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At least 343 records · Page 19

Effect of Zn Addition on Phase Evolution in AlCrFeCoNiZn High–Entropy Alloy

The addition of Zn to AlCrFeCoNi high-entropy alloy (HEA) poses intriguing questions as to how it would affect phase evolution. Herein, the phase evolution in AlCrFeCoNiZn is studied using a combination of experimental techniques (X-ray diffraction, scanning electron microscopy, energy-dispersive spectroscopy, and differential scanning calorimetry) and computational (density-functional theory [DFT], calculation of phase diagrams, and machine-learning) methods. Mechanically alloyed and spark-plasma-sintered AlCrFeCoNiZn assumes a metastable single-phase, body-centered-cubic (BCC) structure that undergoes diffusion-controlled phase separation upon subsequent heat treatment to form separate (Al, Cr)-rich, (Fe, Co)-rich, and (Zn, Ni)-rich phases. The formation of (Al, Cr)-rich phase, not reported previously in AlCrFeCoNi-based HEAs, is attributed to strong clustering tendency of Cr–Zn and Cr–Ni pairs, combined with the strong ordering of Zn–Ni pair, driving out Cr that in turn combines with Al to form a (Al, Cr)-rich phase. In the DFT results, the formation of thermodynamically stable L1 2 phase is shown wherein Cr–Fe–Zn [Al–Ni-Co] preferably occupy1a (000) [3c (0 ½ ½)] positions. Furthermore, the sluggish diffusional transformation to L1 2 phase from BCC precursors is attributed to the small stacking-fault energy of AlCrFeCoNiZn. The equilibrated HEA exhibits a high microhardness of 8.24 GPa with an elastic modulus of 184 GPa.

36 MATERIALS SCIENCE↗

Metasomatic Control of Water in Garnet and Pyroxene from Kaapvaal Craton Mantle Xenoliths

Fourier transform infrared spectrometry (FTIR) and laser ablation inductively coupled plasma mass spectrometry (LA-ICPMS) were used to determine water, rare earth (REE), lithophile (LILE), and high field strength (HFSE) element contents in garnet and pyroxene from mantle xenoliths, Kaapvaal craton, southern Africa. Water enters these nominally anhydrous minerals as protons bonded to structural oxygen in lattice defects. Pyroxene water contents (150-400 ppm in clinopyroxene; 40-250 ppm in orthopyroxene) correlate with their Al, Fe, Ca and Na and are homogeneous within a mineral grains and a xenolith. Garnets from Jagersfontein are chemically zoned for Cr, Ca, Ti and water contents. Garnets contain 0 to 20 ppm H2 Despite the fast diffusion rate of H in mantle m inerals, the observations above indicate that the water contents of mantle xenolith minerals were not disturbed during kimberlite entrainment and that the measured water data represent mantle values. Trace elements in all minerals show various degrees of light REE and LILE enrichments indicative of minimal to strong metasomatism. Water contents of peridotite minerals from the Kaapvaal lithosphere are not related to the degree of depletion of the peridotites. Instead, metasomatism exerts a clear control on the amount of water of mantle minerals. Xenoliths from each location record specific types of metasomatism with different outcomes for the water contents of mantle minerals. At pressures . 5.5 GPa, highly alkaline melts metasomatized Liqhobong and Kimberley peridotites, and increased the water contents of their olivine, pyroxenes and garnet. At higher pressures, the circulation of ultramafic melts reacting with peridotite resulted in co-variation of Ca, Ti and water at the edge of garnets at Jagersfontein, overall decreasing their water content, and lowered the water content of olivines at Finsch Mine. The calculated water content of these melts varies depending on whether the water content of the peridotite (2 wt% HO. 2O) or individual m inerals (<0.5-13 wt% H2O) are used, and also depend on the mineral-melt water partition coefficients. These metasomatic events are thought to have occurred during the Archean and Proterozoic, meaning that the water contents measured here have been preserved since that time and can be used to investigate viscocity and longevity of cratonic mantle roots.

Peslier, Anne H.↗

Thermo-mechanical deterioration and molecular degradation of 3D-printed methacrylate-based polymer in various chemical environments

The advancement of additive manufacturing (AM) has accelerated the development of stereolithographic (SLA) photo-curable resins, particularly methacrylate-based polymers, due to the ability to their high-resolution, robust mechanical properties, and suitability. However, their long-term performance in chemical environments remains poorly understood. This study investigates the extent and mechanisms of degradation on an SLA-printed methacrylate-based polymer subjected to various chemicals, including polar and non-polar solvents, as well as strongly acidic aqueous solutions over a 12-week accelerated aging period. A comprehensive analytical approach incorporating swelling kinetics, surface morphology, tensile and dynamic mechanical analysis (DMA), Fourier-transform infrared (FTIR) spectroscopy, and mass spectrometry (MS) was employed to characterize chemical absorption, structural integrity, and leached products. Results reveal that degradation severity is governed by both the polarity and reactivity of the chemical environment. Notably, exposure to 6 mol L -1 HNO₃ induced the most severe deterioration, with over threefold higher swelling compared to other media, and significant reductions in tensile strength, tensile modulus, and glass transition temperature (T g ). In contrast, specimens aged in non-polar solvents (xylene and dodecane) exhibited negligible chemical interaction and retained mechanical performance. FTIR and MS analyses identified acid-catalyzed hydrolysis of ester groups as prominent degradation pathways in acidic media, while diffusion-controlled plasticization prevailed in polar solvents. Furthermore, this study provides valuable insights into the chemical stability of SLA-printed polymers and develops predictive degradation profiles that are crucial for designing durable polymer systems for advanced industrial use.

36 MATERIALS SCIENCE↗

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, ↗

NASA Tech Briefs, May 2004

Topics include: Embedded Heaters for Joining or Separating Plastic Parts; Curing Composite Materials Using Lower-Energy Electron Beams; Aluminum-Alloy-Matrix/Alumina-Reinforcement Composites; Fibrous-Ceramic/Aerogel Composite Insulating Tiles; Urethane/Silicone Adhesives for Bonding Flexing Metal Parts; Scalable Architecture for Multihop Wireless ad Hoc Networks; Improved Thermoplastic/Iron-Particle Transformer Cores; Cooperative Lander-Surface/Aerial Microflyer Missions for Mars Exploration Dual-Frequency Airborne Scanning Rain Radar Antenna System Eight-Channel Continuous Timer Reduction of Phase Ambiguity in an Offset-QPSK Receiver Ambient-Light-Canceling Camera Using Subtraction of Frames Lightweight, Flexible, Thin, Integrated Solar-Power Packs Windows(Registered Trademark)-Based Software Models Cyclic Oxidation Behavior Software for Analyzing Sequences of Flow-Related Images Improved Ball-and-Socket Docking Mechanism Two-Stage Solenoid Ordered Nanostructures Made Using Chaperonin Polypeptides Low-Temperature Plasma Functionalization of Carbon Nanotubes Improved Cryostat for Cooling a Wide Panel Current Pulses Momentarily Enhance Thermoelectric Cooling Hand-Held Color Meters Based on Interference Filters Calculating Mass Diffusion in High-Pressure Binary Fluids Fresnel Lenses for Wide-Aperture Optical Receivers Increasing Accuracy in Computed Inviscid Boundary Conditions Higher-Order Finite Elements for Computing Thermal Radiation Radar for Monitoring Hurricanes from Geostationary Orbit Time-Transfer System for Two Orbiting Spacecraft

Source record↗

Enhancing Unknown Waveform Detection by Learning Intra and Inter-domain Dependencies with Advanced Attention Fusion Mechanisms

Detection of unknown waveforms in mission-critical communications is a crucial area of interest for the Department of Energy (DoE). Traditional methods and recent deep learning-based approaches often assume that the training set includes all possible classes, which is impractical for detecting new waveforms. This limitation gives rise to the problem of open-set recognition (OSR), which involves correctly identifying known classes while detecting and rejecting unknown or unseen classes. To address this limitation, we propose a novel dual-domain complex-valued neural architecture that jointly processes time-domain and frequency-domain signal representations using transformer mechanisms. A transformer model is a deep learning architecture that uses self-attention mechanisms to process and learn relationships in sequential data. Our model employs a cosine similarity loss to extract domain-specific features and incorporates a transformer architecture in the latent space to weigh the importance of different features from the time and frequency domains. The transformer layer includes stacked self-attention and cross-attention modules to learn intra-domain and inter-domain dependencies, creating a more holistic signal representation. An attention-based fusion module intelligently combines the time and frequency-domain features using multi-head attention, enabling the network to learn the optimal feature for each domain in each input signal. Quantitative results demonstrate the impact of these architectural choices on overall performance, showing significant improvement after incorporating self and cross-attention modules and using complex attention fusion over simple weighted fusion. Our ongoing work will focus on addressing the limitations of threshold-based OSR methods by developing a novel generative framework that integrates a conditional diffusion probabilistic model (DPM). DPM is a generative framework that learns to synthesize complex data by reversing a gradual noising process using a neural network trained to denoise step-by-step. Our goal is to leverage the inherent strengths of DPMs for identifying unknown signals more robustly. One primary advantage of using a DPM is its ability to provide a more reliable anomaly score based on the model's reconstruction error, rather than relying solely on classifier confidence. Additionally, the iterative denoising process of DPMs makes this approach naturally resilient to low Signal-to-Noise Ratio (SNR) conditions, where traditional methods often fail. By implementing this generative framework, we aim to enhance the model's capability to accurately detect unknown waveforms and maintain performance in challenging environments.

99 - GENERAL AND MISCELLANEOUS↗

Stabilized Oxygen Vacancy Chemistry toward High-Performance Layered Oxide Cathodes for Sodium-Ion Batteries

Anionic redox has emerged as a transformative paradigm for high-energy layered transition-metal (TM) oxide cathodes, but it is usually accompanied by the formation of anionic redox-mediated oxygen vacancies (OVs) due to irreversible oxygen release. Additionally, external factor-induced OVs (defined as intrinsic OVs) also play a pivotal role in the physicochemical properties of layered TM oxides. However, an in-depth understanding of the interplay between intrinsic and anionic redox-mediated OVs and the corresponding regulation mechanism of the dynamic evolution of OVs is still missing. Herein, we disclose the strong interrelationship between these OVs and demonstrate that the presence of intrinsic OVs in the TMO2 layers could induce weak integrity of the TM-O frameworks and unlock additional diffusion paths to trigger the generation and migration of anionic redox-mediated OVs. Accordingly, an OV stabilization strategy is proposed by deliberately introducing high-valence Nb5+, which could serve as an important building block in anchoring the oxygen sublattice and preventing the formation of a percolating OV migration network, thereby suppressing the formation/diffusion of anionic redox-mediated OVs. Consequently, superb structural integrity and improved electrochemical performance with reversible anionic redox chemistry are achieved. This work advances our understanding of the role of OVs for developing high-performance energy storage systems utilizing anionic redox.

anionic redox↗

High-pressure characterization of Ag 3 AuTe 2 : Implications for strain-induced band tuning

Recent band structure calculations have suggested the potential for band tuning in the chiral semiconductor Ag 3 AuTe 2 to zero upon application of negative strain. In this study, we report on the synthesis of polycrystalline Ag 3 AuTe 2 and investigate its transport and optical properties and mechanical compressibility. Transport measurements reveal the semiconducting behavior of Ag 3 AuTe 2 with high resistivity and an activation energy E a of 0.2 eV. The optical bandgap determined by diffuse reflectance measurements is about three times wider than the experimental E a ⁠. Despite the difference, both experimental gaps fall within the range of predicted bandgaps by our first-principles density functional theory (DFT) calculations employing the Perdew–Burke–Ernzerhof and modified Becke–Johnson methods. Furthermore, our DFT simulations predict a progressive narrowing of the bandgap under compressive strain, with a full closure expected at a strain of –4% relative to the lattice parameter. To evaluate the feasibility of gap tunability at such substantial strain, the high-pressure behavior of Ag 3 AuTe 2 was investigated by in situ high-pressure x-ray diffraction up to 47 GPa. Mechanical compression beyond 4% resulted in a pressure-induced structural transformation, indicating the possibility of substantial gap modulation under extreme compression conditions.

36 MATERIALS SCIENCE↗

Rigidity‐Driven Structural Isomers in the NaCl–Ga 2 S 3 System: Implications for Energy Storage

Alternative energy sources require the search for innovative materials with promising functionalities. Systems with unusual chemical properties represent an insufficiently explored domain, concealing unexpected features. Using diffraction and Raman spectroscopy over a wide temperature range, supported by first‐principles simulations, a rare phenomenon is unveiled: phase‐dependent chemical interactions between binary components in the NaCl–Ga 2 S 3 system. In this unique occurrence, previously intact binary crystalline species transform upon melting into mixed liquid structural isomers, forming bonds with new partners. The chemical combinatorics appears to be fully reversible for stable crystals and liquids. Despite this, rapidly frozen glasses out of thermodynamic equilibrium remain in a metastable isomeric state, offering remarkable properties, particularly a high room‐temperature Na + conductivity, comparable to the best sodium halide superionic conductors and therefore encouraging for sodium solid‐state batteries and energy applications. A rigidity paradigm is responsible for the observed phenomenon, as the extremely constrained Ga 2 S 3 crystal lattice does not survive viscous flow, breaking up at a short‐range level. The removal of rigidity constraints and dense packing leads to a significant increase in empty space, which is the origin of high sodium diffusivity. Broadly, the rigidity‐driven structural isomerism opens up an inspiring path to the discovery of atypical materials.

25 ENERGY STORAGE↗

Numerical Simulation of Combustion and Extinction of a Solid Cylinder in Low-Speed Cross Flow

The combustion and extinction behavior of a diffusion flame around a solid fuel cylinder (PMMA) in low-speed forced flow in zero gravity was studied numerically using a quasi-steady gas phase model. This model includes two-dimensional continuity, full Navier Stokes' momentum, energy, and species equations with a one-step overall chemical reaction and second-order finite-rate Arrhenius kinetics. Surface radiation and Arrhenius pyrolysis kinetics are included on the solid fuel surface description and a parameter Phi, representing the percentage of gas-phase conductive heat flux going into the solid, is introduced into the interfacial energy balance boundary condition to complete the description for the quasi-steady gas-phase system. The model was solved numerically using a body-fitted coordinate transformation and the SIMPLE algorithm. The effects of varying freestream velocity and Phi were studied. These parameters have a significant effect on the flame structure and extinction limits. Two flame modes were identified: envelope flame and wake flame. Two kinds of flammability limits were found: quenching at low-flow speeds due to radiative loss and blow-off at high flow speeds due to insufficient gas residence time. A flammability map was constructed showing the existence of maximum Phi above which the solid is not flammable at any freestream velocity.

Tien, J. S.↗

The gabbro-eclogite phase transition and the elevation of mountain belts on Venus

The hypothesis is explored that the crust-mantle boundary of Venus is not in phase equilibrium but rather is rate-limited by the temperature-dependent volume diffusion of the slowest ionic species. The 1D thermal evolution problem is solved assuming that the mountains formed by uniform horizontal shortening of the crust and the lithospheric mantle at a constant rate. The time-dependent density structure and surface elevation are calculated by assuming a temperature-dependent reaction rate and local Airy isostatic compensation. For a horizontal strain rate of 10 exp -15/s or greater, the temperature increase at the base of the crust during mountain formation is modest to negligible, the deepening lower crust is metastable, and the surface elevation increases as the crust thickens. For strain rates less than 10 exp -16/s, crustal temperature increases with time because of internal heat production and the lower crust is more readily transformed to the dense eclogite assemblage. For such models, a maximum elevation is reached during crustal shortening.

Namiki, Noriyuki↗

3D printing of architected sulfur cathodes with dual-site atomic catalysts for accelerated polysulfide kinetics and Li-ion transport in high areal-loading lithium–sulfur batteries

The practical deployment of lithium–sulfur batteries (LSBs) is hindered by fundamental limitations in conventional slurry-cast cathodes, including poor sulfur utilization, sluggish ion transport, and low areal capacity, particularly in thick electrodes required for high energy density. To address these challenges, we present direct ink writing (DIW) as an additive manufacturing strategy to fabricate advanced current-collector-free, 3D-printed sulfur cathodes (3DP S@CoNi-DSACs/NC) with hierarchically porous architectures that enhance lithium-ion diffusion, promote electrolyte penetration, and reduce interfacial resistance. The synergistic effects of Co/Ni dual-atom sites accelerate redox kinetics and mitigate polysulfide shuttling. As a result, the optimized 3DP cathode with a sulfur loading of 5.4 mg cm −2 demonstrated excellent rate capability, delivering a high reversible capacity of 1041.4 mAh g −1 at 1C with 85.5% capacity retention after 1000 cycles, significantly outperforming its cast counterpart. Remarkably, even at a higher sulfur loading of 8.1 mg cm −2 , the 3DP cathode maintains outstanding performance, achieving a discharge capacity of 1538.4 mAh g −1 and an areal capacity of 12.5 mAh cm −2 at 0.1C. This study not only demonstrates the functional integration of catalytically active materials into 3D printable sulfur cathode architectures but also offers a scalable and transformative platform for building high-performance LSBs beyond conventional electrode manufacturing methods.

3D electrode↗

Buoyancy Effects on Flow Structure and Instability of Low-Density Gas Jets

A low-density gas jet injected into a high-density ambient gas is known to exhibit self-excited global oscillations accompanied by large vortical structures interacting with the flow field. The primary objective of the proposed research is to study buoyancy effects on the origin and nature of the flow instability and structure in the near-field of low-density gas jets. Quantitative rainbow schlieren deflectometry, Computational fluid dynamics (CFD) and Linear stability analysis were the techniques employed to scale the buoyancy effects. The formation and evolution of vortices and scalar structure of the flow field are investigated in buoyant helium jets discharged from a vertical tube into quiescent air. Oscillations at identical frequency were observed throughout the flow field. The evolving flow structure is described by helium mole percentage contours during an oscillation cycle. Instantaneous, mean, and RMS concentration profiles are presented to describe interactions of the vortex with the jet flow. Oscillations in a narrow wake region near the jet exit are shown to spread through the jet core near the downstream location of the vortex formation. The effects of jet Richardson number on characteristics of vortex and flow field are investigated and discussed. The laminar, axisymmetric, unsteady jet flow of helium injected into air was simulated using CFD. Global oscillations were observed in the flow field. The computed oscillation frequency agreed qualitatively with the experimentally measured frequency. Contours of helium concentration, vorticity and velocity provided information about the evolution and propagation of vortices in the oscillating flow field. Buoyancy effects on the instability mode were evaluated by rainbow schlieren flow visualization and concentration measurements in the near-field of self-excited helium jets undergoing gravitational change in the microgravity environment of 2.2s drop tower at NASA John H. Glenn Research Center. The jet Reynolds number was varied from 200 to 1500 and jet Richardson number was varied from 0.72 to 0.002. Power spectra plots generated from Fast Fourier Transform (FFT) analysis of angular deflection data acquired at a temporal resolution of 1000Hz reveal substantial damping of the oscillation amplitude in microgravity at low Richardson numbers (~0.002). Quantitative concentration data in the form of spatial and temporal evolutions of the instability data in Earth gravity and microgravity reveal significant variations in the jet flow structure upon removal of buoyancy forces. Radial variation of the frequency spectra and time traces of helium concentration revealed the importance of gravitational effects in the jet shear layer region. Linear temporal and spatio-temporal stability analyses of a low-density round gas jet injected into a high-density ambient gas were performed by assuming hyper-tan mean velocity and density profiles. The flow was assumed to be non parallel. Viscous and diffusive effects were ignored. The mean flow parameters were represented as the sum of the mean value and a small normal-mode fluctuation. A second order differential equation governing the pressure disturbance amplitude was derived from the basic conservation equations. The effects of the inhomogeneous shear layer and the Froude number (signifying the effects of gravity) on the temporal and spatio-temporal results were delineated. A decrease in the density ratio (ratio of the density of the jet to the density of the ambient gas) resulted in an increase in the temporal amplification rate of the disturbances. The temporal growth rate of the disturbances increased as the Froude number was reduced. The spatio-temporal analysis performed to determine the absolute instability characteristics of the jet yield positive absolute temporal growth rates at all Fr and different axial locations. As buoyancy was removed (Fr . 8), the previously existing absolute instability disappeared at all locations establhing buoyancy as the primary instability mechanism in self-excited low-density jets.

Pasumarthi, Kasyap Sriramachandra↗

Phase Field Modeling of Chemical Reaction Related Damage Evolution in Environmental Barrier Coatings

The advent of next-generation engines necessitates materials capable of withstanding temperatures beyond the reach of current superalloys. SiC-based ceramic matrix composites, augmented with environmental barrier coatings (EBCs), present a promising materials solution. Given the active search for effective and durable EBCs, there is a pressing need for modeling tools to understand and predict damage evolution in these materials to help accelerate their development. This study introduces a phase-field model (PFM) designed to simulate the thermally grown oxides (TGO) and phase transformation in the degradation and failure of EBCs. The model accounts for the severe volume expansion due to oxidation, alongside phase transformations and porosity evolution during thermal cycling, offering a comprehensive view of the damage processes. Simulation results are validated against experimental findings reported in the literature, establishing the model's potential as a significant tool for understanding and improving the resilience of EBCs in cyclic oxidative environments.

fast-diffusion path↗

Reversible Disorder-to-Order Transition Induced by Aqueous Lithiation in Vanadate Electrode Materials

Vanadium-based oxides are intriguing electrode materials in aqueous electrochemical systems owing to their low cost and high theoretical capacity for alkali storage, especially lithium (Li) ions. However, a sequence of phase transformations and irreversible structure distortion upon Li-ion intercalation causes structural instability and has been a lingering problem for vanadium oxide electrodes. Here, in this work, we investigate lithium vanadate (Li–V 3 O 8 ) for aqueous Li-ion intercalation and deintercalation processes. Unlike its crystalline V 2 O 5 polymorph, Li–V 3 O 8 retains monophasic lithiation, which is attributed to its disordered crystalline nature and large interplanar distance. Importantly, we show a unique and reversible sequence of disorder-to-order structural transition induced by the extent of lithiation, which indicates sequential interlayer and intralayer lithiation process, and vice versa in delithiation process, supported by electrokinetic analysis, in situ X-ray diffraction (XRD), and Debye scattering simulations. The absence of distortive phase transitions and multilithiation pathways facilitates Li-ion diffusion across the vanadate electrode materials to improve storage capacity. This work opens a new dimension for vanadium-based disordered oxides, accelerating the development of low-cost, aqueous electrochemical systems.

36 MATERIALS SCIENCE↗

Point cloud-based diffusion models for the Electron-Ion Collider

At high-energy collider experiments, generative models can be used for a wide range of tasks, including fast detector simulations, unfolding, searches of physics beyond the Standard Model, and inference tasks. In particular, it has been demonstrated that score-based diffusion models can generate high-fidelity and accurate samples of jets or collider events. This work expands on previous generative models in three distinct ways. First, our model is trained to generate entire collider events, including all particle species with complete kinematic information. We quantify how well the model learns event-wide constraints such as the conservation of momentum and discrete quantum numbers. We focus on the events at the future Electron-Ion Collider, but we expect that our results can be extended to proton-proton and heavy-ion collisions. Second, previous generative models often relied on image-based techniques. The sparsity of the data can negatively affect the fidelity and sampling time of the model. We address these issues using point clouds and a novel architecture combining edge creation with transformer modules called Point Edge Transformers. Third, we adapt the foundation model OmniLearn, to generate full collider events. This approach may indicate a transition toward adapting and fine-tuning foundation models for downstream tasks instead of training new models from scratch.

Araz, Jack Y. [Stony Brook Univ., NY (United State↗

An efficient explicit implementation of a near-optimal quantum algorithm for simulating linear dissipative differential equations

We propose an efficient block-encoding technique for the implementation of the Linear Combination of Hamiltonian Simulations (LCHS) for simulating dissipative initial-value problems. This algorithm approximates a target nonunitary operator as a weighted sum of Hamiltonian evolutions, thereby emulating a dissipative problem by mixing various time scales. We introduce an efficient encoding of the LCHS into a quantum circuit based on a simple coordinate transformation that turns the dependence on the summation index into a trigonometric function. Classically, this method is equivalent to the use of a highly accurate Fejér-Clenshaw-Curtis quadrature formula. Quantumly, this significantly simplifies block-encoding of a dissipative problem and allows one to perform an exponential number of Hamiltonian simulations by a single Quantum Signal Processing (QSP) circuit. The resulting LCHS circuit has high success probability and the selector scales logarithmically with the number of terms in the LCHS sum and linearly with time. Careful analysis of error convergence proves that this method is more efficient than other LCHS circuits that have recently appeared in the literature. We verify the quantum circuit and its scaling by simulating it on a digital emulator of fault-tolerant quantum computers and, as a test problem, solve the advection-diffusion equation. The proposed algorithm can be used for simulating a wide class of nonunitary initial-value problems including the Liouville equation with added dissipation and linear embeddings of nonlinear systems, such as the Koopman-von Neumann and Carleman embeddings.

Novikau, I [Lawrence Livermore National Laboratory↗

In Situ Insights into Enhanced Cooperative Ligand Exchange Kinetics via Solvent-Induced Restacking in a 2D Metal–Organic Framework

Understanding the reaction kinetics at catalytically active sites is crucial for integrating catalytic two-dimensional (2D) materials into industrial processes. This study focuses on in situ observation of ligand exchange kinetics and solvent-assisted structural restacking transition in the 2D paddle wheel-based MOF [Cu 2 (dttc) 2 ] n (DUT-134(Cu), dttc = dithieno[3,2-b:2′,3′- d]thiophene-2,6-dicarboxylate). The ligand exchange process, involving the replacement of dimethylformamide (DMF) with nitriles such as acetonitrile (ACN), pentanenitrile, and heptanenitrile, was investigated using advanced in situ characterization techniques with high temporal resolution, including powder X-ray diffraction and Raman spectroscopy. The larger analytes exhibited reduced exchange rates, consistent with enhanced steric hindrance and greater diffusion constraints. Interestingly, the study revealed that the exchange of DMF with ACN induces a structural transition to higher symmetry within few seconds, a transition from AB to AA stacking mode of the layers, and a widening of the interlayer distance. Crucially, this structural transition dramatically accelerates the solvent exchange process through cooperative effects, offering critical advantages for catalytic applications. Notably, the reverse exchange from ACN to DMF proceeds more slowly and does not reverse the structural changes, but a new phase is formed with preserved AA stacking. By isotope labeling of linker molecules in combination with two complementary theoretical vibrational simulation methods, the precise assignment of Raman bands and the vibrational modes associated with the ligand exchange process could be achieved. These pioneering insights into the dynamic behavior of 2D MOFs, coupled with ligand exchange, establish a highly promising and transformative approach to achieving enhanced tunability and responsiveness in future catalytic applications.

Layers↗