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Abstract Low‐level clouds in the tropical cyclone (TC) rainbands modulate the radial inflow of warm, moist boundary layer air, which can impact TC intensity. Yet, precisely measuring rainband cloud boundaries with existing remote sensing techniques remains a challenge. To address this observational gap, this work leverages compact Raman lidar (CRL) backscattered power data collected by a NOAA P‐3 aircraft to distinguish between low‐level convective clouds, shallow clouds, stratiform precipitation, and clear air in the TC rainbands. CRL data are analyzed together with traditional tail Doppler radar (TDR) and in situ observations. An empirical CRL classification scheme finds that convective cloud, stratiform rainfall, and clear air sectors have unique kinematic and precipitation properties. A case study of Hurricane Sam (2021) demonstrates how this method resolves cloud structures with enhanced horizontal detail compared to the TDR. For the first time, the horizontal scales of low‐level convection and shallow clouds are determined. Environmental shear‐relative analyses reveal that the downshear‐left quadrant contains the most low‐level convective coverage and the least clear air. Meanwhile, the upshear‐right quadrant has little low‐level convection and plentiful clear air. Increasing environmental shear from low to moderate magnitudes amplifies these TC shear‐induced precipitation asymmetries. A conceptual framework is developed to highlight the unique information provided by the CRL when classifying cloud and precipitation structures. 

Hybrid integration of two-dimensional (2D) single-crystalline metal oxides (MOs), including semiconductors, dielectrics, ferroelectrics, and ferromagnetics, with silicon circuits enables new functionalities such as spintronic transistors, neuromorphic computing, and quantum computing, contributing as an important part of the More than Moore roadmap. However, the synthesis of 2D MO single crystal films has remained a long-standing difficulty. Here, we report a van der Waals (vdW) surface reconstruction of mica for the general large-scale growth of unidirectional-oriented 2D MOs (where M = Co, Fe, Ni and Mn) and their doped counterparts, which eventually seamlessly coalesce into single-crystalline films. Quantum mechanics calculations reveal that reconstruction of mica’s oxygen atomic plane holds the key to guaranteeing the single-crystal epitaxy of these 2D MOs. As an example, centimeter-scale 2D Fe doped CoO single crystalline films were grown and exhibit room-temperature ferromagnetic semiconductor properties with a high Curie temperature of up to 430 K. These results demonstrate the power of this synthesis strategy, enabling the exploration of 2D MOs for quantum physics and spintronics devices. 

Not AvailableTwo-dimensional (2D) superconductors are emerging platforms supporting both strongly correlated physics and quantum information science1,2. Their reduced dimensionality, atomically flat interfaces, and high-crystallinity are particularly attractive for realizing compact lumped-element devices in superconducting circuits3–5. However, large-scale synthesis of monolayer 2D superconductors remains challenging as they are easily oxidized in air6. Here, we report an “encapsulation epitaxy” mechanism that enables the growth of large-area (>1-inch), air-stable, monolayer NbSe2 films (1L-NbSe2) and explored their potential for superconducting quantum circuits. This work represents a distinct growth phenomenon in which a 2D encapsulation layer, such as graphene or hexagonal boron nitride (hBN), pre-deposited on a 3D substrate (e.g., SiO2, Si3N4) simultaneously serves as a template for the epitaxial growth of 1L-NbSe2 underneath it at encapsulation-substrate interface and as a protective capping layer against ambient degradation. The as-grown 1L-graphene/NbSe2 heterostructures exhibit robust superconductivity (superconducting transition temperature Tc ≈ 1 K) and enhanced charge density wave (CDW; CDW transition temperature TCDW ≈ 177 K). We further demonstrate the integration of 1L-NbSe2 into superconducting circuits by developing oxidation-free transfer and superconducting edge-contact techniques. The 1L-NbSe2 in these circuits feature a measured kinetic inductance LK ≈ 0.7 nH/□, making it suitable for quantum circuits requiring elements with high kinetic inductance. This encapsulation epitaxy methodology enables the production of air-stable 2D superconductors and van der Waals heterostructures, holding the promise for wafer-scale, monolithic fabrication of superconducting quantum circuitry. 

The efficient signal processing in biosystems is largely attributed to the powerful constituent unit of a neuron, which encodes and decodes spatiotemporal information using spiking action potentials of ultralow amplitude and energy. Constructing devices that can emulate neuronal functions is thus considered a promising step toward advancing neuromorphic electronics and enhancing signal flow in bioelectronic interfaces. However, existent artificial neurons often have functional parameters that are distinctly mismatched with their biological counterparts, including signal amplitude and energy levels that are typically an order of magnitude larger. Here, we demonstrate artificial neurons that not only closely emulate biological neurons in functions but also match their parameters in key aspects such as signal amplitude, spiking energy, temporal features, and frequency response. Moreover, these artificial neurons can be modulated by extracellular chemical species in a manner consistent with neuromodulation in biological neurons. We further show that an artificial neuron can connect to a biological cell to process cellular signals in real-time and interpret cell states. These results advance the potential for constructing bio-emulated electronics to improve bioelectronic interface and neuromorphic integration. 

Abstract Biases in tropical cyclone model forecasts impact track, intensity, and structural predictions. Yet, not all of these biases can be assessed using traditional comparisons with observations. This paper fills this research gap by introducing a new model evaluation framework that compares single forecasts to aircraft data from individual flights. Measurements from the novel compact Raman lidar are supplemented by dropsonde and tail Doppler radar data to explore how low-level tropical cyclone kinematics and thermodynamics evolve, particularly in the atmospheric boundary layer. The compact Raman lidar is essential in this framework, as it provides extensive thermodynamic data coverage in the tropical cyclone eye and rainbands. As a demonstration, observations are compared to short lead-time Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS)–Tropical Cyclone (TC) forecasts of Hurricane Sam (2021) over three sampling periods to diagnose model biases. Two important low-level biases consistently appear: The modeled rainband atmospheric boundary layer has a positive moisture bias, and the modeled low-level eye has a cold bias. Despite these consistent thermodynamic differences, Sam’s primary and secondary circulations vary between flights, suggesting that mean tropical cyclone kinematics alone do not drive these temperature and moisture biases. This unique analysis framework focuses on individual flight legs, hinges on the high spatial density of the compact Raman lidar thermodynamic data, and provides an avenue for future model improvement via atmospheric boundary layer scheme adjustments. Significance StatementTropical cyclones rely on the transfer of heat and moisture from the ocean to the lower atmosphere to maintain their structure and intensity. Despite the importance of low-level thermodynamics, these fields are poorly constrained in tropical cyclone models. This study uses a new methodology to compare unique aircraft measurements of temperature and moisture with model forecasts for one storm. Key systematic errors in the model with respect to observations are found, including increased low-level moisture and colder temperatures in the eye of the storm. These model biases alter the characteristics of the simulated storm, partially explaining intensity forecast errors. In the future, if we can correct these thermodynamic biases by improving model physics, a more accurate depiction of tropical cyclones could be achieved. 

Abstract Cardiac microtissues provide a promising platform for disease modeling and developmental studies, which require the close monitoring of the multimodal excitation-contraction dynamics. However, no existing assessing tool can track these multimodal dynamics across the live tissue. We develop a tissue-like mesh bioelectronic system to track these multimodal dynamics. The mesh system has tissue-level softness and cell-level dimensions to enable stable embedment in the tissue. It is integrated with an array of graphene sensors, which uniquely converges both bioelectrical and biomechanical sensing functionalities in one device. The system achieves stable tracking of the excitation-contraction dynamics across the tissue and throughout the developmental process, offering comprehensive assessments for tissue maturation, drug effects, and disease modeling. It holds the promise to provide more accurate quantification of the functional, developmental, and pathophysiological states in cardiac tissues, creating an instrumental tool for improving tissue engineering and studies. 

Abstract This study examines the mesoscale structure and evolution of a polar low associated with a marine cold-air outbreak (MCAO) on 2 April 2024 over the Norwegian Sea. As part of the Cold-Air Outbreak Experiment in the Subarctic Region (CAESAR), the National Science Foundation National Center for Atmospheric Research C-130 aircraft equipped with an array of in situ and remote sensing instrumentation, including profiling radars and lidars, traversed this polar low five times, yielding detailed vertical transects of clouds and precipitation. This polar low was rather shallow and formed in the wake (not at the leading edge) of an MCAO. Observations and output from an operational convection-permitting model reveal that the polar low developed in the lee of an island, Svalbard, under deep northerly flow that roughly aligned with surface-driven baroclinicity. The polar low was marked by a region of surface-driven, mostly open-cellular precipitating convection, and a separate region of deeper stratiform clouds driven by moist-isentropic ascent in an area of suppressed surface heat fluxes. The confluence of a cold air mass from the northeast, only briefly exposed to open water, with a more mature, warmer MCAO air mass with a deeper well-mixed boundary layer previously exposed to high surface heat fluxes over the Fram Strait led to convergent, cyclonically sheared boundaries with enhanced convection. These convergent boundaries emerged as cyclonic potential vorticity streamers generated frictionally by Svalbard’s terrain, became more intense by diabatic heating in clouds, and were transported downstream into the polar low. Significance StatementPolar lows are small, intense cyclones that may cause havoc with maritime transport and may bring strong winds and heavy snowfall to coastal areas. While they are most common across the far northern Atlantic Ocean, they also occur over other high-latitude oceans. Their predictability is hampered not only by the lack of measurements at high latitudes but also by a poor understanding of their vertical structure. An airborne field campaign was conducted in early 2024 to better understand clouds in marine cold-air outbreaks, including polar lows. This study combines profiling radar and lidar data collected aboard an aircraft with operational high-resolution model data to unveil fine-scale cloud and precipitation structures of a polar low in unprecedented detail. 

Abstract This case study analyzes a tornadic supercell observed in northeast Louisiana as part of the Verification of the Origins of Rotation in Tornadoes Experiment Southeast (VORTEX-SE) on 6–7 April 2018. One mobile research radar (SR1-P), one WSR-88D equivalent (KULM), and two airborne radars (TAFT and TFOR) have sampled the storm at close proximity for ∼70 min through its mature phase, tornadogenesis at 2340 UTC, and dissipation and subsequent ingestion into a developing MCS segment. The 4D wind field and reflectivity from up to four Doppler analyses, combined with 4D diabatic Lagrangian analysis (DLA) retrievals, has enabled kinematic and thermodynamic analysis of storm-scale boundaries leading up to, during, and after the dissipation of the NWS-surveyed EF0 tornado. The kinematic and thermodynamic analyses reveal a transient current of low-level streamwise vorticity leading into the low-level supercell updraft, appearing similar to the streamwise vorticity current (SVC) that has been identified in supercell simulations and previously observed only kinematically. Vorticity dynamical calculations demonstrate that both baroclinity and horizontal stretching play significant roles in the generation and amplification of streamwise vorticity associated with this SVC. While the SVC does not directly feed streamwise vorticity to the tornado–cyclone, its development coincides with tornadogenesis and an intensification of the supercell’s main low-level updraft, although a causal relationship is unclear. Although the mesoscale environment is not high-shear/low-CAPE (HSLC), the updraft of the analyzed supercell shares some similarities to past observations and simulations of HSLC storms in the Southeast United States, most notably a pulse-like updraft that is maximized in the low- to midlevels of the storm. Significance StatementThe purpose of this study is to analyze the airflow and thermodynamics of a highly observed tornado-producing supercell. While computer simulations can provide us with highly detailed looks at the complicated evolution of supercells, it is rare, due to the difficulty of data collection, to collect enough data to perform a highly detailed analysis on a particular supercell, especially in the Southeast United States. We identified a “current” of vorticity—rotating wind—that develops at the intersection of the supercell’s rain-cooled outflow and warm inflow, similar to previous simulations. This vorticity current develops and feeds the storm’s updraft as its tornado develops and the storm intensifies, although it does not directly enter the tornado.