Quantitative electron energy-loss spectroscopy (EELS) critically depends on accurate background subtraction, yet standard approaches rely on deterministic parametric fits and provide no statistically rigorous uncertainty estimates. This limitation is particularly severe in the core-loss regime, where the background must be extrapolated into the ionisation-edge window, hindering reliable and automated analyses. Here, we introduce a physics-informed, uncertainty-aware machine learning framework that reformulates core-loss background subtraction as a statistically controlled inference problem with explicit uncertainty propagation. The method combines Monte Carlo replica generation based on empirically determined covariance matrices with neural network ensembles trained on the pre-edge region, and enforces physically consistent extrapolation via an effective-exponent constraint at the edge onset. This approach yields pixel- and energy-resolved background probability distributions, enabling direct propagation of uncertainty to derived spectroscopic observables. Closure tests on synthetic spectral images demonstrate faithful background reconstruction and well-calibrated uncertainty estimates, including in extrapolation regions. Applied to core-loss EELS spectral images of twisted CrSBr, the framework reveals nanoscale, stacking-correlated modulations of Cr L_2,3 white-line intensities that significantly exceed propagated uncertainties. More broadly, this work provides an automation-ready pathway for quantitative, uncertainty-aware core-loss EELS analysis across diverse materials systems.

Moiré superlattices in 2D van der Waals (vdW) materials enable the engineering of local polarization textures and electrostatic potential landscapes. While polarization vortices are demonstrated in bilayer transition metal dichalcogenides (TMDs), their formation mechanisms in multilayers remain unclear. Here, it is shown that in multi-twisted small-angle multilayer WSe₂, nanoscale strain fields, not twist alone, govern the emergence, and stability of polarization vortices. Using 4D scanning transmission electron microscopy (4D-STEM) with an electron microscope pixel array detector (EMPAD), local electrostatic potential variations and strain distributions are spatially resolved with nanometer precision. It is found that vortex-like polarization textures emerge exclusively in regions with significant nanoscale strain, revealing a direct interplay between lattice reconstruction and Moiré-induced polarization textures in twisted multilayers. The findings establish strain as a key tuning parameter for Moiré-induced polarization control, providing new pathways for strain-engineered 2D vdW materials, chiral dipole textures, and next-generation low-power electronic and optoelectronic devices.

Achieving nanoscale strain fields mapping in intricate van der Waals (vdW) nanostructures, like twisted flakes and nanorods, presents several challenges due to their complex geometry, small size, and sensitivity limitations. Understanding these strain fields is pivotal as they significantly influence the optoelectronic properties of vdW materials, playing a crucial role in a plethora of applications ranging from nanoelectronics to nanophotonics. Here, a novel approach for achieving a nanoscale-resolved mapping of strain fields across entire micron-sized vdW nanostructures using four-dimensional (4D) scanning transmission electron microscopy (STEM) imaging equipped with an electron microscope pixel array detector (EMPAD) is presented. This technique extends the capabilities of STEM-based strain mapping by means of the exit-wave power cepstrum method incorporating automated peak tracking and K-means clustering algorithms. This approach is validated on two representative vdW nanostructures: a two-dimensional (2D) MoS₂ thin twisted flakes and a one-dimensional (1D) MoO₃/MoS₂ nanorod heterostructure. Beyond just vdW materials, the versatile methodology offers broader applicability for strain-field analysis in various low-dimensional nanostructured materials. This advances the understanding of the intricate relationship between nanoscale strain patterns and their consequent optoelectronic properties.