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Abstract. The Laurentian Great Lakes significantly influence the climate of the Midwest and Northeast United States due to their vast thermal inertia, moisture source potential, and complex heat and moisture flux dynamics. This study presents a newly developed coupled lake–ice–atmosphere (CLIAv1) modeling system for the Great Lakes by coupling the National Aeronautics and Space Administration (NASA) Unified Weather Research and Forecasting (NU-WRF) regional climate model (RCM) with the three-dimensional (3D) Finite Volume Community Ocean Model (FVCOM) and investigates the impact of coupled dynamics on simulations of the Great Lakes' winter climate. By integrating 3D lake hydrodynamics, CLIAv1 demonstrates superior performance in reproducing observed lake surface temperatures (LSTs), ice cover distribution, and the vertical thermal structure of the Great Lakes compared to the NU-WRF model coupled with the default 1D Lake Ice Snow and Sediment Simulator (LISSS). CLIAv1 also enhances the simulation of over-lake atmospheric conditions, including air temperature, wind speed, and sensible and latent heat fluxes, underscoring the importance of resolving complex lake dynamics for reliable regional Earth system projections. More importantly, the key contribution of this study is the identification of critical physical processes that influence lake thermal structure and ice cover – processes that are missed by 1D lake models but effectively resolved by 3D lake models. Through process-oriented numerical experiments, we identify key 3D hydrodynamic processes – ice transport, heat advection, and shear production in turbulence – that explain the superiority of 3D lake models to 1D lake models, particularly in cold season performance and lake–atmosphere interactions. Critically, all three of these processes are dynamically linked to water currents – spatially and temporally evolving flow fields that are structurally absent in 1D models. This study aims to advance our understanding of the physical mechanisms that underlie the fundamental differences between 3D and 1D lake models in simulating key hydrodynamic processes during the winter season, and it offers generalized insights that are not constrained by specific model configurations. 

Abstract We explore the decay of bound neutrons in the JUNO liquid scintillator detector into invisible particles (e.g.,$$n\rightarrow 3 \nu $$ $n\to 3\nu$or$$nn \rightarrow 2 \nu $$ $nn\to 2\nu$), which do not produce an observable signal. The invisible decay includes two decay modes:$$ n \rightarrow { inv} $$ $n\to \mathrm{inv}$and$$ nn \rightarrow { inv} $$ $nn\to \mathrm{inv}$. The invisible decays ofs-shell neutrons in$$^{12}\textrm{C}$$ $_{}^{12}\text{C}$will leave a highly excited residual nucleus. Subsequently, some de-excitation modes of the excited residual nuclei can produce a time- and space-correlated triple coincidence signal in the JUNO detector. Based on a full Monte Carlo simulation informed with the latest available data, we estimate all backgrounds, including inverse beta decay events of the reactor antineutrino$${\bar{\nu }}_e$$ ${\overline{\nu }}_e$, natural radioactivity, cosmogenic isotopes and neutral current interactions of atmospheric neutrinos. Pulse shape discrimination and multivariate analysis techniques are employed to further suppress backgrounds. With two years of exposure, JUNO is expected to give an order of magnitude improvement compared to the current best limits. After 10 years of data taking, the JUNO expected sensitivities at a 90% confidence level are$$\tau /B( n \rightarrow { inv} ) > 5.0 \times 10^{31} \, \textrm{years}$$ $\tau /B(n\to \mathrm{inv})>5.0\times {10}^{31}\text{years}$and$$\tau /B( nn \rightarrow { inv} ) > 1.4 \times 10^{32} \, \textrm{years}$$ $\tau /B(nn\to \mathrm{inv})>1.4\times {10}^{32}\text{years}$. 

Abstract Smart materials with coupled optical and mechanical responsiveness to external stimuli, as inspired by nature, are of interest for the biomimetic design of the next generation of soft machines and wearable electronics. A tough polymer that shows adaptable and switchable mechanical and fluorescent properties is designed using a fluorescent lanthanide, europium (Eu). The dynamic Eu‐iminodiacetate (IDA) coordination is incorporated to build up the physical cross‐linking network in the polymer film consisting of two interpenetrated networks. Reversible disruption and reformation of Eu‐IDA complexation endow high stiffness, toughness, and stretchability to the polymer elastomer through energy dissipation of dynamic coordination. Water that binds to Eu³⁺ions shows an interesting impact simultaneously on the mechanical strength and fluorescent emission of the Eu‐containing polymer elastomer. The mechanical states of the polymer, along with the visually optical response through the emission color change of the polymer film, are reversibly switchable with moisture as a stimulus. The coupled response in the mechanical strength and emissive color in one single material is potentially applicable for smart materials requiring an optical readout of their mechanical properties.