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Abstract Enhancing reactive species transport at the plasma–liquid interface is important for scaling of atmospheric pressure plasmas studied in the laboratory to real-world applications. It is well-known that the introduction of turbulence at any interface will enhance mixing by enhancing species uptake from the gas phase to the liquid phase by surface renewal processes, entrainment, bubbles and surface area modification. The goal of this work is to isolate surface effects associated with turbulence from the multitude of turbulent transport enhanced processes by artificially introducing surface perturbations using Faraday waves. Experiments were conducted to determine decoloration rate constants of a model contaminant (methylene blue) as a function of both discharge features (including positive and negative streamers) and hydrodynamics (Faraday surface wavelengths). The local plasma ionization wave at the interfacial structure was modeled and compared to experiments. Interestingly, it was found in experiments that plasma in contact with the water also generated capillary waves thus modifying the surface as well. Plasma ionization waves in combination with acoustic driven Faraday waves adds to the complexity of interpreting the effects of, for example, surface area increases, due to these complex coupled phenomenon. Local plasma ionization wave structure appears to be modified (increased propagation distance) when the liquid is perturbed, leading to increased contact of the liquid water surface with reactive species. Along with interfacial surface area growth, nonlinear convective transport is also increased with perturbations, leading to the general realization that acoustic perturbations can improve transport and thus decoloration of the model contaminant dye. 

Abstract During magnetospheric substorms, plasma from magnetic reconnection in the magnetotail is thought to reach the inner magnetosphere and form a partial ring current. We simulate this process using a fully kinetic 3D particle‐in‐cell (PIC) numerical code along with a global magnetohydrodynamics (MHD) model. The PIC simulation extends from the solar wind outside the bow shock to beyond the reconnection region in the tail, while the MHD code extends much further and is run for nominal solar wind parameters and a southward interplanetary magnetic field. By the end of the PIC calculation, ions and electrons from the tail reconnection reach the inner magnetosphere and form a partial ring current and diamagnetic current. The primary source of particles to the inner magnetosphere is bursty bulk flows (BBFs) that originate from a complex pattern of reconnection in the near‐Earth magnetotail at to . Most ion acceleration occurs in this region, gaining from 10 to 50 keV as they traverse the sites of active reconnection. Electrons jet away from the reconnection region much faster than the ions, setting up an ambipolar electric field allowing the ions to catch up after approximately 10 ion inertial lengths. The initial energy flux in the BBFs is mainly kinetic energy flux from the ions, but as they move earthward, the energy flux changes to enthalpy flux at the ring current. The power delivered from the tail reconnection in the simulation to the inner magnetosphere is  W, which is consistent with observations. 

Plasma-based water purification involves the transport of reactive species across the gas–liquid interface. This process is limited by slow diffusion driven mass transport of reactive species across the interface. Additionally, the plasma gas–liquid contact area is typically limited, contributing to reduced dose delivery. These key factors make it difficult to scale up the treatment process to input flows of industrial interest. In this work, turbulence is explored as a means to introduce a fine grain structure, thus greatly increasing the interfacial surface area, leading to large property gradients and more efficient mass transport. Such a fine scale structure can also enhance the local electric field. The test apparatus explored in this work is the packed bed reactor that places thin water jets into contact with plasma. It is theorized that introducing turbulence, via increasing Reynolds number in such thin jets, may enhance the effective plasma dose at fixed plasma power. In this work, changes in the flow regime, from laminar to turbulent, of water jets in a packed bed water reactor (PBR) configuration are investigated experimentally. Methylene blue dye, a model contaminant, was tested in the PBR to demonstrate enhanced treatment via reduced treatment times. Plasma surface morphology around the jets noticeably changed with the flow regime, and turbulent flow demonstrated a faster hydrogen peroxide uptake, along with slower temperature, electrical conductivity, and a pH change in a batch treatment process, compared to laminar flow. The dye was destroyed significantly faster in the turbulent flow, indicating an increased effective plasma dose. 

In the domain of space science, numerous ground-based and space-borne data of various phenomena have been accumulating rapidly, making analysis and scientific interpretation challenging. However, recent trends in the application of artificial intelligence (AI) have been shown to be promising in the extraction of information or knowledge discovery from these extensive data sets. Coincidentally, preparing these data for use as inputs to the AI algorithms, referred to as AI-readiness, is one of the outstanding challenges in leveraging AI in space science. Preparation of AI-ready data includes, among other aspects: 1) collection (accessing and downloading) of appropriate data representing the various physical parameters associated with the phenomena under study from different repositories; 2) addressing data formats such as conversion from one format to another, data gaps, quality flags and labeling; 3) standardizing metadata and keywords in accordance with NASA archive requirements or other defined standards; 4) processing of raw data such as data normalization, detrending, and data modeling; and 5) documentation of technical aspects such as processing steps, operational assumptions, uncertainties, and instrument profiles. Making all existing data AI-ready within a decade is impractical and data from future missions and investigations exacerbates this. This reveals the urgency to set the standards and start implementing them now. This article presents our perspective on the AI-readiness of space science data and mitigation strategies including definition of AI-readiness for AI applications; prioritization of data sets, storage, and accessibility; and identifying the responsible entity (agencies, private sector, or funded individuals) to undertake the task. 

This paper presents a search for massive, charged, long-lived particles with the ATLAS detector at the Large Hadron Collider using an integrated luminosity of $$140~fb^{−1}$$ of proton-proton collisions at $$\sqrt{s}=13$$~TeV. These particles are expected to move significantly slower than the speed of light. In this paper, two signal regions provide complementary sensitivity. In one region, events are selected with at least one charged-particle track with high transverse momentum, large specific ionisation measured in the pixel detector, and time of flight to the hadronic calorimeter inconsistent with the speed of light. In the other region, events are selected with at least two tracks of opposite charge which both have a high transverse momentum and an anomalously large specific ionisation. The search is sensitive to particles with lifetimes greater than about 3 ns with masses ranging from 200 GeV to 3 TeV. The results are interpreted to set constraints on the supersymmetric pair production of long-lived R-hadrons, charginos and staus, with mass limits extending beyond those from previous searches in broad ranges of lifetime 

This report presents a comprehensive collection of searches for new physics performed by the ATLAS Collaboration during the Run~2 period of data taking at the Large Hadron Collider, from 2015 to 2018, corresponding to about 140~$$^{-1}$$ of $$\sqrt{s}=13$$~TeV proton--proton collision data. These searches cover a variety of beyond-the-standard model topics such as dark matter candidates, new vector bosons, hidden-sector particles, leptoquarks, or vector-like quarks, among others. Searches for supersymmetric particles or extended Higgs sectors are explicitly excluded as these are the subject of separate reports by the Collaboration. For each topic, the most relevant searches are described, focusing on their importance and sensitivity and, when appropriate, highlighting the experimental techniques employed. In addition to the description of each analysis, complementary searches are compared, and the overall sensitivity of the ATLAS experiment to each type of new physics is discussed. Summary plots and statistical combinations of multiple searches are included whenever possible. 

Abstract The nearby radio galaxy M87 is a prime target for studying black hole accretion and jet formation 1,2 . Event Horizon Telescope observations of M87 in 2017, at a wavelength of 1.3 mm, revealed a ring-like structure, which was interpreted as gravitationally lensed emission around a central black hole 3 . Here we report images of M87 obtained in 2018, at a wavelength of 3.5 mm, showing that the compact radio core is spatially resolved. High-resolution imaging shows a ring-like structure of $${8.4}_{-1.1}^{+0.5}$$ 8.4 − 1.1 + 0.5 Schwarzschild radii in diameter, approximately 50% larger than that seen at 1.3 mm. The outer edge at 3.5 mm is also larger than that at 1.3 mm. This larger and thicker ring indicates a substantial contribution from the accretion flow with absorption effects, in addition to the gravitationally lensed ring-like emission. The images show that the edge-brightened jet connects to the accretion flow of the black hole. Close to the black hole, the emission profile of the jet-launching region is wider than the expected profile of a black-hole-driven jet, suggesting the possible presence of a wind associated with the accretion flow. 

Top-quark pair production is observed in lead–lead ( $\mathrm{Pb}+\mathrm{Pb}$) collisions at $\sqrt{s_{\mathrm{NN}}}=5.02\mathrm{TeV}$at the Large Hadron Collider with the ATLAS detector. The data sample was recorded in 2015 and 2018, amounting to an integrated luminosity of $1.9{\mathrm{nb}}^{-1}$. Events with exactly one electron and one muon and at least two jets are selected. Top-quark pair production is measured with an observed (expected) significance of 5.0 (4.1) standard deviations. The measured top-quark pair production cross section is ${\sigma }_{t\overline{t}}=3.6{}_{-0.9}^{+1.0}\left(\mathrm{stat}\right){}_{-0.5}^{+0.8}\left(\mathrm{syst}\right)\mathrm{\mu }\mathrm{b}$, with a total relative uncertainty of 31%, and is consistent with theoretical predictions using a range of different nuclear parton distribution functions. The observation of this process consolidates the evidence of the existence of all quark flavors in the preequilibrium stage of the quark-gluon plasma at very high energy densities, similar to the conditions present in the early Universe. © 2025 CERN, for the ATLAS Collaboration2025CERN