790 papers
This paper resolves the well-known pathologies of the Lorentz Abraham Dirac equation by modeling charged particles as finite, deformable spheres with internal breathing modes, thereby deriving a causal radiation reaction force that eliminates pre-acceleration and runaway solutions while providing a mechanical interpretation of the Schott term as reversible internal energy storage.
This paper presents two novel microfluidic platforms—one utilizing pillar arrays and the other employing a custom Pt-coated PMMA photomask—for the in situ micropatterning of PEGDA-PEG hydrogels to enable precise control and tracking of molecular diffusion for diverse applications ranging from biosensing to drug delivery.
This paper presents a novel high-order gas-kinetic scheme integrated with the actuator line model and immersed boundary method on GPUs to accurately simulate three-dimensional wind turbine flows, including nacelle and tower effects, while validating its ability to capture complex wake interactions and turbulent statistics against experimental data.
By applying a deep learning workflow to seismic data from the 2025 Santorini-Amorgos crisis, researchers expanded the earthquake catalogue from 4,000 to 80,000 events, revealing unprecedented fluid-driven volcanic-tectonic swarms and identifying a new deep magmatic reservoir beneath Anydros Islet.
This paper utilizes Vlasov-Poisson-Fokker-Planck simulations to characterize the three-phase evolution of large-amplitude, weakly-collisional electron plasma waves, revealing that collisional effects drive a distinct, long-lived detrapping phase with unique frequency shifts and damping rates before the system transitions to Landau damping.
This paper demonstrates that differentiable programming, enabled by automatic differentiation, serves as a versatile framework in plasma physics that not only accelerates traditional design and inference tasks but also enables novel capabilities such as discovering new nonlinear phenomena, learning hidden kinetic variables for fluid models, and performing high-dimensional inverse design.
This paper proposes reframing biology as a distinct subdiscipline of physics by characterizing living matter as nonunitary and possessing unique organizational features that necessitate a dialectical materialist and multilevel physicalist perspective, thereby challenging informationist and reductionist views.
This study extends the STACIE algorithm by incorporating a Lorentz model and additional pressure tensor components to enable reliable, automated, and uncertainty-quantified viscosity calculations for 2,2,4-trimethylhexane under high pressures, demonstrating that long equilibrium molecular dynamics simulations can achieve experimental accuracy (<6% error) where previous methods failed due to insufficient sampling.
This paper extends the Irreversible Port-Hamiltonian Systems (IPHS) framework to model non-isentropic fluids with viscous dissipation in both Eulerian and Lagrangian coordinates by adapting differential operators for convective transport and defining boundary controls that satisfy the first and second laws of thermodynamics.
The paper introduces MRI2Qmap, a plug-and-play framework that leverages deep denoising autoencoders pretrained on large-scale routine weighted MRI datasets to enable high-quality, ground-truth-free reconstruction of multi-parametric quantitative maps from highly accelerated MRF acquisitions.
This paper proposes an Angular Momentum Integral (AMI) based diagnostics framework to systematically isolate and quantify physical mechanism-specific errors in turbulence models, revealing that while standard Reynolds-averaged Navier-Stokes (RANS) models may accurately predict skin friction through strong error cancellation in simple flows, they exhibit significant, non-canceling errors in complex separated flows that require mechanism-resolved analysis for targeted improvement.
This paper demonstrates that replacing first-order time integration with higher-order Runge-Kutta methods and adaptive time stepping in the E3SMv3 rain microphysics model significantly improves computational efficiency and accuracy, achieving over 10x speedup compared to the default scheme while eliminating the need for stability-limiting ad hoc procedures.
This paper presents the first direct numerical simulations resolving the complete laminar-to-turbulent transition in Herschel-Bulkley yield-stress fluids across pipes and channels, revealing that transition occurs only when local Reynolds stresses exceed the yield stress and identifying a critical generalized Reynolds number range of approximately 2000 to 3000 where turbulence sharply emerges.
This paper investigates Rayleigh-Taylor unstable flames through large-scale Boussinesq model simulations and direct measurements, revealing that while self-generated turbulence can thicken these flames, their internal structure remains distinct from classical turbulent flames, thereby highlighting the need for specialized subgrid models in practical applications.
The paper introduces HawkesRank, a dynamic framework based on multivariate Hawkes point processes that overcomes the limitations of static centrality measures by modeling both exogenous drivers and endogenous amplification to provide a principled, real-time importance ranking that outperforms traditional metrics in predicting system activity.
This paper presents the final design and a comprehensive 3D finite element structural analysis of the PRAGYA tokamak's vacuum vessel, confirming that its distinctive features and robust construction can safely withstand self-weight, atmospheric pressure, and thermal stresses during operation.
This paper presents a rapid and robust simulation workflow that combines the toroidal STRIDE code with the two-fluid slab layer solver SLAYER to accurately predict classical tearing mode stability and growth rates across a wide range of reactor-relevant plasma conditions.
This study utilizes numerical simulations to characterize the deformation and breakup dynamics of shear-thinning viscoelastic drops in steady electric fields, revealing that while behavior in certain parameter regions resembles Newtonian fluids, others exhibit complex non-monotonic responses to elasticity and distinct shape transitions like multi-lobed or conical formations depending on conductivity and permittivity ratios.
This paper generalizes a first-principles closure from the th-order structure function to the -point velocity increment Hopf equation, enabling the analytical derivation of multipoint turbulent statistics such as the 3-point structure function transition, which shows promising agreement with DNS data.
This paper introduces a stochastic single-stage stellarator optimization method that combines fixed-boundary MHD equilibria with randomly perturbed coils to avoid sharp local minima and produce more robust quasi-symmetric configurations with improved flux, symmetry, and particle confinement compared to existing deterministic and two-stage approaches.