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DOE OSTI2022

Climate-Driven Legacies in Simulated Microbial Communities Alter Litter Decomposition Rates

The mechanisms underlying diversity-functioning relationships have been a consistent area of inquiry in biogeochemistry since the 1950s. Though these mechanisms remain unresolved in soil microbiomes, many approaches at varying scales have pointed to the same notion—composition matters. Confronting the methodological challenge arising from the complexity of microbiomes, this study used the model DEMENTpy, a trait-based modeling framework, to explore trait-based drivers of microbiome-dependent litter decomposition. We parameterized DEMENTpy for five sites along a climate gradient in Southern California, United States, and conducted reciprocal transplant simulations analogous to a prior empirical study. The simulations demonstrated climate-dependent legacy effects of microbial communities on plant litter decomposition across the gradient. This result is consistent with the previous empirical study across the same gradient. An analysis of community-level traits further suggests that a 3-way tradeoff among resource acquisition, stress tolerance, and yield strategies influences community assembly. Simulated litter decomposition was predictable with two community traits (indicative of two of the three strategies) plus local environment, regardless of the system state (transient vs. equilibrium). Although more empirical confirmation is still needed, community traits plus local environmental factors (e.g., environment and litter chemistry) may robustly predict litter decomposition across spatial-temporal scales. In conclusion, this study offers a potential trait-based explanation for climate-dependent community effects on litter decomposition with implications for improved understanding of whole-ecosystem functioning across scales.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1998

Scaling up the Single Transducer Thickness-Independent Ultrasonic Imaging Method for Accurate Characterization of Microstructural Gradients in Monolithic and Composite Tubular Structures

Ultrasonic velocity/time-of-flight imaging that uses back surface reflections to gauge volumetric material quality is highly suited for quantitative characterization of microstructural gradients including those due to pore fraction, density, fiber fraction, and chemical composition variations. However, a weakness of conventional pulse-echo ultrasonic velocity/time-of-flight imaging is that the image shows the effects of thickness as well as microstructural variations unless the part is uniformly thick. This limits this imaging method's usefulness in practical applications. Prior studies have described a pulse-echo time-of-flight-based ultrasonic imaging method that requires using a single transducer in combination with a reflector plate placed behind samples that eliminates the effect of thickness variation in the image. In those studies, this method was successful at isolating ultrasonic variations due to material microstructure in plate-like samples of silicon nitride, metal matrix composite, and polymer matrix composite. In this study, the method is engineered for inspection of more complex-shaped structures-those having (hollow) tubular/curved geometry. The experimental inspection technique and results are described as applied to (1) monolithic mullite ceramic and polymer matrix composite 'proof-of-concept' tubular structures that contain machined patches of various depths and (2) as-manufactured monolithic silicon nitride ceramic and silicon carbide/silicon carbide composite tubular structures that might be used in 'real world' applications.

Roth, Don J.↗

DOE OSTI2023

Hybrid physics-based and machine learning tools for materials assessment

In this work, we develop novel physics-based and machine learning computational techniques to predict fundamental properties of metallic systems that affect radiation damage behavior in reactor structural materials. Oftentimes, atomistic predictions of engineering alloys simplify chemical compositions to a single element to reduce computational cost and complexity, introducing large sources of uncertainty and potentially missing important behavior. In addition, engineering alloys such as SS 316 are particularly challenging to simulate with first principles methods because of the additional degrees of freedom introduced by magnetic natures of the constituent elements, and very little data of this type exists within the literature. These novel methods aim to improve the qualitative prediction of radiation damage in engineering alloys by more accurately simulating their compositions, both by accelerating the computations and by developing novel analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Subvoxel Control of Fiber Orientation via Multidirectional Shearing in 3D Printing

Anisotropy, the characteristic of materials exhibiting different properties based on their direction, is widespread in nature. Conventional manufacturing techniques often fall short in recreating such complex anisotropy. While 3D printing allows for precise fiber deposition in anisotropic composites, previous studies have only achieved bulk reorientation of fibers at the voxel level in two dimensions. This limits the replication of localized 3D anisotropies found in natural materials. To address this, a novel 3D printing technique is presented that enables subvoxel control of fiber orientation in all three directions using multidirectional shearing via nozzle rotation and inclination. The fiber orientation control in these experimental tests is driven by a numerical model, enabling a fully digital approach to program microstructures within a strand. This programmability is demonstrated through mechanical and thermal tests, illustrating a localized and controllable response to external stimuli. Achieving such complex anisotropy holds potential across several fields, including wearables and biomedical implants, lightweight composite structures, and energy storage technologies such as batteries and supercapacitors.

3D printing↗

DOE OSTI2022

The quality of organic amendments affects soil microbiome and nitrogen-cycling bacteria in an organic farming system

Organic amendments are applied in organic farming systems to provide nutrients for crop uptake and to improve soil health. Compost is often favored over fresh manure for food safety reasons, while fresh manure can be a valuable source of readily available nitrogen (N). However, the potential for fresh versus composted manure to differentially affect soil microbial and N-cycling functional communities over multiple seasons remains unknown. We compared the effect of composted vs. fresh cattle manure on soil microbial communities using taxonomic and functional approaches. Soils were collected from field plots with three organic N treatments: control (no amendment), composted manure (compost, 224 kg/ha total N), and fresh manure (manure, 224 kg/ha total N) in an organic production system. Illumina amplicon sequencing was used to comprehensively assess the bacterial community (16S rRNA genes), fungal community (ITS), ureolytic community ( ureC ), chitinolytic community ( chiA ), bacterial ammonia oxidizers (AOB amoA ), and nitrite oxidizers ( Nitrospira nxrB ). The results showed that both compost and manure treatment significantly changed the soil microbial communities. Manure had a stronger effect than compost on soil bacterial and fungal community composition, as well as on the ureolytic and chitinolytic communities, while compost treated soils had higher microbial richness than manure treated soils. Both taxonomic and functional approaches showed that the microbial community was more responsive to fresh manure than to compost. Manure treated soil also had more complex microbial interactions than compost treated soil. The abundance and community composition of N-cycling functional groups often played more limited roles than soil chemical properties (soil organic carbon, extractable organic carbon, and pH) in driving N-cycling processes. Results from our study may guide strategies for the management of organic amendments in organic farming systems and provide insights into the linkages between soil microbial communities and soil function.

Ouyang, Yang↗

DOE OSTI2026

Complexity in the medium-range order of gallium as a polyvalent liquid metal

Simplicity in chemical composition does not always translate into simplicity in the structures and dynamics of liquids and solids. Some elementary liquid metals, such as gallium, show unusual behaviors in thermodynamic and transport properties as a result of their complex atomic structure and dynamics. Here, in this work, we study the real-space atomic correlation function of liquid gallium by neutron scattering. In the pair-distribution function, there exist two kinds of medium-range order (MRO), characterized by oscillations beyond the first nearest neighbors. On the other hand, the first neighbor shell shows only one kind of bond. The two types of MRO are strongly overlapping in space and fluctuating in time. We propose that they are the basis for anomalous behavior of liquid gallium. This view challenges the current view that liquid gallium consists of fluctuating metallic and insulating domains. These findings shed light on the interpretation of similar microscopic anomalies observed in other semimetallic liquids.

Hua, Chengyun [Oak Ridge National Laboratory (ORNL↗

DOE OSTI2024

Soil Organic Matter Dynamics in the Critical Zone

Soil is the thin, vital layer of Earth’s surface that forms the foundation of the Critical Zone and sustains life. This chapter explores the intricate dynamics of soil organic matter within the critical zone, focusing on three key thematic areas: deep soil organic matter, wildfire organic matter interactions, and organic matter erosion. Soil organic matter, although a small fraction of soil mass, plays a crucial role in soil function and ecosystem stability. The complexity of soil organic matter arises from its diverse chemical composition and interactions with minerals, which influence its persistence in the environment. This chapter begins by examining deep soil organic matter, which constitutes a significant portion of global carbon storage. We discuss how deep soil organic matter, typically isolated from surface processes, may become vulnerable to decomposition and carbon release due to disturbances. Next, we explore the impacts of fire on soil organic matter, particularly the formation and stability of pyrolyzed organic matter. The decomposition of pyrolyzer organic matter is influenced by its chemical composition and the surrounding environmental conditions, with implications for carbon cycling and soil fertility in post-fire ecosystems. Finally, the chapter addresses the role of erosion in soil organic matter dynamics. Erosion, accelerated by human activities, redistributes soil organic matter across landscapes, affecting its turnover and the broader biogeochemical cycles. We consider how micro-topographic features and erosion processes interact to influence soil OM stability and carbon sequestration. By synthesizing recent advances in these areas, this chapter provides a comprehensive overview of the complex and dynamic nature of soil organic matter in the critical zone, highlighting its importance in understanding the critical zone in the face of environmental change.

Moreland, Kimber↗

NASA NTRS2011

Filamentous Trichomic Prokaryotes in Carbonaceous Meteorites: Indigenous Microfossils, Minerals, or Modern Bio-Contaminants?

Large complex filaments have been detected in freshly fractured interior surfaces of a variety of carbonaceous meteorites. Many exhibit the detailed morphological and morphometric characteristics of known filamentous trichomic prokaryotic microorganisms. In this paper we review prior studies of filamentous microstructures encountered in the meteorites along with the elemental compositions and characteristics of the, fibrous evaporite minerals and filamentous cyanobacteria and homologous trichomic sulfur bacteria. The meteorite images and elemental compositions will compared with data obtained with the same instruments for abiotic microstructures and living and fossil microorganisms in order to evaluate the relative merits of the alternate hypotheses that have been advanced to explain the nature and characteristics of the meteorite filaments. The possibiility that the filaments found in the meteorites may be comprise modern bio-contaminants will be evaluated in light of their observed elemental compositions and data by other researchers on the detection of indigenous complex organic biosignatures, and extraterrestrial amino acids and nucleobases found in the Murchison CM2 and the Orgueil CI1 carbonaceous meteorites.

Hoover, Richard B.↗

NASA NTRSDate not supplied

Preliminary XANES Analysis of Laboratory Analogs of Titan Tholins

Titan, the largest moon of Saturn, is a fascinating object. It is the only other object in the Solar System, besides Earth, with a dense (1.5 bar at the surface) atmosphere whose composition is dominated by N2, with CH4 as the second most abundant gas. A complex organic chemistry between N2 and CH4, induced by solar UV photons and energetic particles, results in the formation of a large variety of organic compounds, including hydrocarbons (e.g., C2H2, C2H4, C2H6, C3H4, C6H6), nitriles (e.g., HCN, HNC, HC3N, CH3CN, C2N2), as well as larger molecules that include aromatic and heteroaromatic compounds [1]. This complex organic chemistry also leads to the formation of aerosols that play an important role in Titan’s atmospheric dynamics, climate, as well as surface composition and processes. Because of its N2-based dense atmosphere, and its CH4 cycle that resembles the hydrological cycle on Earth, Titan is often considered to be an analog of early Earth. In recent years, Titan’s atmosphere and surface were monitored in detail by the NASA Cassini mission, which orbited the Saturnian system from 2004 to 2017, as well as the ESA Huygens probe, which plunged into Titan’s atmosphere and landed on its surface in 2005.

Titan↗

DOE OSTI2023

Surface Complexation/Ion Exchange Hybrid Model for Radionuclide Sorption to Clay Minerals (M4SF-23LL010301062)

This progress report (Level 4 Milestone Number M4SF-23LL010301062) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Argillite International Collaborations Activity Number SF-23LL01030106. The activity is focused on our long-term commitment to engaging our partners in international nuclear waste repository research. The focus of this milestone is the establishment of international collaborations for surface complexation modeling and the associated impacts of unlocking larger, community-based datasets. More specifically, we are developing a database framework for Spent Fuel and Waste and Science Technology (SFWST) that is aligned with the Helmholtz Zentrum Dresden Rossendorf (HZDR) sorption database development group in support of the database needs of the SFWST program. In our FY22 effort, we described a detailed analysis of U(VI) sorption to quartz through both traditional surface complexation modeling and through a hybrid ML framework. In FY23, effort was placed on publication of these results and expansion of the LLNL surface complexation and ion exchange database (L-SCIE) in order to assess mineral-based radionuclide retardation under a wider variety of geochemical conditions (e.g., ionic strength, varying electrolyte compositions). Efforts were initiated to expand L-SCIE to include radionuclide surface complexation and ion exchange to clays that are relevant to subsurface geochemical processes occurring at nuclear waste repositories. In particular, a large source of sorption data for clays resides at the Paul Scherrer Institute (PSI) (work primarily by Bradbury and Baeyens) and we initiated discussions on how to retrieve those data and apply FAIR principles to those datasets. In addition to L-SCIE development, two hybrid models that incorporate AI/ML were investigated and compared to discern the most promising approaches for accurate and precise estimations of radionuclide retardation. Key considerations for future model development include (1) the ability to reduce computational burden on determining retardation coefficients for PA and (2) the ability to quantify and predict radionuclide-mineral partitioning at a more efficient, rapid pace due to automated workflows. Upon the careful consideration of the most effective modeling approaches, we are identifying ways to implement these approaches into PA. Ultimately, the data science-based workflows will provide a major incentive for other institutions to adopt a FAIR-formatted, interoperable database. LLNL will play a key role in disseminating sorption data and acting as good data stewards by updating the database in a consistent format and assessing the quality of the newly assimilated data in an organized fashion. To this end, all data and workflows are open access and made available on the LLNL Seaborg research website (https://seaborg.llnl.gov/resources/geochemical-databases-modeling-codes).

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2024

Evaluation of DED and LPBF Fe-based Alloys Process Application Envelopes based on Performance, Process Economics, Supply Chain Risks, and Reactor-specific Targeted Components

The U.S. Department of Energy (DOE), Office of Nuclear Energy (NE), Advanced Materials and Manufacturing Technologies (AMMT) program aims to develop extreme-environment materials solutions for use in the deployment of advanced nuclear reactors and the sustainment of the current fleet. To achieve this objective, a combination of experiment, a computational tool, and machine learning (ML) for the design of materials is adopted for the maturation of materials for nuclear technology. Through advanced manufacturing techniques such as laser powder bed fusion (LPBF) and laser powder direct energy deposition (LP-DED), components with complex geometries can be fabricated with reduced time and effort. Such advanced manufacturing methods can also provide the opportunity to improve materials performance through optimized microstructures and mechanical properties. However, existing engineering alloys are not always well suited for fabrication with additive manufacturing (AM), as their compositions have been tuned to optimize fabrication via conventional methods. Thus, similar alloys with modified compositions that are better suited for AM can be studied for improved performance. Over the past three years, the AMMT teams from Argonne National Laboratory (ANL) and Pacific Northwest National Laboratory (PNNL) studied various known Fe-based alloys by evaluating their initial printability using LPBF, and an AMMT-developed down-selection and decision matrix reduced the number of alloys to be studied from six to three in fiscal year (FY) 2024. Additionally, in FY 2024, for parallel evaluation, these three alloys were studied using LPDED. While LPBF is better for small- to medium-sized components with high detail and internal features, LP-DED combines a material feed system to place the powder onto the exact spot where the laser will melt the material. This AM method can be easily scaled to extremely large components and provides high build rate speeds compared to those of conventional LPBF systems. Additionally, DED is a better choice for complex geometries and compositional gradients.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Processing of phase change materials by fused deposition modeling: Toward efficient thermal energy storage designs

We report that recently, several efforts have emerged that employ additive manufacturing techniques to integrate phase change material (PCM) thermal energy storage into geometrically complex designs for advanced thermal management. In this work, we contribute to this emerging research by reporting on the production of a composite nylon-based filament for fused deposition modeling incorporating encapsulated PCMs for 3D printing heat sink geometries. Microencapsulated PCM (MEPCM) with a 6 degrees C transition temperature was selected as the material for thermal energy storage. This transition temperature was selected due to its suitability to provide thermal energy storage to target air-conditioning applications in buildings. In an attempt to improve the thermal conductivity of the composite, fine boron nitride fillers were added, although the effect on improvement was found to be negligible in the overall composite mixture. The nylon-MEPCM ratio in the filaments was optimized, and filaments containing up to 40 wt% MEPCM were successfully synthesized, which were found optimal for 3D printing complex heat sink and other geometries. Thermal and mechanical properties of the filaments were characterized, including latent heat of fusion, thermal conductivity, phase change temperature, tensile strength, and more. Thermal infrared imaging of heat sink geometries printed using the MEPCM filaments undergoing thermal discharging was also conducted. This work presents the most promising result to date in the open literature for a 3D-printed PCM composite in the combination of size, energy density, and geometric complexity of printed parts.

25 ENERGY STORAGE↗

DOE OSTI2020

Complementing Nanoscale Galvanic Exchange with Redox Manipulation toward Architectural Control of Multimetallic Hollow Nanostructures

Galvanic exchange occurring within the confinement by nanoparticulate templates provides a unique pathway to controllably transform solid metallic nanoparticles into architecturally more sophisticated multimetallic hollow nanostructures under facile reaction conditions. As such, in this Minireview, we elaborately discuss how the nanoparticle-templated galvanic exchange can be deliberately coupled with redox manipulation to synthesize a large library of complex multimetallic hollow nanostructures exhibiting precisely tailored architectures and compositions, with a particular emphasis on important mechanistic insights concerning the dynamic interplay among multiple structure-remodeling processes that synergistically dictate the versatile nanoparticle transforming behaviors during kinetically and regioselectively modulated galvanic exchange reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Understanding Superatomic Ag Nanohydrides

Abstract Bulk Ag hydrides are extremely challenging to make even at very high pressures, but they may become stable as the particle size shrinks to the nanometer regime. Here, the formation and electronic structure of Ag nanohydrides are investigated from a superatomic perspective by density functional theory. It is found that as the coverage increases, adsorption energy of hydrogen atoms on Ag 38 cluster to form Ag 38 H 2 n nanohydride ( n is from 1 to 15) can be energetically favorable with respect to bare Ag 38 and H 2 . Furthermore, the adsorbed hydrogen atoms contribute their 1s electrons to the superatom electron count and behave as a metal instead of a ligand. The electronic structure of the silver nanohydrides follows the superatomic complex model, leading to magic or relatively more stable compositions such as Ag 38 H 2 , Ag 38 H 20 , and Ag 38 H 30 , which correspond to 40‐electron, 58‐electron, and 68‐electron shell closings, respectively. Angular momentum analyses of the superatomic orbitals suggest a convoluted interaction of geometry, symmetry, and orbital splitting.

He, Xiang↗

DOE OSTI2025

DuctGPT: A Generative Transformer for Forward Screening of Ductile Refractory Multi-Principal Element Alloys

Designing ductile materials for extreme environments such as fusion reactors requires a deep understanding of the complex interplay between electronic structure, mechanical stability, and wide compositional space. Here, in this work, we introduce DuctGPT, a physics-informed, GPT-powered machine learning platform that enables rapid and accurate prediction of ductility across a wide range of refractory multi-principal element alloys (MPEAs). Trained on both experimental and high-fidelity computational data, DuctGPT integrates descriptors such as density of states at the Fermi level, elastic constants, and valence electron concentration to capture the fundamental mechanisms governing ductile versus brittle behavior. Using this framework, we screen over 1000 compositions in of body-centered cubic (BCC) MPEAs, including two new alloy classes, i.e., NbTa-rich (NbTa $>$ 50 at.%) NbTa-Ti-V and W-rich ($>$ 50 at.%) W-Ti-V MPEAs, to rapidly identify promising alloy compositions with enhanced ductility. Validation against experimental data confirms the model's ability to predict ductility with high fidelity and low uncertainty. By leveraging conversational AI and robust physical modeling, DuctGPT provides a blueprint for the next generation of alloy design assistants, enabling human-AI collaboration in the accelerated discovery of ductile, high-performance materials for fusion, aerospace, and advanced manufacturing.

AI/ML↗

DOE OSTI2021

Modeling the effect of habitat availability and quality on endangered winter-run Chinook salmon ( Oncorhynchus tshawytscha ) production in the Sacramento Valley

Reconciliation between water uses and sustaining aquatic species populations requires an effort to identify and quantify essential habitat characteristics for ecosystem health and valuation methods to predict ecosystem response to restoration actions. This process is particularly challenging for anadromous fish species such as California's Sacramento River winter-run Chinook salmon, due to their limited geographic range and diverse life history habitat requirements. Tools, such as life-cycle models, are needed to manage population dynamics and quantify the composite effects of processes across space and time. Nevertheless, complex institutions can hinder result interpretation and communication, and limit model use in decision-making. This paper focuses on the federally endangered and endemic Sacramento River winter-run Chinook (Oncorhynchus tshawytscha) by developing a Winter-Run Habitat-based Population Model (WRHAP). Additionally, WRHAP is a conceptual, freshwater rearing stage model that includes alternative rearing habitats reported in the literature (e.g., floodplains, off-channel and tributaries), defines rules of habitat use based on instream conditions, and incorporates a juvenile growth module that combines bioenergetics modeling with empirical growth rates. Model outputs reasonably follow observed out-migration patterns and provide a realistic smolt size distribution arriving at the San Francisco Bay. This effort demonstrates the importance of currently “non-critical” habitats (as defined by the Endangered Species Act) for juvenile development, with floodplain habitat contributing to a quarter of out-migrating biomass (despite < 18% availability and <10% of total rearing days), and off-channel growth being one of the most sensitive parameters (explaining ~13% of average juvenile weight variance). The model shows the utility of a simple population model to explore relationships between habitat quality/quantity and juvenile development, and to assist water/environmental management and decision-making processes focused on species recovery.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

The influence of submarine canyons-related processes on recent benthic foraminiferal distribution, Espírito Santo Basin, Southeastern Brazil

The complex topography of submarine canyons may result in different composition of benthic foraminifera assemblages. To understand how trophic, hydrological and sedimentological conditions in submarine canyons can influence the distribution of benthic foraminifera, and to use this information to corroborate paleoenvironmental interpretations for the Holocene, we investigated recent benthic foraminiferal assemblages (total fauna >63 μm) and sedimentological data in two canyons (CANWN and CAND) in the Espírito Santo Basin (ESB) between 18°20' and 21°20' S. Surface sediment samples (0–2 cm) were collected inside the canyons (150 to 1300 m water depth) and in shelf-slope adjacent transects (50 to 1300 m water depth). The density, taxonomic diversity, and assemblage composition of benthic foraminifera change with depth and location. The distinct ecological preferences of the most abundant taxa allowed us to recognize five benthic foraminiferal groups. Three groups (V, III, and I) are present in different bathymetric sectors; Group V: outer shelf (50 m), Group III: upper, and middle – lower slope (150 to 400 m), and Group I: middle – lower slope (1000 to 1300 m). Groups II and IV show no characteristic bathymetric distribution and are present only in CAND and in CANWN, respectively. Group V consists of Hanzawaia boueana, Peneroplis planatus, and Quinqueloculina lamarckiana; Group III is dominated by Globocassidulina rossensis and Trifarina spp.; Group I consists of Globocassidulina crassa, Bolivina lowmani, Gavelinopsis versiformis, Alabaminella weddellensis, and Epistominella exigua. The main species in Group II (CAND, 150, 1000 to 1300 m) are Trifarina angulosa, Globocassidulina subglobosa, and Discorbis vilardeboanus. Group IV (middle – lower CANWN, 1000 to 1300 m), consists mainly of agglutinated species Glomospira charoides, Rhabdammina abyssorum, and Psammosphaera fusca. Further, our data suggest that the quantity (and quality) of food supply, hydrodynamic conditions and sediment properties are the main drivers controlling the bathymetric distribution of benthic foraminiferal assemblages in both canyons. The middle – lower CANNW revealed unstable trophic conditions, related to terrigenous sediment input due to turbidity currents. In CAND, the foraminiferal assemblages ecology indicated sufficient organic matter supply that favors species establishment and diversity, indicating a more productive and less unstable environment than in CANWN.

58 GEOSCIENCES↗

DOE OSTI2019

Compositionally Graded High Entropy Alloy with a Strong front and ductile base

Material components with variable properties can be ideal for many advanced applications due to their seamless nature of microstructural transition, cost reduction and high resistance of failure. A compositionally graded AlXCoCrFeNi (x=0.3-0.7) high entropy alloy composite build was additively manufactured using laser engineered net shaping (LENSTM). In this high throughput production process, the elemental composition of Al-Co-Cr-Fe-Ni powders in the hoppers were varied and the feed rates were shifted to create a laminate of Al0.3CoCrFeNi and Al0.7CoCrFeNi layers, with a 500 µm wide transition zone of intermediary composition. The energy-dispersive X-ray spectroscopy along the build direction verified the elemental composition matching closely with the targeted compositions. X-ray diffraction revealed the Al0.3CoCrFeNi to be a single-phase fcc structure whereas Al0.7CoCrFeNi had dual phase fcc + B2/ bcc. Scanning electron microscopy was used to capture the microstructural features in the two layers as well as the transition zone. The massive shift in mechanical properties of hardness, dynamic strength and work hardening rates in this graded composite have been discussed. With this endeavor, the microstructural complexity of HEAs has been combined with the unique advantage of LENSTM to achieve an ingenious path to fabricate materials suited applications demanding variable strength and ductility/toughness.

Gwalani, Bharat↗