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At least 1,369 records · Page 76

Extrusion‐Spheronization of Mock Energetic Materials

The primary method for producing plastic bonded explosive (PBX) granules, or “prills”, has remained relatively unchanged for 70 years despite the complex nature of the process. In this work, we demonstrate the feasibility of using an extrusion‐spheronization technique to produce prills for PBX applications. We begin by detailing an inert formulation with similar properties of PBXs and then demonstrate the extrusion‐spheronization processing of these materials. A study is then performed where the spheronization process time of the extruded materials is varied and the resultant prills are morphologically characterized. Further, these prills are then pressed into high‐density articles and subject to compression testing to elucidate trends in process, properties, and performance. It was found that, for our formulation (95 wt.% melamine/5 wt.% polymer binder) and process, a spheronization time of 60 s yielded relatively uniform particles that exhibited improved poured, tapped, and pressed densities. Mechanical strength did not have a strong trend with process time as all spheronized materials had similar peak compression stress at failure. After further optimization, extrusion‐spheronization may be a promising path for future PBX formulation.

extrusion spheronization

Insulating ground state and 2−𝑘 magnetic structure of candidate Weyl hydrogen-atom K2⁢Mn3⁢(AsO4)3

The ideal Weyl "hydrogen-atom" semimetal exhibits only a single pair of Weyl nodes and no other trivial states at the Fermi energy. Such a material would be a panacea in the study of Weyl quasi-particles, allowing direct unambiguous observation of their topological properties. The alluaudite-like K2⁢Mn3⁢(AsO4)3 compound was recently proposed as such a material. Here, we use comprehensive experimental work and first-principle calculations to assess this prediction. We find K2⁢Mn3⁢(AsO4)3 crystallizes in the 𝐶⁢2/𝑐 symmetry with a quasi-one-dimensional Mn sublattice, growing as small needle-like crystals. Bulk property measurements reveal magnetic transitions at ≈8 and ≈4 K, which neutron scattering experiments show correspond to two distinct magnetic orders, first a partially ordered ferrimagnetic 𝐤𝟏=(0,0,0) structure at 8 K and a second transition of 𝐤𝟐=(1,0,0) at 4 K to a fully ordered state. Below the second transition, both ordering vectors are necessary to describe the complex magnetic structure with modulated spin magnitudes. Both of the best-fit magnetic structures in this work are found to break the symmetry necessary for the generation of Weyl nodes, though one of the magnetic structures allowed by 𝐤𝟏 does preserve this symmetry. However, the crystals are optically transparent and ellipsometry measurements reveal a large band gap, undermining expectations of semimetallic behavior. Density functional theory calculations predict an insulating antiferromagnetic ground state, in contrast to previous reports, and suggest potential frustration on the magnetic sublattice. Given the wide tunability of the alluaudite structure, we consider ways to push the system closer to a semimetallic state.

Taddei, Keith M [Argonne National Laboratory]

Toward Continuous, Oriented Covalent Organic Framework Membranes for Precise Molecular Separations

The goal of achieving energy-efficient, precise molecular separations has motivated interest in developing and employing porous crystalline frameworks as membrane materials. Covalent organic frameworks (COFs) are ordered crystalline matrices composed of covalently bonded organic monomers and are synthesized via reversible reticular chemistry. COFs possess high porosity, structural tunability, and chemical and thermal stability, making them ideally suited for emerging, high-value membrane separation processes, such as ion separations, organic solvent nanofiltration, and gas separations. Although a range of COF membranes have been fabricated and tested in the past decade, these membranes are primarily polycrystalline, weakly crystalline, and/or discontinuous, resulting in suboptimal performance. In this review, we identify the properties that make COFs well-suited as membrane materials, while critically outlining the shortcomings of existing disordered COF membranes. We then highlight the recent emergence of highly crystalline, continuous, oriented two-dimensional COF membranes as a promising path forward for highly selective molecular separations. These continuous, oriented COF membranes exhibit tunable one-dimensional nanochannels, allowing for ultrafast molecular transport and precise species selectivity, thereby expanding the set of separations that can be practically achieved with membrane systems. We discuss synthesis and modification techniques that result in continuous, oriented COF membranes and evaluate the performance of such membranes for a variety of molecular separations. We conclude by identifying ongoing challenges in the development of COF membranes and outlining the future of their applications in molecular separations, which will necessarily rely on advancements in the synthesis of continuous, oriented membranes.

COF modification

A machine-learning approach to measure 3D sample properties from 2D Transmission Electron Microscopy images

Transmission Electron Microscopy (TEM) is a powerful tool for the characterization of materials at the nanoscale; however, its inherent two-dimensional (2D) nature poses significant challenges to accurately measure three-dimensional (3D) properties. We introduce a supervised machine-learning model that predicts 3D structural information, such as sample thickness and curvature, from a series of conventional 2D TEM images. The model, a U-Net convolutional neural network, is trained on a large synthetic dataset generated from dynamical diffraction simulations that model TEM’s complex, nonlinear image formation, accounting for sample thickness and curvature. This physically realistic framework enables exploration of a broad parameter space impractical to sample experimentally. We demonstrate that the trained model has accurate predictions for experimental single-crystal silicon samples, achieving performance comparable to established measurement techniques. This work highlights the critical role of robust, simulation-based training in overcoming the limitations of real-world imaging artifacts and inconsistent sample geometries. By integrating machine learning with numerical simulations, we offer an efficient and scalable framework for quantitative TEM analysis, paving the way for more sophisticated 3D characterization of complex materials.

Dynamical diffraction

Etching-assisted upcycling of Ni-lean to Ni-rich cathode materials

Upcycling is recognized as a sustainable recycling approach for spent lithium-ion batteries. However, existing upcycling methods typically involve intricate pretreatment or post-treatment steps, complicating their practical application. Here, in this study, we propose a straightforward, etching-assisted upcycling method that effectively transforms polycrystalline Ni-lean cathodes into high-performance single crystal Ni-rich cathodes. During the etching step, nickel acetate was dissolved into acetic acid and then polycrystalline NMC111 are etched in the solution. Finally, polycrystalline NMC111 are converted into single crystal particles coated with amorphous nickel acetate. This significantly enhances elemental diffusion during subsequent sintering by minimizing both particle size and the contact distance between NMC111 and nickel acetate. As elemental diffusion is improved and acetate ions decompose completely during sintering, the process requires neither additional pretreatment nor post-treatment. The resulting cathode materials (Etched-UP622) exhibit superior structural and electrochemical properties compared to the Control622, achieving an energy density of 719.7 Wh/kg, approximately 56.7 mAh/g higher than Control622 and 125.5 Wh/kg higher than NMC111. Etched-UP622 also delivers higher discharge capacity, improved rate performance and cycling stability, surpassing Control622 and NMC111. Meanwhile, NMC811 also can be synthesized by the proposed strategy, and the discharge capacity can reach 166.9 mAh/g at 1C, similar to 14 mAh/g higher than Control811. Overall, this etching-assisted strategy simplifies the upcycling process and offers a scalable, sustainable route for producing high-quality cathode materials.

Acid etching

Coal Enhanced PEEK Filament Production for Additive Manufacturing in Industrial Services

The project (Award DE-FE0032146), led by Baker Hughes in collaboration with the University of Wyoming, aims to develop composite PEEK (Polyether-ether-ketone) materials enhanced using coal-derived graphene-based additives suitable for additive manufacturing (3D printing). Coal char (CC), graphene oxide (GO), and reduced graphene oxide (rGO), derived from Powder River Basin (PRB) coal, were successfully integrated into commercial PEEK feedstock. The composite PEEK materials demonstrated tensile and flexural strengths and modulus, Shore hardness, and thermal properties similar to unfilled PEEK. Dielectric strength of 0.5% GO/PEEK is twice that of unfilled PEEK. However, tensile elongation and Izod impact toughness of the composite materials are lower than unfilled PEEK. The 10% CC/PEEK material also shows good recyclability albeit with slightly increased glass transition and cold crystallization temperatures. Filaments of the composite PEEK materials were fabricated using a Filabot system. 3D printing of the composite PEEK initially encountered feeding stoppage caused by the non-uniform diameter of the filament, which was resolved by reducing the nominal diameter from 1.75 to 1.65 mm. The printability of the composite PEEK filaments is limited in geometry and build time, driven by differences in base PEEK feedstock from the commercial PEEK filament at printing conditions. Prototype part printed using the composite filaments shows inconsistent bead width and bead interruption resulting in porosity. Preliminary process and economic evaluation using PRB coal char estimates the cost of GO to be $0.5/lb. Considering the small fraction expected in the composite PEEK, the GO cost is several orders of magnitude lower than the commercial PEEK filament. It is recommended that the printability of composite PEEK filaments to be improved by optimizing the composite PEEK material at the printing conditions and reducing the variations in filament extrusion. Also important is to identify the mechanisms of how coal-derived additives affect the composite PEEK performance and printing characteristics to allow customized material design and processing for target performance.

01 COAL, LIGNITE, AND PEAT

Conductive Organometallic Polymers from Soluble Superatom Ions

Superatomic crystals comprising ligand-capped, metal chalcogenide clusters and fullerenes are modular materials that exhibit enhanced electronic, magnetic, and thermal conductivity properties. We find that neutral, M 4 S 4 (M = Fe, Co) clusters stabilized with N -heterocyclic carbenes (NHCs) can transfer charge to C 60 fullerene to form binary superatomic crystals. Notably, these compounds are soluble in various organic solvents, allowing their properties to be investigated in solution, unlike traditional fullerene-based superatomic crystals. The ion pairs can be further assembled into organometallic polymers using Janus-bis(NHCs) to cross-link the oxidized M 4 S 4 units. We show that the superatomic polymers are more conductive than both the precursor superatomic crystals and the polymers containing only neutral M 4 S 4 clusters. Similar conductivity values can be obtained when neutral M 4 S 4 –NHC polymers are doped with solutions of C 60 fullerene. These findings demonstrate that next generation superatomic materials can be prepared via the combination of charge transfer and polymerization with appropriate cross-linking agents.

carbon nanomaterials

Microwave dielectric properties of LiNbO$_{\mathbf{3}}$ and AlN at millikelvin temperatures and single-photon power

Electro-optic materials are paramount to achieving efficient and reliable microwave-optical signal transduction in the quantum regime. It is of great interest to investigate the performance of these materials at the quantum level and at cryogenic temperatures to assess their compatibility with superconducting circuit-based quantum systems. In this work, we present a detailed study of the microwave electric properties of single-crystal bulk LiNbO$_{3}$ and AlN at millikelvin temperatures and at the single-photon level. We characterize the materials' dielectric loss tangent throughout a wide range of electromagnetic power levels in a temperature range from a few tens of millikelvin to above 1~K. Our findings indicate that both materials' loss tangent behavior is consistent with the two-level system model up to a certain power threshold, beyond which it increases logarithmically with power. This suggests that two-level system loss mechanisms dominate at the single-photon level, while additional loss channels become relevant at higher powers and temperatures.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Structural and thermal properties and the origin of the ultralow thermal conductivity in the defect stannite CuIn 2 Se 4

Phase-pure CuIn 2 Se 4 , a ternary metal chalcogenide that forms in a disordered stannite crystal structure, was synthesized to investigate the structure thermal property relationships as well as reveal the origin of the ultralow thermal conductivity this material possesses over a large temperature range. Modeling of the temperature-dependent heat capacity and thermal conductivity revealed distinctive thermal properties and large lattice anharmonicity. Electron localization function calculations highlight the asymmetric bonding inherent to CuIn 2 Se 4 , which together with lattice anharmonicity directly impacts the thermal properties. Our findings reveal the specific atomic arrangement and bonding governing the thermal properties of this ternary metal chalcogenide. Our findings underscore the specific atomic arrangement and bonding governing the thermal properties in this ternary chalcogenide. This study advances the fundamental understanding of stannites, and our findings can be applied to these and other multinary metal chalcogenides of interest for applications where low thermal conductivity is desirable.

36 MATERIALS SCIENCE

Models and Algorithms for Equilibrium Analysis of Mixed-Material Nucleic Acid Systems

Dynamic programming algorithms within the NUPACK software suite enable analysis of equilibrium base-pairing properties for complex and test tube ensembles containing arbitrary numbers of interacting nucleic acid strands. Currently, calculations are limited to single-material systems that are either all-RNA or all-DNA. Here, to enable analysis of mixed-material systems that are critical for modern applications in vitro, in situ, and in vivo, we develop physical models and dynamic programming algorithms that allow the material of the system to be specified at nucleotide resolution. Free energy parameter sets are constructed for both RNA/DNA and RNA/2'OMe-RNA mixed-material systems by combining available empirical mixed-material parameters with single-material parameter sets to enable treatment of the full complex and test tube ensembles. New dynamic programming recursions account for the material of each nucleotide throughout the recursive process. For a complex with N nucleotides, the mixed-material dynamic programming algorithms maintain the O(N 3 ) time complexity of the single-material algorithms, enabling efficient calculation of diverse physical quantities over complex and test tube ensembles (e.g., complex partition function, equilibrium complex concentrations, equilibrium base-pairing probabilities, minimum free energy secondary structure(s), and Boltzmann-sampled secondary structures) at a cost increase of roughly 2.0-3.5×. The results of existing single-material algorithms are exactly reproduced when applying the new mixed-material algorithms to single-material systems. Accuracy is significantly enhanced using mixed-material models and algorithms to predict RNA/DNA and RNA/2'OMe-RNA duplex melting temperatures from the experimental literature as well as RNA/DNA melt profiles from new experiments. In conclusion, mixed-material analyses can be performed online using the NUPACK web app (www.nupack.org) or locally using the NUPACK Python module.

2′OMe-RNA

Programmable hydrogels by combining persistent and transient dynamic bonds

Out-of-equilibrium chemistry is currently being applied to polymer systems to mimic the autonomous behavior of biological materials. In this study, hydrogels with self-healing properties were developed that combine persistent crosslinks from dynamic metal-ligand coordination with transient crosslinks from dynamic anhydride bonds. Polymers containing terpyridine ligands and carboxylic acid groups were synthesized and crosslinked with divalent metal ions (Fe 2+ , Ni 2+ , Co 2+ , Zn 2+ , Cu 2+ ). The coordination bonds from terpyridine–metal coordination impart persistent stability, while transient anhydrides formed on treatment with 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride (EDC) temporarily increase crosslink density. Distinct behaviors are observed depending on the choice of metal, with Ni 2+ forming robust, stable networks; Zn 2+ creating moderately dynamic gels; and Cu 2+ yielding highly dynamic, soft materials. Treatment with EDC increased storage moduli significantly, with transient effects lasting up to 280 min depending on the metal ion. Self-healing experiments demonstrated independent contributions from metal coordination and transient anhydrides, enabling recovery of stress and strain under varying conditions. Additionally, complex and reversible 2D stiffness patterns were generated by spatially controlled EDC treatment of Zn 2+ and Cu 2+ hydrogel films, demonstrating programmability and reusability.

Rajawasam, Chamoni W. H. [Miami University, Oxford

Hierarchical Epoxy Structures via Tunable Polymerization-Induced Phase Separation Combined with Additive Manufacturing

Polymerization-induced phase separation (PIPS) allows for the control of thermoset morphologies and properties, enabling the tuning of domain sizes and thermomechanical response. However, its use in generating substructural features in additively manufactured materials has been limited. In this work, we combine epoxy PIPS with UV curable acrylate and rheological modifiers to print nano- to macro-phase separating materials via a two-step, dual-cure approach. This method enables direct ink write printing of hierarchical structures with both controlled morphologies through phase separation and macroscale architecture through print design. We find that formulations for phase-separating materials require judicious incorporation of additives to enable printability and to provide sufficient green strength. Atomic force microscopy-nano infrared mapping reveals tunable, reticulated nano- to micron-scale domains of the resultant multiphase materials and their morphology changes due to additives, resulting in alterations to thermomechanical and tensile properties. Shape memory behavior is also demonstrated through multimaterial additive manufacturing of epoxies with functionally graded internal morphology using active mixing techniques, highlighting this method’s ability to fabricate complex architectures with controlled morphologies and thermomechanical response.

Van Meter, Kylie E [Organic Materials Science, San

Electronic Structures of Iron in Oxide Glasses via 1s3p Resonant Inelastic X-ray Scattering

Electronic structures of iron in glasses are essential for unraveling the effect of transition metals on amorphous networks and controlling the electro-optical and transport properties of advanced glasses and amorphous energy-storing materials. The electronic configurations around iron in glasses, however, remain not well understood due to the structural disorders arising from multiple iron species with distinct valence, coordination, and spin states. Here, the first 1s3p resonant inelastic X-ray scattering (RIXS) for oxide glasses identifies hidden electronic configurations for Fe 2+ and Fe 3+ in amorphous networks. The results allow us to quantify the composition-induced evolution of oxygen ligand–field interactions of high-spin Fe 3d states with varying valence and coordination environments in complex glasses. The distinct electronic structures account for the electronic origins of iron-induced changes in the glass properties. The results offer prospects for a simultaneous probing of valence, coordination, and spin states of transition metals in diverse multicomponent oxide glasses and functional amorphous solids via 1s3p RIXS.

Kim, Yong-Hyun [Seoul National Univ. (Korea, Repub

Effect of Thermomechanical Processing on the Microstructure, Properties, and Work Behavior of a Ti50.5 Ni29.5 Pt20 High-Temperature Shape Memory Alloy

TiNiPt shape memory alloys are particularly promising for use as solid state actuators in environments up to 300 °C, due to a reasonable balance of proper ties, including acceptable work output. However, one of the challenges to commercializing a viable high-temperature shape memory alloy (HTSMA) is to establish the appropriate primary and secondary processing techniques for fabrication of the material in a required product form such as rod and wire. Consequently, a Ti 50.5 Ni 29.5 Pt 20 alloy was processed using several techniques including single- pass high-temperature extrusion, multiple-pass high-temperature extrusion, and cold drawing to produce bar stock, thin rod, and fine wire, respectively. The effects of heat treatment on the hardness, grain size, room temperature tensile properties, and transformation temperatures of hot- and cold-worked material were examined. Basic tensile properties as a function of temperature and the strain-temperature response of the alloy under constant load, for the determination of work output, were also investigated for various forms of the Ti 50.5 Ni 29.5 Pt 20 alloy, including fine wire.

Grain Size

Enhancing Cluster Identification in Atom Probe Tomography Data Using Transfer Learning

Atom probe tomography (APT) has enabled the direct visualization of solute clusters, providing valuable insights into material structures. This clustering is crucial for understanding the nanoscale composition and behavior of materials, which can significantly influence their mechanical and physical properties. However, the widely used clustering methods in the APT community face challenges such as subjective parametric selection and limited applicability, particularly in dealing with overlapping clusters, nested clusters, and artifacts across different scales, such as precipitates and dislocations. To address these challenges, we present a framework based on density-based cluster analysis that aims to be less dependent on user input, reproducible, and robust.

Density-based clustering

Segmentation method comparison for residual fiber length measurement across tiled microscopy images

Fiber length distribution (FLD), in part, governs mechanical properties in discontinuous fiber composites, yet manual measurement methods limit the high-throughput characterization needed for materials design optimization. This study compares deep learning segmentation approaches for automated FLD measurement in large-field microscopy, evaluating how method choice affects the microstructural descriptors used in structure-property-processing relationships. A critical challenge is that high-resolution microscopy images (10,000×10,000 pixels) must be tiled for deep learning analysis, fragmenting fibers at boundaries. We demonstrate that segmentation method proves crucial for measurement accuracy. For example, instance segmentation with Slicing Aided Hyper Inference (SAHI) preserves individual fiber integrity across tiles while semantic segmentation prioritizes speed. Comparing against manual measurement of extracted carbon fibers, YOLOv11-SAHI matched manual ground truth (238 μm weighted mean) with 40x speedup (4.5 vs 167 minutes per image). U-Net provides rapid quantification although it is at the cost of reduced accuracy due only reliably measuring stand-alone fibers. Our comparative analysis reveals that instance segmentation with SAHI better preserves length measurements while semantic segmentation prioritizes speed, providing empirical guidance for method selection. The characterization provides essential inputs for mechanical property prediction models and inverse design workflows, accelerating composite materials development cycles.

Additive manufacturing

Symmetry-protected electronic metastability in an optically driven cuprate ladder

Optically excited quantum materials exhibit non-equilibrium states with remarkable emergent properties, but these phenomena are usually transient, decaying on picosecond timescales and limiting practical applications. Advancing the design and control of non-equilibrium phases requires the development of targeted strategies to achieve long-lived, metastable phases. Here, in this study, we report the discovery of symmetry-protected electronic metastability in the model cuprate ladder Sr 14 Cu 24 O 41 . Using femtosecond resonant X-ray scattering and spectroscopy, we show that this metastability is driven by a transfer of holes from chain-like charge reservoirs into the ladders. This ultrafast charge redistribution arises from the optical dressing and activation of a hopping pathway that is forbidden by symmetry at equilibrium. Relaxation back to the ground state is, hence, suppressed after the pump coherence dissipates. Our findings highlight how dressing materials with electromagnetic fields can dynamically activate terms in the electronic Hamiltonian, and provide a rational design strategy for non-equilibrium phases of matter.

36 MATERIALS SCIENCE