Multi-diagnostic characterization of neutrals in the confined region of DIII-D using interpretive DEGAS2 simulations
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Single electron spin qubits trapped in SiMOS quantum dots are a promising technology for scaling to thousand- or million-qubit systems due to their compatibility with mature CMOS manufacturing processes. A readout system that combines a single electron transistor with a custom cryogenic CMOS amplification and digitization chain offers key advantages by avoiding the use of bulky RF components or room-temperature interconnects. We present design techniques and simulation results for an optimized qubit-SET cryoCMOS interface, culminating in the design of the QNDR1 ASIC, the first cryogenic readout ASIC designed under the Quandarum project, which targets the development of a many-channel spin qubit based detector for use in high energy physics.
This work demonstrates a series of functionalization methods to enhance the utility of thermoplastic-elastomer derived ordered mesoporous carbons, including chemical activation, heteroatom doping, and the introduction of nanoparticles.
Radio-mode feedback associated with the active galactic nuclei (AGNs) at the cores of galaxy clusters injects a large amount of energy into the intracluster medium (ICM), offsetting radiative losses through X-ray emission. This mechanism prevents the ICM from rapidly cooling down and fueling extreme starburst activity as it accretes onto the central galaxies, and it is therefore a key ingredient in the evolution of galaxy clusters. However, the influence and mode of feedback at high redshifts (z ∼ 1) remains largely unknown. Low-frequency sub-arcsecond-resolution radio observations taken with the International LOFAR Telescope have demonstrated their ability to assist X-ray observations with constraining the energy output from the AGNs (or “cavity power”) in galaxy clusters, thereby enabling research at higher redshifts than before. In this pilot project, we tested this hybrid method on a high-redshift (0.6 < z < 1.3) sample of 13 galaxy clusters for the first time with the aim of verifying the performance of this method at these redshifts and providing the first estimates of the cavity power associated with the central AGN for a sample of distant clusters. We were able to detect clear radio lobes in three out of 13 galaxy clusters at redshifts of 0.7 < z < 0.9, and we used these detections in combination with ICM pressures surrounding the radio lobes obtained from standard profiles to calculate the corresponding cavity powers of the AGNs. Combining our results with the literature, the current data appear to suggest that the average cavity power peaked at a redshift ofz ∼ 0.4 and slowly decreases toward higher redshifts. However, we require more and tighter constraints on the cavity volume and a better understanding of our observational systematics to confirm any deviation of the cavity power trend from a constant level.
ABSTRACT Many bacteria utilize the type 9 secretion system (T9SS) for gliding motility, surface colonization, and pathogenesis. This dual-function motor supports both gliding motility and protein secretion, where rotation of the T9SS plays a central role. Fueled by the energy of the stored proton motive force and transmitted through the torque of membrane-anchored stator units, the rotary T9SS propels an adhesin-coated conveyor belt along the bacterial outer membrane like a molecular snowmobile, thereby enabling gliding motion. However, the mechanisms controlling the rotational direction and gliding motility of T9SS remain elusive. Shedding light on this mechanism, we find that in the gliding bacteriumFlavobacterium johnsoniae, deletion of the C-terminus of the conveyor belt-associated protein GldJ controls and, in fact, reverses the rotational direction of T9SS from counterclockwise (CCW) to clockwise (CW). This suggests that the interface between the conveyor belt-associated protein GldJ and the T9SS ring protein GldK plays an important role in controlling the directionality of T9SS, potentially by modulating its interaction with the stator complex GldLM, which drives motor rotation. Combined with MD simulation of the T9SS stator units GldLM, we suggest a “tri-component gearset” model where GldJ controls the rotational direction of its driver, the T9SS, thus providing adaptive sensory feedback to influence the motility of the gliding bacterium. IMPORTANCE The type 9 secretion system (T9SS) is fundamental to bacterial gliding motility, pathogenesis, and surface colonization. Our findings reveal that the C-terminal region of the conveyor belt-associated protein GldJ functions as a molecular switch which is capable of reversing the rotational direction of T9SS. Through the coordinated actions of the T9SS stator units (akin to a driving motor), the GldK ring (the gear that converts rotational energy into linear movement), and GldJ, this machinery forms a smart conveyor belt system reminiscent of flexible or cognitive mechanical conveyors. Such advanced conveyors can alter their direction to adapt to shifting demands. Here, we show that the bacterial T9SS similarly adjusts its rotational bias based on feedback from the conveyor belt-associated protein GldJ. This dual-role feedback mechanism underscores an evolved, controllable biological snowmobile, offering new avenues for studying how bacteria fine-tune motility in dynamic environments.
Abstract Interconnect materials with ultralow dielectric constant, and good thermal and mechanical properties are crucial for the further miniaturization of electronic devices. Recently, it has been demonstrated that ultrathin amorphous boron nitride (aBN) films have a very low dielectric constant, high density (above 2.1 g cm −3 ), high thermal stability, and mechanical properties. The excellent properties of aBN derive from the nature and degree of disorder, which can be controlled at fabrication, allowing tuning of the physical properties for desired applications. Here, we report an improvement in the stability and mechanical properties of aBN upon hydrogen doping. With the introduction of a Gaussian approximation potential for atomistic simulations, we investigate the changing morphology of aBN with varying H doping concentrations. We found that for 8 at% of H doping, the concentration ofsp 3 -hybridized atoms reaches to a maximum which leads to an improvement of thermal stability and mechanical properties by 20%. These results will be a guideline for experimentalists and process engineers to tune the growth conditions of aBN films for numerous applications.
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Electrochemical cells and methods of making electrochemical cells are described herein. In some embodiments, an apparatus includes a multi-layer sheet for encasing an electrode material for an electrochemical cell. The multi-layer sheet including an outer layer, an intermediate layer that includes a conductive substrate, and an inner layer disposed on a portion of the conductive substrate. The intermediate layer is disposed between the outer layer and the inner layer. The inner layer defines an opening through which a conductive region of the intermediate layer is exposed such that the electrode material can be electrically connected to the conductive region. Thus, the intermediate layer can serve as a current collector for the electrochemical cell.
Abstract Despite the appeal of flawless order, semiconductor technology has demonstrated that implanting inhomogeneities into single-crystalline materials is pivotal for modern electronics. However, the influence of the local arrangement of chemical inhomogeneities on the material’s functionalities is underexplored. In this work, we control the distribution of chemical inhomogeneities in La 3+ -substituted ferroelectric BiFeO 3 thin films. By means of a stress- and composition-driven phase transition, we trigger the formation of a lattice of La 3+ -rich and La 3+ -poor layers. This ordering correlates with the emergence of an antipolar phase. An electric field restores the original ferroelectric phase and re-randomizes the distribution of the La 3+ inhomogeneities. Leveraging these insights, we tune the polar/antipolar phase coexistence to set the net polarization of La 0.15 Bi 0.85 FeO 3 to any desired value between its saturation limits. Finally, we control the net polarization response in device-compliant capacitor heterostructures to show that inhomogeneity-distribution control is a valuable tool in the design of functional oxide electronics.
A detailed study of depth-resolved magnetization and microstructure of Fe16N2 thin films on MgO (001) and MgAl2O4 (001) substrates and Fe and Cr seed layers is presented. Two aspects of the magnetic properties of Fe16N2 thin films are discussed. First, magnetization enhancement at the interface is observed. Strain and nitrogen deficiency are discussed as possible interfacial mechanisms contributing to this enhancement. Second, the perpendicularly magnetized component (PMC) is identified in Fe16N2 thin films. Correlation with microstructural observations suggests that the PMC is associated with V-shaped grains that are not fully confined within the continuous Fe16N2 layer.
A facile, scalable, wastewater-free synthesis of high energy density LiMn0.5Fe0.5PO4 (LMFP) cathodes with high electrode press density is achieved by employing the spinel LiMnFeO4 (LMFO) as a precursor.
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We analyse the Messinger/Myers model by critically evaluating simplifying assumptions through a rigorous formulation of the rime ice accretion process. We explore the effects of both constant and variable ice density and thermal conductivity, along with the effects of sublimation from the ice surface. The effects of key factors such as droplet impact rate, ambient temperature relative to the freezing temperature and the temperature difference between the ambient air and the airfoil surface are examined. Under these varying conditions, the present rigorous formulation is used to assess the significance of unsteady effects, variable ice properties and sublimation. We observe that the Myers model performs remarkably well in certain icing situations and analyse the reasons for this strong performance. We also show that partially relaxing the model’s assumptions can lead to poorer performance. The Myers model can lead to overprediction of ice surface temperature and correspondingly underprediction of transition time under conditions of relatively weak sublimation and surface cooling. A modified Myers model is presented, which can be used to recover near-perfect results under widely varying icing conditions of relevance. This article is part of the theme issue ‘Heat and mass transfer in frost and ice’.
Actinides are inherently unstable and undergo nuclear decay processes with a concurrent release of energy. Consequently, they are used for nuclear power generation, nuclear weapons, and nuclear medicine. However, the radioactive decay processes also pose significant technological problems for the safe treatment and storage of spent nuclear materials. Cost-effective extraction of the actinides is the key first step in the remediation of nuclear waste, but the appropriate chemical means have yet to be determined. Our present understanding of the chemistry of actinides is limited, with the role of the 5f electrons posing a set of particularly challenging questions. The work reported here is focused on the use of electronic spectroscopy to probe the bonding of small molecules in the gas phase that contains thorium or uranium. Analyses of these data, carried out within the framework of ligand field theory, reveal clear evidence that the 5f electrons are spectators that retain their atomic metal ion character.
ABSTRACT We study galaxy interactions in the large-scale environment around A2670, a massive (M200 = $8.5 \pm 1.2~\times 10^{14} \, \mathrm{{M}_{\odot }}$) and interacting galaxy cluster at z = 0.0763. We first characterize the environment of the cluster out to 5× R200 and find a wealth of substructures, including the main cluster core, a large infalling group, and several other substructures. To study the impact of these substructures (pre-processing) and their accretion into the main cluster (post-processing) on the member galaxies, we visually examined optical images to look for signatures indicative of gravitational or hydrodynamical interactions. We find that ∼21 per cent of the cluster galaxies have clear signs of disturbances, with most of those (∼60 per cent) likely being disturbed by ram pressure. The number of ram-pressure stripping candidates found (101) in A2670 is the largest to date for a single system, and while they are more common in the cluster core, they can be found even at >4 × R200, confirming cluster influence out to large radii. In support of a pre-processing scenario, most of the disturbed galaxies follow the substructures found, with the richest structures having more disturbed galaxies. Post-processing also seems plausible, as many galaxy–galaxy mergers are seen near the cluster core, which is not expected in relaxed clusters. In addition, there is a comparable fraction of disturbed galaxies in and outside substructures. Overall, our results highlight the complex interplay of gas stripping and gravitational interactions in actively assembling clusters up to 5 × R200, motivating wide-area studies in larger cluster samples.
Computational chemistry is an indispensable tool for understanding molecules and predicting chemical properties. However, traditional computational methods face significant challenges due to the difficulty of solving the Schrödinger equations and the increasing computational cost with the size of the molecular system. In response, there has been a surge of interest in leveraging artificial intelligence (AI) and machine learning (ML) techniques to in silico experiments. Integrating AI and ML into computational chemistry increases the scalability and speed of the exploration of chemical space. However, challenges remain, particularly regarding the reproducibility and transferability of ML models. This review highlights the evolution of ML in learning from, complementing, or replacing traditional computational chemistry for energy and property predictions. Starting from models trained entirely on numerical data, a journey set forth toward the ideal model incorporating or learning the physical laws of quantum mechanics. This paper also reviews existing computational methods and ML models and their intertwining, outlines a roadmap for future research, and identifies areas for improvement and innovation. Ultimately, the goal is to develop AI architectures capable of predicting accurate and transferable solutions to the Schrödinger equation, thereby revolutionizing in silico experiments within chemistry and materials science.
It is well established that active galactic nuclei (AGNs) play an important role in the evolution of galaxies. These AGNs can be linked to the accretion processes onto massive black holes and past merger events in their host galaxies, which may lead to different alignments of the jets with respect to the host galaxies. This paper presents a study of the position angle (PA) differences between radio and optical images of radio-AGNs based on the second data release (DR2) of the Low Frequency Array (LOFAR) Two-Meter Sky Survey (LoTSS), theKarl G. JanskyVery Large Array Faint Images of the Radio Sky at Twenty-Centimeters Survey (FIRST), the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys, and the Sloan Digital Sky Survey (SDSS). We assessed PA measurement biases in the data and classified the radio-AGNs based on the radio luminosity and infrared colour from the Wide-field Infrared Survey Explorer (WISE). This resulted in the largest sample of radio AGNs with reliable radio and optical PA measurements published to date, with a total of 3682 AGNs. The PA difference (dPA) distributions for the radio-AGN sample show a prominent minor-axis alignment tendency. Based on some simple assumptions, we simulated the projection effect to estimate the intrinsic jet-galaxy alignment. The observed dPA distribution can be well described by a two-component jet-alignment model in which one component is more aligned with the minor axis of the host galaxy than the other. The fitting results indicate that the jet alignment is dependent on radio luminosity and the shape of the host galaxies, with the jets being more likely to be aligned with the minor axis of the galaxy for lower radio luminosity and for optically more elongated radio-AGNs. The minor-axis alignment of the entire sample may suggest a coherent accretion model present in most AGN host galaxies, while a considerable number of luminous radio-AGNs with massive host galaxies might have undergone accretion – according to the chaotic model – or past merger events.