifunctional material designs. In this work, a new metal–oxide VAN has been designed with plasmonic Au nanopillars embedded in a ferromagnetic La 0.67 Sr 0.33 MnO 3 (LSMO) matrix. Such Au–LSMO nanocomposite presents intriguing plasmon resonance in the visible range and magnetic anisotropy property, which are functionalized by the Au and LSMO phase, respectively. Furthermore, the vertically aligned nanostructure of metal and dielectric oxide results in the hyperbolic property for near-field electromagnetic wave manipulation. Such optical and magnetic response could be further tailored by tuning the composition of Au and LSMO phases.

36 MATERIALS SCIENCE↗

In situ measurement of damage evolution in shocked magnesium as a function of microstructure

Accurate modeling and prediction of damage induced by dynamic loading in materials have long proved to be a difficult task. Examination of postmortem recovered samples cannot capture the time-dependent evolution of void nucleation and growth, and attempts at analytical models are hindered by the necessity to make simplifying assumptions, because of the lack of high-resolution, in situ, time-resolved experimental data. We use absorption contrast imaging to directly image the time evolution of spall damage in metals at ~1.6-μm spatial resolution. We observe a dependence of void distribution and size on time and microstructure. The insights gained from these data can be used to validate and improve dynamic damage prediction models, which have the potential to lead to the design of superior damage-resistant materials.

36 MATERIALS SCIENCE↗

Comprehensive Report For Proposed Elevated Temperature Elastic Perfectly Plastic (EPP) Code Cases Representative Example Problems

Background: The current rules in the nuclear section of the ASME Boiler and Pressure Vessel (B&PV) Code , Section III, Subsection NH for the evaluation of strain limits and creep-fatigue damage using simplified methods based on elastic analysis have been deemed inappropriate for Alloy 617 at temperatures above 1200F (650C)1. To address this issue, proposed code rules have been developed which are based on the use of elastic-perfectly plastic (E-PP) analysis methods and which are expected to be applicable to very high temperatures. The proposed rules for strain limits and creep-fatigue evaluation were initially documented in the technical literature 2, 3, and have been recently revised to incorporate comments and simplify their application. The revised code cases have been developed. Task Objectives: The goal of the Sample Problem task is to exercise these code cases through example problems to demonstrate their feasibility and, also, to identify potential corrections and improvements should problems be encountered. This will provide input to the development of technical background documents for consideration by the applicable B&PV committees considering these code cases for approval. This task has been performed by Hollinger and Pease of Becht Engineering Co., Inc., Nuclear Services Division and a report detailing the results of the E-PP analyses conducted on example problems per the procedures of the E-PP strain limits and creep-fatigue draft code cases is enclosed as Enclosure 1. Conclusions: The feasibility of the application of the E-PP code cases has been demonstrated through example problems that consist of realistic geometry (a nozzle attached to a semi-hemispheric shell with a circumferential weld) and load (pressure; pipe reaction load applied at the end of the nozzle, including axial and shear forces, bending and torsional moments; through-wall transient temperature gradient) and design and operating conditions (Levels A, B and C).

36 MATERIALS SCIENCE↗

Center for Energy Efficient Materials (CEEM) (Final Technical Report)

The mission of the Center for Energy Efficient Materials (CEEM) was to serve the Department of Energy and the nation as a center of excellence dedicated to advancing basic research in nano-structured materials and devices for applications to solar electricity, thermoelectric conversion of waste heat to electricity, and solidstate lighting. The foundation of CEEM was based on the unique capabilities of UCSB and its partner institutions to control, synthesize, characterize, model, and apply materials at the nanoscale for more efficient sustainable energy resources. This unique expertise was a key source of the synergy that unified the research of the Center. Although the Center’s focus was basic research, It’s longer-term objective has been to transfer new materials and devices into the commercial sector where they will have a substantial impact on the nation’s need for efficient sustainable energy resources. As one measure of the impact of the Center, two start-up companies were formed based on its research. In addition, Center participants published a total of 210 archival journal articles, of which 51 were exclusively sponsored by the DOE grant. The work of the Center was structured around four specific tasks: Organic Solar Cells, Solid-State Lighting, Thermoelectrics, and High Efficiency Multi-junction Photovoltaic devices. A brief summary of each follows – detailed descriptions are in Sections 4 & 5 of this report. Research supported through CEEM led to an important shift with respect to the choice of materials used for the fabrication of solution deposited organic solar cells. Solution deposition opens the opportunity to manufacture solar cells via economically-viable high throughput tools, such as roll to roll printing. Prior to CEEM, most organic semiconductors utilized for this purpose involved polymeric materials, which, although they can form thin films reliably, suffer from batch to batch variations due to the statistical nature of the chemical reactions that produce them. In response, the CEEM team developed well-defined molecular semiconductors that produce active layers with very high power conversion efficiencies, in other words they can convert a very high fraction of sunlight into useful electrical power. The fact that the semiconductor is formed from molecular species provides the basis for circumventing the unreliability of polymer counterparts and, as an additional bonus, allows one to attain much grater insight into the structure of the active layer. The latter is particularly important because efficient conversion is the result of a complex arrangement of two semiconductors that need to phase separate in a way akin to oil and water, but with domains that are described by nanoscale dimensions. CEEM was therefore able to provide deep insight into the influence of nanostructure, through the application of structural characterization tools and theoretical methods that describe how electrical charges migrate through the organic layer. Our research in light emitting diode (LED)-based solid state lighting (SSL) was directed at improving efficiency and reducing costs to enable the widespread deployment of economically-viable replacements for inefficient incandescent, halogen, and fluorescent-based lighting. Our specific focus was to advance the fundamental science and technology of light emitting diodes to both understand factors that limit efficiencies and to provide innovative and viable solutions to the current impediments. One of the main challenges we faced is the decrease in efficiency when LEDs are driven harder to increase light output---the so called “droop” effect. It requires large emitting surfaces to reach a desired optical output, and necessitates the use of costly heat sinks, both of which increase the cost. We successfully reduced droop by growing LED crystals having non-conventional orientations. As recognized by the award of the 2014 Nobel prize to the inventors of the nitride LEDs (one of whom was a member of CEEM), LEDs already have a large societal impact in both developed (leading to large energy savings) and developing countries (bringing light where there is no electrical grid). The improvements in efficiency sought after in the CEEM project are key to a further impact of solid state lighting by LEDs with a projected doubling in efficiency by year 2020. Direct generation of electricity from heat has enormous promise for beneficial use of waste heat. But practical power generation directly from heat requires understanding and development of new and improved materials that will be more efficient and rugged than today’s thermoelectric materials. To accomplish this goal CEEM has synthesized five distinct and promising new classes of thermoelectric materials: (a) nanoparticle arrays that are effective in maximizing electric power generation and reducing detrimental loss of heat; (b) nitride and (c) oxide thermal electric materials that are effective at high temperatures where much beneficial heat is available; (d) arrays of silicon nano-wires that integrate thermal electricity generation into silicon-based electronics and materials; and (e) chemically synthesized nanostructured compounds that are cost effective, earth abundant, and environmentally friendly. The further development of these thermoelectric sources of electricity could have revolutionary impact for society in the recovery of waste heat from sources such as power plants and automobile exhaust, where there could be significant associated energy saving. It could even, in the future, provide disruptive alternatives and replacements for today’s internal combustion engines and could enable improved all-electric propulsion by the heat from shipboard nuclear reactors. The High Efficiency Multi-junction Photovoltaics task was a UCSB/NREL collaboration which bonded sub-cells from two different compound semiconductors material systems to make high efficiency multijunction solar cells for concentrating photovoltaic applications thathave substantially higher efficiency than single substrate cells made of elemental semiconductors such as silicon. This task required the development of new cell bonding methods with excellent coupling of both photons and electrons between the sub-cells. To accomplish this, we developed (1) GaInN solar cells with enhanced performance by using quantum-well absorbers and front-surface optical texturing, (2) a hybrid "pillar-array" bond which uses an array of metal pillars for electrical coupling, and (3) a "hybrid moth-eye" optical coating which combines the benefits of nano-imprinted moth-eye coatings and traditional multilayer coatings. The technical effectiveness was assessed by measurement of the photovoltaic efficiency of solar cells made using these techniques; the ultrahigh efficiencies targeted by this work are of compelling economic value for concentrating photovoltaics.

14 SOLAR ENERGY↗

Twin Crystal Induced near Zero Thermal Expansion in SnO 2 Nanowires

Knowledge of controllable thermal expansion is a fundamental issue in the field of materials science and engineering. Direct blocking of the thermal expansions in positive thermal expansion materials is a challenging but fascinating task. We report a near zero thermal expansion (ZTE) of SnO 2 achieved from twin crystal nanowires, which is highly correlated to the twin boundaries. Local structural evolutions followed by pair distribution function revealed a remarkable thermal local distortion along the twin boundary. Lattice dynamics investigated by Raman scattering evidenced the hardening of phonon frequency induced by the twin crystal compressing, giving rise to the ZTE of SnO 2 nanowires. Further DFT calculation of Grüneisen parameters confirms the key role of compressive stress on ZTE. Finally, our results provide an insight into the thermal expansion behavior regarding to twin crystal boundaries, which could be beneficial to the applications.

36 MATERIALS SCIENCE↗

Analytical Results for MOX Colemanite Concrete Samples: Received on September 4, 2013

The Mixed Oxide Fuel Fabrication Facility (MFFF) will use colemanite bearing concrete neutron absorber panels credited with attenuating neutron flux in the criticality design analyses and shielding operators from radiation. The Savannah River National Laboratory (SRNL) is tasked with measuring the total density, partial hydrogen density, and partial boron density of the colemanite concrete. SRNL received three samples of colemanite concrete for analysis on September 4, 2013. The average total density of each of the samples measured by the ASTM method C 642, the average partial hydrogen density was measured using method ASTM E 1131, and the average partial boron density of each sample was measured according to ASTM C 1301. The lower limits and measured values for the total density, hydrogen partial density, and boron partial density are presented. For all the samples tested, the total density and the boron partial density met or exceeded the specified limit. None of the samples met the lower limit for hydrogen partial density.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Analytical Results for MOX Colemanite Concrete Samples: Received on November 21, 2013

The Mixed Oxide Fuel Fabrication Facility (MFFF) will use colemanite bearing concrete neutron absorber panels credited with attenuating neutron flux in the criticality design analyses and shielding operators from radiation. The Savannah River National Laboratory (SRNL) is tasked with measuring the total density, partial hydrogen density, and partial boron density of the colemanite concrete. SRNL received two samples of colemanite concrete for analysis on November 21, 2013. The average total density of each of the samples measured by the ASTM method C 642, the average partial hydrogen density was measured using method ASTM E 1131, and the average partial boron density of each sample was measured according to ASTM C 1301. The lower limits and measured values for the total density, hydrogen partial density, and boron partial density are presented. For all the samples tested, the total density and the boron partial density met or exceeded the specified limit. None of the samples met the lower limit for hydrogen partial density.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Materials Characterization: A Primer for Solid Phase Processing Applications

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development (LDRD) Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems produced via advanced manufacturing methods, such as solid phase processing, for use in national security and advanced energy applications (Smith 2021). As a two-year LDRD investment requiring focused research, the MCPC project applied only a subset of the wide range of available destructive and nondestructive characterization methods to provide data to the predictive modeling and data analytics tasks. The purpose of this report is to review a wide range of destructive and nondestructive characterization methods that are relevant in solid-phase processing (SPP) applications, but not necessarily applied in the MCPC Project as a guide to the planning of characterization activities in future research. Particular attention is given to measured characteristics that can correlate to other material characteristics, with a particular interest in nondestructive evaluation (NDE) that can be applied to samples obtained in the MCPC Project. Destructive examinations include tensile tests, optical and electron microscopy, micro-hardness, and residual stress tests. NDE tests include surface visual inspection, eddy current examination for cracks, 4-point potential drop, ultrasound, x-ray, and computed tomography.

36 MATERIALS SCIENCE↗

Generation of Tin-Vacancy Centers in Diamond via Shallow Ion Implantation and Subsequent Diamond Overgrowth

Group IV color centers in diamond have garnered great interest for their potential as optically active solid-state spin qubits. The future utilization of such emitters requires the development of precise site-controlled emitter generation techniques that are compatible with high-quality nanophotonic devices. This task is more challenging for color centers with large group IV impurity atoms, which are otherwise promising because of their predicted long spin coherence times without a dilution refrigerator. For example, when applied to the negatively charged tin-vacancy (SnV – ) center, conventional site-controlled color center generation methods either damage the diamond surface or yield bulk spectra with unexplained features. Here we demonstrate a novel method to generate site-controlled SnV – centers with clean bulk spectra. We shallowly implant Sn ions through a thin implantation mask and subsequently grow a layer of diamond via chemical vapor deposition. This method can be extended to other color centers and integrated with quantum nanophotonic device fabrication.

36 MATERIALS SCIENCE↗

Benchmarking machine learning strategies for phase-field problems

Abstract We present a comprehensive benchmarking framework for evaluating machine-learning approaches applied to phase-field problems. This framework focuses on four key analysis areas crucial for assessing the performance of such approaches in a systematic and structured way. Firstly, interpolation tasks are examined to identify trends in prediction accuracy and accumulation of error over simulation time. Secondly, extrapolation tasks are also evaluated according to the same metrics. Thirdly, the relationship between model performance and data requirements is investigated to understand the impact on predictions and robustness of these approaches. Finally, systematic errors are analyzed to identify specific events or inadvertent rare events triggering high errors. Quantitative metrics evaluating the local and global description of the microstructure evolution, along with other scalar metrics representative of phase-field problems, are used across these four analysis areas. This benchmarking framework provides a path to evaluate the effectiveness and limitations of machine-learning strategies applied to phase-field problems, ultimately facilitating their practical application.

36 MATERIALS SCIENCE↗

Renewable Energy, Photovoltaic Systems Near Airfields. Electromagnetic Interference

Recent increases in photovoltaic (PV) systems on Department of the Navy (DON) land and potential siting near airfields prompted Commander, Naval Installations Command to fund the Naval Facilities Engineering Command to evaluate the impact of electromagnetic interference (EMI) from PV systems on airfield electronic equipment. Naval Facilities Engineering and Expeditionary Warfare Center tasked Department of Energy National Renewable Energy laboratory (NREL) to conduct the assessment. PV systems often include high-speed switching semiconductor circuits to convert the voltage produced by the PV arrays to the voltage needed by the end user. Switching circuits inherently produce electromagnetic radiation at harmonics of the switching frequency. In this report, existing literature is summarized and tests to measure emissions and mitigation methods are discussed. The literature shows that the emissions from typical PV systems are low strength and unlikely to cause interference to most airfield electronic systems. With diligent procurement and siting of PV systems, including specifications for FCC Part 15 Class A compliant equipment and a 250-foot setback from communication equipment, NREL anticipates little to no EMI impact on nearby communications or telemetry equipment.

14 SOLAR ENERGY↗

Unraveling small-scale defects in irradiated ThO 2 using kinetic Monte Carlo simulations

Point defects and their clusters generated through irradiation can have significant impact on the physical and mechanical properties of materials. However, direct experimental visualization of these small-scale defects using high-resolution scanning transmission electron microscopy remains a challenging task. In this study, using thorium dioxide (ThO 2 ) with the fluorite structure as a model system, we demonstrate the use of ab initio basin-hopping simulations in synergy with object kinetic Monte Carlo simulations as a powerful tool for identifying small defect complexes in irradiated materials. In addition to providing quantitative insights into defect evolution in ThO 2 under irradiation, our study reveals an unexpected role of bound anti-Schottky defect clusters in mediating defect transport. Remarkably, despite their poor thermal stability against dissociation at high temperatures, the transient formation of bound anti-Schottky defects under irradiation and their subsequent migration provide the dominant mechanism for the growth of large interstitial loops that have been experimentally observed in ThO 2 .

36 MATERIALS SCIENCE↗

Hierarchical supramolecular assembly of a single peptoid polymer into a planar nanobrush with two distinct molecular packing motifs

Significance The preparation of hierarchical biomimetic nanostructures remains a challenging task. Bioinspired peptoid polymers offer a promising opportunity to encode assembly information within the component chains. Here, we report a one-pot preparation of planar nanobrush structures from poly(ethyleneglycol)- block -poly( N -octylglycine) based on tuning the interplay of crystallization and solvophobicity. Each nanobrush assembly is composed of two distinct structural domains, which form sequentially by control of the solution temperature, and contain distinct molecular packing motifs. Micellar intermediates first assemble into linear arrays at elevated temperature in a mesophase state, followed by lateral, crystallization-driven growth in a living manner upon cooling. Precise control over the nanobrush dimensions could be achieved. The structural tunability and excellent biocompatibility of polypeptoids offer great potential for nanomaterials inaccessible previously.

36 MATERIALS SCIENCE↗

Accelerating the design of lattice structures using machine learning

Lattices remain an attractive class of structures due to their design versatility; however, rapidly designing lattice structures with tailored or optimal mechanical properties remains a significant challenge. With each added design variable, the design space quickly becomes intractable. To address this challenge, research efforts have sought to combine computational approaches with machine learning (ML)-based approaches to reduce the computational cost of the design process and accelerate mechanical design. While these efforts have made substantial progress, significant challenges remain in (1) building and interpreting the ML-based surrogate models and (2) iteratively and efficiently curating training datasets for optimization tasks. Here, we address the first challenge by combining ML-based surrogate modeling and Shapley additive explanation (SHAP) analysis to interpret the impact of each design variable. We find that our ML-based surrogate models achieve excellent prediction capabilities (R 2 > 0.95) and SHAP values aid in uncovering design variables influencing performance. We address the second challenge by utilizing active learning-based methods, such as Bayesian optimization, to explore the design space and report a 5 × reduction in simulations relative to grid-based search. Collectively, these results underscore the value of building intelligent design systems that leverage ML-based methods for uncovering key design variables and accelerating design.

36 MATERIALS SCIENCE↗