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At least 73 records · Page 4

QCD evolution of entanglement entropy

Entanglement entropy has emerged as a novel tool for probing nonperturbative quantum chromodynamics (QCD) phenomena, such as color confinement in protons. While recent studies have demonstrated its significant capability in describing hadron production in deep inelastic scatterings, the QCD evolution of entanglement entropy remains unexplored. Here, in this work, we investigate the differential rapidity-dependent entanglement entropy within the proton and its connection to final-state hadrons, aiming to elucidate its QCD evolution. Our analysis reveals a strong agreement between the rapidity dependence of von Neumann entropy, obtained from QCD evolution equations, and the corresponding experimental data on hadron entropy. These findings provide compelling evidence for the emergence of a maximally entangled state, offering new insights into the nonperturbative structure of protons.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

GR-Athena++: General-relativistic Magnetohydrodynamics Simulations of Neutron Star Spacetimes

We present the extension of GR-Athena++ to general-relativistic magnetohydrodynamics (GRMHD) for applications to neutron star spacetimes. The new solver couples the constrained transport implementation of Athena++ to the Z4c formulation of the Einstein equations to simulate dynamical spacetimes with GRMHD using oct-tree adaptive mesh refinement. We consider benchmark problems for isolated and binary neutron star spacetimes demonstrating stable and convergent results at relatively low resolutions and without grid symmetries imposed. The code correctly captures magnetic field instabilities in nonrotating stars with total relative violation of the divergence-free constraint of 10 –16 . It handles evolutions with a microphysical equation of state and black hole formation in the gravitational collapse of a rapidly rotating star. For binaries, we demonstrate correctness of the evolution under the gravitational radiation reaction and show convergence of gravitational waveforms. We showcase the use of adaptive mesh refinement to resolve the Kelvin–Helmholtz instability at the collisional interface in a merger of magnetised binary neutron stars. GR-Athena++ shows strong scaling efficiencies above 80% in excess of 10 5 CPU cores and excellent weak scaling is shown up to ~5 × 10 5 CPU cores in a realistic production setup. GR-Athena++ allows for the robust simulation of GRMHD flows in strong and dynamical gravity with exa-scale computers.

79 ASTRONOMY AND ASTROPHYSICS

Rapid synthesis of phase-engineered tungsten carbide electrocatalysts via flash joule heating for high-current-density hydrogen evolution

Fabricating durable and high-performance electrocatalysts operating at high current densities for industrial acidic hydrogen evolution remains a daunting challenge. Tailoring the phase composition of electrocatalysts is a promising strategy to harness synergistic effects and improve charge transfer, thereby optimizing their performance. Here, this work presents a fast, green method based on flash joule heating (FJH) to synthesize phase-engineered tungsten carbide electrocatalysts for the acidic hydrogen evolution reaction (HER) at high current densities. Tungsten carbide electrodes with varying FJH treatment durations (3, 10, 30, and 60 s) are fabricated to fine-tune the mixture of tungsten monocarbide (WC) and tungsten semicarbide (W 2 C) phases. Results show that samples with a 30-s treatment (TC-3) exhibit an optimal balance between these phases, leading to a low overpotential of 180.97 and 387 mV at current densities of 10 mA/cm 2 and 4 A/cm 2 , respectively. TC-3 exhibits significantly lower charge transfer resistance compared to the other electrocatalysts, which can be attributed to its optimal phase ratio. Notably, the TC-3 electrocatalyst remains stable for over 9 days at 4 A/cm 2 due to their controlled phases and excellent corrosion-resistant properties. This work highlights a new method to fabricate cost-effective, high-performance tungsten carbide electrocatalysts with well-controlled phase compositions.

Acidic hydrogen evolution reaction

Neural network interatomic potential-driven analysis of phase stability in Ti–V alloys at the atomistic scale

The evolution of the ω phase in titanium–vanadium (Ti–V) alloys is critical for their mechanical properties, particularly in aerospace and biomedical applications. Here, this study employs a Rapid Artificial Neural Network (RANN) potential to model the ω phase evolution at the atomistic level, demonstrating a high degree of consistency with experimental observations, unlike the Modified Embedded Atom Method (MEAM), which fails to capture this phase transformation accurately. RANN simulations replicate key phenomena such as the nucleation of α precipitates at ω/β interfaces and accurate lattice orientations, enhancing our understanding of phase stability and transformation kinetics. The findings affirm that RANN potentials can significantly improve the prediction accuracy of complex material behaviors, offering a powerful tool for designing advanced materials with tailored properties such as solute effect in various stacking fault energies. This approach not only bridges the gap between theoretical predictions and empirical data but also sets a new direction for future research in materials science, emphasizing the integration of machine learning techniques in the development and optimization of new alloys.

36 MATERIALS SCIENCE

Machine Learning‐Guided Discovery of High‐Entropy Perovskite Oxide Electrocatalysts via Oxygen Vacancy Engineering

Abstract High‐entropy perovskite oxides (HEPOs) have recently emerged as multifunctional catalysts. However, the HEPOs’ structural and compositional complexity hinders the easy and accurate extrapolation of activity indicators, which are essential for establishing structure‐property correlations. Here, OxiGraphX, is introduced as a novel graph neural network (GNN) model designed to capture the complex relationships among structure, composition, and atomic chemical environments for accurate prediction of oxygen vacancy formation energies (OVFEs) in HEPOs. By integrating machine learning (ML), density functional theory (DFT), and experimental validation, this work demonstrates an efficient framework for rapidly and accurately screening HEPO electrocatalysts for oxygen evolution reaction (OER). The OxiGraphX predicts OVFEs with a precision exceeding existing data, enabling the identification of compositions of higher oxygen vacancy content (OVC) and, thus, higher catalytic activity. Furthermore, the model explores latent spaces that translate effectively into experimental domains, bridging computational predictions with real‐world applications. This approach accelerates the discovery of high‐performance HEPO catalysts while providing deeper insights into their catalytic mechanisms.

Chemistry

2D analysis of tokamak divertor-plasma detachment-bifurcation with operational parameters and geometries

UEDGE simulations with density scans for various input power, transport coefficients and outer poloidal leg length are performed to study the conditions for the existence of a bifurcation-like drop of T e at the outer strike point, commonly referred to as a detachment cliff, when transitioning to a detached plasma from an attached plasma in the outer divertor as the upstream density increases (McLean et al., 2015). The simulation results show that a detachment cliff tends to occur with a higher power input regardless of diffusivities and leg length. Further analysis of change of plasma profiles at a cliff indicate that, in addition to the sharp reduction of the E x B drift fluxes in the outer divertor studied in Jaervinen et al., (2018), the substantial change of the Mach number in the outer divertor and the decrease of the outer mid-plane T e due to the radiation front moving across the separatrix into the confinement region above the X-point consistently occur for all UEDGE density scans that have a detachment cliff. UEDGE time-dependent simulation of the evolution of a detachment cliff shows that the rapid increase of radiation above the X-point occurs in a time scale of ~0.3–0.5, which could possibly be the trigger for the formation of a detachment cliff, quicker than the Mach number change in a time scale of ~1 ms and the drop of T e in a time scale of ~2–3 ms in the outer divertor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Improved liquid lithium surfaces in the Lithium Tokamak Experiment-β

Advances in vacuum, surface, and lithium conditioning techniques throughout five years of continuous operations in LTX-β have produced mirror-like liquid lithium surfaces and demonstrated the feasibility of high-performance tokamak discharges fully surrounded by liquid metal without significant operational problems. Improvements in conditioning techniques and procedures, including many weeks of baking and accumulation of 70 g of Li, led to reduced residual gasses and clean Li surfaces - all while still maintaining enough operational flexibility for multiple in-vacuum diagnostic upgrades and calibrations. Coatings had a visibly clean appearance, with reflective liquid metal demonstrating good wetting and surface adhesion with films that were now macroscopically thick. Solidified Li showed large crystal grains, while surface science measurements observed reduced impurities in the lithium. Steadily improved plasma performance was achieved with liquid lithium, with discharges able to match solid Li in terms of evolution of I p and n e , including rapid density pumping indicating low recycling. There were indications of moderately increased Li impurity influx, though few significant disturbances by the large liquid surfaces on tokamak operations over hundreds of discharges. Liquid metal plasma facing components are a potential solution to the extreme heat and particle fluxes that could cause unacceptable damage to solid materials, while liquid lithium also has the potential for greatly increased confinement in the low-recycling regime. While many liquid metal approaches are possible, and numerous experiments have been conducted in test stands and small modules in fusion devices, LTX-β is the only tokamak operated while fully surrounded by liquid metal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Examining infrared thermography based approaches to rapid fatigue characterization of additively manufactured compression molded short fiber thermoplastic composites

A novel additive manufacturing (AM) methodology combined with a compression molding (CM) process has been developed to optimize the microstructure of short fiber thermoplastic composites (SFTs)with higher fiber alignment and lower porosity, yielding superior stiffness, strength, and structural integrity. Here, the current work examines the efficacy of the ‘passive’ infrared thermography (IRT) techniques for rapid fatigue characterization of SFTs that use the surface temperature evolution during cyclic loading due to self-heating as a fatigue indicator. A comparison of fatigue limits obtained from traditional stress-life (SN) (≈53.1%σ uts ) and IRT (≈54.1%σ uts ) shows a close match. However, the SN curve required 18 specimens and two weeks of continuous cyclic testing, while IRT used three specimens with 5 hours of testing. Thus, the IRT approach provides an accelerated testing framework for rapidly estimating the fatigue limit. Additionally, existing phenomenological approaches to IRT fatigue characterization have been examined.

42 ENGINEERING

Did the exposure of coacervate droplets to rain make them the first stable protocells?

Membraneless coacervate microdroplets have long been proposed as model protocells as they can grow, divide, and concentrate RNA by natural partitioning. However, the rapid exchange of RNA between these compartments, along with their rapid fusion, both within minutes, means that individual droplets would be unable to maintain their separate genetic identities. Hence, Darwinian evolution would not be possible, and the population would be vulnerable to collapse due to the rapid spread of parasitic RNAs. In this study, we show that distilled water, mimicking rain/freshwater, leads to the formation of electrostatic crosslinks on the interface of coacervate droplets that not only suppress droplet fusion indefinitely but also allow the spatiotemporal compartmentalization of RNA on a timescale of days depending on the length and structure of RNA. We suggest that these nonfusing membraneless droplets could potentially act as protocells with the capacity to evolve compartmentalized ribozymes in prebiotic environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Analytical simulation of meander morphology from equilibrium to long-term evolution: Impacts of channel geometry and vegetation-induced coarsening

This study introduces an innovative approach to modeling meandering river morphology, integrating and investigating the effects of geometric characteristics and vegetation-induced channel coarsening. The developed comprehensive framework combines several advanced techniques: Genetic Programming for refining the scour factor of transverse bed slope, a Leaf Area Index (LAI)-enhanced analytical model for quantifying vegetative flow resistance, and an upstream-weighted moving average method for efficient approximation of the convolution integral in meander migration calculations. The model is validated against both an idealized Kinoshita meander and a natural bend of the Tumen River (China) in equilibrium, demonstrating its robustness across diverse scales and conditions. The model's ability to simulate the long-term evolution, including cutoff events, provides valuable insight for river management strategies. The current findings demonstrate that channel geometry, particularly width-to-depth ratio, plays a dominant role in meander evolution, with wider channels prone to more complex and rapid morphological changes. Vegetation effects are most pronounced in channels with moderate width-to-depth ratios, where they can significantly influence migration rates and bed topography. A combination of channel widening and deepening, coupled with strategic vegetation management, can effectively enhance navigability while maintaining channel stability in the studied Tumen River reach. Sensitivity analyses highlight the complex interplay between hydraulic conditions, sediment characteristics, and vegetation in shaping river morphology. This research advances understanding of the multifaceted nature of meandering river systems and offers practical tools for informed decision-making in river engineering and environmental management, particularly in the context of climate change and increasing anthropogenic pressures on fluvial ecosystems.

54 ENVIRONMENTAL SCIENCES

Massively parallel phase-field simulations targeting exascale

The interface thickness in the phase-field (PF) method limits its simulation scales. Consequently, large-scale PF simulations become prohibitively expensive for resolving the extremely fine microstructures that typically form during rapid solidification processing. This challenge is significant in predicting microstructure evolution in metal additive manufacturing and has been identified by the United States Department of Energy’s Exascale Computing Project. Here, to address this, we develop a multi-GPU and MPI-based massively parallel simulation code, utilizing state-of-the-art algorithms, software, and libraries, for large-scale three-dimensional (3D) PF simulations. We report the first GPU-parallel PF simulations on Frontier (currently the second TOP500 exascale cluster) and Summit machines, taking dendritic growth as an example problem. We evaluate the parallel performance of our implementation using scaling studies with more than 24 000 GPUs (among the largest known computations to date) and the acceleration performance using large-scale simulations of dendritic growth in 3D. Finally, massively parallel GPUs in these supercomputers enabled the first coupled multiscale simulations of laser melting and subsequent dendritic solidification on the scale of a full melt-pool, demonstrating the feasibility of performing PF simulations with a point total over 2 billion grid points within an acceptable time.

Exascale

Watching Polarons Dance: Coherent Carrier–Phonon Coupling in Hematite Revealed by Transient Absorption Spectroscopy

Hematite remains a prominent photoanode candidate for the oxygen evolution reaction in solar water splitting, despite efficiency limitations from rapid trapping of photoexcited electrons and holes. While the formation of polarons, quasiparticles formed by electron–hole interactions with lattice vibrations, is a proposed trapping mechanism, direct evidence of such states has been elusive. Here, we use potential-dependent transient absorption spectroscopy to identify the coherent phonon mode and strong exciton–phonon coupling responsible for exciton–polaron formation after band gap excitation in α-hematite and identify the three underlying d–d transitions that are strongly modulated by this phonon. The equilibrium geometry of exciton–polarons in α-hematite is displaced from the ground state geometry along the vibrational coordinate of an A 1g symmetric Fe–O stretching motion at 225 ± 7 cm –1 , resulting in vibrational coherence with a lifetime of 1.9 ± 0.1 ps. Our comparative ex situ and in situ experiments reveal that the energy and dephasing time of the A 1g mode are remarkably resilient to applied potential and the addition of an Al 2 O 3 overlayer; however, the dephasing time is sensitive to substrate identity. Furthermore, this potential-dependent transient absorption approach establishes a powerful platform for directly probing polaron dynamics in photoelectrochemical systems, opening new pathways to rationally design modified hematite and other transition metal oxide electrodes with enhanced charge transport properties for more efficient solar water splitting.

Hematite

Developing ML/AI Methods for High-Throughput Characterization of Multiple-Sensor Streams of Tokamak Dynamics for High-Speed Control (Final Report)

This project evaluated and developed new mathematical and algorithmic techniques capable of handling (in real-time) the growing amounts of data generated by modern fusion research. While existing numerical linear algebra (NLA) methods provide the backbone to classical data analysis and algorithms, these methods fundamentally do not port to distributed architectures nor do they allow low-latency data reduction for control. Motivated by the needs for modern fusion reactors, this project explored and implemented new numerical methods to characterize plasma dynamics, respond in real-time to discharge evolution, and to process massive-scale data accurately and rapidly more fully. This project links expertise in multiple-sensor diagnostics of tokamak plasma dynamics from Columbia University’s Plasma Physics Laboratory with expertise in massive-scale data reduction and extreme data control algorithms at Columbia University’s Data Science Institute. This interdisciplinary project (i) applied machine learning methods, (ii) implemented a properly-trained neural-network for very fast processing of high-speed plasma videography, and (ii) developed the applied mathematical methods, based on randomized-NLA (rNLA) routines, for data analysis, reduction, and real-time control. The Columbia University High Beta Tokamak-Extended Pulse (HBT-EP) facility provided data to test new algorithms and partnership with Columbia University's Data Sciences Institute evaluated the broader use of new algorithms for many challenging control applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

High‐Speed Slot‐Die Coating with Donor‐Priority Rapid Aggregation Kinetics for Improved Morphology and Efficiency in Ecofriendly Organic Solar Cells

Abstract Solution‐processable organic solar cells (OSCs) represent a promising renewable photovoltaic technology with significant potential for eco‐compatible production. While high power conversion efficiencies (PCEs) have been achieved in OSCs, scaling this technology for high‐throughput manufacturing remains challenging. Key reason lies in the lack of efficient control strategies for the complex and long‐duration morphology evolution during high‐speed coating process with ecofriendly solvents. Here, a donor‐priority rapid aggregation process (DP‐RAP) scheme is proposed to solve this issue by adjusting the aggregation kinetics of donor and acceptor components. DP‐RAP enables blends with a nanoscale fiber network structure and favorable crystallinity, which contributes to balanced carrier transport and reduced recombination losses. As a result, the PCE is improved from 14.3% (reference) to 17.4% (DP‐RAP) for ultra‐high speed coated PM6:BTP‐eC9 devices in atmosphere, which is one of the highest values for non‐halogenated solvent‐processed solar cells at coating speeds of 500 mm s −1 . Moreover, the DP‐RAP based devices remain a stable PCE of approximately 17.4% across a broad range of coating speeds (20–500 mm s −1 ), illustrating its tolerance to the varied manufacturing conditions. This work highlights a promising avenue for the high‐speed, ecofriendly production of efficient OSCs, pushing the boundaries of practical manufacturing in renewable energy technologies.

Chemistry

Small-x structure of oxygen and neon isotopes as seen by the Large Hadron Collider

Results on collisions of O-16 nuclei performed at the Relativistic Heavy Ion Collider (RHIC) have been presented for the first time at Quark Matter 2023 by the STAR collaboration. O-16+O-16 collisions are also expected to take place in the near future at the Large Hadron Collider (LHC) at much higher beam energies. We explore the potential of beam-energy-dependent studies for this system to probe small-x dynamics and QCD evolution. We perform 3+1D IP-Glasma simulations to predict the rapidity dependence of the initial geometry of light-ion collisions, focusing on O-16+O-16 and Ne-20+Ne-20 collisions at root s(NN) = 70 GeV and 7 TeV. The choice of Ne-20 is motivated by its strongly elongated geometry, which may respond differently to the effect of the high-energy evolution compared to the more spherical O-16. We find that smearing induced by soft gluon production at high energy causes mild variations in the initial-state eccentricities as a function of the collision energy. These effects could be resolved in future experiments and deserve further investigation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Domestication of Algae for Increasing Biomass Productivity

Microalgae cultivation processes have been developed for the production of a variety of bioproducts, however currently only a few species are used in commercial applications. Their domestication, that is strain improvements, is still in its infancy, with major advances required, specifically to maximize biomass productivity a limiting factor in microalgae production. This requires a deep understanding of algal biology, in particular to develop superior strains without the need of genetic technologies that would require lengthy regulatory permits, and often limit consumer acceptance. Adaptive Laboratory Evolution techniques, alone or in conjunction with sexual recombination, can allow for rapid develop of improved strains and their industrial production. Light harvesting antenna reduction has been a major approach to achieve increased photon utilization efficiency by cultures operating under full sunlight conditions due to higher light saturation levels, allowing for higher productivities under outdoor conditions. Decades of research yielded some promising results under controlled conditions with a few specific mutant strains. However, these failed to achieve the anticipated higher productivities in actual algal mass cultures, in part due to the inability of single mutations to overcome photoinhibition, reactive oxygen species, and other pleiotropic impacts on the complex metabolic processes of photosynthesis. Higher productivity strains will require multiple genetic improvements. We report on recent Adaptive Laboratory Evolution with the green alga Scenedesmus obliquus resulting in higher biomass productivity in open pond cultivation. Coupling our approach with sexual recombination and genome sequencing provides a path to algal domestication suitable for large-scale, low-cost biomass production.

09 BIOMASS FUELS

Microstructural evolution and phase stability in Nb-containing interstitial Fe-Mn-Co-Cr-C high-entropy alloys: An in-situ synchrotron X-ray diffraction study during laser melting

The influence of Nb on phase stability and microstructural evolution in an interstitial Fe-Mn-Co-Cr-C high-entropy alloy was investigated using in-situ synchrotron X-ray diffraction (SXRD) during laser melting. Scheil-Gulliver simulations predict the formation of σ and γ-f.c.c. phases in all three alloys, along with NbC in Nb-containing compositions. SXRD confirmed the presence of most predicted phases, but the σ phase was absent. Nb promotes crystallite refinement and increases dislocation density, though excessive additions reduce refinement efficiency due to solubility limits and secondary phase formation. Furthermore, Nb addition also enhances ε-h.c.p. phase formation by reducing stacking fault energy through NbC-induced carbon depletion. Analysis of intensity peak evolution reveals that Nb alters preferred grain orientations, reducing {111} γ intensity while enhancing {220} γ , leading to a more isotropic grain distribution. Overall, Nb plays a key role in phase selection, microstructure refinement, and preferred orientation evolution, allowing the tailored microstructure of high-entropy alloys via rapid solidification.

Interstitial high entropy alloys