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At least 667 records · Page 37

A review of processable high temperature resistant addition-type laminating resins

An important finding that resulted from research that was conducted to develop improved ablative resins was the discovery of a novel approach to synthesize processable high temperature resistant polymers. Low molecular weight polyimide prepolymers end-capped with norbornene groups were polymerized into thermo-oxidatively stable modified polyimides without the evolution of void producing volatile materials. This paper reviews basic studies that were performed using model compounds to elucidate the polymerization mechanism of the so-called addition-type polyimides. The fabrication and properties of polyimide/graphite fiber composites using A-type polyimide prepolymer as the matrix are described. An alternate method for preparing processable A-type polyimides by means of in situ polymerization of monomeric reactants on the fiber reinforcement is also described. Polyimide/graphite fiber composite performance at elevated temperatures is presented for A-type polyimides.

Serafini, T. T.↗

Atomic cooperation in enhancing magnetism: (Fe, Cu)-doped CeCo 5

Developing permanent magnet alloys with decreased critical elements (e.g., Nd, Dy, and Co) requires identifying compositions and structures with uniaxial magneto-crystalline anisotropy energy (MAE), large magnetization, and a high ferromagnetic transition temperature (Curie temperature - T C ). One approach to minimizing the critical elements in potential permanent magnet alloys is to use overly produced Ce, which is less critical. Furthermore, reducing Co content in RCo 5 (R = Rare Earth) alloys is necessary since Co is also a critical element. An obvious choice for decreasing Co content is a substitution with non-critical Fe. However, the Fe is not stable in the lattice due to the reduced number of d -electrons. Concomitant substitution of Cu stabilizes Fe substitution. Employing first-principles electronic structure theory, we identify the weakly localized nature of cobalt in CeCo 5 , which causes high uniaxial magnetic anisotropy of ~10 MJ/m 3 . In contrast, substituted Cu delocalizes the Co’s 3 d -states, resulting in lower anisotropy. Calculations show that 10% Cu can stabilize 20% Fe subsituted for Co, which significantly enhances magnetic moment in the Ce (Co, Fe, Cu) 5 . We report this prediction is in good agreement with a single-crystal experiment in which the optimal composition was identified to be 15% of Fe and 12% Cu. The competitive non-equivalent Co sites preferred by Cu and Fe, a unique electronic structure including exchange and crystal field splitting, and rigid band shift variation are borne by 3 d states of Co, Fe, and Cu around the Fermi level, all play an essential role in tuning the magnetic properties.

36 MATERIALS SCIENCE↗

Additively manufactured refractory high-entropy alloys with superior radiation resistance

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.

36 MATERIALS SCIENCE↗

Charm and bottom hadrons in hot hadronic matter

Heavy quarks, and the hadrons containing them, are excellent probes of the QCD medium formed in high-energy heavy-ion collisions, as they provide essential information on the transport properties of the medium and how quarks color-neutralize into hadrons. Large theoretical and phenomenological efforts have been dedicated thus far to assess the diffusion of charm and bottom quarks in the quark–gluon plasma and their subsequent hadronization into heavy-flavor (HF) hadrons. However, the fireball formed in heavy-ion collisions also features an extended hadronic phase, and therefore any quantitative analysis of experimental observables needs to account for the rescattering of charm and bottom hadrons. This is further reinforced by the presence of a QCD cross-over transition and the notion that the interaction strength is maximal in the vicinity of the pseudo-critical temperature. We review existing approaches for evaluating the interactions of open HF hadrons in a hadronic heat bath and the pertinent results for scattering amplitudes, spectral functions and transport coefficients. While most of the work to date has focused on D -mesons, we also discuss excited states as well as HF baryons and the bottom sector. Both the HF hadro-chemistry and bottom observables will play a key role in future experimental measurements. We also conduct a survey of transport calculations in heavy-ion collisions that have included effects of hadronic HF diffusion and assess its impact on various observables.

effective field theories↗

A first principles approach for determining solute effect on electrical resistivity of Aluminum solid solution

There are no general approaches for predicting the effect of solutes on electrical resistivity changes in aluminum (Al) solid solutions. Here, we introduce a first principles-based approach for predicting temperature-dependent electrical resistivity of Al solid solutions. A combination of electronic structure methods was applied to calculate electronic scattering effects on chemical disorder and temperature induced atomic vibrations or phonons. Our calculations are validated by contrasting experimental resistivity measurements for two elements in Al solid solution: at 0.3 at. % concentration, Sn (an sp-valence solute) increases the residual resistivity by 0.2 μΩ·m, whereas Zr (a d-valence solute) causes a 2.5 μΩ·m increase. This trend may deviate for solute elements in Al that form semiconductors in pure state, like Si. Our findings provide an understanding of the role of valence electron character of solute atoms in determining electrical resistivity of Al alloys.

Samolyuk, German [ORNL] (ORCID:0000000168778255)↗

Ripening of Rh Nanoparticle Catalysts in Reverse Water–Gas Shift via a Data-Driven Model Combining Physics, Theory, and Experiment

Degradation via sintering is an ongoing challenge that impedes the broad commercial success of supported metallic nanoparticle catalysts. To mitigate degradation via informed catalyst design and process operations, here we aim to disambiguate the underlying mechanisms of sintering by combining theory and experiment in a quantitative framework. While mechanistic sintering models exist, they only model a single sintering pathway, even though multiple sintering mechanisms can occur simultaneously or dominate at different stages of the process. Data-driven machine learning models have emerged as a means to represent complex processes through data regression. However, machine learning models have very large data needs and lack mechanistic insights due to their black-box encoding. To develop an interpretive model of catalyst degradation via sintering, we constructed a hybrid model combining mechanistic “physics-based” models and data-driven methods to obtain both reliable predictions and mechanistic insights regarding experimentally observed sintering phenomena. Focusing on nanoparticle sintering in the Rh–TiO 2 catalyst for the reverse water–gas shift (RWGS) reaction, the hybrid model couples a mechanistic term for Ostwald ripening with energy values calculated via density functional theory (DFT) with a parametric, data-driven discrepancy function term for unmodeled mechanisms. The hybrid model is trained using Bayesian inference with data collected from small-angle X-ray scattering (SAXS) in situ experiments wherein average nanoparticle diameter versus time was measured at three relevant operating temperatures. The calibrated hybrid model results show that an Ostwald ripening-only model parameterized with fixed DFT energies does not fully capture the time and temperature dependence of the SAXS-observed sintering kinetics, and that an additional functional contribution, or DFT energy calibration, is required to reconcile simulation and experiment. Analysis of the hybrid-model error confirms that the hybrid model outperforms both the purely mechanistic and purely data-driven alternatives in terms of expected predictive accuracy for time-evolving average particle sizes. Furthermore, the results support the hypothesis that the Ostwald ripening mechanism is less important for explaining the sintering phenomena as operating temperature increases under an assumed fixed DFT parameterization. This could be explained in one of two ways: either latent, unmodeled sintering mechanisms dominate at higher temperatures, or the DFT uncertainty increases with temperature. The proposed modeling approach directly links theory to experiments and simulations via a statistical hybrid modeling framework and can be extended to other catalytic systems to improve predictive models and mechanistic understanding.

Bayesian hybrid modeling↗

Alkyl-Substituted Polycaprolactone Poly(urethane-urea)s as Mechanically Competitive and Chemically Recyclable Materials

We report the mechanical performance and chemical recycling advantages of implementing alkyl-substituted poly(ε-caprolactones) (PCLs) as soft segments in thermoplastic poly(urethane-urea) (TPUU) materials. Poly(4-methylcaprolactone) (P4MCL) and poly(4-propylcaprolactone) (P4PrCL) were prepared, reacted with isophorone diisocyanate, and chain-extended with water to form TPUUs. The resulting materials’ tensile properties were similar or superior to a commercially available polyester thermoplastic poly(urethane) and had superior elastic recovery properties compared to a PCL analogue due to the noncrystalline nature of P4MCL and P4PrCL. Additionally, monomers were recovered from the TPUU materials in high yields via ring-closing depolymerization using a reactive distillation approach at an elevated temperature and a reduced pressure (240–260 °C, 25–140 mTorr) with zinc chloride (ZnCl 2 ) as the catalyst. The thermodynamics of polymerization were estimated using Van’t Hoff analyses for 4MCL and 4PrCL; these results indicated that the propyl group in 4PrCL results in a lower practical ceiling temperature (T c ) for P4PrCL.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Continuous Encodable Reshaping of Gold Nanocrystals through Facet Modulation

Shape control of nanocrystals (NCs) is crucial for tuning their assembly behavior and functional properties, yet the precise manipulation of facet composition remains challenging. Here, we present a nanocrystal reshaping strategy to control and modulate the facets of gold (Au) NCs. Our one-pot approach, conducted at room temperature, requires only initial Au NCs, Au 3+ ions, and surfactants, distinguishing it from conventional reduction-mediated “etching-and-regrowth” methods. Detailed structural studies using electron microscopy, small-angle X-ray scattering (SAXS), and UV−vis spectroscopy reveal the surfactant-encoded pathway for NC transformation from shaped particles to spheres and then into various polyhedral shapes while preserving the individual particles' volume. The proposed reshaping mechanism involves the dissolution of surface Au atoms into Au + complexes in the presence of Au 3+ and surfactant, followed by surfactant-guided redeposition and formation of facets with different atomic planes. Using the ethanol oxidation reaction (EOR) as a probe, we observe a quasi-linear decrease in onset potential and an increase in activity with increasing {100} facet exposure. This work broadens synthetic strategies by offering precise NC reshaping and facet control.

36 MATERIALS SCIENCE↗

Reconfigurable spin current transmission and magnon–magnon coupling in hybrid ferrimagnetic insulators

Coherent spin waves possess immense potential in wave-based information computation, storage, and transmission with high fidelity and ultra-low energy consumption. However, despite their seminal importance for magnonic devices, there is a paucity of both structural prototypes and theoretical frameworks that regulate the spin current transmission and magnon hybridization mediated by coherent spin waves. Here, we demonstrate reconfigurable coherent spin current transmission, as well as magnon–magnon coupling, in a hybrid ferrimagnetic heterostructure comprising epitaxial Gd 3 Fe 5 O 12 and Y 3 Fe 5 O 12 insulators. By adjusting the compensated moment in Gd 3 Fe 5 O 12 , magnon–magnon coupling was achieved and engineered with pronounced anticrossings between two Kittel modes, accompanied by divergent dissipative coupling approaching the magnetic compensation temperature of Gd 3 Fe 5 O 12 (T M,GdIG ), which were modeled by coherent spin pumping. Remarkably, we further identified, both experimentally and theoretically, a drastic variation in the coherent spin wave-mediated spin current across T M,GdIG , which manifested as a strong dependence on the relative alignment of magnetic moments. Our findings provide significant fundamental insight into the reconfiguration of coherent spin waves and offer a new route towards constructing artificial magnonic architectures.

42 ENGINEERING↗

Critical enhancement of the spin Hall effect by spin fluctuations

The spin Hall (SH) effect, the conversion of the electric current to the spin current along the transverse direction, relies on the relativistic spin-orbit coupling (SOC). Here, we develop a microscopic theory on the mechanisms of the SH effect in magnetic metals, where itinerant electrons are coupled with localized magnetic moments via the Hund exchange interaction and the SOC. Both antiferromagnetic metals and ferromagnetic metals are considered. It is shown that the SH conductivity can be significantly enhanced by the spin fluctuation when approaching the magnetic transition temperature of both cases. For antiferromagnetic metals, the pure SH effect appears in the entire temperature range, while for ferromagnetic metals, the pure SH effect is expected to be replaced by the anomalous Hall effect below the transition temperature. We discuss possible experimental realizations and the effect of the quantum criticality when the antiferromagnetic transition temperature is tuned to zero temperature.

36 MATERIALS SCIENCE↗

Achieving high tensile strength and ductility in refractory alloys by tuning electronic structure

The energy efficiency of heat engines (gas and steam turbines) for electricity production and propulsion is determined by the Carnot cycle and scales with operating temperature. Commercial nickel- and cobalt-based superalloys melt near 1,500 °C and rapidly lose mechanical strength beyond 1,000 °C. Refractory metals melt well above 2,000 °C but have inherent manufacturability challenges that are barriers to adoption, such as high ductile-to-brittle transition temperatures. Using density functional theory-guided design, we demonstrate tailored local lattice distortions that promote phase-stable, non-equiatomic refractory concentrated solid solutions with both high ductility and strength. Here, we exemplify this for single-phase, body-centred cubic Nb 4 Ta 4 V 3 Ti that exhibits castability, excellent room-temperature tensile yield strength (∼1 GPa) and ductility (approaching 20% uniform strain), and exceptional high-temperature tensile strength (500 MPa at 1,000 °C). These findings illustrate a path for designing materials that hold great potential for advancing next-generation technologies such as Generation IV fission reactors, first-generation fusion-plasma reactors, and more efficient gas turbines for electricity generation and propulsion.

DFT↗

Signal amplification in a solid-state sensor through asymmetric many-body echo

Electronic spins of nitrogen–vacancy centres in diamond constitute a promising system for micro- and nanoscale magnetic sensing, because of their operation under ambient conditions, ease of placement in close proximity to sensing targets and biological compatibility. At high densities, the electronic spins interact through dipolar coupling, which typically limits but can also potentially enhance sensing performance. Here we report the experimental demonstration of many-body signal amplification in a solid-state, room-temperature quantum sensor. Our approach uses time-reversed two-axis-twisting interactions, engineered through dynamical control of the quantization axis and Floquet engineering in a two-dimensional ensemble of nitrogen–vacancy centres. We observe that optimal amplification occurs when the backward evolution time equals twice the forward evolution time, in sharp contrast to the conventional Loschmidt echo. These observations can be understood as resulting from an underlying time-reversed mirror symmetry of the microscopic dynamics, providing key insights into signal amplification and opportunities for practical entanglement-enhanced quantum sensing.

quantum information↗

Unlocking superplasticity in medium and high-entropy alloys

Superplasticity, the capacity of materials to sustain extraordinary tensile elongations at elevated temperatures, underpins a range of advanced metal-forming technologies. Conventionally, it is achieved in fine-grained alloys where deformation is dominated by grain-boundary sliding, accommodated by diffusion and dislocation activity. The advent of medium- and high-entropy alloys (M/HEAs), with their high chemical complexity and unconventional phase stability, offers new pathways to superplastic behavior beyond traditional alloy systems. Although investigated only recently, several M/HEAs already exhibit elongations that rival or exceed those of classical superplastic materials, particularly when ultrafine or metastable microstructures are engineered. Here, we review progress in understanding superplastic deformation in M/HEAs, emphasizing the interplay among composition, initial microstructure, thermomechanical processing, and microstructural evolution during high-temperature deformation. We discuss approaches to generating the fine-grained structures necessary for grain-boundary sliding, including severe plastic deformation and tailored heat treatments. We further highlight dynamic phenomena such as phase transformations, evolving grain-boundary chemistry, and deformation-induced grain refinement that can enhance plasticity in these systems. These mechanisms often shift the balance of deformation processes, enabling large elongations even outside classical criteria. Finally, we outline key challenges for application, including cost, scalability, recyclability, and microstructural stability.

klenam, Desmond [University of the Witwatersrand, ↗

Electrified vapour deposition at ultrahigh temperature and atmospheric pressure for nanomaterials synthesis

Vapour-phase synthesis methods have shown promise for the scalable synthesis of nanomaterials and coatings. However, the vaporization of different precursors for the synthesis of a broad nanomaterial space, particularly at atmospheric pressure, while maintaining compositional and structural control of the final product is challenging. Here we report the generation of an ultrahigh-temperature atomic vapour at atmospheric pressure based on electrified heating, for the growth of multi-elemental nanomaterials and thin films. This process relies on a reactor design whereby solid-state precursors are vaporized within a semi-confined space beneath an electrified heater that can reach ~3,000 K. The proximity of the heater rapidly breaks down the bonds of metal salt precursors and decomposes them into an atomic vapour that expands into a high-temperature (>2,000 K), highly reactive and high-flux vapour (10 21 –10 22 atoms per cm 2 per second) that travels upwards in a directional flow. When mixed with entrained ambient gases, the highly reactive atomic species rapidly nucleate and grow into the desired final products, including alloys, oxides, sulfides and thin films, which can be deposited on a low-temperature substrate. This EVD approach can synthesize a broad range of functional nanomaterials at atmospheric pressure, including single-phase multi-elemental nanomaterials formed under thermodynamically non-equilibrium conditions.

36 MATERIALS SCIENCE↗

Progress towards a phenomenological picture and theoretical understanding of glassy dynamics and vitrification near interfaces and under nanoconfinement

The nature of alterations to dynamics and vitrification in the nanoscale vicinity of interfaces-commonly referred to as "nanoconfinement" effects on the glass transition-has been an open question for a quarter century. We first analyze experimental and simulation results over the last decade to construct an overall phenomenological picture. Key features include the following: after a metrology- and chemistry-dependent onset, near-interface relaxation times obey a fractional power law decoupling relation with bulk relaxation; relaxation times vary in a double-exponential manner with distance from the interface, with an intrinsic dynamical length scale appearing to saturate at low temperatures; the activation barrier and vitrification temperature T-g approach bulk behavior in a spatially exponential manner; and all these behaviors depend quantitatively on the nature of the interface. We demonstrate that the thickness dependence of film-averaged T-g for individual systems provides a poor basis for discrimination between different theories, and thus we assess their merits based on the above dynamical gradient properties. Entropy-based theories appear to exhibit significant inconsistencies with the phenomenology. Diverse free-volume-motivated theories vary in their agreement with observations, with approaches invoking cooperative motion exhibiting the most promise. The elastically cooperative nonlinear Langevin equation theory appears to capture the largest portion of the phenomenology, although important aspects remain to be addressed. A full theoretical understanding requires improved confrontation with simulations and experiments that probe spatially heterogeneous dynamics within the accessible 1-ps to 1-year time window, minimal use of adjustable parameters, and recognition of the rich quantitative dependence on chemistry and interface. Published under license by AIP Publishing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanical detwinning device for anisotropic resistivity measurements in samples requiring dismounting for particle irradiation

Uniaxial stress is used to detwin samples of orthorhombic iron based superconductors to study their intrinsic electronic anisotropy. Here we describe the development of a new detwinning setup enabling variable-load stress-detwinning with easy sample mounting/dismounting without the need to re-solder the contacts. It enables the systematic study of the anisotropy evolution as a function of an external parameter when the sample is modified between the measurements. In our case, the external parameter is the dose of 2.5 MeV electron irradiation at low temperature. We illustrate the approach by studying resistivity anisotropy in single crystals of Ba 1-x K x Fe 2 As 2 at x =0.25 where the much discussed unusual re-entrance of tetragonal C 4 phase, C 4 → C 2 → C 4 , is observed on cooling. With the described technique we found a significant anisotropy increase in C 2 phase after electron irradiation with dose of 2.35 C/cm 2 .

47 OTHER INSTRUMENTATION↗

Fluorine spillover for ceria- vs silica-supported palladium nanoparticles: A MD study using machine learning potentials

Supported metallic nanoparticles play a central role in catalysis. However, predictive modeling is particularly challenging due to the structural and dynamic complexity of the nanoparticle and its interface with the support, given that the sizes of interest are often well beyond those accessible via traditional ab initio methods. With recent advances in machine learning, it is now feasible to perform MD simulations with potentials retaining near-density-functional theory (DFT) accuracy, which can elucidate the growth and relaxation of supported metal nanoparticles, as well as reactions on those catalysts, at temperatures and time scales approaching those relevant to experiments. Furthermore, the surfaces of the support materials can also be modeled realistically through simulated annealing to include effects such as defects and amorphous structures. We study the adsorption of fluorine atoms on ceria and silica supported palladium nanoparticles using machine learning potential trained by DFT data using the DeePMD framework. We show defects on ceria and Pd/ceria interfaces are crucial for the initial adsorption of fluorine, while the interplay between Pd and ceria and the reverse oxygen migration from ceria to Pd control spillover of fluorine from Pd to ceria at later stages. In contrast, silica supports do not induce fluorine spillover from Pd particles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Supervised machine learning-based multivariate regression of parallel closures for a high-collisionality deuterium-carbon plasma

Many plasmas of interest in laboratory experiments and space consist of multiple ion species. In tokamak edge plasmas, for instance, ionized impurities expelled from the vessel wall influence plasma transport. When describing multi-species plasmas using fluid equations, we need accurate closure relations to close the set of fluid equations. In this study, we introduce the development of fitting formulas for parallel closures using supervised machine learning, in conjunction with the recent closure theory, considering multi-ion collisions and arbitrary ion temperatures. We apply this approach to a high-collisionality deuterium-carbon plasma and demonstrate its effectiveness. As a result, the machine learning-based method for developing practical and accurate closures can be extended to a wider range of plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗