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Virtual melting (VM) as alternative deformation and stress relaxation mechanisms under extreme load is directly validated by molecular dynamics (MD) simulations of the simple shear of single crystal Si I at a temperature 1383K below the melting temperature. The shear band consisting of liquid Si is formed immediately after the shear instability while stresses drop to zero. This process is independent of the applied shear rate. A new thermodynamic approach is developed, and the thermodynamic criterion for VM, which depends on the ratio of the sample to shear band widths, is derived analytically and confirmed by MD simulations. Since stress-free melt is unstable at 300K, with further shear, the VM immediately transforms to a mixture of low-density amorphous a-Si, stable Si I, and metastable Si IV. Cyclic transformations between a-Si ↔ Si I, a-Si ↔ Si IV, and Si I ↔ Si IV with volume fraction of all phases mostly between 0.2 and 0.4 and non-repeatable nanostructure evolution are reveled. Such cyclic transformations produce additional important carriers for plastic deformation through transformation strain and transformation-induced plasticity due to volume change, which may occur in shear bands in various material systems but missed in experiments and simulations. The release of shear stresses quenches the microstructure, and shows reasonable qualitative correspondence with existing experiments. 

Abstract Multi-year marine heatwaves (MHWs) in the Gulf of Alaska (GOA) are major climate events with lasting ecological and economic effects. Though often seen as local Pacific phenomena, our study shows their persistence depends on trans-basin interactions between the North Pacific and North Atlantic. Using observational data and climate model experiments, we find that prolonged MHWs occur as sequential warming episodes triggered by atmospheric wave trains crossing ocean basins. These wave trains alter surface heat flux, initiating MHWs in the GOA and changing North Atlantic sea surface temperatures (SSTs). In turn, Atlantic SST anomalies reinforce wave activity, fueling subsequent MHW episodes in a feedback loop. This mechanism appears in historical events (1949–52, 1962–65, 2013–16, and 2018–22), highlighting MHWs as a trans-basin phenomenon. Our findings link GOA MHWs to trans-basin atmospheric wave dynamics and identify North Atlantic SSTs as a potential predictor of their duration. 

Abstract Geometrical frustration and long-range couplings are key contributors to create quantum phases with different properties throughout physics. We propose a scheme where both ingredients naturally emerge in a Raman induced subwavelength lattice. We first demonstrate that Raman-coupled multicomponent quantum gases can realize a highly versatile frustrated Hubbard Hamiltonian with long-range interactions. The deeply subwavelength lattice period leads to strong long-range interparticle repulsion with tunable range and decay. We numerically demonstrate that the combination of frustration and long-range couplings generates many-body phases of bosons, including a range of density-wave and superfluid phases with broken translational and time reversal symmetries, respectively. Our results thus represent a powerful approach for efficiently combining long-range interactions and frustration in quantum simulations. 

Precise and accurate charge measurements on microdroplets are essential for understanding the role of charge in modulating microdroplet chemistry, including reaction kinetics, ion distribution, and interfacial dynamics. Despite the availability of various charge measurement techniques, existing contactless techniques either lack the sensitivity to accurately detect charges with ∼1 fC precision or lack the ability to measure charge on micron-sized particles, leaving a significant gap in the field. Here, a new technique is presented to directly measure the net charge of microdroplets exiting a quadrupole electrodynamic trap (QET) using induced charge detection. With this method, the charge droplets induce on a cylindrical electrode (Qinduced) is detected using a homebuilt charge sensitive pre-amplifier (CSP). The long time constant of the CSP (1.02 ± 0.01 s−1) facilitates accurate measurement of Qinduced on slow-moving microdroplets that interact with the detection electrode for up to 100s of ms. The new charge detection method is validated by comparing Qinduced with the charge of droplets measured using a Faraday cup (QFaraday cup) for roughly 2900 droplets with different net charges, sizes, and velocities. Regardless of droplet properties, Qinduced closely correlates with QFaraday cup with absolute differences averaging <5 fC (i.e., 1% accuracy). While the charge detection system is coupled to a QET, it could easily be adapted for other droplet-based measurements (e.g., droplet train experiments). Ultimately, the induced charge detection system presented here will support future studies exploring how charge influences the physical and chemical processing of microdroplets, such as understanding how charge can drive accelerated chemistry in microdroplets. 

Sixth-order boundary value problems (BVPs) arise in thin-film flows with a surface that has elastic bending resistance. We consider the case in which the elastic interface is clamped at the lateral walls of a closed trough and thus encloses a finite amount of fluid. For a slender film undergoing infinitesimal deformations, the displacement of the elastic surface from its initial equilibrium position obeys a sixth-order (in space) initial boundary value problem (IBVP). To solve this IBVP, we construct a set of odd and even eigenfunctions that intrinsically satisfy the boundary conditions (BCs) of the original IBVP. These eigenfunctions are the solutions of a non-self-adjoint sixth-order eigenvalue problem (EVP). To use the eigenfunctions for series expansions, we also construct and solve the adjoint EVP, leading to another set of even and odd eigenfunctions, which are orthogonal to the original set (biorthogonal). The eigenvalues of the adjoint EVP are the same as those of the original EVP, and we find accurate asymptotic formulas for them. Next, employing the biorthogonal sets of eigenfunctions, a Petrov–Galerkin spectral method for sixth-order problems is proposed, which can also handle lower-order terms in the IBVP. The proposed method is tested on two model sixth-order BVPs, which admit exact solutions. We explicitly derive all the necessary formulas for expanding the quantities that appear in the model problems into the set(s) of eigenfunctions. For both model problems, we find that the approximate Petrov–Galerkin spectral solution is in excellent agreement with the exact solution. The convergence rate of the spectral series is rapid, exceeding the expected sixth-order algebraic rate. 

Open source software (OSS) underpins modern software infrastructure, yet many projects struggle with long- term sustainability. We introduce OSSPREY, an AI-powered platform that can predict the sustainability of any GitHub- hosted project. OSSPREY collects longitudinal socio-technical data, such as: commits, issues, and contributor interactions, and uses a transformer-based model to generate month-by-month sustainability forecasts. When project downturns are detected, it recommends evidence-based interventions drawn from published software engineering studies. OSSPREY integrates scraping, forecasting, and actionable guidance into an interactive dash- board, enabling maintainers to monitor project health, anticipate decline, and respond with targeted strategies. By connecting real- time project data with research-backed insights, OSSPREY offers a practical tool for sustaining OSS projects at scale. The codebase is linked to the project website at: https: //oss-prey.github.io/OSSPREY-Website/ The screencast is available at: https://www.youtube.com/ watch?v=N7a0v4hPylU