858 papers
This paper demonstrates that leveraging relative motion between components in neutron microscopy to introduce diversity significantly improves image quality by suppressing static noise and enabling the reconstruction of flat-field corrections directly from the scan data, thereby reducing or eliminating the need for separate open-beam acquisitions without increasing radiation dose.
This study employs manifold learning on a curated dataset of NiTi-like alloys to identify a specific emergent compositional variable (the fifth diffusion coordinate) that exhibits a strong, monotonic correlation with martensitic start temperatures, thereby offering a compact and transferable framework for predicting and designing shape memory alloys.
This study utilizes start-to-end simulations to evaluate the dosimetric performance of laser-driven Very High Energy Electron (VHEE) pencil beams for FLASH radiotherapy of brain tumors, specifically analyzing the impact of energy spread and beamlet tessellation on dose coverage while outlining the technological path toward achieving FLASH dose rates.
This study demonstrates that spin-coating at 3000 rpm yields the highest crystalline quality for open-air-processed MAPbI₃ thin films and utilizes the resulting experimentally derived optical bandgaps in SCAPS-1D simulations to optimize device parameters, predicting a power conversion efficiency of 25.38%.
This pre-experimental design study proposes converting the macroscopic, shielded Börekci Energy Field cavity into a trapped-ion quantum teleportation platform (BEF-T) to conduct three specific experiments testing atomic-state teleportation and entanglement-enhanced probing of the ξ parameter, while strictly adhering to physical limits against faster-than-light signaling.
This study employs variance-based sensitivity analysis on birch wood and medium-density fibreboard to demonstrate that activation energy is the dominant parameter governing pyrolysis, while revealing that the relative importance of chemical kinetics versus physical heat transfer varies significantly with moisture content.
This study employs a comprehensive numerical simulation using Buongiorno's model and the SIMPLER algorithm to investigate how partial nanoparticle injection and thermal dispersion influence the hydrothermal performance of Darcy-Forchheimer porous channel flows, revealing that while injection thickness and dispersion significantly enhance heat transfer, these effects plateau beyond a certain threshold, with Cu-water nanofluids demonstrating superior thermal conductivity.
This paper addresses the ill-posed nature of multi-view tomographic background-oriented Schlieren reconstruction by conducting a parametric study of implicit neural representations to develop a lightweight, adaptive sampling network that significantly improves both training efficiency and reconstruction accuracy for 3D flow field diagnostics.
This paper claims to resolve the long-standing mystery of high-temperature superconductivity by theoretically deriving and experimentally demonstrating room-temperature zero-resistance interconnects using Mersenne prime superlattices and 4-phase orthogonal drives to eliminate electron-phonon scattering, thereby enabling heat-dissipation-free semiconductor systems.
This study demonstrates that alloying NaMgBi half-Heusler compounds with lithium effectively optimizes both electronic and phonon transport properties, significantly reducing lattice thermal conductivity and enhancing the thermoelectric figure-of-merit (ZT) to a maximum of approximately 1.78.