Large magnetovolume effect in multifunctional ferromagnet MnSb driven by unconventional magnetostructural coupling
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Oak Ridge National Laboratory (ORNL) worked with Mitsubishi Chemical America, Inc. to develop a highly biodegradable ~100% biobased feedstock for large format additive manufacturing (AM). Together, they developed an AM feedstock based on the biobased polyester, polybutylene succinate (PBS), that is typically used in agriculture and packaging projects. The motivation for this work was to leverage the high degradability of this polymer in AM to create a new avenue for end-of-life disposal of the product. A composite feedstock was developed from PBS, polylactic acid (PLA), and wood flour (WF). While WF improves printability, reduces feedstock cost, and can improve stiffness, it also often results in a loss in tensile strength which can inhibit/limit applications of the material. To recover the loss in tensile strength suffered by including large quantities, up to 30 wt.% WF in the composite, a chain extender was used to compatibilize the different composite constituents with each other. The feedstock was used to 3D-print a demonstration mold for precast concrete catch basins and was tested by casting 750 lbs of concrete. The mold survived the demonstration. Aerobic degradation testing of the composite feedstock showed that it was highly degradable, 40% biodegradation after 90 days, compared to other incumbent biobased feedstocks.
Tidal energy conversion is a relatively new application for additive manufacturing (AM), where the focus has been on fabricating axial-flow turbine blades. AM techniques add material precisely where it is needed, creating more complex shapes with less waste. Cross-flow rotor geometry presents an opportunity for AM to improve rotor performance by fabricating features that cannot be created economically via conventional manufacturing. The challenges associated with using AM in cross-flow design include water resistance and degradation over time while retaining a level of quality equivalent to conventionally machined parts. In this work, AM materials were tested by environmentally conditioning samples in a seawater tank for 5 months, followed by performance and phase-resolved load testing of laboratory-scale rotors in a hydraulic flume. We found that while metals like titanium and Inconel have excellent performance in marine environments, achieving the desired geometry and performance is difficult. Thermoplastics degraded in seawater but were easier to form into desired geometries and could exceed the performance of an aluminum control rotor. Warping and surface finish were significant detractors from AM rotor performance. These results suggest that the primary benefits of using AM for cross-flow rotors is to quickly fabricate and test unconventional rotor geometries.
Eurasian mammoths (Mammuthus) underwent substantial modifications in molar morphology as later-diverging species evolved progressively thinner enamel and increased enamel crest complexity. These features have been hypothesized to reduce whole-tooth wear and extend dental longevity as increasingly graze-dominated diets evolved within the lineage. This hypothesis has yet to be directly tested. Here, in this study, we developed an in-silico wear model using experimentally derived wear rates from fossil and extant proboscidean dental tissues. The models revealed that shifts in tissue topology do not affect whole-tooth wear rate, as inverse trends in lamellar frequency and enamel thickness preserve a consistent surface enamel area fraction; the determining factor of wear. Rather, topological shifts produce a wear-emergent secondary occlusal surface with greater numbers of triturating crests that create a regular, low-relief, file-like shearing pavement. These changes in occlusal architecture likely directly impacted the mastication capacity of Mammuthus dentitions, facilitating their dietary expansion to incorporate fibrous, lower-nutrient graze.
Refractory high-entropy alloys (RHEAs) are promising candidates for next-generation nuclear and high-temperature applications. Among many approaches to manufacture RHEAs, additive manufacturing (AM) represents the most recent and advanced metal manufacturing method which allows near-net-shape manufacturing to reduce material waste and post-processing time. However, performance of AM RHEAs under complex irradiation conditions remains largely unexplored. Here, in this study, we demonstrate for the first time the response of directed energy deposition (DED) AM quaternary RHEAs (HfTaVW, CrTaVW) subjected to sequential dual-beam ion irradiation, consisting of helium pre-implantation followed by high-dose heavy ion bombardment. Compositions of DED AM RHEAs were selected using Monte Carlo (MC) simulations based on a cluster expansion (CE) Hamiltonian parameterized by density functional theory (DFT). Post-irradiation microstructural characterization revealed that the AM RHEA maintained remarkable stability, with suppressed helium bubble growth and reduced defect accumulation compared to conventional alloys. Even at high doses (∼100 dpa), the alloy exhibited no void swelling, a low density of dislocation loops, and no evidence of severe degradation. These results highlight the intrinsic ability of AM-derived microstructures and multicomponent chemistry to synergistically mitigate irradiation effects. Our findings establish AM RHEAs as a class of materials with superior resistance to radiation damage under conditions relevant to advanced fusion and fission environments and demonstrate the importance of sequential ion beam studies in evaluating their long-term performance.
Multimodal luminescent materials, while promising for anti-counterfeiting, often lack dynamic time-dependent responses and controllable spatial distribution, limiting their encryption capabilities in the spatiotemporal dimension. Here, this work presents a coordinated control strategy based on entropy and defect engineering, and uses a backpropagation (BP) neural network for material screening to successfully prepare spinel Mg 0.8 (Fe 0.04 Co 0.04 Ni 0.04 Cu 0.04 Zn 0.04 )Cr 2 O 4 (MgA 5 CO) phosphors with time-dependent dynamic luminescence behavior. This phosphor simultaneously activated the d-d transition luminescence (∼618 nm) derived from Co 2+ /Cr 3+ and the defect luminescence (∼398 nm) related to zinc vacancies (V Zn ) in a single-phase solid solution. The phosphor exhibits a time-dependent color evolution from pink to purple under fixed-wavelength excitation, due to the different excited-state dynamics and decay lifetimes associated with the d-d transition and defect luminescence. Structural characterization and spectral analysis confirmed the existence of V Zn and its significant role in defect luminescence process. The fluorescent and dynamic luminescent properties of entropy-based spinel oxide enable its use in advanced anti-counterfeiting applications like fingerprint recognition and color-changing dedicated anti-counterfeiting mark, showing promise in high-end and time-dynamic anti-counterfeiting fields. This research not only developed a new type of fluorescent dynamic anti-counterfeiting material, but also provided a new idea for constructing advanced optical functional materials with multiple luminescence mechanisms.
Additively manufactured (AM) metals offer the potential for customizable, cost-effective components, but qualification and certification are crucial. Key to this process is understanding pore dynamics under stress, typically analyzed using micro-computed tomography. This study introduces laboratory-scale “betatron” x-rays from laser wakefield acceleration as a high-throughput alternative for x-ray tomography of advanced materials, such as AM AlSi10Mg alloys. Coupled with 3D finite element modeling, this method provides detailed insights into stress-porosity interactions. The approach delivers high-resolution scans, revealing that pore shape and local triaxiality significantly influence fracture dynamics, supporting advanced material characterization. This work also demonstrates the potential and versatility of laser-betatron x-ray μCT for generating large datasets to accelerate our understanding of the stochastic, process-specific nature of pore formation in AM alloys.
To address the significant productivity challenges associated with the qualification and certification (Q&C) tasks of additively manufactured (AM) parts, which have traditionally relied on rigorous post‐build inspection and testing, we propose an integrated framework that combines model‐based qualification and certification (MBQ&C) with autonomous additive manufacturing (AAM). MBQ&C employs high‐fidelity predictive models, developed within the Integrated Computational Materials Engineering (ICME) paradigm, to simulate process–structure–property–performance relationships for assessing a part’s fitness for use. Since predictive models are commonly machine learning (ML)-based or reduced-order surrogates of validated physics models, they run efficiently, enabling timely inference. In parallel, the self-driving AAM utilises ML-based adaptive, closed‐loop control strategies to avoid, mitigate, or repair defects and anomalies during fabrication, thereby increasing the likelihood of producing acceptable parts. A key feature of the combined AAM-MBQ&C framework is that predictive models explicitly incorporate defects or anomalies that persist after the build, using instance-specific data captured via in-situ sensing. This customisation enables a build‐specific assessment of fitness for use, rather than relying on nominal or generic parameters. Such individualised evaluation provides a robust basis for Q&C-related acceptance decisions relating to each build. Additionally, the rapid solution capabilities of ML or reduced-order models enable the determination of a part’s suitability for service shortly after build completion. As the framework matures, it has the potential to substantially reduce reliance on conventional point‐design approaches—such as time‐consuming post‐build computed tomography scanning and costly destructive testing. Thus, the AAM-MBQ&C framework represents a transformative, scalable strategy for quality assurance of AM components, as parts produced within a stable, validated, and certified envelope can be certified with reduced testing. Key benefits include: (1) significant gains in Q&C productivity through efficient, model-centric assessment; (2) performance-based classification of defects into critical and non-critical categories; (3) the ability to predict potential deviations in the performance of parts affected by real-time, adaptive process control interventions relative to those produced under a certified process, and (4) the enabling of virtual Q&C for service environments that are difficult, hazardous, or impractical to access or reproduce experimentally. Collectively, these capabilities strengthen the business case for AM, particularly for high‐consequence and mission‐critical applications. Finally, although this work focuses on powder-based AM, the proposed techniques could be extended to AM processes employing alternative feedstock forms.
The topological magnet MnBi2Te4 (MBT), with gapped topological surface state, is an attractive platform for realizing quantum anomalous Hall and axion insulator states. However, the experimentally observed surface state gaps fail to meet theoretical predictions, although the exact mechanism behind the gap suppression has been debated. Recent theoretical studies suggest that intrinsic antisite defects push the topological surface state away from the MBT surface, closing its gap and making it less accessible to scanning probe experiments. Here, we report on the local effect of defects on the MBT surface states and demonstrate that high defect concentrations lead to a displacement of the surface states well into the MBT crystal, validating the theorized mechanism. The local and global influence of antisite defects on the topological surface states are studied with samples of varying defect densities by combining scanning tunneling microscopy, angle-resolved photoemission spectroscopy, and density functional theory. Our findings identify a combination of increased defect density and reduced defect spacing as the primary factors underlying the displacement of the surface states and suppression of surface gap, guiding further development of topological quantum materials.
Uranyl oxy-hydroxy-hydrate minerals are common alteration products of uraninite (UO2+x) which is chemically and structurally analogous to uranium dioxide nuclear fuel. Therefore, structural and spectroscopic investigations of these alteration minerals and their analogous anthropogenic counterparts can provide insight into the environmental behavior of nuclear fuel cycle materials. Previously, we compiled available vibrational spectroscopic data for uranyl minerals in the Compendium of Uranium Raman and Infrared Experimental Spectra (CURIES) and found that only 37% of known uranyl oxy-hydroxy-hydrate minerals had spectra readily available in the literature and existing databases for inclusion therein. Furthermore, no available infrared spectra for this mineral group were included in CURIES. To expand our understanding of the spectroscopic features of uranyl oxy-hydroxy-hydrates and the structural origins thereof, we collected, and now include in CURIES, Raman and infrared spectra for an additional 12 uranyl hydroxide phases. To better understand the impact of structural and compositional variations of these phases on their spectroscopic features, we compare Raman spectra of different anion sheet topological groups and of analogous phases hosting different counter cations. We identify spectroscopic variations related to differences in equatorial bonding and structural changes as a result of cation substitution. We also prepare a uranyl hydroxide phase via hydrolysis of uranyl fluoride (UO2F2) as an analog of hydrolysis reactions that occur in nuclear fuel cycle materials; and we find that the alteration product of UO2F2, despite chemical and structural similarities to uranyl oxy-hydroxy-hydrate minerals, is readily distinguishable from related mineral phases using Raman spectroscopy. In this work, we provide new insights into the structural origins of spectroscopic features in uranyl oxy-hydroxy-hydrate minerals, improve the average Raman spectrum for this group of minerals, and thereby improve capabilities for identifying these mineral species and related anthropogenic phases using Raman spectroscopy.
To address the high cost, cobalt dependency, and resource constraints typical of conventional high-entropy oxide (HEO) anodes, this study reports the successful synthesis of two Co-free, six-component spinel-type HEOs(FeNiCrMnZnAl) 3 O 4 (HEO-Al) and (FeNiCrMnZnMg) 3 O 4 (HEO-Mg), via a sol-gel method. The distinct effects of Al 3+ and Mg 2+ incorporation on the electrochemical performance and lithium storage kinetics were systematically investigated. XRD, Raman, and TEM characterizations confirm that both materials possess a pure spinel phase, uniform particle size, and homogeneous elemental distribution. Notably, electrochemical evaluations reveal that HEO-Al delivers a superior reversible capacity of 480.7 mAh g −1 after 100 cycles at 0.1 A g −1 , and maintains 354.5 mAh g −1 after 1000 long-term cycles at 1 A g −1 , significantly outperforming HEO-Mg. Kinetic analysis indicates that HEO-Al exhibits lower charge transfer resistance, a higher Li + diffusion coefficient, and a pseudocapacitive contribution of up to 82%. Furthermore, these findings demonstrate that Al substitution effectively optimizes the structural stability and lithium storage kinetics of Co-free HEOs, providing a viable strategy for designing low-cost, highly stable HEO anode systems.
Additive manufacturing (AM) potentially enables fabrication and repair of plasma facing components (PFCs) of tungsten. However, deformation mechanisms in AM-fabricated tungsten under service-relevant thermomechanical conditions remain unknown majorly due to challenges in achieving crack-free W. This study reveals the deformation mechanisms operative under tension at 800 °C and 1200 °C in the electron beam melting powder bed fusion (EBM-PBF) fabricated W. Textured columnar grains with mixed <001 >/<111 >|| build-direction were observed. Strong anisotropy in tensile properties persisted across test temperatures, and all specimens exhibited extensive deformation-induced banding phenomena. Grain boundary character analysis of the deformed specimens indicated that these deformation bands were kink bands with tilt grain boundaries prominently present at the band-matrix interface. Interestingly, the material within the kink bands rotated toward higher resolved shear stress, providing insights into the origins of kink band formation in body-centered cubic refractory metals. Intragranular misorientation axis analysis revealed that plasticity was dominated by {110} <111 > slip at 800 °C, whereas additional (213)[11̄1] and (112)[11̄1] slip systems activated at 1200 °C. A dense low-angle boundary networks observed near fractured surface indicated the onset of dynamic recrystallization. Results reveal plasticity governing mechanisms in AM-fabricated W under power plant-relevant conditions, and provide insights into kink band attributes in refractory metals.
Additive Manufacturing (AM) of alloys holds significant promise as a disruptive technology in various industries, yet its adoption is often hindered by challenges in achieving consistent part quality. These issues are primarily due to the complex process-microstructure-property (PSP) relationships inherent to AM. Computational models can greatly aid in understanding these relationships, but their widespread impact and adoption has been limited by a lack of validated, open-source, and computationally efficient PSP modeling frameworks and hardware limitations. Here, this study leverages the ExaAM software suite and data from the AMBench-2018 series of laser powder bed fusion (LPBF) benchmark experiments to perform a comprehensive model assessment, including verification, validation, sensitivity analysis, and uncertainty quantification. The RADICAL-EnTK workflow manager was used to perform an ensemble of heat transport, solidification, and mechanical response simulations on the exascale computer Frontier, considering uncertainties in critical model inputs such as laser spot size and nucleation parameters, and consisting of 125 explicit grain structure simulations and 7875 crystal plasticity simulations. For a selected location within the Inconel 625 AMBench-2018 test artifact, sensitivity analysis and uncertainty quantification were performed using the predicted distributions of grain structure and mechanical properties. Qualitative agreement was found between the predicted grain size and texture and the observed AMBench-2018 microstructure, the mean predicted yield stress was within 5% of the experimental measurement mean, and the mean predicted engineering stress at 5% strain was within 10% of the experimental measurement mean. The insights gained from development and validation of the ExaAM PSP modeling framework will help guide future directions for enhancing the credibility and reliability of PSP models in AM, thereby accelerating the adoption of AM technologies in various industries.
Residual stresses cause geometric distortion and affect mechanical performance of additively manufactured structures, yet they are notoriously difficult to assess and predict. Distortion (warpage) can drive parts outside dimensional tolerance limits, leading to part rejection or rework. For parts that meet tolerance, locked-in residual stress fields can affect structural integrity during operation, particularly subcritical cracking by fatigue, creep, or corrosion. This work develops benchmark data for a common additive manufacturing process (Wire Arc Additive Manufacturing) that can be applied for calibration and validation of physical process models that predict residual stress fields. The work includes design of two different samples of differing geometry, detailed manufacturing records for a set of physical samples, and an extensive set of residual stress measurement data developed using two diverse techniques (the contour method and neutron diffraction). An initial application of the work is also reported, where a modeling challenge was issued to secure residual stress model predictions from two independent laboratories that were blind to residual stress measurement data. These initial blind residual stress predictions show significant discrepancies relative to the measurement data, illustrating the potential value of the underlying validation data. An open repository for this work, including the sample designs, manufacturing process records, and the residual stress data, is also provided for future application in non-blind validation efforts.
Advances in manufacturing techniques are viewed as enabling technologies for development of high performance nuclear fuel forms that couple high uranium density with improvements to key properties such as thermal conductivity unattainable through conventional fabrication routes. Additive manufacturing (AM) enables the fabrication of complex fuel geometries that are difficult or impossible to achieve using conventional manufacturing methods. Melting-based AM processes, such as laser powder bed fusion (LPBF), provide high geometric resolution (>200 µm depending on the feature) across a variety of metal alloys, including those suitable for high-temperature fuel cladding applications, such as Nb, W, and Mo. Molybdenum is particularly attractive due to its high thermal conductivity, low thermal expansion, and excellent mechanical stability at elevated temperatures. However, its high melting temperature and brittle nature at low temperatures pose significant challenges during LPBF processing. Rapid solidification inherent to LPBF induces high residual stresses, often leading to post-solidification cracking, which limits the manufacturability of Mo components via this method.
This work presents a physics-informed framework for predicting solidification morphology and defect susceptibility in additively manufactured Ti–22Al–25Nb across a broad processing space. The framework integrates solidification microstructure selection (SMS) analysis with a single-track defect-based printability map to establish a unified methodology linking processing parameters to both interfacial morphology and manufacturability. Thermal gradients G and solidification rates R are first computed using the Thermo-Calc Additive Manufacturing (TC-AM) module, a finite-interface-dissipation (FID) phase-field (PF) model coupled with CALPHAD method is then employed to systematically distinguish planar and dendritic regimes as functions of $G$ and $R$. By superimposing the printability map onto the morphology projections, a comprehensive process–structure framework is obtained. Across most processing conditions, the predicted microstructure is predominantly dendritic, while planar growth emerges only under selected laser power $P$ and scan speed $v$ combinations. In addition to morphology classification, the framework quantifies the dendritic area fraction and introduces a width-based morphology descriptor to characterize the spatial extent of planar/dendritic regions within the melt pool. It provides mechanistic insight into the interplay between solidification physics and defect formation, offering practical guidance for parameter selection and microstructural control in Ti–22Al–25Nb additive manufacturing (AM).
Synergizing wire arc-directed energy deposition (WA-DED) additive manufacturing (AM) with particle-strengthened creep strength-enhanced ferritic (CSEF) steels enables fabrication and repair of critical power-plant components. Investigations focused on fusion-welded particle-strengthened CSEF steels, such as Grade 91 steel, have linked microstructurally heterogeneous regions—forming due to heat affected zones (HAZ)—with premature failure during elevated temperature service. Fusion-based AM, including WA-DED, likewise generates microstructurally and plastically heterogeneous regions due to spatiotemporally varying thermokinetics during deposition. However, works investigating such microstructural heterogeneities, their implications for mechanical behavior, and strategies to mitigate their formation remain scarce. This work identifies microstructurally and plastically heterogeneous regions within the WA-DED-processed Grade 91 steel. Spatial microhardness variations in the as-fabricated specimen correlate with the variation in the attributes of grain, martensitic microstructure, and precipitates across the fusion zone and HAZ. Digital image correlation-enabled tensile tests performed at 500 °C revealed pronounced deformation localization and a wave-like strain distribution, with wavelength close to the melt pool depth, indicating susceptibility of the as-fabricated components to premature creep failure. Such heterogeneity in microstructural and mechanical behavior was attributed to recurring solid-state phase transformations. Subsequently, an interlayer temperature control strategy was implemented, wherein maintaining interlayer temperature above the martensitic start temperature mitigated the heterogeneous microstructural and plastic response in the as-fabricated condition. Findings open pathways to achieving deformation-localization- and creep-resistant microstructures in WA-DED fabricated particle-strengthened CSEF steel components, reducing reliance on post-welding heat treatments—conventionally required to enhance creep resistance—and enabling on-demand, short lead-time fabrication of next-generation power-plant components.
We report results from searches for new physics models through electron recoils using data collected by the LUX-ZEPLIN experiment during its first two science runs, with a total exposure of 4.2 tonne−years. The observed data are consistent with a background-only hypothesis. Constraints are derived for electromagnetic interactions of solar neutrinos, solar axionlike particles (ALPs), mirror dark matter, and the absorption of bosonic dark matter candidates. The inverse Primakoff process for 57 Fe deexcitation solar ALPs is considered for the first time. These results represent the most stringent constraints to date on keV-scale Primakoff and 57 Fe solar ALPs, bosonic dark matter, mirror dark matter, and neutrino millicharge, while remaining competitive for the other signal models investigated.